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Time to Say Goodbye, torch 1.7 and 1.8 (#22291)

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* time to say goodbye, torch 1.7 and 1.8

* clean up torch_int_div

* clean up is_torch_less_than_1_8-9

* update

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Yih-Dar
2023-03-21 19:22:01 +01:00
committed by GitHub
parent 86c7931a70
commit 67c2dbdb54
42 changed files with 61 additions and 149 deletions
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19
tests/models/wav2vec2/test_modeling_wav2vec2.py
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@@ -71,9 +71,6 @@ if is_torch_available():
_compute_mask_indices,
_sample_negative_indices,
)
from transformers.pytorch_utils import is_torch_less_than_1_9, torch_int_div
else:
is_torch_less_than_1_9 = True
if is_torchaudio_available():
@@ -1217,7 +1214,9 @@ class Wav2Vec2UtilsTest(unittest.TestCase):
sequence_length = 10
hidden_size = 4
num_negatives = 3
sequence = torch_int_div(torch.arange(sequence_length * hidden_size, device=torch_device), hidden_size)
sequence = torch.div(
torch.arange(sequence_length * hidden_size, device=torch_device), hidden_size, rounding_mode="floor"
)
features = sequence.view(sequence_length, hidden_size) # each value in vector consits of same value
features = features[None, :].expand(batch_size, sequence_length, hidden_size).contiguous()
@@ -1245,7 +1244,9 @@ class Wav2Vec2UtilsTest(unittest.TestCase):
mask = torch.ones((batch_size, sequence_length), dtype=torch.long, device=torch_device)
mask[-1, sequence_length // 2 :] = 0
sequence = torch_int_div(torch.arange(sequence_length * hidden_size, device=torch_device), hidden_size)
sequence = torch.div(
torch.arange(sequence_length * hidden_size, device=torch_device), hidden_size, rounding_mode="floor"
)
features = sequence.view(sequence_length, hidden_size) # each value in vector consits of same value
features = features[None, :].expand(batch_size, sequence_length, hidden_size).contiguous()
@@ -1651,10 +1652,6 @@ class Wav2Vec2ModelIntegrationTest(unittest.TestCase):
@require_pyctcdecode
@require_torchaudio
@unittest.skipIf(
is_torch_less_than_1_9,
reason="`torchaudio.functional.resample` needs torchaudio >= 0.9 which requires torch >= 0.9",
)
def test_wav2vec2_with_lm(self):
ds = load_dataset("common_voice", "es", split="test", streaming=True)
sample = next(iter(ds))
@@ -1679,10 +1676,6 @@ class Wav2Vec2ModelIntegrationTest(unittest.TestCase):
@require_pyctcdecode
@require_torchaudio
@unittest.skipIf(
is_torch_less_than_1_9,
reason="`torchaudio.functional.resample` needs torchaudio >= 0.9 which requires torch >= 0.9",
)
def test_wav2vec2_with_lm_pool(self):
ds = load_dataset("common_voice", "es", split="test", streaming=True)
sample = next(iter(ds))