Openspeech CTC Model¶
Openspeech CTC Model¶
-
class
openspeech.models.openspeech_ctc_model.
OpenspeechCTCModel
(configs: omegaconf.dictconfig.DictConfig, tokenizer: openspeech.tokenizers.tokenizer.Tokenizer)[source]¶ Base class for OpenSpeech’s encoder-only models (ctc-model).
- Parameters
configs (DictConfig) – configuration set.
tokenizer (Tokenizer) – tokenizer is in charge of preparing the inputs for a model.
- Inputs:
inputs (torch.FloatTensor): A input sequence passed to encoders. Typically for inputs this will be a padded FloatTensor of size
(batch, seq_length, dimension)
. input_lengths (torch.LongTensor): The length of input tensor.(batch)
- Returns
Result of model predictions that contains y_hats, logits, output_lengths
- Return type
ouputs (dict)
-
forward
(inputs: torch.FloatTensor, input_lengths: torch.IntTensor) → Dict[str, torch.Tensor][source]¶ Forward propagate a inputs and targets pair for inference.
- Parameters
inputs (torch.FloatTensor) – A input sequence passed to encoders. Typically for inputs this will be a padded FloatTensor of size
(batch, seq_length, dimension)
.input_lengths (torch.IntTensor) – The length of input tensor.
(batch)
- Returns
Result of model predictions that contains y_hats, logits, output_lengths
- Return type
ouputs (dict)
-
test_step
(batch: tuple, batch_idx: int) → collections.OrderedDict[source]¶ Forward propagate a inputs and targets pair for test.
- Inputs:
train_batch (tuple): A train batch contains inputs, targets, input_lengths, target_lengths batch_idx (int): The index of batch
- Returns
loss for training
- Return type
loss (torch.Tensor)
-
training_step
(batch: tuple, batch_idx: int) → collections.OrderedDict[source]¶ Forward propagate a inputs and targets pair for training.
- Inputs:
train_batch (tuple): A train batch contains inputs, targets, input_lengths, target_lengths batch_idx (int): The index of batch
- Returns
loss for training
- Return type
loss (torch.Tensor)
-
validation_step
(batch: tuple, batch_idx: int) → collections.OrderedDict[source]¶ Forward propagate a inputs and targets pair for validation.
- Inputs:
train_batch (tuple): A train batch contains inputs, targets, input_lengths, target_lengths batch_idx (int): The index of batch
- Returns
loss for training
- Return type
loss (torch.Tensor)