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Unverified Commit 27d348f2 authored by Patrick von Platen's avatar Patrick von Platen Committed by GitHub
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[Wav2Vec2, Hubert] Fix ctc loss test (#12458) 

* fix_torch_device_generate_test

* remove @

* fix test
parent b655f16d
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Showing with 8 additions and 6 deletions
tests/test_modeling_hubert.py
View file @ 27d348f2
...@@ -176,12 +176,13 @@ class HubertModelTester: ...@@ -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
......
tests/test_modeling_wav2vec2.py
View file @ 27d348f2
...@@ -184,12 +184,13 @@ class Wav2Vec2ModelTester: ...@@ -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
......
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