Models: sampled_loss() got an unexpected keyword argument 'logits'
I am using tesorflow version 1.2 (gpu)
i try to run tensorflow chatbot which is a varient of translate example . fixed many problems due to version change ,but can't fix this error
Traceback (most recent call last):
File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\execute.py", line 319, in <module>
train()
File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\execute.py", line 137, in train
model = create_model(sess, False)
File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\execute.py", line 104, in create_model
model = seq2seq_model.Seq2SeqModel( gConfig['enc_vocab_size'], gConfig['dec_vocab_size'], _buckets, gConfig['layer_size'], gConfig['num_layers'], gConfig['max_gradient_norm'], gConfig['batch_size'], gConfig['learning_rate'], gConfig['learning_rate_decay_factor'], forward_only=forward_only)
File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\seq2seq_model.py", line 150, in __init__
softmax_loss_function=softmax_loss_function)
File "C:\Python35\lib\site-packages\tensorflow\contrib\legacy_seq2seq\python\ops\seq2seq.py", line 1221, in model_with_buckets
softmax_loss_function=softmax_loss_function))
File "C:\Python35\lib\site-packages\tensorflow\contrib\legacy_seq2seq\python\ops\seq2seq.py", line 1134, in sequence_loss
softmax_loss_function=softmax_loss_function))
File "C:\Python35\lib\site-packages\tensorflow\contrib\legacy_seq2seq\python\ops\seq2seq.py", line 1089, in sequence_loss_by_example
crossent = softmax_loss_function(labels=target, logits=logit)
TypeError: sampled_loss() got an unexpected keyword argument 'logits'
error causing line of code
self.outputs, self.losses = tf.contrib.legacy_seq2seq.model_with_buckets(
self.encoder_inputs, self.decoder_inputs, targets,
self.target_weights, buckets,
lambda x, y: seq2seq_f(x, y, False),
softmax_loss_function=softmax_loss_function) <-- line 150 from seq2seq.py
and softmax_loss_function is come from here
def sampled_loss(inputs, labels):
labels = tf.reshape(labels, [-1, 1])
return tf.nn.sampled_softmax_loss(w_t, b, labels, inputs, num_samples,
self.target_vocab_size)
softmax_loss_function = sampled_loss
please help
athuldevin
All 14 comments
@athuldevin Hi, i also met this error, but when i changed 'sampled_loss(inputs, labels)' to 'sampled_loss(labels, logits) : labels = tf.reshape(labels, [-1, 1]) return tf.nn.sampled_softmax_loss(w_t, b, labels, logits, num_samples, self.target_vocab_size) ' , the error gone.
StephenLee2016
on 23 Jun 2017
@StephenLee2016 hi, thanks that error is fixed but a new one is generated may be it is related to that one
Traceback (most recent call last):
File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\execute.py", line 319, in <module>
train()
File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\execute.py", line 137, in train
model = create_model(sess, False)
File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\execute.py", line 104, in create_model
model = seq2seq_model.Seq2SeqModel( gConfig['enc_vocab_size'], gConfig['dec_vocab_size'], _buckets, gConfig['layer_size'], gConfig['num_layers'], gConfig['max_gradient_norm'], gConfig['batch_size'], gConfig['learning_rate'], gConfig['learning_rate_decay_factor'], forward_only=forward_only)
File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\seq2seq_model.py", line 150, in __init__
softmax_loss_function=softmax_loss_function)
File "C:\Python35\lib\site-packages\tensorflow\contrib\legacy_seq2seq\python\ops\seq2seq.py", line 1206, in model_with_buckets
decoder_inputs[:bucket[1]])
File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\seq2seq_model.py", line 149, in <lambda>
lambda x, y: seq2seq_f(x, y, False),
File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\seq2seq_model.py", line 113, in seq2seq_f
feed_previous=do_decode)
File "C:\Python35\lib\site-packages\tensorflow\contrib\legacy_seq2seq\python\ops\seq2seq.py", line 848, in embedding_attention_seq2seq
encoder_cell = copy.deepcopy(cell)
File "C:\Python35\lib\copy.py", line 166, in deepcopy
y = copier(memo)
File "C:\Python35\lib\site-packages\tensorflow\python\layers\base.py", line 476, in __deepcopy__
setattr(result, k, copy.deepcopy(v, memo))
File "C:\Python35\lib\copy.py", line 155, in deepcopy
y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 218, in _deepcopy_list
y.append(deepcopy(a, memo))
File "C:\Python35\lib\copy.py", line 166, in deepcopy
y = copier(memo)
File "C:\Python35\lib\site-packages\tensorflow\python\layers\base.py", line 476, in __deepcopy__
setattr(result, k, copy.deepcopy(v, memo))
File "C:\Python35\lib\copy.py", line 155, in deepcopy
y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 218, in _deepcopy_list
y.append(deepcopy(a, memo))
File "C:\Python35\lib\copy.py", line 182, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "C:\Python35\lib\copy.py", line 297, in _reconstruct
state = deepcopy(state, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy
y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "C:\Python35\lib\copy.py", line 182, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "C:\Python35\lib\copy.py", line 297, in _reconstruct
state = deepcopy(state, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy
y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy
y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 218, in _deepcopy_list
y.append(deepcopy(a, memo))
File "C:\Python35\lib\copy.py", line 182, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "C:\Python35\lib\copy.py", line 297, in _reconstruct
state = deepcopy(state, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy
y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "C:\Python35\lib\copy.py", line 182, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "C:\Python35\lib\copy.py", line 297, in _reconstruct
state = deepcopy(state, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy
y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "C:\Python35\lib\copy.py", line 182, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "C:\Python35\lib\copy.py", line 291, in _reconstruct
args = deepcopy(args, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy
y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 223, in _deepcopy_tuple
y = [deepcopy(a, memo) for a in x]
File "C:\Python35\lib\copy.py", line 223, in <listcomp>
y = [deepcopy(a, memo) for a in x]
File "C:\Python35\lib\copy.py", line 155, in deepcopy
y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 218, in _deepcopy_list
y.append(deepcopy(a, memo))
File "C:\Python35\lib\copy.py", line 182, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "C:\Python35\lib\copy.py", line 297, in _reconstruct
state = deepcopy(state, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy
y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy
y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 218, in _deepcopy_list
y.append(deepcopy(a, memo))
File "C:\Python35\lib\copy.py", line 182, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "C:\Python35\lib\copy.py", line 297, in _reconstruct
state = deepcopy(state, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy
y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy
y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 218, in _deepcopy_list
y.append(deepcopy(a, memo))
File "C:\Python35\lib\copy.py", line 182, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "C:\Python35\lib\copy.py", line 297, in _reconstruct
state = deepcopy(state, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy
y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "C:\Python35\lib\copy.py", line 182, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "C:\Python35\lib\copy.py", line 297, in _reconstruct
state = deepcopy(state, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy
y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy
y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 218, in _deepcopy_list
y.append(deepcopy(a, memo))
File "C:\Python35\lib\copy.py", line 155, in deepcopy
y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 223, in _deepcopy_tuple
y = [deepcopy(a, memo) for a in x]
File "C:\Python35\lib\copy.py", line 223, in <listcomp>
y = [deepcopy(a, memo) for a in x]
File "C:\Python35\lib\copy.py", line 155, in deepcopy
y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "C:\Python35\lib\copy.py", line 182, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "C:\Python35\lib\copy.py", line 306, in _reconstruct
y.__dict__.update(state)
AttributeError: 'NoneType' object has no attribute 'update'
is i need to change this line of code from execute.py
"""Create model and initialize or load parameters"""
def create_model(session, forward_only):
model = seq2seq_model.Seq2SeqModel( gConfig['enc_vocab_size'], gConfig['dec_vocab_size'], _buckets, gConfig['layer_size'], gConfig['num_layers'], gConfig['max_gradient_norm'], gConfig['batch_size'], gConfig['learning_rate'], gConfig['learning_rate_decay_factor'], forward_only=forward_only)
this error also happens in translate program
thanks for helping
athuldevin
on 23 Jun 2017
@athuldevin Hi, I also met this issue now, maybe translate.py need be updated, and you can focus https://github.com/tensorflow/models/issues/1733
StephenLee2016
on 24 Jun 2017
Hi,
I also got this error when trying to run seq2seq model (translate.py) with tensorflow 1.2 python 3.5.
...
File "C:\Python35\lib\copy.py", line 182, in deepcopy y = _reconstruct(x, rv, 1, memo)
File "C:\Python35\lib\copy.py", line 297, in _reconstruct state = deepcopy(state, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo)
File "C:\Python35\lib\copy.py", line 182, in deepcopy y = _reconstruct(x, rv, 1, memo)
File "C:\Python35\lib\copy.py", line 297, in _reconstruct state = deepcopy(state, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 218, in _deepcopy_list y.append(deepcopy(a, memo))
File "C:\Python35\lib\copy.py", line 182, in deepcopy y = _reconstruct(x, rv, 1, memo)
File "C:\Python35\lib\copy.py", line 306, in _reconstruct y.__dict__.update(state) AttributeError: 'NoneType' object has no attribute 'update'
...
Please help to fix it.
Katsatsaka
on 18 Aug 2017
can you share the full error message
athuldevin
on 19 Aug 2017
@athuldevin Thanks my error is resolved but now i received another error
python3 execute.py
Mode : train
Preparing data in working_dir/
2017-09-05 17:03:48.291647: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2017-09-05 17:03:48.291668: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-09-05 17:03:48.291673: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2017-09-05 17:03:48.291677: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Creating 3 layers of 128 units.
Traceback (most recent call last):
File "execute.py", line 290, in
train()
File "execute.py", line 114, in train
model = create_model(sess, False)
File "execute.py", line 82, in create_model
model = seq2seq_model.Seq2SeqModel( gConfig['enc_vocab_size'], gConfig['dec_vocab_size'], _buckets, gConfig['layer_size'], gConfig['num_layers'], gConfig['max_gradient_norm'], gConfig['batch_size'], gConfig['learning_rate'], gConfig['learning_rate_decay_factor'], forward_only=forward_only)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/chatbot_model/chatbot-master/seq2seq_model.py", line 112, in __init__
softmax_loss_function=softmax_loss_function)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/site-packages/tensorflow/contrib/legacy_seq2seq/python/ops/seq2seq.py", line 1206, in model_with_buckets
decoder_inputs[:bucket[1]])
File "/Users/ttmac2/Documents/Shahab/MachineLearning/chatbot_model/chatbot-master/seq2seq_model.py", line 111, in
lambda x, y: seq2seq_f(x, y, False),
File "/Users/ttmac2/Documents/Shahab/MachineLearning/chatbot_model/chatbot-master/seq2seq_model.py", line 75, in seq2seq_f
feed_previous=do_decode)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/site-packages/tensorflow/contrib/legacy_seq2seq/python/ops/seq2seq.py", line 848, in embedding_attention_seq2seq
encoder_cell = copy.deepcopy(cell)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 161, in deepcopy
y = copier(memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/site-packages/tensorflow/python/layers/base.py", line 487, in __deepcopy__
setattr(result, k, copy.deepcopy(v, memo))
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 150, in deepcopy
y = copier(x, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 215, in _deepcopy_list
append(deepcopy(a, memo))
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 180, in deepcopy
y = _reconstruct(x, memo, *rv)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 280, in _reconstruct
state = deepcopy(state, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 150, in deepcopy
y = copier(x, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 240, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 180, in deepcopy
y = _reconstruct(x, memo, *rv)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 280, in _reconstruct
state = deepcopy(state, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 150, in deepcopy
y = copier(x, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 240, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 180, in deepcopy
y = _reconstruct(x, memo, *rv)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 280, in _reconstruct
state = deepcopy(state, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 150, in deepcopy
y = copier(x, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 240, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 180, in deepcopy
y = _reconstruct(x, memo, *rv)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 280, in _reconstruct
state = deepcopy(state, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 150, in deepcopy
y = copier(x, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 240, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 169, in deepcopy
rv = reductor(4)
TypeError: can't pickle _thread.lock objects
shahabdroid
on 5 Sep 2017
current solution for this error is downgrading your tensorflow version to 1.0.0 as said by the community
athuldevin
on 6 Sep 2017
this not solution. solution is to update code !!!
MartinAbilev
on 20 Oct 2017
@MartinAbilev where do we update? could you give few directions?
anne1994
on 11 Nov 2017
@shahabdroid i am also getting the same error.
anne1994
on 11 Nov 2017
@StephenLee2016 solved this problem
wantongtang
on 17 Dec 2017
@shahabdroid @anne1994 This error is actually, firstly, not an error, and secondly, not related to tensorflow. Basically numpy or tensor objects cannot be pickled (atleast normally through the pickle module) since they are thread.locked, and deepcopy cannot copy such objects. Refer to this for a similar discussion.
Pk13055
on 24 Dec 2017
HEllo I'm having same issue , any solutions?
b7amine
on 19 Jan 2019
what is the issue ?? :)
MartinAbilev
on 21 Jan 2019
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Most helpful comment
@athuldevin Hi, i also met this error, but when i changed 'sampled_loss(inputs, labels)' to 'sampled_loss(labels, logits) : labels = tf.reshape(labels, [-1, 1]) return tf.nn.sampled_softmax_loss(w_t, b, labels, logits, num_samples, self.target_vocab_size) ' , the error gone.