Add TF generate sample tests with all logit processors (#15852)
* Add GPT2 TF generate sample test with all logits processor * Add T5 generate sample test
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@@ -442,7 +442,7 @@ class TFGPT2ModelLanguageGenerationTest(unittest.TestCase):
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self.assertListEqual(output_ids[0].numpy().tolist(), expected_output_ids)
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@slow
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def test_lm_generate_distilgpt2_batch_special(self):
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def test_lm_generate_greedy_distilgpt2_batch_special(self):
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model = TFGPT2LMHeadModel.from_pretrained("distilgpt2")
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tokenizer = GPT2Tokenizer.from_pretrained("distilgpt2")
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@@ -468,6 +468,37 @@ class TFGPT2ModelLanguageGenerationTest(unittest.TestCase):
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]
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self.assertListEqual(output_strings, expected_output_string)
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@slow
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def test_lm_generate_sample_distilgpt2_batch_special(self):
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model = TFGPT2LMHeadModel.from_pretrained("distilgpt2")
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tokenizer = GPT2Tokenizer.from_pretrained("distilgpt2")
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tokenizer.pad_token = tokenizer.eos_token
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tokenizer.padding_side = "left"
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sentences = ["Today is a beautiful day and", "Yesterday was"]
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input_ids = tokenizer(sentences, return_tensors="tf", padding=True).input_ids
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generation_kwargs = {
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"do_sample": True,
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"bad_words_ids": [tokenizer("is").input_ids, tokenizer("angry about").input_ids],
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"no_repeat_ngram_size": 2,
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"repetition_penalty": 1.3,
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"temperature": 1.5,
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"top_k": 500,
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"top_p": 0.9,
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}
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tf.random.set_seed(42) # deterministic sampling sequence -> deterministic generation
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output_ids = model.generate(input_ids, **generation_kwargs)
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output_strings = tokenizer.batch_decode(output_ids, skip_special_tokens=True)
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expected_output_string = [
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"Today is a beautiful day and this makes finding holiday travel easier for you to do other project\nOh",
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"Yesterday was an enjoyable but especially great note though it certainly upset many Democrats who say",
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]
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self.assertListEqual(output_strings, expected_output_string)
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@slow
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def test_lm_generate_gpt2(self):
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model = TFGPT2LMHeadModel.from_pretrained("gpt2")
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