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drethage / speech-denoising-wavenet

A neural network for end-to-end speech denoising
MIT License
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Meaning of "in_memory_percentage" config parameter #29

Open KDuzinkiewicz opened 5 years ago

KDuzinkiewicz commented 5 years ago

The config file documentation mentions that: "...in_memory_percentage: (float) Percentage of the dataset to load into memory, useful when dataset requires more memory than available..."

Does it mean that if I set the value to "1.00" the training toolchain will try load 100% of the recordings to memory? And when I set it to "0.10" the training toolchain will try load only 10% of the recordings to memory at first, but later it will eventually load the other 90% during subsequent iterations - or it will just use 10% in total and ignore the other 90%?

MeiGM commented 5 years ago

How did you train this model, I follow the author's code, the following error will occur Using Theano backend. E:\anaconda\lib\site-packages\theano\gpuarray\dnn.py:184: UserWarning: Your cuDNN version is more recent than Theano. If you encounter problems, try updating Theano or downgrading cuDNN to a version >= v5 and <= v7. warnings.warn("Your cuDNN version is more recent than " Using cuDNN version 7401 on context None Mapped name None to device cuda: GeForce GTX 1060 (0000:01:00.0) Traceback (most recent call last): File "main.py", line 169, in main() File "main.py", line 165, in main inference(config, cla) File "main.py", line 108, in inference load_checkpoint=cla.load_checkpoint, print_model_summary=cla.print_model_summary) File "E:\speech-denoising-wavenet-master\models.py", line 67, in init self.model = self.setup_model(load_checkpoint, print_model_summary) File "E:\speech-denoising-wavenet-master\models.py", line 76, in setup_model model = self.build_model() File "E:\speech-denoising-wavenet-master\models.py", line 220, in build_model name='data_input_target_field_length')(data_expanded) File "E:\anaconda\lib\site-packages\keras\engine\base_layer.py", line 457, in call output = self.call(inputs, **kwargs) File "E:\speech-denoising-wavenet-master\layers.py", line 47, in call x = keras.backend.permute_dimensions(x, [0, 2, 1]) File "E:\anaconda\lib\site-packages\keras\backend\theano_backend.py", line 936, in permute_dimensions y._keras_shape = tuple(np.asarray(x._keras_shape)[list(pattern)]) IndexError: index 2 is out of bounds for axis 0 with size 2

KDuzinkiewicz commented 5 years ago

Hi, I followed the instructions on the GitHub and didn't run into same issue as you, sorry :(

Regards

Karol

śr., 13 mar 2019, 08:53 użytkownik 梦想好 notifications@github.com napisał:

How did you train this model, I follow the author's code, the following error will occur Using Theano backend. E:\anaconda\lib\site-packages\theano\gpuarray\dnn.py:184: UserWarning: Your cuDNN version is more recent than Theano. If you encounter problems, try updating Theano or downgrading cuDNN to a version >= v5 and <= v7. warnings.warn("Your cuDNN version is more recent than " Using cuDNN version 7401 on context None Mapped name None to device cuda: GeForce GTX 1060 (0000:01:00.0) Traceback (most recent call last): File "main.py", line 169, in main() File "main.py", line 165, in main inference(config, cla) File "main.py", line 108, in inference load_checkpoint=cla.load_checkpoint, print_model_summary=cla.print_model_summary) File "E:\speech-denoising-wavenet-master\models.py", line 67, in init self.model = self.setup_model(load_checkpoint, print_model_summary) File "E:\speech-denoising-wavenet-master\models.py", line 76, in setup_model model = self.build_model() File "E:\speech-denoising-wavenet-master\models.py", line 220, in build_model name='data_input_target_field_length')(data_expanded) File "E:\anaconda\lib\site-packages\keras\engine\base_layer.py", line 457, in call output = self.call(inputs, **kwargs) File "E:\speech-denoising-wavenet-master\layers.py", line 47, in call x = keras.backend.permute_dimensions(x, [0, 2, 1]) File "E:\anaconda\lib\site-packages\keras\backend\theano_backend.py", line 936, in permute_dimensions y._keras_shape = tuple(np.asarray(x._keras_shape)[list(pattern)]) IndexError: index 2 is out of bounds for axis 0 with size 2

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