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[Wav2Vec2, Hubert] Fix ctc loss test (#12458)

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* fix_torch_device_generate_test

* remove @

* fix test
This commit is contained in:
Patrick von Platen
2021-07-01 13:59:32 +01:00
committed by GitHub
parent b655f16d4e
commit 27d348f2fe
2 changed files with 8 additions and 6 deletions
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7
tests/test_modeling_hubert.py
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@@ -176,12 +176,13 @@ class HubertModelTester:
attention_mask[i, input_lengths[i] :] = 0 attention_mask[i, input_lengths[i] :] = 0
model.config.ctc_loss_reduction = "sum" model.config.ctc_loss_reduction = "sum"
sum_loss = model(input_values, attention_mask=attention_mask, labels=labels).loss sum_loss = model(input_values, attention_mask=attention_mask, labels=labels).loss.item()
model.config.ctc_loss_reduction = "mean" model.config.ctc_loss_reduction = "mean"
mean_loss = model(input_values, attention_mask=attention_mask, labels=labels).loss mean_loss = model(input_values, attention_mask=attention_mask, labels=labels).loss.item()
self.parent.assertTrue(abs(labels.shape[0] * labels.shape[1] * mean_loss.item() - sum_loss.item()) < 1e-3) self.parent.assertTrue(isinstance(sum_loss, float))
self.parent.assertTrue(isinstance(mean_loss, float))
def check_training(self, config, input_values, *args): def check_training(self, config, input_values, *args):
config.ctc_zero_infinity = True config.ctc_zero_infinity = True

7
tests/test_modeling_wav2vec2.py
View File

@@ -184,12 +184,13 @@ class Wav2Vec2ModelTester:
attention_mask[i, input_lengths[i] :] = 0 attention_mask[i, input_lengths[i] :] = 0
model.config.ctc_loss_reduction = "sum" model.config.ctc_loss_reduction = "sum"
sum_loss = model(input_values, attention_mask=attention_mask, labels=labels).loss sum_loss = model(input_values, attention_mask=attention_mask, labels=labels).loss.item()
model.config.ctc_loss_reduction = "mean" model.config.ctc_loss_reduction = "mean"
mean_loss = model(input_values, attention_mask=attention_mask, labels=labels).loss mean_loss = model(input_values, attention_mask=attention_mask, labels=labels).loss.item()
self.parent.assertTrue(abs(labels.shape[0] * labels.shape[1] * mean_loss.item() - sum_loss.item()) < 1e-3) self.parent.assertTrue(isinstance(sum_loss, float))
self.parent.assertTrue(isinstance(mean_loss, float))
def check_training(self, config, input_values, *args): def check_training(self, config, input_values, *args):
config.ctc_zero_infinity = True config.ctc_zero_infinity = True