SUMIN/HuggingFace_transformer
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refactored code a bit and made more generic

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This commit is contained in:
Patrick von Platen
2020-03-05 14:56:56 +01:00
parent d8e2b3c547
commit c0d9dd3ba9
4 changed files with 28 additions and 16 deletions
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2
tests/test_modeling_bart.py
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@@ -442,7 +442,7 @@ class BartModelIntegrationTest(unittest.TestCase):
tokens = tok.encode(text, return_tensors="pt").to(torch_device)
extra_len = 20
gen_tokens_1 = hf.generate_1(tokens, num_beams=4, max_length=extra_len,) # repetition_penalty=10.,
gen_tokens = hf.generate(tokens, num_beams=4, max_length=extra_len, do_sample=False) # repetition_penalty=10.,
gen_tokens = hf.generate(tokens, num_beams=4, max_length=extra_len + 2, do_sample=False) # repetition_penalty=10.,
print("1: {}".format(gen_tokens_1))
print("2: {}".format(gen_tokens))
ipdb.set_trace()

2
tests/test_modeling_common.py
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@@ -621,7 +621,7 @@ class ModelTesterMixin:
with torch.no_grad():
model(**inputs_dict)
def _A_test_lm_head_model_random_generate(self):
def test_lm_head_model_random_generate(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
input_ids = inputs_dict.get(