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Fix weight loading issue (#14016)

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Yih-Dar
2021-11-15 17:48:40 +01:00
committed by GitHub
parent 74e6111ba7
commit a67d47b40c
2 changed files with 40 additions and 0 deletions
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18
tests/test_modeling_tf_encoder_decoder.py
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@@ -457,6 +457,14 @@ class TFBertEncoderDecoderModelTest(TFEncoderDecoderMixin, unittest.TestCase):
self.assertEqual(summary, [EXPECTED_SUMMARY_STUDENTS])
# Test with the TF checkpoint
model = TFEncoderDecoderModel.from_pretrained("ydshieh/bert2bert-cnn_dailymail-fp16")
output_ids = model.generate(input_ids=input_dict["input_ids"], max_length=None).numpy().tolist()
summary = tokenizer.batch_decode(output_ids, skip_special_tokens=True)
self.assertEqual(summary, [EXPECTED_SUMMARY_STUDENTS])
@require_tf
class TFGPT2EncoderDecoderModelTest(TFEncoderDecoderMixin, unittest.TestCase):
@@ -785,6 +793,16 @@ class TFEncoderDecoderModelSaveLoadTests(unittest.TestCase):
max_diff = np.max(np.abs(logits_pt.detach().cpu().numpy() - logits_tf.numpy()))
self.assertAlmostEqual(max_diff, 0.0, places=3)
# Make sure `from_pretrained` following `save_pretrained` work and give the same result
with tempfile.TemporaryDirectory() as tmp_dirname:
encoder_decoder_tf.save_pretrained(tmp_dirname)
encoder_decoder_tf = TFEncoderDecoderModel.from_pretrained(tmp_dirname)
logits_tf_2 = encoder_decoder_tf(input_ids=input_ids, decoder_input_ids=decoder_input_ids).logits
max_diff = np.max(np.abs(logits_tf_2.numpy() - logits_tf.numpy()))
self.assertAlmostEqual(max_diff, 0.0, places=3)
# TensorFlow => PyTorch
with tempfile.TemporaryDirectory() as tmp_dirname:
encoder_decoder_tf.save_pretrained(tmp_dirname)