Comments (2)
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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Related Issues (20)
- Nvidia driver version exception HOT 1
- Denoised Speech is silence HOT 3
- What kind of HW is needed to run the "best performing model"? HOT 2
- Denoised audio 0db on NSDTSEA HOT 5
- index 2 is out of bounds for axis 0 with size 2
- PESQ and STOI
- requirements doesn't include TF HOT 2
- Readme requirements HOT 7
- TypeError: 'float' object cannot be interpreted as an integer HOT 7
- No optparse in python3
- No version in python3 ? HOT 1
- Not using XLA:CPU for cluster because envvar TF_XLA_FLAGS=--tf_xla_cpu_global_jit was not set. If you want XLA:CPU, either set that envvar, or use experimental_jit_scope to enable XLA:CPU. To confirm that XLA is active, pass --vmodule=xla_compilation_cache=1 (as a proper command-line flag, not via TF_XLA_FLAGS) or set the envvar XLA_FLAGS=--xla_hlo_profile.
- cudnn version
- parameter size
- out memory? HOT 5
- Difference Between this and others
- sor with shape[655360,31,1,256] and type float on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu HOT 3
- Has someone do inference (denoise an audio) successfully? HOT 2
- Implement the code
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