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Generate: move misplaced test (#29902)
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@ -1467,17 +1467,6 @@ class GenerationTesterMixin:
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past_kv[i][1].shape, (batch_size, num_attention_heads, seq_length, per_head_embed_dim)
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)
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def test_generate_from_inputs_embeds_with_bos_token_id_is_none(self):
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article = "Today a dragon flew over Paris."
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model = AutoModelForCausalLM.from_pretrained("hf-internal-testing/tiny-random-gpt2").to(torch_device)
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tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2")
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input_ids = tokenizer(article, return_tensors="pt").input_ids.to(torch_device)
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inputs_embeds = model.get_input_embeddings()(input_ids)
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model.generate(inputs_embeds=inputs_embeds, max_length=20, bos_token_id=None)
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with self.assertRaises(ValueError):
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model.generate(max_length=20, bos_token_id=None)
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def test_generate_from_inputs_embeds_decoder_only(self):
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# When supported, tests that the decoder model can generate from `inputs_embeds` instead of `input_ids`
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# if fails, you should probably update the `prepare_inputs_for_generation` function
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@ -2817,3 +2806,16 @@ class GenerationIntegrationTests(unittest.TestCase, GenerationIntegrationTestsMi
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self.assertTrue(y_prob > 0.001 and n_prob > 0.001)
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self.assertTrue(y_prob <= 1.0 and n_prob <= 1.0)
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def test_generate_from_inputs_embeds_with_bos_token_id_is_none(self):
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article = "Today a dragon flew over Paris."
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model = AutoModelForCausalLM.from_pretrained("hf-internal-testing/tiny-random-gpt2").to(torch_device)
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tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2")
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input_ids = tokenizer(article, return_tensors="pt").input_ids.to(torch_device)
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inputs_embeds = model.get_input_embeddings()(input_ids)
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model.generate(inputs_embeds=inputs_embeds, max_length=20, bos_token_id=None)
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# bos_token_id is required when no input ids nor inputs_embeds is passed
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with self.assertRaises(ValueError):
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model.generate(max_length=20, bos_token_id=None)
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