Skip to content
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
16 changes: 10 additions & 6 deletions tests/models/gpt2/test_modeling_gpt2.py
Original file line number Diff line number Diff line change
Expand Up @@ -651,16 +651,18 @@ def test_batch_generation(self):
outputs = model.generate(
input_ids=input_ids,
attention_mask=inputs["attention_mask"].to(torch_device),
max_length=20,
)

outputs_tt = model.generate(
input_ids=input_ids,
attention_mask=inputs["attention_mask"].to(torch_device),
token_type_ids=token_type_ids,
max_length=20,
)

inputs_non_padded = tokenizer(sentences[0], return_tensors="pt").input_ids.to(torch_device)
output_non_padded = model.generate(input_ids=inputs_non_padded)
output_non_padded = model.generate(input_ids=inputs_non_padded, max_length=20)

num_paddings = inputs_non_padded.shape[-1] - inputs["attention_mask"][-1].long().sum().cpu().item()
inputs_padded = tokenizer(sentences[1], return_tensors="pt").input_ids.to(torch_device)
Expand Down Expand Up @@ -711,16 +713,18 @@ def test_batch_generation_2heads(self):
outputs = model.generate(
input_ids=input_ids,
attention_mask=inputs["attention_mask"].to(torch_device),
max_length=20,
)

outputs_tt = model.generate(
input_ids=input_ids,
attention_mask=inputs["attention_mask"].to(torch_device),
token_type_ids=token_type_ids,
max_length=20,
)

inputs_non_padded = tokenizer(sentences[0], return_tensors="pt").input_ids.to(torch_device)
output_non_padded = model.generate(input_ids=inputs_non_padded)
output_non_padded = model.generate(input_ids=inputs_non_padded, max_length=20)

num_paddings = inputs_non_padded.shape[-1] - inputs["attention_mask"][-1].long().sum().cpu().item()
inputs_padded = tokenizer(sentences[1], return_tensors="pt").input_ids.to(torch_device)
Expand Down Expand Up @@ -776,7 +780,7 @@ def _test_lm_generate_gpt2_helper(

# The dog was found in a field near the intersection of West and West Streets.\n\nThe dog
expected_output_ids = [464, 3290, 373, 1043, 287, 257, 2214, 1474, 262, 16246, 286, 2688, 290, 2688, 27262, 13, 198, 198, 464, 3290,] # fmt: skip
output_ids = model.generate(input_ids, do_sample=False)
output_ids = model.generate(input_ids, do_sample=False, max_length=20)
if verify_outputs:
self.assertListEqual(output_ids[0].tolist(), expected_output_ids)

Expand Down Expand Up @@ -805,13 +809,13 @@ def test_gpt2_sample(self):
torch.manual_seed(0)
tokenized = tokenizer("Today is a nice day and", return_tensors="pt", return_token_type_ids=True)
input_ids = tokenized.input_ids.to(torch_device)
output_ids = model.generate(input_ids, do_sample=True)
output_ids = model.generate(input_ids, do_sample=True, max_length=20)
output_str = tokenizer.decode(output_ids[0], skip_special_tokens=True)

token_type_ids = tokenized.token_type_ids.to(torch_device)
output_seq = model.generate(input_ids=input_ids, do_sample=True, num_return_sequences=5)
output_seq = model.generate(input_ids=input_ids, do_sample=True, num_return_sequences=5, max_length=20)
output_seq_tt = model.generate(
input_ids=input_ids, token_type_ids=token_type_ids, do_sample=True, num_return_sequences=5
input_ids=input_ids, token_type_ids=token_type_ids, do_sample=True, num_return_sequences=5, max_length=20
)
output_seq_strs = tokenizer.batch_decode(output_seq, skip_special_tokens=True)
output_seq_tt_strs = tokenizer.batch_decode(output_seq_tt, skip_special_tokens=True)
Expand Down