Train loss 55 0.477043 Grad Norm 0.824708 4.30s/it
here
Traceback (most recent call last):
File "train.py", line 286, in
args.warm_start, args.n_gpus, args.rank, args.group_name, hparams)
File "train.py", line 210, in train
y_pred = model(x)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, kwargs)
File "/content/mellotron/model.py", line 611, in forward
embedded_text = self.encoder(embedded_inputs, input_lengths)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, *kwargs)
File "/content/mellotron/model.py", line 193, in forward
curr_x = F.dropout(F.relu(conv(curr_x)), drop_rate, self.training)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(input, kwargs)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/container.py", line 119, in forward
input = module(input)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/batchnorm.py", line 140, in forward
self.weight, self.bias, bn_training, exponential_average_factor, self.eps)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py", line 2147, in batch_norm
_verify_batch_size(input.size())
File "/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py", line 2114, in _verify_batch_size
raise ValueError("Expected more than 1 value per channel when training, got input size {}".format(size))
ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 512, 1])
Train loss 55 0.477043 Grad Norm 0.824708 4.30s/it here Traceback (most recent call last): File "train.py", line 286, in
args.warm_start, args.n_gpus, args.rank, args.group_name, hparams)
File "train.py", line 210, in train
y_pred = model(x)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, kwargs)
File "/content/mellotron/model.py", line 611, in forward
embedded_text = self.encoder(embedded_inputs, input_lengths)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, *kwargs)
File "/content/mellotron/model.py", line 193, in forward
curr_x = F.dropout(F.relu(conv(curr_x)), drop_rate, self.training)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(input, kwargs)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/container.py", line 119, in forward
input = module(input)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/batchnorm.py", line 140, in forward
self.weight, self.bias, bn_training, exponential_average_factor, self.eps)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py", line 2147, in batch_norm
_verify_batch_size(input.size())
File "/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py", line 2114, in _verify_batch_size
raise ValueError("Expected more than 1 value per channel when training, got input size {}".format(size))
ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 512, 1])