@@ -306,7 +306,7 @@ class TFWav2Vec2ModelTester:
|
||||
model = TFWav2Vec2ForCTC(config)
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||||
input_lengths = tf.constant([input_values.shape[-1] // i for i in [4, 2, 1]])
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||||
max_length_labels = model.wav2vec2._get_feat_extract_output_lengths(input_lengths)
|
||||
labels = ids_tensor((input_values.shape[0], min(max_length_labels) - 1), model.config.vocab_size + 100)
|
||||
labels = ids_tensor((input_values.shape[0], min(max_length_labels) - 1), model.config.vocab_size + 500)
|
||||
with pytest.raises(ValueError):
|
||||
model(input_values, labels=labels)
|
||||
|
||||
|
||||
@@ -23,7 +23,7 @@ from requests import ReadTimeout
|
||||
from tests.pipelines.test_pipelines_document_question_answering import INVOICE_URL
|
||||
from transformers import is_torch_available, is_vision_available
|
||||
from transformers.image_utils import ChannelDimension, get_channel_dimension_axis, make_list_of_images
|
||||
from transformers.testing_utils import require_torch, require_vision
|
||||
from transformers.testing_utils import is_flaky, require_torch, require_vision
|
||||
|
||||
|
||||
if is_torch_available():
|
||||
@@ -486,6 +486,7 @@ class LoadImageTester(unittest.TestCase):
|
||||
|
||||
self.assertEqual(img_arr.shape, (1061, 750, 3))
|
||||
|
||||
@is_flaky()
|
||||
def test_load_img_url_timeout(self):
|
||||
with self.assertRaises(ReadTimeout):
|
||||
load_image(INVOICE_URL, timeout=0.001)
|
||||
|
||||
Reference in New Issue
Block a user