python smoke_test.py
Randomly generating input and output data...
inputs shape torch.Size([50, 500, 13])
target shape torch.Size([50, 20])
Sequential(
(0): Conv1d(13, 250, kernel_size=(48,), stride=(2,))
(1): ReLU()
(2): Conv1d(250, 250, kernel_size=(7,), stride=(1,))
(3): ReLU()
(4): Conv1d(250, 250, kernel_size=(7,), stride=(1,))
(5): ReLU()
(6): Conv1d(250, 250, kernel_size=(7,), stride=(1,))
(7): ReLU()
(8): Conv1d(250, 250, kernel_size=(7,), stride=(1,))
(9): ReLU()
(10): Conv1d(250, 250, kernel_size=(7,), stride=(1,))
(11): ReLU()
(12): Conv1d(250, 250, kernel_size=(7,), stride=(1,))
(13): ReLU()
(14): Conv1d(250, 250, kernel_size=(7,), stride=(1,))
(15): ReLU()
(16): Conv1d(250, 2000, kernel_size=(32,), stride=(1,))
(17): ReLU()
(18): Conv1d(2000, 2000, kernel_size=(1,), stride=(1,))
(19): ReLU()
(20): Conv1d(2000, 27, kernel_size=(1,), stride=(1,))
)
Traceback (most recent call last):
File "smoke_test.py", line 61, in <module>
smoke_test()
File "smoke_test.py", line 51, in smoke_test
model.fit(inputs, targets, optimizer, ctc_loss, batch_size, epoch=1, print_every=1)
File "/home/ubuntu/honghe/Wav2Letter_simple/Wav2Letter/model.py", line 98, in fit
log_probs = self.forward(batch)
File "/home/ubuntu/honghe/Wav2Letter_simple/Wav2Letter/model.py", line 64, in forward
y_pred = self.layers(batch)
File "/home/ubuntu/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__
result = self.forward(*input, **kwargs)
File "/home/ubuntu/anaconda3/lib/python3.6/site-packages/torch/nn/modules/container.py", line 92, in forward
input = module(input)
File "/home/ubuntu/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__
result = self.forward(*input, **kwargs)
File "/home/ubuntu/anaconda3/lib/python3.6/site-packages/torch/nn/modules/conv.py", line 187, in forward
self.padding, self.dilation, self.groups)
RuntimeError: code is too big
