Theano: I re-installed everything starting from ubuntu and still have errors. Could you help ?
THEANO_FLAGS=device=cpu python -c "import theano; theano.test()"
Theano version 0.10.0beta4+42.g47ff0da
theano is installed in /usr/src/Theano/theano
NumPy version 1.11.0
NumPy relaxed strides checking option: False
NumPy is installed in /usr/lib/python3/dist-packages/numpy
Python version 3.5.2 (default, Sep 14 2017, 22:51:06) [GCC 5.4.0 20160609]
nose version 1.3.7
Using cuDNN version 7003 on context None
Mapped name None to device cuda: TITAN X (Pascal) (0000:01:00.0)
..........................................ERROR (theano.gof.opt): Optimization failure due to: insert_bad_dtype
ERROR (theano.gof.opt): node: Elemwise{add,no_inplace}(<TensorType(float64, vector)>, <TensorType(float64, vector)>)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/src/Theano/theano/gof/opt.py", line 2059, in process_node
remove=remove)
File "/usr/src/Theano/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
chk = fgraph.replace_all_validate(replacements, reason)
File "/usr/src/Theano/theano/gof/toolbox.py", line 518, in replace_all_validate
fgraph.replace(r, new_r, reason=reason, verbose=False)
File "/usr/src/Theano/theano/gof/fg.py", line 486, in replace
". The type of the replacement must be the same.", old, new)
theano.gof.toolbox.BadOptimization: BadOptimization Error
Variable: id 139752011015056 Elemwise{Cast{float32}}.0
Op Elemwise{Cast{float32}}(Elemwise{add,no_inplace}.0)
Value Type: <class 'NoneType'>
Old Value: None
New Value: None
Reason: insert_bad_dtype. The type of the replacement must be the same.
Old Graph:
Elemwise{add,no_inplace} [id A] <TensorType(float64, vector)> ''
|<TensorType(float64, vector)> [id B] <TensorType(float64, vector)>
|<TensorType(float64, vector)> [id C] <TensorType(float64, vector)>
New Graph:
Elemwise{Cast{float32}} [id D] <TensorType(float32, vector)> ''
|Elemwise{add,no_inplace} [id A] <TensorType(float64, vector)> ''
Hint: relax the tolerance by setting tensor.cmp_sloppy=1
or even tensor.cmp_sloppy=2 for less-strict comparison
......................................S............................./usr/lib/python3/dist-packages/numpy/lib/nanfunctions.py:326: RuntimeWarning: All-NaN slice encountered
warnings.warn("All-NaN slice encountered", RuntimeWarning)
/usr/lib/python3/dist-packages/numpy/lib/nanfunctions.py:227: RuntimeWarning: All-NaN axis encountered
warnings.warn("All-NaN axis encountered", RuntimeWarning)
............................................../usr/src/Theano/theano/gof/vm.py:886: UserWarning: CVM does not support memory profile, using Stack VM.
'CVM does not support memory profile, using Stack VM.')
./usr/src/Theano/theano/gof/vm.py:886: UserWarning: CVM does not support memory profile, using Stack VM.
'CVM does not support memory profile, using Stack VM.')
..........SS.............0.058164613716645386
0.058164613716645386
0.058164613716645386
0.058164613716645386
.................................................................................................................................................................../usr/src/Theano/theano/gof/vm.py:889: UserWarning: LoopGC does not support partial evaluation, using Stack VM.
'LoopGC does not support partial evaluation, '
./usr/src/Theano/theano/gof/vm.py:889: UserWarning: LoopGC does not support partial evaluation, using Stack VM.
'LoopGC does not support partial evaluation, '
./usr/src/Theano/theano/gof/vm.py:889: UserWarning: LoopGC does not support partial evaluation, using Stack VM.
'LoopGC does not support partial evaluation, '
/usr/src/Theano/theano/gof/vm.py:889: UserWarning: LoopGC does not support partial evaluation, using Stack VM.
'LoopGC does not support partial evaluation, '
..............................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS...............S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSS..................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSS..............SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS............................../usr/lib/python3.5/unittest/case.py:600: DeprecationWarning: stack(*tensors) interface is deprecated, use stack(tensors, axis=0) instead.
testMethod()
.............................................................................................................................SSS................SSS......................SSS..................................../usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 18, 18, 17), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
/usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 9, 9, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
/usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 11, 10, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 18, 18, 17), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
/usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 9, 9, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
/usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 11, 10, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 16, 16, 17), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
/usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 8, 8, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
/usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 8, 8, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 16, 16, 17), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
/usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 8, 8, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
/usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 8, 8, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.../usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConvGradI'>, we received an input with a shape that has some repeated values: (3, 4, 1, 1), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
/usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConvGradI'>, we received an input with a shape that has some repeated values: (3, 4, 1, 1), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
...../usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConvGradW'>, we received an input with a shape that has some repeated values: (5, 1, 2, 1), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConvGradW'>, we received an input with a shape that has some repeated values: (5, 1, 2, 1), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 8, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 8, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 7, 8), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 7, 8), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
./usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
........../usr/src/Theano/theano/gpuarray/tests/test_dnn.py:1408: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.grad(T.nnet.softmax(y).mean(), y),
/usr/src/Theano/theano/gpuarray/tests/test_dnn.py:1434: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.grad(T.nnet.softmax(y).mean(), y),
..................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................../usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.elemwise.GpuCAReduceCuda'>, we received an input with a shape that has some repeated values: (128, 1, 3, 3), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
/usr/src/Theano/theano/tests/unittest_tools.py:257: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
cls, inp.shape)
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.elemwise.GpuCAReduceCuda'>, we received an input with a shape that has some repeated values: (128, 1, 3, 3), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.......................................S.........................................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS..../usr/src/Theano/theano/sandbox/rng_mrg.py:1031: UserWarning: MRG_RandomStreams.multinomial_wo_replacement() is deprecated and will be removed in the next release of Theano. Please use MRG_RandomStreams.choice() instead.
warnings.warn('MRG_RandomStreams.multinomial_wo_replacement() is '
./usr/src/Theano/theano/sandbox/rng_mrg.py:1031: UserWarning: MRG_RandomStreams.multinomial_wo_replacement() is deprecated and will be removed in the next release of Theano. Please use MRG_RandomStreams.choice() instead.
warnings.warn('MRG_RandomStreams.multinomial_wo_replacement() is '
.......................................ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 3, 5, 5), kshp=(12, 3, 3, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/src/Theano/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/src/Theano/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 3, 5, 5), kshp=(12, 3, 3, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/src/Theano/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/src/Theano/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 3, 5, 5), kshp=(12, 3, 3, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/src/Theano/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/src/Theano/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 3, 5, 5), kshp=(12, 3, 3, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/src/Theano/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/src/Theano/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 3, 5, 5), kshp=(12, 3, 3, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/src/Theano/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/src/Theano/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 2, 7, 5), kshp=(9, 2, 5, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/src/Theano/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/src/Theano/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 2, 7, 5), kshp=(9, 2, 5, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/src/Theano/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/src/Theano/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 2, 7, 5), kshp=(9, 2, 5, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/src/Theano/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/src/Theano/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 2, 7, 5), kshp=(9, 2, 5, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/src/Theano/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/src/Theano/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 2, 7, 5), kshp=(9, 2, 5, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/src/Theano/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/src/Theano/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(6, 1, 3, 3), kshp=(4, 1, 1, 1), filter_dilation=(1, 1), num_groups=1, unshared=False}(InplaceGpuDimShuffle{0,x,1,2}.0, InplaceGpuDimShuffle{0,x,x,x}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/src/Theano/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/src/Theano/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(6, 1, 3, 3), kshp=(4, 1, 1, 1), filter_dilation=(1, 1), num_groups=1, unshared=False}(InplaceGpuDimShuffle{0,x,1,2}.0, InplaceGpuDimShuffle{0,x,x,x}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/src/Theano/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/src/Theano/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(6, 1, 3, 3), kshp=(4, 1, 1, 1), filter_dilation=(1, 1), num_groups=1, unshared=False}(InplaceGpuDimShuffle{0,x,1,2}.0, InplaceGpuDimShuffle{0,x,x,x}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/src/Theano/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/src/Theano/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(6, 1, 3, 3), kshp=(4, 1, 1, 1), filter_dilation=(1, 1), num_groups=1, unshared=False}(InplaceGpuDimShuffle{0,x,1,2}.0, InplaceGpuDimShuffle{0,x,x,x}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/src/Theano/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/src/Theano/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(6, 1, 3, 3), kshp=(4, 1, 1, 1), filter_dilation=(1, 1), num_groups=1, unshared=False}(InplaceGpuDimShuffle{0,x,1,2}.0, InplaceGpuDimShuffle{0,x,x,x}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/src/Theano/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/src/Theano/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
................SS......SSSSS.....................SSSS.../usr/src/Theano/theano/tensor/basic.py:2184: UserWarning: theano.tensor.round() changed its default from `half_away_from_zero` to `half_to_even` to have the same default as NumPy. Use the Theano flag `warn.round=False` to disable this warning.
"theano.tensor.round() changed its default from"
./usr/src/Theano/theano/tensor/basic.py:2184: UserWarning: theano.tensor.round() changed its default from `half_away_from_zero` to `half_to_even` to have the same default as NumPy. Use the Theano flag `warn.round=False` to disable this warning.
"theano.tensor.round() changed its default from"
......S/usr/src/Theano/theano/gpuarray/type.py:861: UserWarning: config.experimental.unpickle_gpu_on_cpu is set to True. Unpickling GpuArray as numpy.ndarray
"config.experimental.unpickle_gpu_on_cpu is set to True. "
..................................................................................................................................................................................................................................................................S............../usr/src/Theano/theano/sandbox/rng_mrg.py:1031: UserWarning: MRG_RandomStreams.multinomial_wo_replacement() is deprecated and will be removed in the next release of Theano. Please use MRG_RandomStreams.choice() instead.
warnings.warn('MRG_RandomStreams.multinomial_wo_replacement() is '
.........../usr/src/Theano/theano/sandbox/rng_mrg.py:1031: UserWarning: MRG_RandomStreams.multinomial_wo_replacement() is deprecated and will be removed in the next release of Theano. Please use MRG_RandomStreams.choice() instead.
warnings.warn('MRG_RandomStreams.multinomial_wo_replacement() is '
..................../usr/src/Theano/theano/sandbox/rng_mrg.py:1031: UserWarning: MRG_RandomStreams.multinomial_wo_replacement() is deprecated and will be removed in the next release of Theano. Please use MRG_RandomStreams.choice() instead.
warnings.warn('MRG_RandomStreams.multinomial_wo_replacement() is '
....................................................S...S.......................................
.
.
...........
....S...................S........................................................................................................../usr/lib/python3/dist-packages/scipy/sparse/data.py:61: ComplexWarning: Casting complex values to real discards the imaginary part
return self._with_data(self.data.astype(t))
/usr/src/Theano/theano/sparse/tests/test_basic.py:2414: ComplexWarning: Casting complex values to real discards the imaginary part
expected = data.toarray().astype(o_dtype)
...../usr/lib/python3/dist-packages/scipy/sparse/compressed.py:730: SparseEfficiencyWarning: Changing the sparsity structure of a csc_matrix is expensive. lil_matrix is more efficient.
SparseEfficiencyWarning)
/usr/lib/python3/dist-packages/scipy/sparse/compressed.py:730: SparseEfficiencyWarning: Changing the sparsity structure of a csr_matrix is expensive. lil_matrix is more efficient.
SparseEfficiencyWarning)
.......................................................S........S........................................../usr/lib/python3/dist-packages/scipy/sparse/csr.py:282: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.
col.step in (1, None) and
S...../usr/lib/python3/dist-packages/scipy/sparse/compressed.py:730: SparseEfficiencyWarning: Changing the sparsity structure of a csr_matrix is expensive. lil_matrix is more efficient.
SparseEfficiencyWarning)
................./usr/lib/python3/dist-packages/scipy/sparse/compressed.py:296: SparseEfficiencyWarning: Comparing sparse matrices using >= and <= is inefficient, using <, >, or !=, instead.
"using <, >, or !=, instead.", SparseEfficiencyWarning)
.................../usr/lib/python3/dist-packages/scipy/sparse/compressed.py:730: SparseEfficiencyWarning: Changing the sparsity structure of a csr_matrix is expensive. lil_matrix is more efficient.
SparseEfficiencyWarning)
............./usr/lib/python3/dist-packages/scipy/sparse/compressed.py:730: SparseEfficiencyWarning: Changing the sparsity structure of a csc_matrix is expensive. lil_matrix is more efficient.
SparseEfficiencyWarning)
/usr/lib/python3/dist-packages/scipy/sparse/compressed.py:730: SparseEfficiencyWarning: Changing the sparsity structure of a csr_matrix is expensive. lil_matrix is more efficient.
SparseEfficiencyWarning)
...S.........................................................................................................................................................................................................................................../usr/src/Theano/theano/tensor/nnet/abstract_conv.py:1807: DeprecationWarning: fractions.gcd() is deprecated. Use math.gcd() instead.
div = gcd(p, q)
/usr/src/Theano/theano/tensor/nnet/abstract_conv.py:1807: DeprecationWarning: fractions.gcd() is deprecated. Use math.gcd() instead.
div = gcd(p, q)
..................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................../usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
../usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
./usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
.................../usr/src/Theano/theano/tensor/nnet/tests/test_corr.py:283: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr.py:283: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr.py:283: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr.py:283: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr.py:283: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr.py:283: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr.py:283: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr.py:283: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr.py:283: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr.py:283: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr.py:283: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr.py:283: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
........................../usr/src/Theano/theano/tensor/nnet/tests/test_corr3d.py:292: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr3d.py:292: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr3d.py:292: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr3d.py:292: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr3d.py:292: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr3d.py:292: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr3d.py:292: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr3d.py:292: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr3d.py:292: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr3d.py:292: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr3d.py:292: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
/usr/src/Theano/theano/tensor/nnet/tests/test_corr3d.py:292: DeprecationWarning: Please use assertEqual instead.
assert_equals(f(a_tens_val, b_tens_val).dtype, c_dtype)
....................................SSS............................/usr/src/Theano/theano/tensor/nnet/tests/test_nnet.py:1008: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(x)[T.arange(y.shape[0]), y])),
/usr/src/Theano/theano/tensor/nnet/tests/test_nnet.py:1009: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(x)[T.arange(y.shape[0]), y]))]
./usr/src/Theano/theano/tensor/nnet/tests/test_nnet.py:1055: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(x + b)[T.arange(y.shape[0]), y])),
/usr/src/Theano/theano/tensor/nnet/tests/test_nnet.py:1056: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(b + x)[T.arange(y.shape[0]), y])),
/usr/src/Theano/theano/tensor/nnet/tests/test_nnet.py:1057: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(x + b))[T.arange(y.shape[0]), y]),
/usr/src/Theano/theano/tensor/nnet/tests/test_nnet.py:1058: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(b + x))[T.arange(y.shape[0]), y])]
./usr/src/Theano/theano/tensor/nnet/tests/test_nnet.py:1116: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(x + b)[T.arange(y.shape[0]), y])),
/usr/src/Theano/theano/tensor/nnet/tests/test_nnet.py:1117: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(b + x)[T.arange(y.shape[0]), y])),
/usr/src/Theano/theano/tensor/nnet/tests/test_nnet.py:1118: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(x + b))[T.arange(y.shape[0]), y]),
/usr/src/Theano/theano/tensor/nnet/tests/test_nnet.py:1119: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(b + x))[T.arange(y.shape[0]), y])]
./usr/src/Theano/theano/tensor/nnet/tests/test_nnet.py:1178: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(x + b)[T.arange(y.shape[0]), y])),
/usr/src/Theano/theano/tensor/nnet/tests/test_nnet.py:1179: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(b + x)[T.arange(y.shape[0]), y])),
/usr/src/Theano/theano/tensor/nnet/tests/test_nnet.py:1180: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(x + b))[T.arange(y.shape[0]), y]),
/usr/src/Theano/theano/tensor/nnet/tests/test_nnet.py:1181: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(b + x))[T.arange(y.shape[0]), y])]
./usr/src/Theano/theano/gof/opt.py:242: UserWarning: WARNING: Supervisor is not added. Please build a FunctionGraphvia theano.compile.function_module.std_graph()or add the Supervisor class manually.
sub_prof = optimizer.optimize(fgraph)
./usr/lib/python3.5/unittest/case.py:600: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
testMethod()
.........................../usr/src/Theano/theano/gof/opt.py:242: UserWarning: WARNING: Supervisor is not added. Please build a FunctionGraphvia theano.compile.function_module.std_graph()or add the Supervisor class manually.
sub_prof = optimizer.optimize(fgraph)
../usr/lib/python3.5/unittest/case.py:600: UserWarning: DEPRECATION: If x is a vector, LogSoftmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
testMethod()
./usr/src/Theano/theano/gradient.py:1728: UserWarning: DEPRECATION: If x is a vector, LogSoftmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
o_output = fun(*tensor_pt)
....../usr/lib/python3.5/unittest/case.py:600: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
testMethod()
./usr/src/Theano/theano/gradient.py:1728: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
o_output = fun(*tensor_pt)
......../usr/src/Theano/theano/tensor/nnet/tests/test_nnet.py:155: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
sm = T.nnet.softmax(a + b)
........S..SS/usr/src/Theano/theano/gof/opt.py:242: UserWarning: WARNING: Supervisor is not added. Please build a FunctionGraphvia theano.compile.function_module.std_graph()or add the Supervisor class manually.
sub_prof = optimizer.optimize(fgraph)
....................................................................................................................................................................................................................................................................................................................................................................................................................................................................................../usr/src/Theano/theano/tensor/signal/tests/test_pool.py:919: UserWarning: DEPRECATION: the 'ds' parameter is not going to exist anymore as it is going to be replaced by the parameter 'ws'.
mode=mode)
/usr/src/Theano/theano/tensor/signal/tests/test_pool.py:919: UserWarning: DEPRECATION: the 'st' parameter is not going to exist anymore as it is going to be replaced by the parameter 'stride'.
mode=mode)
/usr/src/Theano/theano/tensor/signal/tests/test_pool.py:919: UserWarning: DEPRECATION: the 'padding' parameter is not going to exist anymore as it is going to be replaced by the parameter 'pad'.
mode=mode)
..../usr/src/Theano/theano/tensor/signal/tests/test_pool.py:1103: UserWarning: DEPRECATION: the 'ds' parameter is not going to exist anymore as it is going to be replaced by the parameter 'ws'.
mode=mode)
/usr/src/Theano/theano/tensor/signal/tests/test_pool.py:1103: UserWarning: DEPRECATION: the 'st' parameter is not going to exist anymore as it is going to be replaced by the parameter 'stride'.
mode=mode)
/usr/src/Theano/theano/tensor/signal/tests/test_pool.py:1103: UserWarning: DEPRECATION: the 'padding' parameter is not going to exist anymore as it is going to be replaced by the parameter 'pad'.
mode=mode)
/usr/src/Theano/theano/tensor/signal/tests/test_pool.py:1119: UserWarning: DEPRECATION: the 'ds' parameter is not going to exist anymore as it is going to be replaced by the parameter 'ws'.
mode=mode)
/usr/src/Theano/theano/tensor/signal/tests/test_pool.py:1119: UserWarning: DEPRECATION: the 'st' parameter is not going to exist anymore as it is going to be replaced by the parameter 'stride'.
mode=mode)
/usr/src/Theano/theano/tensor/signal/tests/test_pool.py:1119: UserWarning: DEPRECATION: the 'padding' parameter is not going to exist anymore as it is going to be replaced by the parameter 'pad'.
mode=mode)
....................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................../usr/lib/python3.5/unittest/case.py:600: DeprecationWarning: stack(*tensors) interface is deprecated, use stack(tensors, axis=0) instead.
testMethod()
............................................................................................................................................../usr/src/Theano/theano/tensor/tests/test_basic.py:8227: UserWarning: Tile op is deprecated, use tile function instead.
[Tile(ndim)(advec, aivec_val)],
/usr/src/Theano/theano/tensor/tests/test_basic.py:8235: UserWarning: Tile op is deprecated, use tile function instead.
[Tile(ndim)(admat, aivec_val)],
/usr/src/Theano/theano/tensor/tests/test_basic.py:8243: UserWarning: Tile op is deprecated, use tile function instead.
[Tile(ndim)(adtens4, aivec_val)],
........................../usr/src/Theano/theano/tensor/basic.py:2184: UserWarning: theano.tensor.round() changed its default from `half_away_from_zero` to `half_to_even` to have the same default as NumPy. Use the Theano flag `warn.round=False` to disable this warning.
"theano.tensor.round() changed its default from"
.................................................................................S........................................................F........................................................................................................................./usr/src/Theano/theano/tensor/basic.py:5262: UserWarning: flatten outdim parameter is deprecated, use ndim instead.
"flatten outdim parameter is deprecated, use ndim instead.")
...........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................S..SSSS.S..........................................................................................................S.....................S.............................../usr/src/Theano/theano/tensor/nlinalg.py:175: DeprecationWarning: DeprecationWarning: theano.tensor.nlinalg.AllocDiagis deprecated, please use theano.tensor.AllocDiaginstead.
category=DeprecationWarning)
/usr/src/Theano/theano/tensor/nlinalg.py:175: DeprecationWarning: DeprecationWarning: theano.tensor.nlinalg.AllocDiagis deprecated, please use theano.tensor.AllocDiaginstead.
category=DeprecationWarning)
./usr/src/Theano/theano/tensor/nlinalg.py:175: DeprecationWarning: DeprecationWarning: theano.tensor.nlinalg.AllocDiagis deprecated, please use theano.tensor.AllocDiaginstead.
category=DeprecationWarning)
./usr/src/Theano/theano/tensor/nlinalg.py:175: DeprecationWarning: DeprecationWarning: theano.tensor.nlinalg.AllocDiagis deprecated, please use theano.tensor.AllocDiaginstead.
category=DeprecationWarning)
.................................................................................................................................S.S..S......./usr/src/Theano/theano/tensor/basic.py:2184: UserWarning: theano.tensor.round() changed its default from `half_away_from_zero` to `half_to_even` to have the same default as NumPy. Use the Theano flag `warn.round=False` to disable this warning.
"theano.tensor.round() changed its default from"
./usr/src/Theano/theano/tensor/basic.py:2184: UserWarning: theano.tensor.round() changed its default from `half_away_from_zero` to `half_to_even` to have the same default as NumPy. Use the Theano flag `warn.round=False` to disable this warning.
"theano.tensor.round() changed its default from"
....../usr/src/Theano/theano/tensor/opt.py:3523: UserWarning: Your current code is fine, but Theano versions between 0.7rc1 and 0.10 (or development versions between Nov. 2014 and May 2017) might have given incorrect results. This graph has following pattern: inc_subtensor(zeros[idx], x)[idx], where idx is an array of integers. This used to be optimized to "x", which is incorrect if there are duplicated indices in idx. To disable this warning, set the Theano flag warn.inc_subtensor1_opt to False.
'Your current code is fine, but Theano versions '
.../usr/src/Theano/theano/gof/opt.py:242: UserWarning: WARNING: Supervisor is not added. Please build a FunctionGraphvia theano.compile.function_module.std_graph()or add the Supervisor class manually.
sub_prof = optimizer.optimize(fgraph)
...................................................S..............S............/usr/src/Theano/theano/gof/opt.py:242: UserWarning: WARNING: Supervisor is not added. Please build a FunctionGraphvia theano.compile.function_module.std_graph()or add the Supervisor class manually.
sub_prof = optimizer.optimize(fgraph)
..............................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................S/usr/lib/python3.5/unittest/case.py:600: UserWarning: consider_constant() is deprecated, use zero_grad() or disconnected_grad() instead.
testMethod()
./usr/lib/python3.5/unittest/case.py:600: UserWarning: consider_constant() is deprecated, use zero_grad() or disconnected_grad() instead.
testMethod()
...............................................SS......SSSSS...SSSS.......S......../usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
/usr/src/Theano/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
..S.S............../usr/src/Theano/theano/tests/test_rop.py:388: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
self.check_rop_lop(tensor.nnet.softmax(self.x)[0], self.in_shape[0])
.......
======================================================================
FAIL: test_weird_valid_axes (theano.tensor.tests.test_basic.test_tensordot)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/usr/src/Theano/theano/tensor/tests/test_basic.py", line 6587, in test_weird_valid_axes
f3(aval, bval)))
AssertionError: False is not true
----------------------------------------------------------------------
Ran 9916 tests in 9486.622s
FAILED (SKIP=664, failures=1)
fsalmasri
All 11 comments
Could you run the failing test alone and check if it still fails ?
THEANO_FLAGS=device=cpu nosetests -xvs theano.tensor.tests.test_basic:test_tensordot.test_weird_valid_axes
If it still fails, could you apply the following path, re-run that test, and post the result ?
````diff
diff --git a/theano/tensor/tests/test_basic.py b/theano/tensor/tests/test_basic.py
index 986bbf07a..dc6677bca 100644
--- a/theano/tensor/tests/test_basic.py
+++ b/theano/tensor/tests/test_basic.py
@@ -6583,8 +6583,7 @@ class test_tensordot(unittest.TestCase):
f3 = inplace_func([amat, bmat], c)
aval = rand(4, 7)
bval = rand(7, 9)
- self.assertTrue(np.allclose(np.tensordot(aval, bval, axes),
- f3(aval, bval)))
- utt.assert_allclose(np.tensordot(aval, bval, axes), f3(aval, bval))
utt.verify_grad(self.TensorDot(axes), [aval, bval])
def test_scalar_axes(self):
````
notoraptor
on 20 Oct 2017
here is the result
test_weird_valid_axes (theano.tensor.tests.test_basic.test_tensordot) ... ok
Ran 1 test in 32.615s
OK
fsalmasri
on 20 Oct 2017
Ok, so isolated test gives no error.
I guess you have error because it runs through theano.test(), ie. after many data are initialized in memory, and after many random numbers are generated.
What do you think, @nouiz @lamblin ?
notoraptor
on 20 Oct 2017
I have new issue right now when I tried to test theano
ERROR (theano.gpuarray): Could not initialize pygpu, support disabled
Traceback (most recent call last):
File "/usr/src/Theano/theano/gpuarray/__init__.py", line 220, in <module>
use(config.device)
File "/usr/src/Theano/theano/gpuarray/__init__.py", line 207, in use
init_dev(device, preallocate=preallocate)
File "/usr/src/Theano/theano/gpuarray/__init__.py", line 94, in init_dev
**args)
File "pygpu/gpuarray.pyx", line 651, in pygpu.gpuarray.init
File "pygpu/gpuarray.pyx", line 587, in pygpu.gpuarray.pygpu_init
pygpu.gpuarray.GpuArrayException: b'Could not load "libnvrtc.so": libnvrtc.so: cannot open shared object file: No such file or directory'
It seems for my like python3.5 problem since my other projects can't find relative module in other folders even __init__ is included
fsalmasri
on 21 Oct 2017
So Actually I did this which solved the first issue
sudo sh -c "echo '/usr/local/cuda-9.0/lib64' > /etc/ld.so.conf.d/cuda.conf"
and then added root=/usr/local/cuda-9.0/ to the flag file
It is working with a message saying
Using cuDNN version 7003 on context None
Mapped name None to device cuda0: TITAN X (Pascal) (0000:01:00.0)
fsalmasri
on 21 Oct 2017
why it says Using cuDNN version 7003 on context None ?
fsalmasri
on 23 Oct 2017
That's normal.
"context None" is the default context, the one specified by device=...
cuDNN 7003 is the internal version number, I think it corresponds to 7.0.3.
lamblin
on 23 Oct 2017
Hello, I am trying to import Theano in an Ubuntu 16.04 server with cuda-9.1 by using the next command:
python -c "import theano; theano.test()".And I get the following error and warnings:
heano version 1.0.1
theano is installed in /usr/local/lib/python2.7/dist-packages/theano
NumPy version 1.13.3
NumPy relaxed strides checking option: True
NumPy is installed in /usr/local/lib/python2.7/dist-packages/numpy
Python version 2.7.12 (default, Nov 20 2017, 18:23:56) [GCC 5.4.0 20160609]
nose version 1.3.7
Using cuDNN version 7005 on context None
Mapped name None to device cuda: GeForce GTX 970 (0000:01:00.0)
..........................................ERROR (theano.gof.opt): Optimization failure due to: insert_bad_dtype
ERROR (theano.gof.opt): node: Elemwise{add,no_inplace}(<TensorType(float64, vector)>, <TensorType(float64, vector)>)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2059, in process_node
remove=remove)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
chk = fgraph.replace_all_validate(replacements, reason)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/toolbox.py", line 518, in replace_all_validate
fgraph.replace(r, new_r, reason=reason, verbose=False)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/fg.py", line 486, in replace
". The type of the replacement must be the same.", old, new)
BadOptimization: BadOptimization Error
Variable: id 140606464591568 Elemwise{Cast{float32}}.0
Op Elemwise{Cast{float32}}(Elemwise{add,no_inplace}.0)
Value Type: <type 'NoneType'>
Old Value: None
New Value: None
Reason: insert_bad_dtype. The type of the replacement must be the same.
Old Graph:
Elemwise{add,no_inplace} [id A] <TensorType(float64, vector)> ''
|<TensorType(float64, vector)> [id B] <TensorType(float64, vector)>
|<TensorType(float64, vector)> [id C] <TensorType(float64, vector)>
New Graph:
Elemwise{Cast{float32}} [id D] <TensorType(float32, vector)> ''
|Elemwise{add,no_inplace} [id A] <TensorType(float64, vector)> ''
Hint: relax the tolerance by setting tensor.cmp_sloppy=1
or even tensor.cmp_sloppy=2 for less-strict comparison
......................................S............................./usr/local/lib/python2.7/dist-packages/theano/compile/nanguardmode.py:150: RuntimeWarning: All-NaN slice encountered
return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))
/usr/local/lib/python2.7/dist-packages/theano/compile/nanguardmode.py:150: RuntimeWarning: All-NaN axis encountered
return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))
............................................../usr/local/lib/python2.7/dist-packages/theano/gof/vm.py:886: UserWarning: CVM does not support memory profile, using Stack VM.
'CVM does not support memory profile, using Stack VM.')
...........SS.............0.0581646137166
0.0581646137166
Theano version 1.0.1
theano is installed in /usr/local/lib/python2.7/dist-packages/theano
NumPy version 1.13.3
NumPy relaxed strides checking option: True
NumPy is installed in /usr/local/lib/python2.7/dist-packages/numpy
Python version 2.7.12 (default, Nov 20 2017, 18:23:56) [GCC 5.4.0 20160609]
nose version 1.3.7
Using cuDNN version 7005 on context None
Mapped name None to device cuda: GeForce GTX 970 (0000:01:00.0)
..........................................ERROR (theano.gof.opt): Optimization failure due to: insert_bad_dtype
ERROR (theano.gof.opt): node: Elemwise{add,no_inplace}(<TensorType(float64, vector)>, <TensorType(float64, vector)>)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2059, in process_node
remove=remove)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
chk = fgraph.replace_all_validate(replacements, reason)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/toolbox.py", line 518, in replace_all_validate
fgraph.replace(r, new_r, reason=reason, verbose=False)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/fg.py", line 486, in replace
". The type of the replacement must be the same.", old, new)
BadOptimization: BadOptimization Error
Variable: id 140299844289168 Elemwise{Cast{float32}}.0
Op Elemwise{Cast{float32}}(Elemwise{add,no_inplace}.0)
Value Type: <type 'NoneType'>
Old Value: None
New Value: None
Reason: insert_bad_dtype. The type of the replacement must be the same.
Old Graph:
Elemwise{add,no_inplace} [id A] <TensorType(float64, vector)> ''
|<TensorType(float64, vector)> [id B] <TensorType(float64, vector)>
|<TensorType(float64, vector)> [id C] <TensorType(float64, vector)>
New Graph:
Elemwise{Cast{float32}} [id D] <TensorType(float32, vector)> ''
|Elemwise{add,no_inplace} [id A] <TensorType(float64, vector)> ''
Hint: relax the tolerance by setting tensor.cmp_sloppy=1
or even tensor.cmp_sloppy=2 for less-strict comparison
......................................S............................./usr/local/lib/python2.7/dist-packages/theano/compile/nanguardmode.py:150: RuntimeWarning: All-NaN slice encountered
return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))
/usr/local/lib/python2.7/dist-packages/theano/compile/nanguardmode.py:150: RuntimeWarning: All-NaN axis encountered
return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))
............................................../usr/local/lib/python2.7/dist-packages/theano/gof/vm.py:886: UserWarning: CVM does not support memory profile, using Stack VM.
'CVM does not support memory profile, using Stack VM.')
...........SS.............0.0581646137166
0.0581646137166
0.0581646137166
0.0581646137166
.................................................................................................................................................................../usr/local/lib/python2.7/dist-packages/theano/gof/vm.py:889: UserWarning: LoopGC does not support partial evaluation, using Stack VM.
'LoopGC does not support partial evaluation, '
.......................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................^C
----------------------------------------------------------------------
Ran 1233 tests in 724.361s
OK (SKIP=3)
mqg@svstation:~$ sudo theano-cache purge
[sudo] password for mqg:
mqg@svstation:~$ python -c "import theano; theano.test()"
Theano version 1.0.1
theano is installed in /usr/local/lib/python2.7/dist-packages/theano
NumPy version 1.13.3
NumPy relaxed strides checking option: True
NumPy is installed in /usr/local/lib/python2.7/dist-packages/numpy
Python version 2.7.12 (default, Nov 20 2017, 18:23:56) [GCC 5.4.0 20160609]
nose version 1.3.7
Using cuDNN version 7005 on context None
Mapped name None to device cuda: GeForce GTX 970 (0000:01:00.0)
..........................................ERROR (theano.gof.opt): Optimization failure due to: insert_bad_dtype
ERROR (theano.gof.opt): node: Elemwise{add,no_inplace}(<TensorType(float64, vector)>, <TensorType(float64, vector)>)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2059, in process_node
remove=remove)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
chk = fgraph.replace_all_validate(replacements, reason)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/toolbox.py", line 518, in replace_all_validate
fgraph.replace(r, new_r, reason=reason, verbose=False)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/fg.py", line 486, in replace
". The type of the replacement must be the same.", old, new)
BadOptimization: BadOptimization Error
Variable: id 140606464591568 Elemwise{Cast{float32}}.0
Op Elemwise{Cast{float32}}(Elemwise{add,no_inplace}.0)
Value Type: <type 'NoneType'>
Old Value: None
New Value: None
Reason: insert_bad_dtype. The type of the replacement must be the same.
Old Graph:
Elemwise{add,no_inplace} [id A] <TensorType(float64, vector)> ''
|<TensorType(float64, vector)> [id B] <TensorType(float64, vector)>
|<TensorType(float64, vector)> [id C] <TensorType(float64, vector)>
New Graph:
Elemwise{Cast{float32}} [id D] <TensorType(float32, vector)> ''
|Elemwise{add,no_inplace} [id A] <TensorType(float64, vector)> ''
Hint: relax the tolerance by setting tensor.cmp_sloppy=1
or even tensor.cmp_sloppy=2 for less-strict comparison
......................................S............................./usr/local/lib/python2.7/dist-packages/theano/compile/nanguardmode.py:150: RuntimeWarning: All-NaN slice encountered
return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))
/usr/local/lib/python2.7/dist-packages/theano/compile/nanguardmode.py:150: RuntimeWarning: All-NaN axis encountered
return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))
............................................../usr/local/lib/python2.7/dist-packages/theano/gof/vm.py:886: UserWarning: CVM does not support memory profile, using Stack VM.
'CVM does not support memory profile, using Stack VM.')
...........SS.............0.0581646137166
0.0581646137166
0.0581646137166
0.0581646137166
.................................................................................................................................................................../usr/local/lib/python2.7/dist-packages/theano/gof/vm.py:889: UserWarning: LoopGC does not support partial evaluation, using Stack VM.
'LoopGC does not support partial evaluation, '
................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS...............S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSS..................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSS..............SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS............................../usr/lib/python2.7/unittest/case.py:329: DeprecationWarning: stack(*tensors) interface is deprecated, use stack(tensors, axis=0) instead.
testMethod()
.................................................................................E...........................................SSS................SSS......................SSS....................................WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 18, 18, 17), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 9, 9, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 11, 10, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 18, 18, 17), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 9, 9, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 11, 10, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 16, 16, 17), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 8, 8, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 8, 8, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 16, 16, 17), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 8, 8, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 8, 8, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
...WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConvGradI'>, we received an input with a shape that has some repeated values: (3, 4, 1, 1), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConvGradI'>, we received an input with a shape that has some repeated values: (3, 4, 1, 1), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.....WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConvGradW'>, we received an input with a shape that has some repeated values: (5, 1, 2, 1), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConvGradW'>, we received an input with a shape that has some repeated values: (5, 1, 2, 1), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 8, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 8, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 7, 8), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 7, 8), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
........../usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_dnn.py:1408: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.grad(T.nnet.softmax(y).mean(), y),
/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_dnn.py:1434: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.grad(T.nnet.softmax(y).mean(), y),
.......................................................................................................................................................................................................................................................................................................................................................E................................................................................................................................................^C
======================================================================
ERROR: test_all (theano.gpuarray.tests.test_blas.GpuGemmBatchTester)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_basic_ops.py", line 97, in test_all
self.run_case(testname, inputs)
File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_basic_ops.py", line 131, in run_case
variables = f_tst()
File "/usr/local/lib/python2.7/dist-packages/theano/compile/function_module.py", line 917, in __call__
storage_map=getattr(self.fn, 'storage_map', None))
File "/usr/local/lib/python2.7/dist-packages/theano/gof/link.py", line 325, in raise_with_op
reraise(exc_type, exc_value, exc_trace)
File "/usr/local/lib/python2.7/dist-packages/theano/compile/function_module.py", line 903, in __call__
self.fn() if output_subset is None else\
RuntimeError: ('Blas operation not supported by library in use: hgemmBatch\nApply node that caused the error: GpuGemmBatch{inplace=True}(GpuAllocEmpty{dtype=\'float16\', context_name=None}.0, TensorConstant{1.0}, GpuFromHost<None>.0, GpuFromHost<None>.0, TensorConstant{0.0})\nToposort index: 11\nInputs types: [GpuArrayType<None>(float16, 3D), TensorType(float32, scalar), GpuArrayType<None>(float16, 3D), GpuArrayType<None>(float16, 3D), TensorType(float32, scalar)]\nInputs shapes: [(3, 4, 7), (), (3, 4, 4), (3, 4, 7), ()]\nInputs strides: [(56, 14, 2), (), (32, 8, 2), (56, 14, 2), ()]\nInputs values: [\'not shown\', array(1.0, dtype=float32), \'not shown\', \'not shown\', array(0.0, dtype=float32)]\nOutputs clients: [[GpuElemwise{Composite{((i0 * i1) + (i2 * i3))}}[(0, 1)]<gpuarray>(InplaceGpuDimShuffle{x,x,x}.0, GpuGemmBatch{inplace=True}.0, InplaceGpuDimShuffle{x,x,x}.0, GpuFromHost<None>.0)]]\n\nBacktrace when the node is created(use Theano flag traceback.limit=N to make it longer):\n File "/usr/lib/python2.7/dist-packages/nose/case.py", line 133, in run\n self.runTest(result)\n File "/usr/lib/python2.7/dist-packages/nose/case.py", line 151, in runTest\n test(result)\n File "/usr/lib/python2.7/unittest/case.py", line 393, in __call__\n return self.run(*args, **kwds)\n File "/usr/lib/python2.7/unittest/case.py", line 329, in run\n testMethod()\n File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_basic_ops.py", line 97, in test_all\n self.run_case(testname, inputs)\n File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_basic_ops.py", line 105, in run_case\n node_tst = safe_make_node(self.op, *inputs_tst)\n File "/usr/local/lib/python2.7/dist-packages/theano/tensor/tests/test_basic.py", line 203, in safe_make_node\n node = op(*inputs)\n File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_blas.py", line 153, in <lambda>\n op=lambda z, alpha, x, y, beta: alpha * batched_dot(x, y) + beta * z,\n File "/usr/lib/python2.7/dist-packages/nose/case.py", line 133, in run\n self.runTest(result)\n File "/usr/lib/python2.7/dist-packages/nose/case.py", line 151, in runTest\n test(result)\n File "/usr/lib/python2.7/unittest/case.py", line 393, in __call__\n return self.run(*args, **kwds)\n File "/usr/lib/python2.7/unittest/case.py", line 329, in run\n testMethod()\n File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_basic_ops.py", line 97, in test_all\n self.run_case(testname, inputs)\n File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_basic_ops.py", line 105, in run_case\n node_tst = safe_make_node(self.op, *inputs_tst)\n File "/usr/local/lib/python2.7/dist-packages/theano/tensor/tests/test_basic.py", line 203, in safe_make_node\n node = op(*inputs)\n File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_blas.py", line 153, in <lambda>\n op=lambda z, alpha, x, y, beta: alpha * batched_dot(x, y) + beta * z,\n\nHINT: Use the Theano flag \'exception_verbosity=high\' for a debugprint and storage map footprint of this apply node.', 'Test GpuGemmBatch{inplace=True}::float16: exception when calling the Function')
-------------------- >> begin captured stdout << ---------------------
Disabling C code for BatchedDot due to unsupported float16
--------------------- >> end captured stdout << ----------------------
======================================================================
ERROR: theano.gpuarray.tests.test_dnn.test_conv3d_bwd((8, 1, 1030, 3, 4), (5, 1, 1025, 1, 1), (1, 1, 1), (1, 1, 1), 'full', 'conv')
----------------------------------------------------------------------
Traceback (most recent call last):
File "/usr/lib/python2.7/dist-packages/nose/case.py", line 197, in runTest
self.test(*self.arg)
File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_dnn.py", line 1300, in run_conv3d_bwd
utt.assert_allclose(res_ref[1], res[1], rtol=rtol)
File "/usr/local/lib/python2.7/dist-packages/theano/tests/unittest_tools.py", line 358, in assert_allclose
raise WrongValue(expected, value, rtol, atol)
WrongValue: WrongValue
: shape, dtype, strides, min, max, n_inf, n_nan:
Expected : (5, 1, 1025, 1, 1) float32 (4100, 4100, 4, 4, 4) 49362.3 49362.9 0 0
Value : (5, 1, 1025, 1, 1) float32 (4100, 4100, 4, 4, 4) 49363.0 49363.0 0 0
expected : [[[[[ 49362.30078125]]
[[ 49362.30078125]]
[[ 49362.30078125]]
...,
[[ 49362.92578125]]
[[ 49362.91796875]]
[[ 49362.91796875]]]]
[[[[ 49362.30078125]]
[[ 49362.30078125]]
[[ 49362.30078125]]
...,
[[ 49362.92578125]]
[[ 49362.91796875]]
[[ 49362.91796875]]]]
[[[[ 49362.30078125]]
[[ 49362.30078125]]
[[ 49362.30078125]]
...,
[[ 49362.92578125]]
[[ 49362.91796875]]
[[ 49362.91796875]]]]
[[[[ 49362.30078125]]
[[ 49362.30078125]]
[[ 49362.30078125]]
...,
[[ 49362.92578125]]
[[ 49362.91796875]]
[[ 49362.91796875]]]]
[[[[ 49362.30078125]]
[[ 49362.30078125]]
[[ 49362.30078125]]
...,
[[ 49362.92578125]]
[[ 49362.91796875]]
[[ 49362.91796875]]]]]
value : [[[[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]
...,
[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]]]
[[[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]
...,
[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]]]
[[[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]
...,
[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]]]
[[[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]
...,
[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]]]
[[[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]
...,
[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]]]]
Max Abs Diff: 0.660156
Mean Abs Diff: 0.0551105
Median Abs Diff: 0.046875
Std Abs Diff: 0.0788838
Max Rel Diff: 1.33737e-05
Mean Rel Diff: 1.11644e-06
Median Rel Diff: 9.496e-07
Std Rel Diff: 1.59806e-06
rtol, atol: 1e-05 1e-05
----------------------------------------------------------------------
Ran 2836 tests in 2532.958s
FAILED (SKIP=576, errors=2)
mqg@svstation:~$ python -c "import theano; theano.test()"
Theano version 1.0.1
theano is installed in /usr/local/lib/python2.7/dist-packages/theano
NumPy version 1.13.3
NumPy relaxed strides checking option: True
NumPy is installed in /usr/local/lib/python2.7/dist-packages/numpy
Python version 2.7.12 (default, Nov 20 2017, 18:23:56) [GCC 5.4.0 20160609]
nose version 1.3.7
Using cuDNN version 7005 on context None
Mapped name None to device cuda: GeForce GTX 970 (0000:01:00.0)
..........................................ERROR (theano.gof.opt): Optimization failure due to: insert_bad_dtype
ERROR (theano.gof.opt): node: Elemwise{add,no_inplace}(<TensorType(float64, vector)>, <TensorType(float64, vector)>)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2059, in process_node
remove=remove)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
chk = fgraph.replace_all_validate(replacements, reason)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/toolbox.py", line 518, in replace_all_validate
fgraph.replace(r, new_r, reason=reason, verbose=False)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/fg.py", line 486, in replace
". The type of the replacement must be the same.", old, new)
BadOptimization: BadOptimization Error
Variable: id 140044072816400 Elemwise{Cast{float32}}.0
Op Elemwise{Cast{float32}}(Elemwise{add,no_inplace}.0)
Value Type: <type 'NoneType'>
Old Value: None
New Value: None
Reason: insert_bad_dtype. The type of the replacement must be the same.
Old Graph:
Elemwise{add,no_inplace} [id A] <TensorType(float64, vector)> ''
|<TensorType(float64, vector)> [id B] <TensorType(float64, vector)>
|<TensorType(float64, vector)> [id C] <TensorType(float64, vector)>
New Graph:
Elemwise{Cast{float32}} [id D] <TensorType(float32, vector)> ''
|Elemwise{add,no_inplace} [id A] <TensorType(float64, vector)> ''
Hint: relax the tolerance by setting tensor.cmp_sloppy=1
or even tensor.cmp_sloppy=2 for less-strict comparison
......................................S............................./usr/local/lib/python2.7/dist-packages/theano/compile/nanguardmode.py:150: RuntimeWarning: All-NaN slice encountered
return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))
/usr/local/lib/python2.7/dist-packages/theano/compile/nanguardmode.py:150: RuntimeWarning: All-NaN axis encountered
return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))
............................................../usr/local/lib/python2.7/dist-packages/theano/gof/vm.py:886: UserWarning: CVM does not support memory profile, using Stack VM.
'CVM does not support memory profile, using Stack VM.')
...........SS.............0.0581646137166
0.0581646137166
0.0581646137166
0.0581646137166
.................................................................................................................................................................../usr/local/lib/python2.7/dist-packages/theano/gof/vm.py:889: UserWarning: LoopGC does not support partial evaluation, using Stack VM.
'LoopGC does not support partial evaluation, '
...............................................................................^C
----------------------------------------------------------------------
Ran 425 tests in 179.138s
OK (SKIP=3)
mqg@svstation:~$ python -c "import theano; theano.test()"
Theano version 1.0.1
theano is installed in /usr/local/lib/python2.7/dist-packages/theano
NumPy version 1.13.3
NumPy relaxed strides checking option: True
NumPy is installed in /usr/local/lib/python2.7/dist-packages/numpy
Python version 2.7.12 (default, Nov 20 2017, 18:23:56) [GCC 5.4.0 20160609]
nose version 1.3.7
Using cuDNN version 7005 on context None
Mapped name None to device cuda: GeForce GTX 970 (0000:01:00.0)
..........................................ERROR (theano.gof.opt): Optimization failure due to: insert_bad_dtype
ERROR (theano.gof.opt): node: Elemwise{add,no_inplace}(<TensorType(float64, vector)>, <TensorType(float64, vector)>)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2059, in process_node
remove=remove)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
chk = fgraph.replace_all_validate(replacements, reason)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/toolbox.py", line 518, in replace_all_validate
fgraph.replace(r, new_r, reason=reason, verbose=False)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/fg.py", line 486, in replace
". The type of the replacement must be the same.", old, new)
BadOptimization: BadOptimization Error
Variable: id 140555820072720 Elemwise{Cast{float32}}.0
Op Elemwise{Cast{float32}}(Elemwise{add,no_inplace}.0)
Value Type: <type 'NoneType'>
Old Value: None
New Value: None
Reason: insert_bad_dtype. The type of the replacement must be the same.
Old Graph:
Elemwise{add,no_inplace} [id A] <TensorType(float64, vector)> ''
|<TensorType(float64, vector)> [id B] <TensorType(float64, vector)>
|<TensorType(float64, vector)> [id C] <TensorType(float64, vector)>
New Graph:
Elemwise{Cast{float32}} [id D] <TensorType(float32, vector)> ''
|Elemwise{add,no_inplace} [id A] <TensorType(float64, vector)> ''
Hint: relax the tolerance by setting tensor.cmp_sloppy=1
or even tensor.cmp_sloppy=2 for less-strict comparison
......................................S............................./usr/local/lib/python2.7/dist-packages/theano/compile/nanguardmode.py:150: RuntimeWarning: All-NaN slice encountered
return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))
/usr/local/lib/python2.7/dist-packages/theano/compile/nanguardmode.py:150: RuntimeWarning: All-NaN axis encountered
return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))
............................................../usr/local/lib/python2.7/dist-packages/theano/gof/vm.py:886: UserWarning: CVM does not support memory profile, using Stack VM.
'CVM does not support memory profile, using Stack VM.')
...........SS.............0.0581646137166
0.0581646137166
0.0581646137166
0.0581646137166
.................................................................................................................................................................../usr/local/lib/python2.7/dist-packages/theano/gof/vm.py:889: UserWarning: LoopGC does not support partial evaluation, using Stack VM.
'LoopGC does not support partial evaluation, '
...............................................................................^C
----------------------------------------------------------------------
Ran 425 tests in 178.520s
OK (SKIP=3)
mqg@svstation:~$ python -c "import theano; theano.test()"
Theano version 1.0.1
theano is installed in /usr/local/lib/python2.7/dist-packages/theano
NumPy version 1.13.3
NumPy relaxed strides checking option: True
NumPy is installed in /usr/local/lib/python2.7/dist-packages/numpy
Python version 2.7.12 (default, Nov 20 2017, 18:23:56) [GCC 5.4.0 20160609]
nose version 1.3.7
Using cuDNN version 7005 on context None
Mapped name None to device cuda: GeForce GTX 970 (0000:01:00.0)
..........................................ERROR (theano.gof.opt): Optimization failure due to: insert_bad_dtype
ERROR (theano.gof.opt): node: Elemwise{add,no_inplace}(<TensorType(float64, vector)>, <TensorType(float64, vector)>)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2059, in process_node
remove=remove)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
chk = fgraph.replace_all_validate(replacements, reason)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/toolbox.py", line 518, in replace_all_validate
fgraph.replace(r, new_r, reason=reason, verbose=False)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/fg.py", line 486, in replace
". The type of the replacement must be the same.", old, new)
BadOptimization: BadOptimization Error
Variable: id 140464786644752 Elemwise{Cast{float32}}.0
Op Elemwise{Cast{float32}}(Elemwise{add,no_inplace}.0)
Value Type: <type 'NoneType'>
Old Value: None
New Value: None
Reason: insert_bad_dtype. The type of the replacement must be the same.
Old Graph:
Elemwise{add,no_inplace} [id A] <TensorType(float64, vector)> ''
|<TensorType(float64, vector)> [id B] <TensorType(float64, vector)>
|<TensorType(float64, vector)> [id C] <TensorType(float64, vector)>
New Graph:
Elemwise{Cast{float32}} [id D] <TensorType(float32, vector)> ''
|Elemwise{add,no_inplace} [id A] <TensorType(float64, vector)> ''
Hint: relax the tolerance by setting tensor.cmp_sloppy=1
or even tensor.cmp_sloppy=2 for less-strict comparison
......................................S............................./usr/local/lib/python2.7/dist-packages/theano/compile/nanguardmode.py:150: RuntimeWarning: All-NaN slice encountered
return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))
/usr/local/lib/python2.7/dist-packages/theano/compile/nanguardmode.py:150: RuntimeWarning: All-NaN axis encountered
return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))
............................................../usr/local/lib/python2.7/dist-packages/theano/gof/vm.py:886: UserWarning: CVM does not support memory profile, using Stack VM.
'CVM does not support memory profile, using Stack VM.')
...........SS.............0.0581646137166
0.0581646137166
0.0581646137166
0.0581646137166
.................................................................................................................................................................../usr/local/lib/python2.7/dist-packages/theano/gof/vm.py:889: UserWarning: LoopGC does not support partial evaluation, using Stack VM.
'LoopGC does not support partial evaluation, '
................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS...............S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSS..................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSS..............SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS............................../usr/lib/python2.7/unittest/case.py:329: DeprecationWarning: stack(*tensors) interface is deprecated, use stack(tensors, axis=0) instead.
testMethod()
.................................................................................E...........................................SSS................SSS......................SSS....................................WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 18, 18, 17), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 9, 9, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 11, 10, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 18, 18, 17), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 9, 9, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 11, 10, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 16, 16, 17), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 8, 8, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 8, 8, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 16, 16, 17), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 8, 8, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (10, 8, 8, 8, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
...WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConvGradI'>, we received an input with a shape that has some repeated values: (3, 4, 1, 1), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConvGradI'>, we received an input with a shape that has some repeated values: (3, 4, 1, 1), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.....WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConvGradW'>, we received an input with a shape that has some repeated values: (5, 1, 2, 1), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConvGradW'>, we received an input with a shape that has some repeated values: (5, 1, 2, 1), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 8, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 8, 9), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 7, 8), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 7, 8), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.dnn.GpuDnnConv'>, we received an input with a shape that has some repeated values: (7, 8, 5, 7), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
........../usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_dnn.py:1408: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.grad(T.nnet.softmax(y).mean(), y),
/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_dnn.py:1434: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.grad(T.nnet.softmax(y).mean(), y),
.......................................................................................................................................................................................................................................................................................................................................................E................................................................................................................................................................WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.elemwise.GpuCAReduceCuda'>, we received an input with a shape that has some repeated values: (128, 1, 3, 3), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
WARNING (theano.tests.unittest_tools): While testing shape inference for <class 'theano.gpuarray.elemwise.GpuCAReduceCuda'>, we received an input with a shape that has some repeated values: (128, 1, 3, 3), like a square matrix. This makes it impossible to check if the values for these dimensions have been correctly used, or if they have been mixed up.
.......................................S.........................................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS..../usr/local/lib/python2.7/dist-packages/theano/sandbox/rng_mrg.py:1031: UserWarning: MRG_RandomStreams.multinomial_wo_replacement() is deprecated and will be removed in the next release of Theano. Please use MRG_RandomStreams.choice() instead.
warnings.warn('MRG_RandomStreams.multinomial_wo_replacement() is '
........................................ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 3, 5, 5), kshp=(12, 3, 3, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 3, 5, 5), kshp=(12, 3, 3, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 3, 5, 5), kshp=(12, 3, 3, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 3, 5, 5), kshp=(12, 3, 3, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 3, 5, 5), kshp=(12, 3, 3, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 2, 7, 5), kshp=(9, 2, 5, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 2, 7, 5), kshp=(9, 2, 5, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 2, 7, 5), kshp=(9, 2, 5, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 2, 7, 5), kshp=(9, 2, 5, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 2, 7, 5), kshp=(9, 2, 5, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(6, 1, 3, 3), kshp=(4, 1, 1, 1), filter_dilation=(1, 1), num_groups=1, unshared=False}(InplaceGpuDimShuffle{0,x,1,2}.0, InplaceGpuDimShuffle{0,x,x,x}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(6, 1, 3, 3), kshp=(4, 1, 1, 1), filter_dilation=(1, 1), num_groups=1, unshared=False}(InplaceGpuDimShuffle{0,x,1,2}.0, InplaceGpuDimShuffle{0,x,x,x}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(6, 1, 3, 3), kshp=(4, 1, 1, 1), filter_dilation=(1, 1), num_groups=1, unshared=False}(InplaceGpuDimShuffle{0,x,1,2}.0, InplaceGpuDimShuffle{0,x,x,x}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(6, 1, 3, 3), kshp=(4, 1, 1, 1), filter_dilation=(1, 1), num_groups=1, unshared=False}(InplaceGpuDimShuffle{0,x,1,2}.0, InplaceGpuDimShuffle{0,x,x,x}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(6, 1, 3, 3), kshp=(4, 1, 1, 1), filter_dilation=(1, 1), num_groups=1, unshared=False}(InplaceGpuDimShuffle{0,x,1,2}.0, InplaceGpuDimShuffle{0,x,x,x}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
................SS......SSSSS.....................SSSS.../usr/local/lib/python2.7/dist-packages/theano/tensor/basic.py:2184: UserWarning: theano.tensor.round() changed its default from `half_away_from_zero` to `half_to_even` to have the same default as NumPy. Use the Theano flag `warn.round=False` to disable this warning.
"theano.tensor.round() changed its default from"
.......S/usr/local/lib/python2.7/dist-packages/theano/gpuarray/type.py:861: UserWarning: config.experimental.unpickle_gpu_on_cpu is set to True. Unpickling GpuArray as numpy.ndarray
"config.experimental.unpickle_gpu_on_cpu is set to True. "
.....................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................S.................................................................................................S...S.......................................
.
.
...........
....S...................S........................................................................................................../usr/lib/python2.7/dist-packages/scipy/sparse/data.py:61: ComplexWarning: Casting complex values to real discards the imaginary part
return self._with_data(self.data.astype(t))
/usr/local/lib/python2.7/dist-packages/theano/sparse/tests/test_basic.py:2414: ComplexWarning: Casting complex values to real discards the imaginary part
expected = data.toarray().astype(o_dtype)
...../usr/lib/python2.7/dist-packages/scipy/sparse/compressed.py:730: SparseEfficiencyWarning: Changing the sparsity structure of a csc_matrix is expensive. lil_matrix is more efficient.
SparseEfficiencyWarning)
/usr/lib/python2.7/dist-packages/scipy/sparse/compressed.py:730: SparseEfficiencyWarning: Changing the sparsity structure of a csr_matrix is expensive. lil_matrix is more efficient.
SparseEfficiencyWarning)
.......................................................S........S..........................................S....................../usr/lib/python2.7/dist-packages/scipy/sparse/compressed.py:296: SparseEfficiencyWarning: Comparing sparse matrices using >= and <= is inefficient, using <, >, or !=, instead.
"using <, >, or !=, instead.", SparseEfficiencyWarning)
...................................S.............................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................../usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
......................................................................................................SSS............................/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1008: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(x)[T.arange(y.shape[0]), y])),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1009: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(x)[T.arange(y.shape[0]), y]))]
./usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1055: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(x + b)[T.arange(y.shape[0]), y])),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1056: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(b + x)[T.arange(y.shape[0]), y])),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1057: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(x + b))[T.arange(y.shape[0]), y]),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1058: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(b + x))[T.arange(y.shape[0]), y])]
./usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1116: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(x + b)[T.arange(y.shape[0]), y])),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1117: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(b + x)[T.arange(y.shape[0]), y])),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1118: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(x + b))[T.arange(y.shape[0]), y]),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1119: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(b + x))[T.arange(y.shape[0]), y])]
./usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1178: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(x + b)[T.arange(y.shape[0]), y])),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1179: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(b + x)[T.arange(y.shape[0]), y])),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1180: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(x + b))[T.arange(y.shape[0]), y]),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1181: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(b + x))[T.arange(y.shape[0]), y])]
./usr/local/lib/python2.7/dist-packages/theano/gof/opt.py:242: UserWarning: WARNING: Supervisor is not added. Please build a FunctionGraphvia theano.compile.function_module.std_graph()or add the Supervisor class manually.
sub_prof = optimizer.optimize(fgraph)
./usr/lib/python2.7/unittest/case.py:329: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
testMethod()
............................./usr/lib/python2.7/unittest/case.py:329: UserWarning: DEPRECATION: If x is a vector, LogSoftmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
testMethod()
./usr/local/lib/python2.7/dist-packages/theano/gradient.py:1728: UserWarning: DEPRECATION: If x is a vector, LogSoftmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
o_output = fun(*tensor_pt)
......./usr/local/lib/python2.7/dist-packages/theano/gradient.py:1728: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
o_output = fun(*tensor_pt)
......../usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:155: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
sm = T.nnet.softmax(a + b)
........S..SS....................................................................................................................................................................................................................................................................................................................................................................................................................................................................................../usr/local/lib/python2.7/dist-packages/theano/tensor/signal/tests/test_pool.py:919: UserWarning: DEPRECATION: the 'ds' parameter is not going to exist anymore as it is going to be replaced by the parameter 'ws'.
mode=mode)
/usr/local/lib/python2.7/dist-packages/theano/tensor/signal/tests/test_pool.py:919: UserWarning: DEPRECATION: the 'st' parameter is not going to exist anymore as it is going to be replaced by the parameter 'stride'.
mode=mode)
/usr/local/lib/python2.7/dist-packages/theano/tensor/signal/tests/test_pool.py:919: UserWarning: DEPRECATION: the 'padding' parameter is not going to exist anymore as it is going to be replaced by the parameter 'pad'.
mode=mode)
.S../usr/local/lib/python2.7/dist-packages/theano/tensor/signal/tests/test_pool.py:1103: UserWarning: DEPRECATION: the 'ds' parameter is not going to exist anymore as it is going to be replaced by the parameter 'ws'.
mode=mode)
/usr/local/lib/python2.7/dist-packages/theano/tensor/signal/tests/test_pool.py:1103: UserWarning: DEPRECATION: the 'st' parameter is not going to exist anymore as it is going to be replaced by the parameter 'stride'.
mode=mode)
/usr/local/lib/python2.7/dist-packages/theano/tensor/signal/tests/test_pool.py:1103: UserWarning: DEPRECATION: the 'padding' parameter is not going to exist anymore as it is going to be replaced by the parameter 'pad'.
mode=mode)
/usr/local/lib/python2.7/dist-packages/theano/tensor/signal/tests/test_pool.py:1119: UserWarning: DEPRECATION: the 'ds' parameter is not going to exist anymore as it is going to be replaced by the parameter 'ws'.
mode=mode)
/usr/local/lib/python2.7/dist-packages/theano/tensor/signal/tests/test_pool.py:1119: UserWarning: DEPRECATION: the 'st' parameter is not going to exist anymore as it is going to be replaced by the parameter 'stride'.
mode=mode)
/usr/local/lib/python2.7/dist-packages/theano/tensor/signal/tests/test_pool.py:1119: UserWarning: DEPRECATION: the 'padding' parameter is not going to exist anymore as it is going to be replaced by the parameter 'pad'.
mode=mode)
....................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................../usr/lib/python2.7/unittest/case.py:329: DeprecationWarning: stack(*tensors) interface is deprecated, use stack(tensors, axis=0) instead.
testMethod()
............................................................................................................................................../usr/local/lib/python2.7/dist-packages/theano/tensor/tests/test_basic.py:8227: UserWarning: Tile op is deprecated, use tile function instead.
[Tile(ndim)(advec, aivec_val)],
/usr/local/lib/python2.7/dist-packages/theano/tensor/tests/test_basic.py:8235: UserWarning: Tile op is deprecated, use tile function instead.
[Tile(ndim)(admat, aivec_val)],
/usr/local/lib/python2.7/dist-packages/theano/tensor/tests/test_basic.py:8243: UserWarning: Tile op is deprecated, use tile function instead.
[Tile(ndim)(adtens4, aivec_val)],
...........................................................................................................S........................................................F........................................................................................................................./usr/local/lib/python2.7/dist-packages/theano/tensor/basic.py:5262: UserWarning: flatten outdim parameter is deprecated, use ndim instead.
"flatten outdim parameter is deprecated, use ndim instead.")
...........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................S..SSSS.S..........................................................................................................S.....................S.............................../usr/local/lib/python2.7/dist-packages/theano/tensor/nlinalg.py:175: DeprecationWarning: DeprecationWarning: theano.tensor.nlinalg.AllocDiagis deprecated, please use theano.tensor.AllocDiaginstead.
category=DeprecationWarning)
/usr/local/lib/python2.7/dist-packages/theano/tensor/nlinalg.py:175: DeprecationWarning: DeprecationWarning: theano.tensor.nlinalg.AllocDiagis deprecated, please use theano.tensor.AllocDiaginstead.
category=DeprecationWarning)
./usr/local/lib/python2.7/dist-packages/theano/tensor/nlinalg.py:175: DeprecationWarning: DeprecationWarning: theano.tensor.nlinalg.AllocDiagis deprecated, please use theano.tensor.AllocDiaginstead.
category=DeprecationWarning)
./usr/local/lib/python2.7/dist-packages/theano/tensor/nlinalg.py:175: DeprecationWarning: DeprecationWarning: theano.tensor.nlinalg.AllocDiagis deprecated, please use theano.tensor.AllocDiaginstead.
category=DeprecationWarning)
.................................................................................................................................S.S..S............../usr/local/lib/python2.7/dist-packages/theano/tensor/opt.py:3523: UserWarning: Your current code is fine, but Theano versions between 0.7rc1 and 0.10 (or development versions between Nov. 2014 and May 2017) might have given incorrect results. This graph has following pattern: inc_subtensor(zeros[idx], x)[idx], where idx is an array of integers. This used to be optimized to "x", which is incorrect if there are duplicated indices in idx. To disable this warning, set the Theano flag warn.inc_subtensor1_opt to False.
'Your current code is fine, but Theano versions '
......................................................S..............S..........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................S/usr/lib/python2.7/unittest/case.py:329: UserWarning: consider_constant() is deprecated, use zero_grad() or disconnected_grad() instead.
testMethod()
................................................SS......SSSSS...SSSS.......S..........S.S............../usr/local/lib/python2.7/dist-packages/theano/tests/test_rop.py:388: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
self.check_rop_lop(tensor.nnet.softmax(self.x)[0], self.in_shape[0])
.......
======================================================================
ERROR: test_all (theano.gpuarray.tests.test_blas.GpuGemmBatchTester)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_basic_ops.py", line 97, in test_all
self.run_case(testname, inputs)
File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_basic_ops.py", line 131, in run_case
variables = f_tst()
File "/usr/local/lib/python2.7/dist-packages/theano/compile/function_module.py", line 917, in __call__
storage_map=getattr(self.fn, 'storage_map', None))
File "/usr/local/lib/python2.7/dist-packages/theano/gof/link.py", line 325, in raise_with_op
reraise(exc_type, exc_value, exc_trace)
File "/usr/local/lib/python2.7/dist-packages/theano/compile/function_module.py", line 903, in __call__
self.fn() if output_subset is None else\
RuntimeError: ('Blas operation not supported by library in use: hgemmBatch\nApply node that caused the error: GpuGemmBatch{inplace=True}(GpuAllocEmpty{dtype=\'float16\', context_name=None}.0, TensorConstant{1.0}, GpuFromHost<None>.0, GpuFromHost<None>.0, TensorConstant{0.0})\nToposort index: 11\nInputs types: [GpuArrayType<None>(float16, 3D), TensorType(float32, scalar), GpuArrayType<None>(float16, 3D), GpuArrayType<None>(float16, 3D), TensorType(float32, scalar)]\nInputs shapes: [(3, 4, 7), (), (3, 4, 4), (3, 4, 7), ()]\nInputs strides: [(56, 14, 2), (), (32, 8, 2), (56, 14, 2), ()]\nInputs values: [\'not shown\', array(1.0, dtype=float32), \'not shown\', \'not shown\', array(0.0, dtype=float32)]\nOutputs clients: [[GpuElemwise{Composite{((i0 * i1) + (i2 * i3))}}[(0, 1)]<gpuarray>(InplaceGpuDimShuffle{x,x,x}.0, GpuGemmBatch{inplace=True}.0, InplaceGpuDimShuffle{x,x,x}.0, GpuFromHost<None>.0)]]\n\nBacktrace when the node is created(use Theano flag traceback.limit=N to make it longer):\n File "/usr/lib/python2.7/dist-packages/nose/case.py", line 133, in run\n self.runTest(result)\n File "/usr/lib/python2.7/dist-packages/nose/case.py", line 151, in runTest\n test(result)\n File "/usr/lib/python2.7/unittest/case.py", line 393, in __call__\n return self.run(*args, **kwds)\n File "/usr/lib/python2.7/unittest/case.py", line 329, in run\n testMethod()\n File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_basic_ops.py", line 97, in test_all\n self.run_case(testname, inputs)\n File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_basic_ops.py", line 105, in run_case\n node_tst = safe_make_node(self.op, *inputs_tst)\n File "/usr/local/lib/python2.7/dist-packages/theano/tensor/tests/test_basic.py", line 203, in safe_make_node\n node = op(*inputs)\n File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_blas.py", line 153, in <lambda>\n op=lambda z, alpha, x, y, beta: alpha * batched_dot(x, y) + beta * z,\n File "/usr/lib/python2.7/dist-packages/nose/case.py", line 133, in run\n self.runTest(result)\n File "/usr/lib/python2.7/dist-packages/nose/case.py", line 151, in runTest\n test(result)\n File "/usr/lib/python2.7/unittest/case.py", line 393, in __call__\n return self.run(*args, **kwds)\n File "/usr/lib/python2.7/unittest/case.py", line 329, in run\n testMethod()\n File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_basic_ops.py", line 97, in test_all\n self.run_case(testname, inputs)\n File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_basic_ops.py", line 105, in run_case\n node_tst = safe_make_node(self.op, *inputs_tst)\n File "/usr/local/lib/python2.7/dist-packages/theano/tensor/tests/test_basic.py", line 203, in safe_make_node\n node = op(*inputs)\n File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_blas.py", line 153, in <lambda>\n op=lambda z, alpha, x, y, beta: alpha * batched_dot(x, y) + beta * z,\n\nHINT: Use the Theano flag \'exception_verbosity=high\' for a debugprint and storage map footprint of this apply node.', 'Test GpuGemmBatch{inplace=True}::float16: exception when calling the Function')
-------------------- >> begin captured stdout << ---------------------
Disabling C code for BatchedDot due to unsupported float16
--------------------- >> end captured stdout << ----------------------
======================================================================
ERROR: theano.gpuarray.tests.test_dnn.test_conv3d_bwd((8, 1, 1030, 3, 4), (5, 1, 1025, 1, 1), (1, 1, 1), (1, 1, 1), 'full', 'conv')
----------------------------------------------------------------------
Traceback (most recent call last):
File "/usr/lib/python2.7/dist-packages/nose/case.py", line 197, in runTest
self.test(*self.arg)
File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_dnn.py", line 1300, in run_conv3d_bwd
utt.assert_allclose(res_ref[1], res[1], rtol=rtol)
File "/usr/local/lib/python2.7/dist-packages/theano/tests/unittest_tools.py", line 358, in assert_allclose
raise WrongValue(expected, value, rtol, atol)
WrongValue: WrongValue
: shape, dtype, strides, min, max, n_inf, n_nan:
Expected : (5, 1, 1025, 1, 1) float32 (4100, 4100, 4, 4, 4) 49362.3 49362.9 0 0
Value : (5, 1, 1025, 1, 1) float32 (4100, 4100, 4, 4, 4) 49363.0 49363.0 0 0
expected : [[[[[ 49362.30078125]]
[[ 49362.30078125]]
[[ 49362.30078125]]
...,
[[ 49362.92578125]]
[[ 49362.91796875]]
[[ 49362.91796875]]]]
[[[[ 49362.30078125]]
[[ 49362.30078125]]
[[ 49362.30078125]]
...,
[[ 49362.92578125]]
[[ 49362.91796875]]
[[ 49362.91796875]]]]
[[[[ 49362.30078125]]
[[ 49362.30078125]]
[[ 49362.30078125]]
...,
[[ 49362.92578125]]
[[ 49362.91796875]]
[[ 49362.91796875]]]]
[[[[ 49362.30078125]]
[[ 49362.30078125]]
[[ 49362.30078125]]
...,
[[ 49362.92578125]]
[[ 49362.91796875]]
[[ 49362.91796875]]]]
[[[[ 49362.30078125]]
[[ 49362.30078125]]
[[ 49362.30078125]]
...,
[[ 49362.92578125]]
[[ 49362.91796875]]
[[ 49362.91796875]]]]]
value : [[[[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]
...,
[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]]]
[[[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]
...,
[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]]]
[[[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]
...,
[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]]]
[[[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]
...,
[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]]]
[[[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]
...,
[[ 49362.9609375]]
[[ 49362.9609375]]
[[ 49362.9609375]]]]]
Max Abs Diff: 0.660156
Mean Abs Diff: 0.0551105
Median Abs Diff: 0.046875
Std Abs Diff: 0.0788838
Max Rel Diff: 1.33737e-05
Mean Rel Diff: 1.11644e-06
Median Rel Diff: 9.496e-07
Std Rel Diff: 1.59806e-06
rtol, atol: 1e-05 1e-05
======================================================================
FAIL: test_weird_valid_axes (theano.tensor.tests.test_basic.test_tensordot)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/tests/test_basic.py", line 6587, in test_weird_valid_axes
f3(aval, bval)))
AssertionError: False is not true
----------------------------------------------------------------------
Ran 10803 tests in 9561.865s
FAILED (SKIP=665, errors=2, failures=1)
And this is my .theanorc file:
[global]
floatX = float32
device = cpu
[cuda]
root = /usr/local/cuda-9.1
[lib]
cnmem = 1.0
#[gpuarray]
#preallocate = 0.7
[global]
config.compile.timeout = 1000
[blas]
ldflags=-L/usr/lib/ -lblas
[nvcc]
flags=-D_FORCE_INLINES
I tried previously mentioned solutions but not any of them worked out. Could you please help me to solve the errors, and should I be worried about any of the warnings?
Thank you, bests.
quintasxcv
on 16 Dec 2017
You can ignore those errors. They are problems in the tests. It won't affect you. But to help us make those tests pass in your environment, can you do tell us what is your CUDA version and driver version?
Also, can you try this diff and run the test again?
```
diff --git a/theano/gpuarray/tests/test_dnn.py b/theano/gpuarray/tests/test_dnn.py
index a697da89f..910c57d54 100644
--- a/theano/gpuarray/tests/test_dnn.py
+++ b/theano/gpuarray/tests/test_dnn.py
@@ -1296,6 +1296,8 @@ def test_conv3d_bwd():
# Raise tolerance for float16
if theano.config.floatX == 'float16':
rtol = 5e-2
- elif max(inputs_shape) > 1024 or max(filters_shape) > 1024:
- rtol = 2e-5
utt.assert_allclose(res_ref[0], res[0], rtol=rtol)
utt.assert_allclose(res_ref[1], res[1], rtol=rtol)
diff --git a/theano/tensor/tests/test_basic.py b/theano/tensor/tests/test_basic.py
index 4ea96b1c6..2ec41a147 100644
--- a/theano/tensor/tests/test_basic.py
+++ b/theano/tensor/tests/test_basic.py
@@ -6583,8 +6583,8 @@ class test_tensordot(unittest.TestCase):
f3 = inplace_func([amat, bmat], c)
aval = rand(4, 7)
bval = rand(7, 9)
- self.assertTrue(np.allclose(np.tensordot(aval, bval, axes),
- f3(aval, bval)))
- utt.assert_allclose(np.tensordot(aval, bval, axes),
- f3(aval, bval))
utt.verify_grad(self.TensorDot(axes), [aval, bval])
def test_scalar_axes(self):
```
nouiz
on 18 Dec 2017
Cuda version is 9.1, when you say apply the diff you mean store the instructions that you have posted in a diff file, then go to my python dist-packages (where Theano source files are located) and run the command git apply
Thank you for your help.
quintasxcv
on 19 Dec 2017
Here the output:
Theano version 1.0.1 New Graph: Hint: relax the tolerance by setting tensor.cmp_sloppy=1 ......................................S............................./usr/local/lib/python2.7/dist-packages/theano/compile/nanguardmode.py:150: RuntimeWarning: All-NaN slice encountered ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check ................SS......SSSSS.....................SSSS.../usr/local/lib/python2.7/dist-packages/theano/tensor/basic.py:2184: UserWarning: theano.tensor.round() changed its default from Traceback (most recent call last): --------------------- >> end captured stdout << ---------------------- ====================================================================== Traceback (most recent call last): Ran 10803 tests in 9725.845s FAILED (SKIP=665, errors=2)
theano is installed in /usr/local/lib/python2.7/dist-packages/theano
NumPy version 1.13.3
NumPy relaxed strides checking option: True
NumPy is installed in /usr/local/lib/python2.7/dist-packages/numpy
Python version 2.7.12 (default, Nov 20 2017, 18:23:56) [GCC 5.4.0 20160609]
nose version 1.3.7
Using cuDNN version 7005 on context None
Mapped name None to device cuda: GeForce GTX 970 (0000:01:00.0)
..........................................ERROR (theano.gof.opt): Optimization failure due to: insert_bad_dtype
ERROR (theano.gof.opt): node: Elemwise{add,no_inplace}(
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2059, in process_node
remove=remove)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
chk = fgraph.replace_all_validate(replacements, reason)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/toolbox.py", line 518, in replace_all_validate
fgraph.replace(r, new_r, reason=reason, verbose=False)
File "/usr/local/lib/python2.7/dist-packages/theano/gof/fg.py", line 486, in replace
". The type of the replacement must be the same.", old, new)
BadOptimization: BadOptimization Error
Variable: id 139846715929040 Elemwise{Cast{float32}}.0
Op Elemwise{Cast{float32}}(Elemwise{add,no_inplace}.0)
Value Type:
Old Value: None
New Value: None
Reason: insert_bad_dtype. The type of the replacement must be the same.
Old Graph:
Elemwise{add,no_inplace} [id A]
Elemwise{Cast{float32}} [id D]
or even tensor.cmp_sloppy=2 for less-strict comparison
return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))
/usr/local/lib/python2.7/dist-packages/theano/compile/nanguardmode.py:150: RuntimeWarning: All-NaN axis encountered
return np.isinf(np.nanmax(arr)) or np.isinf(np.nanmin(arr))
............................................../usr/local/lib/python2.7/dist-packages/theano/gof/vm.py:886: UserWarning: CVM does not support memory profile, using Stack VM.
'CVM does not support memory profile, using Stack VM.')
...........SS.............0.0581646137166
0.0581646137166
0.0581646137166
0.0581646137166
.................................................................................................................................................................../usr/local/lib/python2.7/dist-packages/theano/gof/vm.py:889: UserWarning: LoopGC does not support partial evaluation, using Stack VM.
'LoopGC does not support partial evaluation, '
................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS........................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS...............S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S.S................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSS..................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSS..............SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS............................../usr/lib/python2.7/unittest/case.py:329: DeprecationWarning: stack(*tensors) interface is deprecated, use stack(tensors, axis=0) instead.
testMethod()
.................................................................................E...........................................SSS................SSS......................SSS....................................WARNING (theano.tests.unittest_tools): While testing shape inference for
WARNING (theano.tests.unittest_tools): While testing shape inference for
WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
WARNING (theano.tests.unittest_tools): While testing shape inference for
WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
WARNING (theano.tests.unittest_tools): While testing shape inference for
WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
WARNING (theano.tests.unittest_tools): While testing shape inference for
WARNING (theano.tests.unittest_tools): While testing shape inference for
...WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
WARNING (theano.tests.unittest_tools): While testing shape inference for
.....WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
.WARNING (theano.tests.unittest_tools): While testing shape inference for
........../usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_dnn.py:1410: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.grad(T.nnet.softmax(y).mean(), y),
/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_dnn.py:1436: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.grad(T.nnet.softmax(y).mean(), y),
........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................WARNING (theano.tests.unittest_tools): While testing shape inference for
WARNING (theano.tests.unittest_tools): While testing shape inference for
.......................................S.........................................SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS..../usr/local/lib/python2.7/dist-packages/theano/sandbox/rng_mrg.py:1031: UserWarning: MRG_RandomStreams.multinomial_wo_replacement() is deprecated and will be removed in the next release of Theano. Please use MRG_RandomStreams.choice() instead.
warnings.warn('MRG_RandomStreams.multinomial_wo_replacement() is '
........................................ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 3, 5, 5), kshp=(12, 3, 3, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 3, 5, 5), kshp=(12, 3, 3, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 3, 5, 5), kshp=(12, 3, 3, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 3, 5, 5), kshp=(12, 3, 3, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 3, 5, 5), kshp=(12, 3, 3, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 2, 7, 5), kshp=(9, 2, 5, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 2, 7, 5), kshp=(9, 2, 5, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 2, 7, 5), kshp=(9, 2, 5, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 2, 7, 5), kshp=(9, 2, 5, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(10, 2, 7, 5), kshp=(9, 2, 5, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(GpuReshape{4}.0, GpuReshape{4}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(6, 1, 3, 3), kshp=(4, 1, 1, 1), filter_dilation=(1, 1), num_groups=1, unshared=False}(InplaceGpuDimShuffle{0,x,1,2}.0, InplaceGpuDimShuffle{0,x,x,x}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(6, 1, 3, 3), kshp=(4, 1, 1, 1), filter_dilation=(1, 1), num_groups=1, unshared=False}(InplaceGpuDimShuffle{0,x,1,2}.0, InplaceGpuDimShuffle{0,x,x,x}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(6, 1, 3, 3), kshp=(4, 1, 1, 1), filter_dilation=(1, 1), num_groups=1, unshared=False}(InplaceGpuDimShuffle{0,x,1,2}.0, InplaceGpuDimShuffle{0,x,x,x}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(6, 1, 3, 3), kshp=(4, 1, 1, 1), filter_dilation=(1, 1), num_groups=1, unshared=False}(InplaceGpuDimShuffle{0,x,1,2}.0, InplaceGpuDimShuffle{0,x,x,x}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode='valid', subsample=(1, 1), filter_flip=True, imshp=(6, 1, 3, 3), kshp=(4, 1, 1, 1), filter_dilation=(1, 1), num_groups=1, unshared=False}(InplaceGpuDimShuffle{0,x,1,2}.0, InplaceGpuDimShuffle{0,x,x,x}.0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/theano/gof/opt.py", line 2019, in process_node
replacements = lopt.transform(node)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.half_away_from_zero to half_to_even to have the same default as NumPy. Use the Theano flag warn.round=False to disable this warning.
"theano.tensor.round() changed its default from"
......ES/usr/local/lib/python2.7/dist-packages/theano/gpuarray/type.py:861: UserWarning: config.experimental.unpickle_gpu_on_cpu is set to True. Unpickling GpuArray as numpy.ndarray
"config.experimental.unpickle_gpu_on_cpu is set to True. "
.....................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................S.................................................................................................S...S.......................................
.
.
...........
....S...................S........................................................................................................../usr/lib/python2.7/dist-packages/scipy/sparse/data.py:61: ComplexWarning: Casting complex values to real discards the imaginary part
return self._with_data(self.data.astype(t))
/usr/local/lib/python2.7/dist-packages/theano/sparse/tests/test_basic.py:2414: ComplexWarning: Casting complex values to real discards the imaginary part
expected = data.toarray().astype(o_dtype)
...../usr/lib/python2.7/dist-packages/scipy/sparse/compressed.py:730: SparseEfficiencyWarning: Changing the sparsity structure of a csc_matrix is expensive. lil_matrix is more efficient.
SparseEfficiencyWarning)
/usr/lib/python2.7/dist-packages/scipy/sparse/compressed.py:730: SparseEfficiencyWarning: Changing the sparsity structure of a csr_matrix is expensive. lil_matrix is more efficient.
SparseEfficiencyWarning)
.......................................................S........S..........................................S....................../usr/lib/python2.7/dist-packages/scipy/sparse/compressed.py:296: SparseEfficiencyWarning: Comparing sparse matrices using >= and <= is inefficient, using <, >, or !=, instead.
"using <, >, or !=, instead.", SparseEfficiencyWarning)
...................................S.............................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................../usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/conv.py:98: UserWarning: theano.tensor.nnet.conv.conv2d is deprecated. Use theano.tensor.nnet.conv2d instead.
warnings.warn("theano.tensor.nnet.conv.conv2d is deprecated."
......................................................................................................SSS............................/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1008: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(x)[T.arange(y.shape[0]), y])),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1009: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(x)[T.arange(y.shape[0]), y]))]
./usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1055: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(x + b)[T.arange(y.shape[0]), y])),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1056: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(b + x)[T.arange(y.shape[0]), y])),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1057: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(x + b))[T.arange(y.shape[0]), y]),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1058: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(b + x))[T.arange(y.shape[0]), y])]
./usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1116: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(x + b)[T.arange(y.shape[0]), y])),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1117: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(b + x)[T.arange(y.shape[0]), y])),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1118: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(x + b))[T.arange(y.shape[0]), y]),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1119: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(b + x))[T.arange(y.shape[0]), y])]
./usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1178: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(x + b)[T.arange(y.shape[0]), y])),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1179: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(b + x)[T.arange(y.shape[0]), y])),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1180: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
-T.sum(T.log(softmax(x + b))[T.arange(y.shape[0]), y]),
/usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:1181: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
T.sum(-T.log(softmax(b + x))[T.arange(y.shape[0]), y])]
./usr/local/lib/python2.7/dist-packages/theano/gof/opt.py:242: UserWarning: WARNING: Supervisor is not added. Please build a FunctionGraphvia theano.compile.function_module.std_graph()or add the Supervisor class manually.
sub_prof = optimizer.optimize(fgraph)
./usr/lib/python2.7/unittest/case.py:329: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
testMethod()
............................./usr/lib/python2.7/unittest/case.py:329: UserWarning: DEPRECATION: If x is a vector, LogSoftmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
testMethod()
./usr/local/lib/python2.7/dist-packages/theano/gradient.py:1728: UserWarning: DEPRECATION: If x is a vector, LogSoftmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
o_output = fun(tensor_pt)
......./usr/local/lib/python2.7/dist-packages/theano/gradient.py:1728: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
o_output = fun(tensor_pt)
......../usr/local/lib/python2.7/dist-packages/theano/tensor/nnet/tests/test_nnet.py:155: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
sm = T.nnet.softmax(a + b)
........S..SS....................................................................................................................................................................................................................................................................................................................................................................................................................................................................................../usr/local/lib/python2.7/dist-packages/theano/tensor/signal/tests/test_pool.py:919: UserWarning: DEPRECATION: the 'ds' parameter is not going to exist anymore as it is going to be replaced by the parameter 'ws'.
mode=mode)
/usr/local/lib/python2.7/dist-packages/theano/tensor/signal/tests/test_pool.py:919: UserWarning: DEPRECATION: the 'st' parameter is not going to exist anymore as it is going to be replaced by the parameter 'stride'.
mode=mode)
/usr/local/lib/python2.7/dist-packages/theano/tensor/signal/tests/test_pool.py:919: UserWarning: DEPRECATION: the 'padding' parameter is not going to exist anymore as it is going to be replaced by the parameter 'pad'.
mode=mode)
.S../usr/local/lib/python2.7/dist-packages/theano/tensor/signal/tests/test_pool.py:1103: UserWarning: DEPRECATION: the 'ds' parameter is not going to exist anymore as it is going to be replaced by the parameter 'ws'.
mode=mode)
/usr/local/lib/python2.7/dist-packages/theano/tensor/signal/tests/test_pool.py:1103: UserWarning: DEPRECATION: the 'st' parameter is not going to exist anymore as it is going to be replaced by the parameter 'stride'.
mode=mode)
/usr/local/lib/python2.7/dist-packages/theano/tensor/signal/tests/test_pool.py:1103: UserWarning: DEPRECATION: the 'padding' parameter is not going to exist anymore as it is going to be replaced by the parameter 'pad'.
mode=mode)
/usr/local/lib/python2.7/dist-packages/theano/tensor/signal/tests/test_pool.py:1119: UserWarning: DEPRECATION: the 'ds' parameter is not going to exist anymore as it is going to be replaced by the parameter 'ws'.
mode=mode)
/usr/local/lib/python2.7/dist-packages/theano/tensor/signal/tests/test_pool.py:1119: UserWarning: DEPRECATION: the 'st' parameter is not going to exist anymore as it is going to be replaced by the parameter 'stride'.
mode=mode)
/usr/local/lib/python2.7/dist-packages/theano/tensor/signal/tests/test_pool.py:1119: UserWarning: DEPRECATION: the 'padding' parameter is not going to exist anymore as it is going to be replaced by the parameter 'pad'.
mode=mode)
....................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................../usr/lib/python2.7/unittest/case.py:329: DeprecationWarning: stack(*tensors) interface is deprecated, use stack(tensors, axis=0) instead.
testMethod()
............................................................................................................................................../usr/local/lib/python2.7/dist-packages/theano/tensor/tests/test_basic.py:8227: UserWarning: Tile op is deprecated, use tile function instead.
[Tile(ndim)(advec, aivec_val)],
/usr/local/lib/python2.7/dist-packages/theano/tensor/tests/test_basic.py:8235: UserWarning: Tile op is deprecated, use tile function instead.
[Tile(ndim)(admat, aivec_val)],
/usr/local/lib/python2.7/dist-packages/theano/tensor/tests/test_basic.py:8243: UserWarning: Tile op is deprecated, use tile function instead.
[Tile(ndim)(adtens4, aivec_val)],
...........................................................................................................S................................................................................................................................................................................../usr/local/lib/python2.7/dist-packages/theano/tensor/basic.py:5262: UserWarning: flatten outdim parameter is deprecated, use ndim instead.
"flatten outdim parameter is deprecated, use ndim instead.")
...........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................S..SSSS.S..........................................................................................................S.....................S.............................../usr/local/lib/python2.7/dist-packages/theano/tensor/nlinalg.py:175: DeprecationWarning: DeprecationWarning: theano.tensor.nlinalg.AllocDiagis deprecated, please use theano.tensor.AllocDiaginstead.
category=DeprecationWarning)
/usr/local/lib/python2.7/dist-packages/theano/tensor/nlinalg.py:175: DeprecationWarning: DeprecationWarning: theano.tensor.nlinalg.AllocDiagis deprecated, please use theano.tensor.AllocDiaginstead.
category=DeprecationWarning)
./usr/local/lib/python2.7/dist-packages/theano/tensor/nlinalg.py:175: DeprecationWarning: DeprecationWarning: theano.tensor.nlinalg.AllocDiagis deprecated, please use theano.tensor.AllocDiaginstead.
category=DeprecationWarning)
./usr/local/lib/python2.7/dist-packages/theano/tensor/nlinalg.py:175: DeprecationWarning: DeprecationWarning: theano.tensor.nlinalg.AllocDiagis deprecated, please use theano.tensor.AllocDiaginstead.
category=DeprecationWarning)
.................................................................................................................................S.S..S............../usr/local/lib/python2.7/dist-packages/theano/tensor/opt.py:3523: UserWarning: Your current code is fine, but Theano versions between 0.7rc1 and 0.10 (or development versions between Nov. 2014 and May 2017) might have given incorrect results. This graph has following pattern: inc_subtensor(zeros[idx], x)[idx], where idx is an array of integers. This used to be optimized to "x", which is incorrect if there are duplicated indices in idx. To disable this warning, set the Theano flag warn.inc_subtensor1_opt to False.
'Your current code is fine, but Theano versions '
......................................................S..............S..........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................S/usr/lib/python2.7/unittest/case.py:329: UserWarning: consider_constant() is deprecated, use zero_grad() or disconnected_grad() instead.
testMethod()
................................................SS......SSSSS...SSSS.......S..........S.S............../usr/local/lib/python2.7/dist-packages/theano/tests/test_rop.py:388: UserWarning: DEPRECATION: If x is a vector, Softmax will not automatically pad x anymore in next releases. If you need it, please do it manually. The vector case is gonna be supported soon and the output will be a vector.
self.check_rop_lop(tensor.nnet.softmax(self.x)[0], self.in_shape[0]).......
ERROR: test_all (theano.gpuarray.tests.test_blas.GpuGemmBatchTester)
File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_basic_ops.py", line 97, in test_all
self.run_case(testname, inputs)
File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_basic_ops.py", line 131, in run_case
variables = f_tst()
File "/usr/local/lib/python2.7/dist-packages/theano/compile/function_module.py", line 917, in __call__
storage_map=getattr(self.fn, 'storage_map', None))
File "/usr/local/lib/python2.7/dist-packages/theano/gof/link.py", line 325, in raise_with_op
reraise(exc_type, exc_value, exc_trace)
File "/usr/local/lib/python2.7/dist-packages/theano/compile/function_module.py", line 903, in __call__
self.fn() if output_subset is None else\
RuntimeError: ('Blas operation not supported by library in use: hgemmBatch\nApply node that caused the error: GpuGemmBatch{inplace=True}(GpuAllocEmpty{dtype=\'float16\', context_name=None}.0, TensorConstant{1.0}, GpuFromHost
-------------------- >> begin captured stdout << ---------------------
Disabling C code for BatchedDot due to unsupported float16ERROR: theano.gpuarray.tests.test_others.test_dump_load
File "/usr/lib/python2.7/dist-packages/nose/case.py", line 197, in runTest
self.test(*self.arg)
File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/tests/test_others.py", line 37, in test_dump_load
with open('test', 'wb') as f:
IOError: [Errno 13] Permission denied: 'test'
quintasxcv
on 20 Dec 2017
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Most helpful comment
I have new issue right now when I tried to test theano
It seems for my like python3.5 problem since my other projects can't find relative module in other folders even __init__ is included