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Hi, some people have reported that putting torch==0.4.1 in the requirements works for them. For me this produces this error:
/content/samplernn-pytorch/model.py:60: UserWarning: nn.init.kaiming_uniform is now deprecated in favor of nn.init.kaiming_uniform_. init.kaiming_uniform(self.input_expand.weight) /content/samplernn-pytorch/model.py:61: UserWarning: nn.init.constant is now deprecated in favor of nn.init.constant_. init.constant(self.input_expand.bias, 0) /content/samplernn-pytorch/nn.py:48: UserWarning: nn.init.uniform is now deprecated in favor of nn.init.uniform_. nn.init.uniform(tensor, -math.sqrt(3 / fan_in), math.sqrt(3 / fan_in)) /content/samplernn-pytorch/model.py:76: UserWarning: nn.init.constant is now deprecated in favor of nn.init.constant_. init.constant(getattr(self.rnn, 'bias_ih_l{}'.format(i)), 0) /content/samplernn-pytorch/nn.py:62: UserWarning: nn.init.orthogonal is now deprecated in favor of nn.init.orthogonal_. init(chunk) /content/samplernn-pytorch/model.py:82: UserWarning: nn.init.constant is now deprecated in favor of nn.init.constant_. init.constant(getattr(self.rnn, 'bias_hh_l{}'.format(i)), 0) /content/samplernn-pytorch/nn.py:31: UserWarning: nn.init.constant is now deprecated in favor of nn.init.constant_. nn.init.constant(self.bias, 0) /content/samplernn-pytorch/model.py:90: UserWarning: nn.init.uniform is now deprecated in favor of nn.init.uniform_. self.upsampling.conv_t.weight, -np.sqrt(6 / dim), np.sqrt(6 / dim) /content/samplernn-pytorch/model.py:92: UserWarning: nn.init.constant is now deprecated in favor of nn.init.constant_. init.constant(self.upsampling.bias, 0) /content/samplernn-pytorch/model.py:141: UserWarning: nn.init.kaiming_uniform is now deprecated in favor of nn.init.kaiming_uniform_. init.kaiming_uniform(self.input.weight) /content/samplernn-pytorch/model.py:150: UserWarning: nn.init.kaiming_uniform is now deprecated in favor of nn.init.kaiming_uniform_. init.kaiming_uniform(self.hidden.weight) /content/samplernn-pytorch/model.py:151: UserWarning: nn.init.constant is now deprecated in favor of nn.init.constant_. init.constant(self.hidden.bias, 0) /content/samplernn-pytorch/model.py:161: UserWarning: nn.init.constant is now deprecated in favor of nn.init.constant_. init.constant(self.output.bias, 0) Traceback (most recent call last): File "train.py", line 360, in <module> main(**vars(parser.parse_args())) File "train.py", line 258, in main trainer.run(params['epoch_limit']) File "/content/samplernn-pytorch/trainer/__init__.py", line 56, in run self.train() File "/content/samplernn-pytorch/trainer/__init__.py", line 61, in train enumerate(self.dataset, self.iterations + 1): File "/content/samplernn-pytorch/dataset.py", line 51, in __iter__ for batch in super().__iter__(): File "/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py", line 314, in __next__ batch = self.collate_fn([self.dataset[i] for i in indices]) File "/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py", line 314, in <listcomp> batch = self.collate_fn([self.dataset[i] for i in indices]) File "/content/samplernn-pytorch/dataset.py", line 34, in __getitem__ torch.from_numpy(seq), self.q_levels RuntimeError: PyTorch was compiled without NumPy support
Hi, some people have reported that putting torch==0.4.1 in the requirements works for them. For me this produces this error:
/content/samplernn-pytorch/model.py:60: UserWarning: nn.init.kaiming_uniform is now deprecated in favor of nn.init.kaiming_uniform_. init.kaiming_uniform(self.input_expand.weight) /content/samplernn-pytorch/model.py:61: UserWarning: nn.init.constant is now deprecated in favor of nn.init.constant_. init.constant(self.input_expand.bias, 0) /content/samplernn-pytorch/nn.py:48: UserWarning: nn.init.uniform is now deprecated in favor of nn.init.uniform_. nn.init.uniform(tensor, -math.sqrt(3 / fan_in), math.sqrt(3 / fan_in)) /content/samplernn-pytorch/model.py:76: UserWarning: nn.init.constant is now deprecated in favor of nn.init.constant_. init.constant(getattr(self.rnn, 'bias_ih_l{}'.format(i)), 0) /content/samplernn-pytorch/nn.py:62: UserWarning: nn.init.orthogonal is now deprecated in favor of nn.init.orthogonal_. init(chunk) /content/samplernn-pytorch/model.py:82: UserWarning: nn.init.constant is now deprecated in favor of nn.init.constant_. init.constant(getattr(self.rnn, 'bias_hh_l{}'.format(i)), 0) /content/samplernn-pytorch/nn.py:31: UserWarning: nn.init.constant is now deprecated in favor of nn.init.constant_. nn.init.constant(self.bias, 0) /content/samplernn-pytorch/model.py:90: UserWarning: nn.init.uniform is now deprecated in favor of nn.init.uniform_. self.upsampling.conv_t.weight, -np.sqrt(6 / dim), np.sqrt(6 / dim) /content/samplernn-pytorch/model.py:92: UserWarning: nn.init.constant is now deprecated in favor of nn.init.constant_. init.constant(self.upsampling.bias, 0) /content/samplernn-pytorch/model.py:141: UserWarning: nn.init.kaiming_uniform is now deprecated in favor of nn.init.kaiming_uniform_. init.kaiming_uniform(self.input.weight) /content/samplernn-pytorch/model.py:150: UserWarning: nn.init.kaiming_uniform is now deprecated in favor of nn.init.kaiming_uniform_. init.kaiming_uniform(self.hidden.weight) /content/samplernn-pytorch/model.py:151: UserWarning: nn.init.constant is now deprecated in favor of nn.init.constant_. init.constant(self.hidden.bias, 0) /content/samplernn-pytorch/model.py:161: UserWarning: nn.init.constant is now deprecated in favor of nn.init.constant_. init.constant(self.output.bias, 0) Traceback (most recent call last): File "train.py", line 360, in <module> main(**vars(parser.parse_args())) File "train.py", line 258, in main trainer.run(params['epoch_limit']) File "/content/samplernn-pytorch/trainer/__init__.py", line 56, in run self.train() File "/content/samplernn-pytorch/trainer/__init__.py", line 61, in train enumerate(self.dataset, self.iterations + 1): File "/content/samplernn-pytorch/dataset.py", line 51, in __iter__ for batch in super().__iter__(): File "/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py", line 314, in __next__ batch = self.collate_fn([self.dataset[i] for i in indices]) File "/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py", line 314, in <listcomp> batch = self.collate_fn([self.dataset[i] for i in indices]) File "/content/samplernn-pytorch/dataset.py", line 34, in __getitem__ torch.from_numpy(seq), self.q_levels RuntimeError: PyTorch was compiled without NumPy support
I'm using this Colab notebook btw: https://drive.google.com/file/d/13tVz73FXyG8Xvidl-SqyxNtBwozAlvth/view?usp=sharing
Any help would be appreciated!
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