Skip to content

Fix minor review comments #16

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
gauravjain14 merged 1 commit into from
Jan 27, 2025
Merged

Fix minor review comments #16

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
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
6 changes: 3 additions & 3 deletions src/transformers/generation/candidate_generator.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -635,10 +635,10 @@ def __init__(
self._target_tokenizer: "PreTrainedTokenizerBase" = target_tokenizer
self._assistant_tokenizer: "PreTrainedTokenizerBase" = assistant_tokenizer
self._assistant_model_device: str = assistant_model_device
if target_vocab_size:
self.target_vocab_size: int = target_vocab_size
else:
if target_vocab_size is None:
self.target_vocab_size: int = len(self._target_tokenizer.get_vocab())
else:
self.target_vocab_size: int = target_vocab_size
self.filter_value: float = filter_value
self.suppress_tokens_id: int = suppress_tokens_id
self._assistant_to_target_input_ids, self.target_to_assistant_input_ids = (
Expand Down
5 changes: 2 additions & 3 deletions src/transformers/generation/logits_process.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1860,15 +1860,14 @@ class SuppressTokensLogitsProcessor(LogitsProcessor):
```
"""

def __init__(self, suppress_tokens, device: str = "cpu", filter_value: float = -float("Inf")):
def __init__(self, suppress_tokens, device: str = "cpu"):
self.suppress_tokens = torch.tensor(list(suppress_tokens), device=device)
self.filter_value = filter_value

@add_start_docstrings(LOGITS_PROCESSOR_INPUTS_DOCSTRING)
def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor) -> torch.FloatTensor:
vocab_tensor = torch.arange(scores.shape[-1], device=scores.device)
suppress_token_mask = isin_mps_friendly(vocab_tensor, self.suppress_tokens)
scores = torch.where(suppress_token_mask, self.filter_value, scores)
scores = torch.where(suppress_token_mask, -float("inf"), scores)
return scores


Expand Down
2 changes: 0 additions & 2 deletions src/transformers/generation/utils.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -4282,8 +4282,6 @@ def _assisted_decoding(

# 1. Fetch candidate sequences from a `CandidateGenerator` and move to the correct device
candidate_input_ids, candidate_logits = candidate_generator.get_candidates(input_ids)
candidate_input_ids = candidate_input_ids.to(self.device)

candidate_input_ids = candidate_input_ids.to(self.device)
if candidate_logits is not None:
candidate_logits = candidate_logits.to(self.device)
Expand Down
38 changes: 0 additions & 38 deletions tests/generation/test_candidate_generator.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -16,44 +16,6 @@
)


class TestAssistedCandidateGeneratorDifferentTokenizers(unittest.TestCase):
def test_no_intersection(self):
prompt = np.array([[1, 2, 3]])
prompt_plus_new_tokens = np.array([[4, 5, 6]])
result = AssistedCandidateGeneratorDifferentTokenizers._get_tokens_diag(prompt, prompt_plus_new_tokens)
self.assertEqual(result, (None, None, None))

def test_complete_overlap(self):
prompt = np.array([[1, 2, 3]])
prompt_plus_new_tokens = np.array([[1, 2, 3, 4, 5]])
discrep_length, new_tokens_only, discrep_only = AssistedCandidateGeneratorDifferentTokenizers._get_tokens_diag(
prompt, prompt_plus_new_tokens
)
self.assertEqual(discrep_length, 0)
np.testing.assert_array_equal(new_tokens_only, np.array([[4, 5]]))
np.testing.assert_array_equal(discrep_only, np.array([[]]))

def test_partial_overlap(self):
prompt = np.array([[1, 2, 3]])
prompt_plus_new_tokens = np.array([[2, 3, 4, 5]])
discrep_length, new_tokens_only, discrep_only = AssistedCandidateGeneratorDifferentTokenizers._get_tokens_diag(
prompt, prompt_plus_new_tokens
)
self.assertEqual(discrep_length, 0)
np.testing.assert_array_equal(new_tokens_only, np.array([[4, 5]]))
np.testing.assert_array_equal(discrep_only, np.array([[]]))

def test_no_new_tokens(self):
prompt = np.array([[1, 2, 3]])
prompt_plus_new_tokens = np.array([[1, 2, 3]])
discrep_length, new_tokens_only, discrep_only = AssistedCandidateGeneratorDifferentTokenizers._get_tokens_diag(
prompt, prompt_plus_new_tokens
)
self.assertEqual(discrep_length, 0)
np.testing.assert_array_equal(new_tokens_only, np.array([[]]))
np.testing.assert_array_equal(discrep_only, np.array([[]]))


class TestAssistantToTargetTranslator(unittest.TestCase):
def setUp(self):
# Create mock tokenizers with predefined vocabularies
Expand Down