You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Model I am using (ListenAttendSpell, Transformer, Conformer ...): conformer_transducer
The problem arises when using:
CUDA_VISIBLE_DEVICES=8 python ./openspeech_cli/hydra_train.py dataset=libri dataset.dataset_path=/data/dataset/Libri/LibriSpeech dataset.dataset_download=False dataset.manifest_file_path=/home/gpu/WorkSpace/Speech/OpenSpeech/dataset/libri_subword_manifest.txt vocab=libri_subword vocab.vocab_size=5000 vocab.vocab_path=/home/gpu/WorkSpace/Speech/OpenSpeech/dataset model=conformer_transducer audio=fbank lr_scheduler=warmup_reduce_lr_on_plateau trainer=gpu trainer.batch_size=4 criterion=transducer
Error executing job with overrides: ['dataset=libri', 'dataset.dataset_path=/data/dataset/Libri/LibriSpeech', 'dataset.dataset_download=False', 'dataset.manifest_file_path=/home/gpu/WorkSpace/Speech/OpenSpeech/dataset/libri_subword_manifest.txt', 'vocab=libri_subword', 'vocab.vocab_size=5000', 'vocab.vocab_path=/home/gpu/WorkSpace/Speech/OpenSpeech/dataset', 'model=conformer_transducer', 'audio=fbank', 'lr_scheduler=warmup_reduce_lr_on_plateau', 'trainer=gpu', 'trainer.batch_size=4', 'criterion=transducer']
Traceback (most recent call last):
File "./openspeech_cli/hydra_train.py", line 51, in hydra_main
trainer.fit(model, data_module)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 458, in fit
self._run(model)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 756, in _run
self.dispatch()
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 797, in dispatch
self.accelerator.start_training(self)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/accelerators/accelerator.py", line 96, in start_training
self.training_type_plugin.start_training(trainer)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/plugins/training_type/training_type_plugin.py", line 144, in start_training
self._results = trainer.run_stage()
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 807, in run_stage
return self.run_train()
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 869, in run_train
self.train_loop.run_training_epoch()
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 499, in run_training_epoch
batch_output = self.run_training_batch(batch, batch_idx, dataloader_idx)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 738, in run_training_batch
self.optimizer_step(optimizer, opt_idx, batch_idx, train_step_and_backward_closure)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 442, in optimizer_step
using_lbfgs=is_lbfgs,
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/core/lightning.py", line 1403, in optimizer_step
optimizer.step(closure=optimizer_closure)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/core/optimizer.py", line 214, in step
self.__optimizer_step(*args, closure=closure, profiler_name=profiler_name, **kwargs)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/core/optimizer.py", line 134, in __optimizer_step
trainer.accelerator.optimizer_step(optimizer, self._optimizer_idx, lambda_closure=closure, **kwargs)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/accelerators/accelerator.py", line 329, in optimizer_step
self.run_optimizer_step(optimizer, opt_idx, lambda_closure, **kwargs)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/accelerators/accelerator.py", line 336, in run_optimizer_step
self.training_type_plugin.optimizer_step(optimizer, lambda_closure=lambda_closure, **kwargs)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/plugins/training_type/training_type_plugin.py", line 193, in optimizer_step
optimizer.step(closure=lambda_closure, **kwargs)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/torch/autograd/grad_mode.py", line 26, in decorate_context
return func(*args, **kwargs)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/torch/optim/adam.py", line 66, in step
loss = closure()
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 733, in train_step_and_backward_closure
split_batch, batch_idx, opt_idx, optimizer, self.trainer.hiddens
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 823, in training_step_and_backward
result = self.training_step(split_batch, batch_idx, opt_idx, hiddens)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 290, in training_step
training_step_output = self.trainer.accelerator.training_step(args)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/accelerators/accelerator.py", line 204, in training_step
return self.training_type_plugin.training_step(*args)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/plugins/training_type/dp.py", line 98, in training_step
return self.model(*args, **kwargs)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/torch/nn/parallel/data_parallel.py", line 159, in forward
return self.module(*inputs[0], **kwargs[0])
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/overrides/data_parallel.py", line 77, in forward
output = super().forward(*inputs, **kwargs)
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/pytorch_lightning/overrides/base.py", line 46, in forward
output = self.module.training_step(*inputs, **kwargs)
File "/home/gpu/WorkSpace/Speech/OpenSpeech/openspeech/models/conformer_transducer/model.py", line 110, in training_step
return super(ConformerTransducerModel, self).training_step(batch, batch_idx)
File "/home/gpu/WorkSpace/Speech/OpenSpeech/openspeech/models/openspeech_transducer_model.py", line 268, in training_step
target_lengths=target_lengths,
File "/home/gpu/WorkSpace/Speech/OpenSpeech/openspeech/models/openspeech_transducer_model.py", line 90, in collect_outputs
target_lengths=target_lengths.int(),
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/gpu/WorkSpace/Speech/OpenSpeech/openspeech/criterion/transducer/transducer.py", line 96, in forward
gather=self.gather,
File "/home/gpu/anaconda3/envs/openspeech/lib/python3.7/site-packages/warp_rnnt-0.4.0-py3.7-linux-x86_64.egg/warp_rnnt/__init__.py", line 74, in rnnt_loss
index[:, :, :U-1, 1] = labels.unsqueeze(dim=1)
RuntimeError: The expanded size of the tensor (61) must match the existing size (62) at non-singleton dimension 2. Target sizes: [4, 355, 61]. Tensor sizes: [4, 1, 62]
The Loss function:
def rnnt_loss(log_probs: torch.FloatTensor,
labels: torch.IntTensor,
frames_lengths: torch.IntTensor,
labels_lengths: torch.IntTensor,
average_frames: bool = False,
reduction: Optional[AnyStr] = None,
blank: int = 0,
gather: bool = False) -> torch.Tensor:
The CUDA-Warp RNN-Transducer loss.
Args:
log_probs (torch.FloatTensor): Input tensor with shape (N, T, U, V)
where N is the minibatch size, T is the maximum number of
input frames, U is the maximum number of output labels and V is
the vocabulary of labels (including the blank).
labels (torch.IntTensor): Tensor with shape (N, U-1) representing the
reference labels for all samples in the minibatch.
frames_lengths (torch.IntTensor): Tensor with shape (N,) representing the
number of frames for each sample in the minibatch.
labels_lengths (torch.IntTensor): Tensor with shape (N,) representing the
length of the transcription for each sample in the minibatch.
average_frames (bool, optional): Specifies whether the loss of each
sample should be divided by its number of frames.
Default: False.
reduction (string, optional): Specifies the type of reduction.
Default: None.
blank (int, optional): label used to represent the blank symbol.
Default: 0.
gather (bool, optional): Reduce memory consumption.
Default: False.
The log_probs and labels of model output and function requirements are inconsistent
The text was updated successfully, but these errors were encountered:
Environment info
Information
Model I am using (ListenAttendSpell, Transformer, Conformer ...): conformer_transducer
The problem arises when using:
CUDA_VISIBLE_DEVICES=8 python ./openspeech_cli/hydra_train.py dataset=libri dataset.dataset_path=/data/dataset/Libri/LibriSpeech dataset.dataset_download=False dataset.manifest_file_path=/home/gpu/WorkSpace/Speech/OpenSpeech/dataset/libri_subword_manifest.txt vocab=libri_subword vocab.vocab_size=5000 vocab.vocab_path=/home/gpu/WorkSpace/Speech/OpenSpeech/dataset model=conformer_transducer audio=fbank lr_scheduler=warmup_reduce_lr_on_plateau trainer=gpu trainer.batch_size=4 criterion=transducer
The Loss function:
The log_probs and labels of model output and function requirements are inconsistent
The text was updated successfully, but these errors were encountered: