Merge branch 'master' into optimize-mean-subtoken-pooling

flair/embeddings/transformer.py

@@ -65,7 +65,7 @@ def pad_sequence_embeddings(all_hidden_states: List[torch.Tensor]) -> torch.Tens
 
 @torch.jit.script_if_tracing
 def truncate_hidden_states(hidden_states: torch.Tensor, input_ids: torch.Tensor) -> torch.Tensor:
- return hidden_states[:, :, : input_ids.size()[1]]
+ return hidden_states[:, :, : input_ids.size(1)]
 
 
 @torch.jit.script_if_tracing
@@ -95,14 +95,12 @@ def combine_strided_tensors(
  if selected_sentences.size(0) > 1:
  start_part = selected_sentences[0, : half_stride + 1]
  mid_part = selected_sentences[:, half_stride + 1 : max_length - 1 - half_stride]
- mid_part = torch.reshape(mid_part, (mid_part.shape[0] * mid_part.shape[1],) + mid_part.shape[2:])
- end_part = selected_sentences[selected_sentences.shape[0] - 1, max_length - half_stride - 1 :]
+ mid_part = torch.reshape(mid_part, (mid_part.size(0) * mid_part.size(1),) + mid_part.size()[2:])
+ end_part = selected_sentences[selected_sentences.size(0) - 1, max_length - half_stride - 1 :]
  sentence_hidden_state = torch.cat((start_part, mid_part, end_part), dim=0)
- sentence_hidden_states[sentence_id, : sentence_hidden_state.shape[0]] = torch.cat(
- (start_part, mid_part, end_part), dim=0
- )
+ sentence_hidden_states[sentence_id, : sentence_hidden_state.size(0)] = sentence_hidden_state
  else:
- sentence_hidden_states[sentence_id, : selected_sentences.shape[1]] = selected_sentences[0, :]
+ sentence_hidden_states[sentence_id, : selected_sentences.size(1)] = selected_sentences[0, :]
 
  return sentence_hidden_states