Ludwig: Spoken Digit Speech Recognition Example Failed! (Not working).

[bharatsewani1993]

Describe the bug
I performed all the things step by step mentioned in
https://ludwig-ai.github.io/ludwig-docs/examples/#spoken-digit-speech-recognition
But it is not working and returning the error.

Output log
2020-10-04 16:05:51.078440: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudart64_101.dll
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ludwig v0.3.0-rc.1 - Train

2020-10-04 16:05:52.485930: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library nvcuda.dll
2020-10-04 16:05:52.509582: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties:
pciBusID: 0000:09:00.0 name: GeForce GTX 1050 Ti computeCapability: 6.1
coreClock: 1.455GHz coreCount: 6 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 104.43GiB/s
2020-10-04 16:05:52.516291: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudart64_101.dll
2020-10-04 16:05:52.525349: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cublas64_10.dll
2020-10-04 16:05:52.533118: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cufft64_10.dll
2020-10-04 16:05:52.538876: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library curand64_10.dll
2020-10-04 16:05:52.546868: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cusolver64_10.dll
2020-10-04 16:05:52.552861: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cusparse64_10.dll
2020-10-04 16:05:52.570946: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudnn64_7.dll
2020-10-04 16:05:52.575899: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1858] Adding visible gpu devices: 0
Experiment name: experiment
Model name: run
Output directory: resultsexperiment_run_40

ludwig_version: '0.3.0-rc.1'
command: ('C:\ludwig\venv\Scripts\ludwig train --dataset spoken_digit.csv '
'--data_format csv --model_definition_file model_definition_file.yaml')
random_seed: 42
dataset: 'spoken_digit.csv'
data_format: 'csv'
model_definition: { 'combiner': {'type': 'concat'},
'input_features': [ { 'conv_layers': [ { 'dropout': True,
'filter_size': 7,
'num_filters': 256,
'pool_size': 3,
'pool_stride': 1},
{ 'dropout': True,
'filter_size': 7,
'num_filters': 256,
'pool_size': 3,
'pool_stride': 1}],
'encoder': 'stacked_cnn',
'fc_layers': [{'dropout': True, 'fc_size': 256}],
'name': 'audio_path',
'preprocessing': { 'audio_feature': { 'num_filter_bands': 80,
'type': 'fbank',
'window_length_in_s': 0.025,
'window_shift_in_s': 0.01},
'audio_file_length_limit_in_s': 1.0,
'norm': 'per_file'},
'reduce_output': 'concat',
'tied': None,
'type': 'audio'}],
'output_features': [ { 'dependencies': [],
'loss': { 'class_similarities_temperature': 0,
'class_weights': 1,
'confidence_penalty': 0,
'labels_smoothing': 0,
'robust_lambda': 0,
'type': 'softmax_cross_entropy',
'weight': 1},
'name': 'label',
'reduce_dependencies': 'sum',
'reduce_input': 'sum',
'top_k': 3,
'type': 'category'}],
'preprocessing': { 'audio': { 'audio_feature': {'type': 'raw'},
'audio_file_length_limit_in_s': 7.5,
'in_memory': True,
'missing_value_strategy': 'backfill',
'norm': None,
'padding_value': 0},
'bag': { 'fill_value': '',
'lowercase': False,
'missing_value_strategy': 'fill_with_const',
'most_common': 10000,
'tokenizer': 'space'},
'binary': { 'fill_value': 0,
'missing_value_strategy': 'fill_with_const'},
'category': { 'fill_value': '',
'lowercase': False,
'missing_value_strategy': 'fill_with_const',
'most_common': 10000},
'date': { 'datetime_format': None,
'fill_value': '',
'missing_value_strategy': 'fill_with_const'},
'force_split': False,
'h3': { 'fill_value': 576495936675512319,
'missing_value_strategy': 'fill_with_const'},
'image': { 'in_memory': True,
'missing_value_strategy': 'backfill',
'num_processes': 1,
'resize_method': 'interpolate',
'scaling': 'pixel_normalization'},
'numerical': { 'fill_value': 0,
'missing_value_strategy': 'fill_with_const',
'normalization': None},
'sequence': { 'fill_value': '',
'lowercase': False,
'missing_value_strategy': 'fill_with_const',
'most_common': 20000,
'padding': 'right',
'padding_symbol': '',
'sequence_length_limit': 256,
'tokenizer': 'space',
'unknown_symbol': '',
'vocab_file': None},
'set': { 'fill_value': '',
'lowercase': False,
'missing_value_strategy': 'fill_with_const',
'most_common': 10000,
'tokenizer': 'space'},
'split_probabilities': (0.7, 0.1, 0.2),
'stratify': None,
'text': { 'char_most_common': 70,
'char_sequence_length_limit': 1024,
'char_tokenizer': 'characters',
'char_vocab_file': None,
'fill_value': '',
'lowercase': True,
'missing_value_strategy': 'fill_with_const',
'padding': 'right',
'padding_symbol': '',
'pretrained_model_name_or_path': None,
'unknown_symbol': '',
'word_most_common': 20000,
'word_sequence_length_limit': 256,
'word_tokenizer': 'space_punct',
'word_vocab_file': None},
'timeseries': { 'fill_value': '',
'missing_value_strategy': 'fill_with_const',
'padding': 'right',
'padding_value': 0,
'timeseries_length_limit': 256,
'tokenizer': 'space'},
'vector': { 'fill_value': '',
'missing_value_strategy': 'fill_with_const'}},
'training': { 'batch_size': 128,
'bucketing_field': None,
'decay': False,
'decay_rate': 0.96,
'decay_steps': 10000,
'dropout_rate': 0.4,
'early_stop': 10,
'epochs': 100,
'eval_batch_size': 0,
'gradient_clipping': None,
'increase_batch_size_on_plateau': 0,
'increase_batch_size_on_plateau_max': 512,
'increase_batch_size_on_plateau_patience': 5,
'increase_batch_size_on_plateau_rate': 2,
'learning_rate': 0.001,
'learning_rate_warmup_epochs': 1,
'optimizer': { 'beta_1': 0.9,
'beta_2': 0.999,
'epsilon': 1e-08,
'type': 'adam'},
'reduce_learning_rate_on_plateau': 0,
'reduce_learning_rate_on_plateau_patience': 5,
'reduce_learning_rate_on_plateau_rate': 0.5,
'regularization_lambda': 0,
'regularizer': 'l2',
'staircase': False,
'validation_field': 'combined',
'validation_metric': 'loss'}}
tf_version: '2.3.1'

Found hdf5 and meta.json with the same filename of the input file, using them instead
Using full hdf5 and json
Loading data from: spoken_digit.hdf5
Training set: 2094
Validation set: 298
Test set: 608
2020-10-04 16:05:52.739566: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations: AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2020-10-04 16:05:52.757829: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x1a95650cc10 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-10-04 16:05:52.762899: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
2020-10-04 16:05:52.766847: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties:
pciBusID: 0000:09:00.0 name: GeForce GTX 1050 Ti computeCapability: 6.1
coreClock: 1.455GHz coreCount: 6 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 104.43GiB/s
2020-10-04 16:05:52.775404: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudart64_101.dll
2020-10-04 16:05:52.780311: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cublas64_10.dll
2020-10-04 16:05:52.784792: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cufft64_10.dll
2020-10-04 16:05:52.789819: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library curand64_10.dll
2020-10-04 16:05:52.794514: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cusolver64_10.dll
2020-10-04 16:05:52.799771: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cusparse64_10.dll
2020-10-04 16:05:52.804885: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudnn64_7.dll
2020-10-04 16:05:52.809373: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1858] Adding visible gpu devices: 0
2020-10-04 16:05:53.304404: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1257] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-10-04 16:05:53.308601: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1263] 0
2020-10-04 16:05:53.311159: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1276] 0: N
2020-10-04 16:05:53.314434: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1402] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2982 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1050 Ti, pci bus id: 0000:09:00.0, compute capability: 6.1)
2020-10-04 16:05:53.325215: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x1a9022e3840 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2020-10-04 16:05:53.330092: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): GeForce GTX 1050 Ti, Compute Capability 6.1

╒══════════╕
│ TRAINING │
╘══════════╛

Epoch 1
Training: 0%| | 0/17 [00:00 File "C:ludwigvenvScriptsludwig-script.py", line 33, in
sys.exit(load_entry_point('ludwig==0.3.0rc1', 'console_scripts', 'ludwig')())
File "C:ludwigvenvlibsite-packagesludwig-0.3.0rc1-py3.7.eggludwigcli.py", line 134, in main
CLI()
File "C:ludwigvenvlibsite-packagesludwig-0.3.0rc1-py3.7.eggludwigcli.py", line 70, in __init__
getattr(self, args.command)()
File "C:ludwigvenvlibsite-packagesludwig-0.3.0rc1-py3.7.eggludwigcli.py", line 80, in train
train.cli(sys.argv[2:])
File "C:ludwigvenvlibsite-packagesludwig-0.3.0rc1-py3.7.eggludwigtrain.py", line 406, in cli
train_cli(*vars(args))
File "C:ludwigvenvlibsite-packagesludwig-0.3.0rc1-py3.7.eggludwigtrain.py", line 191, in train_cli
debug=debug,
File "C:ludwigvenvlibsite-packagesludwig-0.3.0rc1-py3.7.eggludwigapi.py", line 397, in train
save_path=model_dir,
File "C:ludwigvenvlibsite-packagesludwig-0.3.0rc1-py3.7.eggludwigmodelstrainer.py", line 516, in train
self.regularization_lambda
File "C:ludwigvenvlibsite-packagestensorflowpythoneagerdef_function.py", line 780, in __call__
result = self._call(args, *kwds)
File "C:ludwigvenvlibsite-packagestensorflowpythoneagerdef_function.py", line 823, in _call
self._initialize(args, kwds, add_initializers_to=initializers)
File "C:ludwigvenvlibsite-packagestensorflowpythoneagerdef_function.py", line 697, in _initialize
*args, *kwds))
File "C:ludwigvenvlibsite-packagestensorflowpythoneagerfunction.py", line 2855, in _get_concrete_function_internal_garbage_collected
graph_function, _, _ = self._maybe_define_function(args, kwargs)
File "C:ludwigvenvlibsite-packagestensorflowpythoneagerfunction.py", line 3213, in _maybe_define_function
graph_function = self._create_graph_function(args, kwargs)
File "C:ludwigvenvlibsite-packagestensorflowpythoneagerfunction.py", line 3075, in _create_graph_function
capture_by_value=self._capture_by_value),
File "C:ludwigvenvlibsite-packagestensorflowpythonframeworkfunc_graph.py", line 986, in func_graph_from_py_func
func_outputs = python_func(func_args, *func_kwargs)
File "C:ludwigvenvlibsite-packagestensorflowpythoneagerdef_function.py", line 600, in wrapped_fn
return weak_wrapped_fn().__wrapped__(args, *kwds)
File "C:ludwigvenvlibsite-packagestensorflowpythoneagerfunction.py", line 3735, in bound_method_wrapper
return wrapped_fn(args, *kwargs)
File "C:ludwigvenvlibsite-packagestensorflowpythonframeworkfunc_graph.py", line 973, in wrapper
raise e.ag_error_metadata.to_exception(e)
ValueError: in user code:

C:\ludwig\venv\lib\site-packages\ludwig-0.3.0rc1-py3.7.egg\ludwig\models\ecd.py:176 train_step  *
    model_outputs = self((inputs, targets), training=True)
C:\ludwig\venv\lib\site-packages\ludwig-0.3.0rc1-py3.7.egg\ludwig\models\ecd.py:101 call  *
    encoder_output = encoder(input_values, training=training,
C:\ludwig\venv\lib\site-packages\ludwig-0.3.0rc1-py3.7.egg\ludwig\features\audio_feature.py:367 call  *
    encoder_output = self.encoder_obj(
C:\ludwig\venv\lib\site-packages\ludwig-0.3.0rc1-py3.7.egg\ludwig\encoders\sequence_encoders.py:871 call  *
    hidden = self.conv1d_stack(
C:\ludwig\venv\lib\site-packages\ludwig-0.3.0rc1-py3.7.egg\ludwig\modules\convolutional_modules.py:247 call  *
    hidden = layer(hidden, training=training)
C:\ludwig\venv\lib\site-packages\ludwig-0.3.0rc1-py3.7.egg\ludwig\modules\convolutional_modules.py:111 call  *
    hidden = layer(hidden, training=training)
C:\ludwig\venv\lib\site-packages\tensorflow\python\keras\engine\base_layer.py:985 __call__  **
    outputs = call_fn(inputs, *args, **kwargs)
C:\ludwig\venv\lib\site-packages\tensorflow\python\keras\layers\core.py:218 call
    lambda: array_ops.identity(inputs))
C:\ludwig\venv\lib\site-packages\tensorflow\python\keras\utils\tf_utils.py:65 smart_cond
    pred, true_fn=true_fn, false_fn=false_fn, name=name)
C:\ludwig\venv\lib\site-packages\tensorflow\python\framework\smart_cond.py:54 smart_cond
    return true_fn()
C:\ludwig\venv\lib\site-packages\tensorflow\python\keras\layers\core.py:214 dropped_inputs
    rate=self.rate)
C:\ludwig\venv\lib\site-packages\tensorflow\python\util\dispatch.py:201 wrapper
    return target(*args, **kwargs)
C:\ludwig\venv\lib\site-packages\tensorflow\python\util\deprecation.py:507 new_func
    return func(*args, **kwargs)
C:\ludwig\venv\lib\site-packages\tensorflow\python\ops\nn_ops.py:4941 dropout
    return dropout_v2(x, rate, noise_shape=noise_shape, seed=seed, name=name)
C:\ludwig\venv\lib\site-packages\tensorflow\python\util\dispatch.py:201 wrapper
    return target(*args, **kwargs)
C:\ludwig\venv\lib\site-packages\tensorflow\python\ops\nn_ops.py:5022 dropout_v2
    "range [0, 1), got %g" % rate)

ValueError: rate must be a scalar tensor or a float in the range [0, 1), got 1

Training: 0%|

To Reproduce
Perform the instructions given in this example step by step.
https://ludwig-ai.github.io/ludwig-docs/examples/#spoken-digit-speech-recognition

YAML file and sample data is given in this example:
Perform the instructions given in this example step by step.
https://ludwig-ai.github.io/ludwig-docs/examples/#spoken-digit-speech-recognition

Expected behavior
I was expecting this will start to train the data as it is mentioned in the example but id return error.

Screenshots
I am attaching the error snapshot.

Environment (please complete the following information):

• OS: Window 10
• Version Window 10
  
  
  
  • Python: 3.7.0
  
  
  • Ludwig: current version
  
  

Additional context
It is not training the data and giving an error.

[bharatsewani1993]

I performed the same steps in Linux Ubuntu operating system and got the same error.
This example is no more working.
https://ludwig-ai.github.io/ludwig-docs/examples/#spoken-digit-speech-recognition
.
.
Help is appreciated.
Thanks in advance.

[bharatsewani1993]

Output in Linux system:

(venv) bharat@bharat-pc:~/Desktop/awesome_python_project/ludwig/speech_recog_digit_data$ ludwig experiment -g 0 --dataset /home/bharat/Desktop/awesome_python_project/ludwig/speech_recog_digit_data/spoken_digit.csv --model_definition_file /home/bharat/Desktop/awesome_python_project/ludwig/model_definition_file.yaml
2020-10-04 20:44:56.235117: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcudart.so.10.1'; dlerror: libcudart.so.10.1: cannot open shared object file: No such file or directory
2020-10-04 20:44:56.235149: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
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███████████████████████
ludwig v0.3.0-rc.1 - Experiment

2020-10-04 20:44:57.023944: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2020-10-04 20:44:57.023971: W tensorflow/stream_executor/cuda/cuda_driver.cc:312] failed call to cuInit: UNKNOWN ERROR (303)
2020-10-04 20:44:57.023983: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (bharat-pc): /proc/driver/nvidia/version does not exist
Experiment name: experiment
Model name: run
Output directory: results/experiment_run_0

ludwig_version: '0.3.0-rc.1'
command: ('/home/bharat/Desktop/awesome_python_project/ludwig/venv/bin/ludwig '
'experiment -g 0 --dataset '
'/home/bharat/Desktop/awesome_python_project/ludwig/speech_recog_digit_data/spoken_digit.csv '
'--model_definition_file '
'/home/bharat/Desktop/awesome_python_project/ludwig/model_definition_file.yaml')
commit_hash: '64d4e6328a92'
random_seed: 42
dataset: '/home/bharat/Desktop/awesome_python_project/ludwig/speech_recog_digit_data/spoken_digit.csv'
data_format: 'csv'
model_definition: { 'combiner': {'type': 'concat'},
'input_features': [ { 'conv_layers': [ { 'dropout': True,
'filter_size': 6,
'num_filters': 16,
'pool_size': 4,
'pool_stride': 4},
{ 'dropout': True,
'filter_size': 3,
'num_filters': 32,
'pool_size': 2,
'pool_stride': 2}],
'encoder': 'stacked_cnn',
'fc_layers': [{'dropout': True, 'fc_size': 64}],
'name': 'audio_path',
'preprocessing': { 'audio_feature': { 'num_filter_bands': 80,
'type': 'fbank',
'window_length_in_s': 0.025,
'window_shift_in_s': 0.01},
'audio_file_length_limit_in_s': 1.0,
'norm': 'per_file'},
'reduce_output': 'concat',
'tied': None,
'type': 'audio'}],
'output_features': [ { 'dependencies': [],
'loss': { 'class_similarities_temperature': 0,
'class_weights': 1,
'confidence_penalty': 0,
'labels_smoothing': 0,
'robust_lambda': 0,
'type': 'softmax_cross_entropy',
'weight': 1},
'name': 'label',
'reduce_dependencies': 'sum',
'reduce_input': 'sum',
'top_k': 3,
'type': 'category'}],
'preprocessing': { 'audio': { 'audio_feature': {'type': 'raw'},
'audio_file_length_limit_in_s': 7.5,
'in_memory': True,
'missing_value_strategy': 'backfill',
'norm': None,
'padding_value': 0},
'bag': { 'fill_value': '',
'lowercase': False,
'missing_value_strategy': 'fill_with_const',
'most_common': 10000,
'tokenizer': 'space'},
'binary': { 'fill_value': 0,
'missing_value_strategy': 'fill_with_const'},
'category': { 'fill_value': '',
'lowercase': False,
'missing_value_strategy': 'fill_with_const',
'most_common': 10000},
'date': { 'datetime_format': None,
'fill_value': '',
'missing_value_strategy': 'fill_with_const'},
'force_split': False,
'h3': { 'fill_value': 576495936675512319,
'missing_value_strategy': 'fill_with_const'},
'image': { 'in_memory': True,
'missing_value_strategy': 'backfill',
'num_processes': 1,
'resize_method': 'interpolate',
'scaling': 'pixel_normalization'},
'numerical': { 'fill_value': 0,
'missing_value_strategy': 'fill_with_const',
'normalization': None},
'sequence': { 'fill_value': '',
'lowercase': False,
'missing_value_strategy': 'fill_with_const',
'most_common': 20000,
'padding': 'right',
'padding_symbol': '',
'sequence_length_limit': 256,
'tokenizer': 'space',
'unknown_symbol': '',
'vocab_file': None},
'set': { 'fill_value': '',
'lowercase': False,
'missing_value_strategy': 'fill_with_const',
'most_common': 10000,
'tokenizer': 'space'},
'split_probabilities': (0.7, 0.1, 0.2),
'stratify': None,
'text': { 'char_most_common': 70,
'char_sequence_length_limit': 1024,
'char_tokenizer': 'characters',
'char_vocab_file': None,
'fill_value': '',
'lowercase': True,
'missing_value_strategy': 'fill_with_const',
'padding': 'right',
'padding_symbol': '',
'pretrained_model_name_or_path': None,
'unknown_symbol': '',
'word_most_common': 20000,
'word_sequence_length_limit': 256,
'word_tokenizer': 'space_punct',
'word_vocab_file': None},
'timeseries': { 'fill_value': '',
'missing_value_strategy': 'fill_with_const',
'padding': 'right',
'padding_value': 0,
'timeseries_length_limit': 256,
'tokenizer': 'space'},
'vector': { 'fill_value': '',
'missing_value_strategy': 'fill_with_const'}},
'training': { 'batch_size': 128,
'bucketing_field': None,
'decay': False,
'decay_rate': 0.96,
'decay_steps': 10000,
'dropout_rate': 0.4,
'early_stop': 10,
'epochs': 100,
'eval_batch_size': 0,
'gradient_clipping': None,
'increase_batch_size_on_plateau': 0,
'increase_batch_size_on_plateau_max': 512,
'increase_batch_size_on_plateau_patience': 5,
'increase_batch_size_on_plateau_rate': 2,
'learning_rate': 0.001,
'learning_rate_warmup_epochs': 1,
'optimizer': { 'beta_1': 0.9,
'beta_2': 0.999,
'epsilon': 1e-08,
'type': 'adam'},
'reduce_learning_rate_on_plateau': 0,
'reduce_learning_rate_on_plateau_patience': 5,
'reduce_learning_rate_on_plateau_rate': 0.5,
'regularization_lambda': 0,
'regularizer': 'l2',
'staircase': False,
'validation_field': 'combined',
'validation_metric': 'loss'}}
tf_version: '2.3.1'

Found hdf5 and meta.json with the same filename of the input file, using them instead
Using full hdf5 and json
Loading data from: /home/bharat/Desktop/awesome_python_project/ludwig/speech_recog_digit_data/spoken_digit.hdf5
Training set: 2094
Validation set: 298
Test set: 608
2020-10-04 20:44:57.134819: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2020-10-04 20:44:57.160651: I tensorflow/core/platform/profile_utils/cpu_utils.cc:104] CPU Frequency: 3699485000 Hz
2020-10-04 20:44:57.162356: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x47b8c00 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-10-04 20:44:57.162395: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version

╒══════════╕
│ TRAINING │
╘══════════╛

Epoch 1
Training: 0%| | 0/17 [00:00 File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/bin/ludwig", line 33, in
sys.exit(load_entry_point('ludwig==0.3.0rc1', 'console_scripts', 'ludwig')())
File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/ludwig-0.3.0rc1-py3.6.egg/ludwig/cli.py", line 134, in main
CLI()
File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/ludwig-0.3.0rc1-py3.6.egg/ludwig/cli.py", line 70, in __init__
getattr(self, args.command)()
File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/ludwig-0.3.0rc1-py3.6.egg/ludwig/cli.py", line 75, in experiment
experiment.cli(sys.argv[2:])
File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/ludwig-0.3.0rc1-py3.6.egg/ludwig/experiment.py", line 571, in cli
experiment_cli(*vars(args))
File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/ludwig-0.3.0rc1-py3.6.egg/ludwig/experiment.py", line 239, in experiment_cli
debug=debug,
File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/ludwig-0.3.0rc1-py3.6.egg/ludwig/api.py", line 1036, in experiment
debug=debug,
File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/ludwig-0.3.0rc1-py3.6.egg/ludwig/api.py", line 470, in train
save_path=model_dir,
File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/ludwig-0.3.0rc1-py3.6.egg/ludwig/models/trainer.py", line 516, in train
self.regularization_lambda
File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py", line 780, in __call__
result = self._call(args, *kwds)
File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py", line 823, in _call
self._initialize(args, kwds, add_initializers_to=initializers)
File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py", line 697, in _initialize
*args, *kwds))
File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/eager/function.py", line 2855, in _get_concrete_function_internal_garbage_collected
graph_function, _, _ = self._maybe_define_function(args, kwargs)
File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/eager/function.py", line 3213, in _maybe_define_function
graph_function = self._create_graph_function(args, kwargs)
File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/eager/function.py", line 3075, in _create_graph_function
capture_by_value=self._capture_by_value),
File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/framework/func_graph.py", line 986, in func_graph_from_py_func
func_outputs = python_func(func_args, *func_kwargs)
File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py", line 600, in wrapped_fn
return weak_wrapped_fn().__wrapped__(args, *kwds)
File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/eager/function.py", line 3735, in bound_method_wrapper
return wrapped_fn(args, *kwargs)
File "/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/framework/func_graph.py", line 973, in wrapper
raise e.ag_error_metadata.to_exception(e)
ValueError: in user code:

/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/ludwig-0.3.0rc1-py3.6.egg/ludwig/models/ecd.py:176 train_step  *
    model_outputs = self((inputs, targets), training=True)
/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/ludwig-0.3.0rc1-py3.6.egg/ludwig/models/ecd.py:101 call  *
    encoder_output = encoder(input_values, training=training,
/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/ludwig-0.3.0rc1-py3.6.egg/ludwig/features/audio_feature.py:367 call  *
    encoder_output = self.encoder_obj(
/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/ludwig-0.3.0rc1-py3.6.egg/ludwig/encoders/sequence_encoders.py:871 call  *
    hidden = self.conv1d_stack(
/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/ludwig-0.3.0rc1-py3.6.egg/ludwig/modules/convolutional_modules.py:239 call  *
    hidden = layer(hidden, training=training)
/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/ludwig-0.3.0rc1-py3.6.egg/ludwig/modules/convolutional_modules.py:103 call  *
    hidden = layer(hidden, training=training)
/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py:985 __call__  **
    outputs = call_fn(inputs, *args, **kwargs)
/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/keras/layers/core.py:218 call
    lambda: array_ops.identity(inputs))
/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/keras/utils/tf_utils.py:65 smart_cond
    pred, true_fn=true_fn, false_fn=false_fn, name=name)
/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/framework/smart_cond.py:54 smart_cond
    return true_fn()
/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/keras/layers/core.py:214 dropped_inputs
    rate=self.rate)
/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/util/dispatch.py:201 wrapper
    return target(*args, **kwargs)
/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py:507 new_func
    return func(*args, **kwargs)
/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py:4941 dropout
    return dropout_v2(x, rate, noise_shape=noise_shape, seed=seed, name=name)
/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/util/dispatch.py:201 wrapper
    return target(*args, **kwargs)
/home/bharat/Desktop/awesome_python_project/ludwig/venv/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py:5022 dropout_v2
    "range [0, 1), got %g" % rate)

ValueError: rate must be a scalar tensor or a float in the range [0, 1), got 1

[kanishk16]

@bharatsewani1993 Try 'dropout': x (0<x<1) instead of 'dropout': True in the model definition. Also, you may skip defining 'dropout_rate': x (0<x<1) in the training part of the model definition. Let us know if the error still persists.

We would be updating the docs soon.

[bharatsewani1993]

Thanks, @kanishk16,
It worked for me. :)
Help is really appreciated.
<3