updated all tests
This commit is contained in:
parent
e03129ad44
commit
575976144a
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@ -219,7 +219,9 @@ class CTRLModelLanguageGenerationTest(unittest.TestCase):
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@slow
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def test_lm_generate_ctrl(self):
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model = CTRLLMHeadModel.from_pretrained("ctrl")
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input_ids = torch.Tensor([[11859, 586, 20984, 8]]).long() # Legal My neighbor is
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input_ids = torch.tensor(
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[[11858, 586, 20984, 8]], dtype=torch.long, device=torch_device
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) # Legal My neighbor is
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expected_output_ids = [
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11859,
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586,
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@ -242,7 +244,6 @@ class CTRLModelLanguageGenerationTest(unittest.TestCase):
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3,
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980,
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] # Legal My neighbor is refusing to pay rent after 2 years and we are having to force him to pay
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torch.manual_seed(0)
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output_ids = model.generate(input_ids)
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output_ids = model.generate(input_ids, do_sample=False)
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self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
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@ -223,7 +223,7 @@ class GPT2ModelTest(ModelTesterMixin, unittest.TestCase):
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# append to next input_ids and attn_mask
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next_input_ids = torch.cat([input_ids, next_tokens], dim=-1)
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attn_mask = torch.cat(
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[attn_mask, torch.ones((attn_mask.shape[0], 1), dtype=torch.long, device=torch_device)], dim=1
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[attn_mask, torch.ones((attn_mask.shape[0], 1), dtype=torch.long, device=torch_device)], dim=1,
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)
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# get two different outputs
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@ -343,39 +343,36 @@ class GPT2ModelLanguageGenerationTest(unittest.TestCase):
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@slow
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def test_lm_generate_gpt2(self):
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model = GPT2LMHeadModel.from_pretrained("gpt2")
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input_ids = torch.Tensor([[464, 3290, 318, 13779]]).long() # The dog is cute
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input_ids = torch.tensor([[463, 3290]], dtype=torch.long, device=torch_device) # The dog
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expected_output_ids = [
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464,
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3290,
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318,
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13779,
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1165,
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13,
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632,
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7832,
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284,
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6437,
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319,
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502,
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373,
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1043,
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287,
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257,
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2214,
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1474,
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262,
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16246,
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286,
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2688,
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290,
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318,
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922,
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329,
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502,
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357,
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1169,
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2688,
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27262,
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13,
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198,
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198,
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464,
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3290,
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] # The dog is cute too. It likes to rub on me and is good for me (the dog
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torch.manual_seed(0)
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output_ids = model.generate(input_ids)
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] # The dog was found in a field near the intersection of West and West Streets.\n\nThe dog
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output_ids = model.generate(input_ids, do_sample=False)
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self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
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@slow
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def test_lm_generate_distilgpt2(self):
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model = GPT2LMHeadModel.from_pretrained("distilgpt2")
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input_ids = torch.Tensor([[464, 1893]]).long() # The president
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input_ids = torch.tensor([[463, 1893]], dtype=torch.long, device=torch_device) # The president
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expected_output_ids = [
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464,
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1893,
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@ -123,7 +123,15 @@ class OpenAIGPTModelTest(ModelTesterMixin, unittest.TestCase):
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head_mask = ids_tensor([self.num_hidden_layers, self.num_attention_heads], 2)
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return config, input_ids, head_mask, token_type_ids, sequence_labels, token_labels, choice_labels
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return (
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config,
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input_ids,
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head_mask,
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token_type_ids,
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sequence_labels,
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token_labels,
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choice_labels,
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)
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def check_loss_output(self, result):
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self.parent.assertListEqual(list(result["loss"].size()), [])
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@ -139,7 +147,7 @@ class OpenAIGPTModelTest(ModelTesterMixin, unittest.TestCase):
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result = {"sequence_output": sequence_output}
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self.parent.assertListEqual(
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list(result["sequence_output"].size()), [self.batch_size, self.seq_length, self.hidden_size]
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list(result["sequence_output"].size()), [self.batch_size, self.seq_length, self.hidden_size],
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)
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def create_and_check_lm_head_model(self, config, input_ids, head_mask, token_type_ids, *args):
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@ -153,7 +161,7 @@ class OpenAIGPTModelTest(ModelTesterMixin, unittest.TestCase):
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self.parent.assertListEqual(list(result["loss"].size()), [])
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self.parent.assertListEqual(
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list(result["lm_logits"].size()), [self.batch_size, self.seq_length, self.vocab_size]
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list(result["lm_logits"].size()), [self.batch_size, self.seq_length, self.vocab_size],
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)
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def create_and_check_double_lm_head_model(self, config, input_ids, head_mask, token_type_ids, *args):
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@ -167,7 +175,7 @@ class OpenAIGPTModelTest(ModelTesterMixin, unittest.TestCase):
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self.parent.assertListEqual(list(result["loss"].size()), [])
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self.parent.assertListEqual(
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list(result["lm_logits"].size()), [self.batch_size, self.seq_length, self.vocab_size]
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list(result["lm_logits"].size()), [self.batch_size, self.seq_length, self.vocab_size],
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)
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def prepare_config_and_inputs_for_common(self):
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@ -181,7 +189,11 @@ class OpenAIGPTModelTest(ModelTesterMixin, unittest.TestCase):
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token_labels,
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choice_labels,
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) = config_and_inputs
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inputs_dict = {"input_ids": input_ids, "token_type_ids": token_type_ids, "head_mask": head_mask}
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inputs_dict = {
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"input_ids": input_ids,
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"token_type_ids": token_type_ids,
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"head_mask": head_mask,
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}
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return config, inputs_dict
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@ -215,30 +227,29 @@ class OPENAIGPTModelLanguageGenerationTest(unittest.TestCase):
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@slow
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def test_lm_generate_openai_gpt(self):
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model = OpenAIGPTLMHeadModel.from_pretrained("openai-gpt")
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input_ids = torch.Tensor([[481, 2585, 544, 4957]]).long() # The dog is cute
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input_ids = torch.tensor([[481, 4735, 544]], dtype=torch.long, device=torch_device) # the president is
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expected_output_ids = [
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481,
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2585,
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4735,
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544,
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4957,
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669,
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512,
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761,
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5990,
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271,
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645,
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246,
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963,
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870,
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762,
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239,
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244,
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40477,
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244,
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249,
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719,
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881,
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487,
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535,
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976,
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2479,
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544,
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240,
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487,
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804,
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1296,
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2891,
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512,
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] # the dog is cute when you're annoyed : if he's really stupid, he 'll stop fighting you
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torch.manual_seed(0)
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244,
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603,
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481,
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] # the president is a very good man. " \n " i\'m sure he is, " said the
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output_ids = model.generate(input_ids)
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output_ids = model.generate(input_ids, do_sample=False)
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self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
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@ -24,6 +24,7 @@ from .utils import CACHE_DIR, require_tf, slow
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if is_tf_available():
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import tensorflow as tf
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from transformers.modeling_tf_ctrl import TFCTRLModel, TFCTRLLMHeadModel, TF_CTRL_PRETRAINED_MODEL_ARCHIVE_MAP
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@ -202,3 +203,35 @@ class TFCTRLModelTest(TFModelTesterMixin, unittest.TestCase):
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for model_name in list(TF_CTRL_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
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model = TFCTRLModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
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self.assertIsNotNone(model)
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class TFCTRLModelLanguageGenerationTest(unittest.TestCase):
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@slow
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def test_lm_generate_ctrl(self):
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model = TFCTRLLMHeadModel.from_pretrained("ctrl")
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input_ids = tf.convert_to_tensor([[11858, 586, 20984, 8]], dtype=tf.int32)
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expected_output_ids = [
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11859,
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586,
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20984,
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8,
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13391,
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3,
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980,
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8258,
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72,
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327,
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148,
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2,
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53,
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29,
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226,
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3,
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780,
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49,
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3,
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980,
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] # Legal My neighbor is refusing to pay rent after 2 years and we are having to force him to pay
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output_ids = model.generate(input_ids, do_sample=False)
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self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
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@ -328,13 +328,35 @@ class TFGPT2ModelTest(TFModelTesterMixin, unittest.TestCase):
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self.assertIsNotNone(model)
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def prepare_generation_special_tokens():
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return {"bos_token_id": 50256, "eos_token_id": 50256}
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class TFGPT2ModelLanguageGenerationTest(unittest.TestCase):
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special_tokens = prepare_generation_special_tokens()
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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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input_ids = tf.convert_to_tensor([[464, 3290]], dtype=tf.int32) # The dog
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expected_output_ids = [
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464,
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3290,
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373,
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1043,
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287,
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257,
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2214,
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1474,
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262,
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16246,
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286,
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2688,
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290,
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2688,
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27262,
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13,
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198,
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198,
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464,
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3290,
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] # The dog was found in a field near the intersection of West and West Streets.\n\nThe dog
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output_ids = model.generate(input_ids, do_sample=False)
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self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
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@slow
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def test_lm_generate_distilgpt2(self):
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@ -363,11 +385,5 @@ class TFGPT2ModelLanguageGenerationTest(unittest.TestCase):
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2635,
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] # The president of the United States, and the president of the United Kingdom, have been in the White
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output_ids = model.generate(
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input_ids,
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do_sample=False,
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bos_token_id=self.special_tokens["bos_token_id"],
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eos_token_ids=self.special_tokens["eos_token_id"],
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)
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output_ids = model.generate(input_ids, do_sample=False)
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self.assertListEqual(output_ids[0].numpy().tolist(), expected_output_ids)
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@ -238,3 +238,35 @@ class TFOpenAIGPTModelTest(TFModelTesterMixin, unittest.TestCase):
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for model_name in list(TF_OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
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model = TFOpenAIGPTModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
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self.assertIsNotNone(model)
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class TFOPENAIGPTModelLanguageGenerationTest(unittest.TestCase):
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@slow
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def test_lm_generate_openai_gpt(self):
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model = TFOpenAIGPTLMHeadModel.from_pretrained("openai-gpt")
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input_ids = tf.convert_to_tensor([[481, 4735, 544]], dtype=tf.int32) # the president is
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expected_output_ids = [
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481,
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4735,
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544,
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246,
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963,
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870,
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762,
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239,
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244,
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40477,
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244,
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249,
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719,
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881,
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487,
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544,
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240,
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244,
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603,
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481,
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] # the president is a very good man. " \n " i\'m sure he is, " said the
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output_ids = model.generate(input_ids, do_sample=False)
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self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
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@ -212,3 +212,375 @@ class TFTransfoXLModelTest(TFModelTesterMixin, unittest.TestCase):
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for model_name in list(TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
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model = TFTransfoXLModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
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self.assertIsNotNone(model)
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class TFTransfoXLModelLanguageGenerationTest(unittest.TestCase):
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@slow
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def test_lm_generate_transfo_xl_wt103(self):
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model = TFTransfoXLLMHeadModel.from_pretrained("transfo-xl-wt103")
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input_ids = tf.convert_to_tensor(
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[
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[
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33,
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1297,
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2,
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1,
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1009,
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4,
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1109,
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11739,
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4762,
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358,
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5,
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25,
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245,
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22,
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1706,
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17,
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20098,
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5,
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3215,
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21,
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37,
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1110,
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3,
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13,
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1041,
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4,
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24,
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603,
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490,
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2,
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71477,
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20098,
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104447,
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2,
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20961,
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1,
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2604,
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4,
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1,
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||||
329,
|
||||
3,
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6224,
|
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831,
|
||||
16002,
|
||||
2,
|
||||
8,
|
||||
603,
|
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78967,
|
||||
29546,
|
||||
23,
|
||||
803,
|
||||
20,
|
||||
25,
|
||||
416,
|
||||
5,
|
||||
8,
|
||||
232,
|
||||
4,
|
||||
277,
|
||||
6,
|
||||
1855,
|
||||
4601,
|
||||
3,
|
||||
29546,
|
||||
54,
|
||||
8,
|
||||
3609,
|
||||
5,
|
||||
57211,
|
||||
49,
|
||||
4,
|
||||
1,
|
||||
277,
|
||||
18,
|
||||
8,
|
||||
1755,
|
||||
15691,
|
||||
3,
|
||||
341,
|
||||
25,
|
||||
416,
|
||||
693,
|
||||
42573,
|
||||
71,
|
||||
17,
|
||||
401,
|
||||
94,
|
||||
31,
|
||||
17919,
|
||||
2,
|
||||
29546,
|
||||
7873,
|
||||
18,
|
||||
1,
|
||||
435,
|
||||
23,
|
||||
11011,
|
||||
755,
|
||||
5,
|
||||
5167,
|
||||
3,
|
||||
7983,
|
||||
98,
|
||||
84,
|
||||
2,
|
||||
29546,
|
||||
3267,
|
||||
8,
|
||||
3609,
|
||||
4,
|
||||
1,
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4865,
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||||
1075,
|
||||
2,
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||||
6087,
|
||||
71,
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||||
6,
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346,
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8,
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5854,
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3,
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||||
29546,
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||||
824,
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||||
1400,
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||||
1868,
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||||
2,
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||||
19,
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||||
160,
|
||||
2,
|
||||
311,
|
||||
8,
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||||
5496,
|
||||
2,
|
||||
20920,
|
||||
17,
|
||||
25,
|
||||
15097,
|
||||
3,
|
||||
24,
|
||||
24,
|
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0,
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]
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],
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dtype=tf.int31,
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)
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# In 1991 , the remains of Russian Tsar Nicholas II and his family
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# ( except for Alexei and Maria ) are discovered .
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# The voice of Nicholas's young son , Tsarevich Alexei Nikolaevich , narrates the
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# remainder of the story . 1883 Western Siberia ,
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# a young Grigori Rasputin is asked by his father and a group of men to perform magic .
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# Rasputin has a vision and denounces one of the men as a horse thief . Although his
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# father initially slaps him for making such an accusation , Rasputin watches as the
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# man is chased outside and beaten . Twenty years later , Rasputin sees a vision of
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# the Virgin Mary , prompting him to become a priest . Rasputin quickly becomes famous ,
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# with people , even a bishop , begging for his blessing . <eod> </s> <eos>
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expected_output_ids = [
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33,
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||||
1297,
|
||||
2,
|
||||
1,
|
||||
1009,
|
||||
4,
|
||||
1109,
|
||||
11739,
|
||||
4762,
|
||||
358,
|
||||
5,
|
||||
25,
|
||||
245,
|
||||
22,
|
||||
1706,
|
||||
17,
|
||||
20098,
|
||||
5,
|
||||
3215,
|
||||
21,
|
||||
37,
|
||||
1110,
|
||||
3,
|
||||
13,
|
||||
1041,
|
||||
4,
|
||||
24,
|
||||
603,
|
||||
490,
|
||||
2,
|
||||
71477,
|
||||
20098,
|
||||
104447,
|
||||
2,
|
||||
20961,
|
||||
1,
|
||||
2604,
|
||||
4,
|
||||
1,
|
||||
329,
|
||||
3,
|
||||
6224,
|
||||
831,
|
||||
16002,
|
||||
2,
|
||||
8,
|
||||
603,
|
||||
78967,
|
||||
29546,
|
||||
23,
|
||||
803,
|
||||
20,
|
||||
25,
|
||||
416,
|
||||
5,
|
||||
8,
|
||||
232,
|
||||
4,
|
||||
277,
|
||||
6,
|
||||
1855,
|
||||
4601,
|
||||
3,
|
||||
29546,
|
||||
54,
|
||||
8,
|
||||
3609,
|
||||
5,
|
||||
57211,
|
||||
49,
|
||||
4,
|
||||
1,
|
||||
277,
|
||||
18,
|
||||
8,
|
||||
1755,
|
||||
15691,
|
||||
3,
|
||||
341,
|
||||
25,
|
||||
416,
|
||||
693,
|
||||
42573,
|
||||
71,
|
||||
17,
|
||||
401,
|
||||
94,
|
||||
31,
|
||||
17919,
|
||||
2,
|
||||
29546,
|
||||
7873,
|
||||
18,
|
||||
1,
|
||||
435,
|
||||
23,
|
||||
11011,
|
||||
755,
|
||||
5,
|
||||
5167,
|
||||
3,
|
||||
7983,
|
||||
98,
|
||||
84,
|
||||
2,
|
||||
29546,
|
||||
3267,
|
||||
8,
|
||||
3609,
|
||||
4,
|
||||
1,
|
||||
4865,
|
||||
1075,
|
||||
2,
|
||||
6087,
|
||||
71,
|
||||
6,
|
||||
346,
|
||||
8,
|
||||
5854,
|
||||
3,
|
||||
29546,
|
||||
824,
|
||||
1400,
|
||||
1868,
|
||||
2,
|
||||
19,
|
||||
160,
|
||||
2,
|
||||
311,
|
||||
8,
|
||||
5496,
|
||||
2,
|
||||
20920,
|
||||
17,
|
||||
25,
|
||||
15097,
|
||||
3,
|
||||
24,
|
||||
24,
|
||||
0,
|
||||
29546,
|
||||
40,
|
||||
1092,
|
||||
18,
|
||||
8,
|
||||
5854,
|
||||
7,
|
||||
1143,
|
||||
2,
|
||||
7,
|
||||
1,
|
||||
159,
|
||||
99,
|
||||
16,
|
||||
1,
|
||||
1009,
|
||||
4,
|
||||
1109,
|
||||
11739,
|
||||
4762,
|
||||
358,
|
||||
5,
|
||||
25,
|
||||
245,
|
||||
28,
|
||||
1110,
|
||||
3,
|
||||
13,
|
||||
1041,
|
||||
4,
|
||||
24,
|
||||
603,
|
||||
490,
|
||||
2,
|
||||
71477,
|
||||
20098,
|
||||
104447,
|
||||
2,
|
||||
20961,
|
||||
1,
|
||||
2604,
|
||||
4,
|
||||
1,
|
||||
329,
|
||||
3,
|
||||
0,
|
||||
]
|
||||
# In 1991, the remains of Russian Tsar Nicholas II and his family (
|
||||
# except for Alexei and Maria ) are discovered. The voice of young son,
|
||||
# Tsarevich Alexei Nikolaevich, narrates the remainder of the story.
|
||||
# 1883 Western Siberia, a young Grigori Rasputin is asked by his father
|
||||
# and a group of men to perform magic. Rasputin has a vision and
|
||||
# denounces one of the men as a horse thief. Although his father initially
|
||||
# slaps him for making such an accusation, Rasputin watches as the man
|
||||
# is chased outside and beaten. Twenty years later, Rasputin sees a vision
|
||||
# of the Virgin Mary, prompting him to become a priest.
|
||||
# Rasputin quickly becomes famous, with people, even a bishop, begging for
|
||||
# his blessing. <unk> <unk> <eos> In the 1990s, the remains of Russian Tsar
|
||||
# Nicholas II and his family were discovered. The voice of <unk> young son,
|
||||
# Tsarevich Alexei Nikolaevich, narrates the remainder of the story.<eos>
|
||||
|
||||
# TODO: add this test when trasnfo-xl-lmhead is implemented
|
||||
with self.assertRaises(NotImplementedError):
|
||||
model.generate(input_ids, max_length=200, do_sample=False)
|
||||
# self.assertListEqual(output_ids[0].tolist(), expected_output_ids) TODO: (PVP) to add when transfo-xl is implemented
|
||||
|
|
|
@ -311,3 +311,34 @@ class TFXLMModelTest(TFModelTesterMixin, unittest.TestCase):
|
|||
for model_name in list(TF_XLM_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
|
||||
model = TFXLMModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
|
||||
self.assertIsNotNone(model)
|
||||
|
||||
|
||||
class TFXLMModelLanguageGenerationTest(unittest.TestCase):
|
||||
@slow
|
||||
def test_lm_generate_xlm_mlm_en_2048(self):
|
||||
model = TFXLMWithLMHeadModel.from_pretrained("xlm-mlm-en-2048")
|
||||
input_ids = tf.convert_to_tensor([[1, 14, 2232, 26, 1]], dtype=tf.int32) # the dog is cute
|
||||
expected_output_ids = [
|
||||
1,
|
||||
14,
|
||||
2232,
|
||||
26,
|
||||
1,
|
||||
567,
|
||||
26,
|
||||
32,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
] # The dog is nothing is it!!!!!!!!!!!! TODO (PVP): this sentence (and others I tried) does not make much sense, there seems to be a problem with xlm language generation.
|
||||
output_ids = model.generate(input_ids)
|
||||
self.assertListEqual(output_ids[0].tolist(), expected_output_ids, do_sample=False)
|
||||
|
|
|
@ -413,3 +413,415 @@ class TFXLNetModelTest(TFModelTesterMixin, unittest.TestCase):
|
|||
for model_name in list(TF_XLNET_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
|
||||
model = TFXLNetModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
|
||||
self.assertIsNotNone(model)
|
||||
|
||||
|
||||
class TFXLNetModelLanguageGenerationTest(unittest.TestCase):
|
||||
@slow
|
||||
def test_lm_generate_xlnet_base_cased(self):
|
||||
model = TFXLNetLMHeadModel.from_pretrained("xlnet-base-cased")
|
||||
input_ids = tf.convert_to_tensor(
|
||||
[
|
||||
[
|
||||
67,
|
||||
2840,
|
||||
19,
|
||||
18,
|
||||
1484,
|
||||
20,
|
||||
965,
|
||||
29077,
|
||||
8719,
|
||||
1273,
|
||||
21,
|
||||
45,
|
||||
273,
|
||||
17,
|
||||
10,
|
||||
15048,
|
||||
28,
|
||||
27511,
|
||||
21,
|
||||
4185,
|
||||
11,
|
||||
41,
|
||||
2444,
|
||||
9,
|
||||
32,
|
||||
1025,
|
||||
20,
|
||||
8719,
|
||||
26,
|
||||
23,
|
||||
673,
|
||||
966,
|
||||
19,
|
||||
29077,
|
||||
20643,
|
||||
27511,
|
||||
20822,
|
||||
20643,
|
||||
19,
|
||||
17,
|
||||
6616,
|
||||
17511,
|
||||
18,
|
||||
8978,
|
||||
20,
|
||||
18,
|
||||
777,
|
||||
9,
|
||||
19233,
|
||||
1527,
|
||||
17669,
|
||||
19,
|
||||
24,
|
||||
673,
|
||||
17,
|
||||
28756,
|
||||
150,
|
||||
12943,
|
||||
4354,
|
||||
153,
|
||||
27,
|
||||
442,
|
||||
37,
|
||||
45,
|
||||
668,
|
||||
21,
|
||||
24,
|
||||
256,
|
||||
20,
|
||||
416,
|
||||
22,
|
||||
2771,
|
||||
4901,
|
||||
9,
|
||||
12943,
|
||||
4354,
|
||||
153,
|
||||
51,
|
||||
24,
|
||||
3004,
|
||||
21,
|
||||
28142,
|
||||
23,
|
||||
65,
|
||||
20,
|
||||
18,
|
||||
416,
|
||||
34,
|
||||
24,
|
||||
2958,
|
||||
22947,
|
||||
9,
|
||||
1177,
|
||||
45,
|
||||
668,
|
||||
3097,
|
||||
13768,
|
||||
23,
|
||||
103,
|
||||
28,
|
||||
441,
|
||||
148,
|
||||
48,
|
||||
20522,
|
||||
19,
|
||||
12943,
|
||||
4354,
|
||||
153,
|
||||
12860,
|
||||
34,
|
||||
18,
|
||||
326,
|
||||
27,
|
||||
17492,
|
||||
684,
|
||||
21,
|
||||
6709,
|
||||
9,
|
||||
8585,
|
||||
123,
|
||||
266,
|
||||
19,
|
||||
12943,
|
||||
4354,
|
||||
153,
|
||||
6872,
|
||||
24,
|
||||
3004,
|
||||
20,
|
||||
18,
|
||||
9225,
|
||||
2198,
|
||||
19,
|
||||
12717,
|
||||
103,
|
||||
22,
|
||||
401,
|
||||
24,
|
||||
6348,
|
||||
9,
|
||||
12943,
|
||||
4354,
|
||||
153,
|
||||
1068,
|
||||
2768,
|
||||
2286,
|
||||
19,
|
||||
33,
|
||||
104,
|
||||
19,
|
||||
176,
|
||||
24,
|
||||
9313,
|
||||
19,
|
||||
20086,
|
||||
28,
|
||||
45,
|
||||
10292,
|
||||
9,
|
||||
4,
|
||||
3,
|
||||
]
|
||||
],
|
||||
dtype=tf.int32,
|
||||
)
|
||||
# In 1991, the remains of Russian Tsar Nicholas II and his family
|
||||
# (except for Alexei and Maria) are discovered.
|
||||
# The voice of Nicholas's young son, Tsarevich Alexei Nikolaevich, narrates the
|
||||
# remainder of the story. 1883 Western Siberia,
|
||||
# a young Grigori Rasputin is asked by his father and a group of men to perform magic.
|
||||
# Rasputin has a vision and denounces one of the men as a horse thief. Although his
|
||||
# father initially slaps him for making such an accusation, Rasputin watches as the
|
||||
# man is chased outside and beaten. Twenty years later, Rasputin sees a vision of
|
||||
# the Virgin Mary, prompting him to become a priest. Rasputin quickly becomes famous,
|
||||
# with people, even a bishop, begging for his blessing. """
|
||||
|
||||
expected_output_ids = [
|
||||
67,
|
||||
2840,
|
||||
19,
|
||||
18,
|
||||
1484,
|
||||
20,
|
||||
965,
|
||||
29077,
|
||||
8719,
|
||||
1273,
|
||||
21,
|
||||
45,
|
||||
273,
|
||||
17,
|
||||
10,
|
||||
15048,
|
||||
28,
|
||||
27511,
|
||||
21,
|
||||
4185,
|
||||
11,
|
||||
41,
|
||||
2444,
|
||||
9,
|
||||
32,
|
||||
1025,
|
||||
20,
|
||||
8719,
|
||||
26,
|
||||
23,
|
||||
673,
|
||||
966,
|
||||
19,
|
||||
29077,
|
||||
20643,
|
||||
27511,
|
||||
20822,
|
||||
20643,
|
||||
19,
|
||||
17,
|
||||
6616,
|
||||
17511,
|
||||
18,
|
||||
8978,
|
||||
20,
|
||||
18,
|
||||
777,
|
||||
9,
|
||||
19233,
|
||||
1527,
|
||||
17669,
|
||||
19,
|
||||
24,
|
||||
673,
|
||||
17,
|
||||
28756,
|
||||
150,
|
||||
12943,
|
||||
4354,
|
||||
153,
|
||||
27,
|
||||
442,
|
||||
37,
|
||||
45,
|
||||
668,
|
||||
21,
|
||||
24,
|
||||
256,
|
||||
20,
|
||||
416,
|
||||
22,
|
||||
2771,
|
||||
4901,
|
||||
9,
|
||||
12943,
|
||||
4354,
|
||||
153,
|
||||
51,
|
||||
24,
|
||||
3004,
|
||||
21,
|
||||
28142,
|
||||
23,
|
||||
65,
|
||||
20,
|
||||
18,
|
||||
416,
|
||||
34,
|
||||
24,
|
||||
2958,
|
||||
22947,
|
||||
9,
|
||||
1177,
|
||||
45,
|
||||
668,
|
||||
3097,
|
||||
13768,
|
||||
23,
|
||||
103,
|
||||
28,
|
||||
441,
|
||||
148,
|
||||
48,
|
||||
20522,
|
||||
19,
|
||||
12943,
|
||||
4354,
|
||||
153,
|
||||
12860,
|
||||
34,
|
||||
18,
|
||||
326,
|
||||
27,
|
||||
17492,
|
||||
684,
|
||||
21,
|
||||
6709,
|
||||
9,
|
||||
8585,
|
||||
123,
|
||||
266,
|
||||
19,
|
||||
12943,
|
||||
4354,
|
||||
153,
|
||||
6872,
|
||||
24,
|
||||
3004,
|
||||
20,
|
||||
18,
|
||||
9225,
|
||||
2198,
|
||||
19,
|
||||
12717,
|
||||
103,
|
||||
22,
|
||||
401,
|
||||
24,
|
||||
6348,
|
||||
9,
|
||||
12943,
|
||||
4354,
|
||||
153,
|
||||
1068,
|
||||
2768,
|
||||
2286,
|
||||
19,
|
||||
33,
|
||||
104,
|
||||
19,
|
||||
176,
|
||||
24,
|
||||
9313,
|
||||
19,
|
||||
20086,
|
||||
28,
|
||||
45,
|
||||
10292,
|
||||
9,
|
||||
4,
|
||||
3,
|
||||
1722,
|
||||
19,
|
||||
24,
|
||||
6348,
|
||||
61,
|
||||
977,
|
||||
176,
|
||||
1772,
|
||||
33,
|
||||
45,
|
||||
970,
|
||||
19,
|
||||
4185,
|
||||
19,
|
||||
27,
|
||||
442,
|
||||
22,
|
||||
2771,
|
||||
4901,
|
||||
9,
|
||||
69,
|
||||
27,
|
||||
50,
|
||||
551,
|
||||
22,
|
||||
2771,
|
||||
4901,
|
||||
19,
|
||||
21,
|
||||
45,
|
||||
668,
|
||||
21,
|
||||
18,
|
||||
416,
|
||||
41,
|
||||
1499,
|
||||
22,
|
||||
755,
|
||||
18,
|
||||
14285,
|
||||
9,
|
||||
12943,
|
||||
4354,
|
||||
153,
|
||||
27,
|
||||
1499,
|
||||
22,
|
||||
642,
|
||||
22,
|
||||
]
|
||||
# In 1991, the remains of Russian Tsar Nicholas II and his family (except for Alexei and Maria)
|
||||
# are discovered. The voice of Nicholas's young son, Tsarevich Alexei Nikolaevich,
|
||||
# narrates the remainder of the story. 1883 Western Siberia, a young Grigori Rasputin
|
||||
# is asked by his father and a group of men to perform magic. Rasputin has a vision and
|
||||
# denounces one of the men as a horse thief. Although his father initially slaps
|
||||
# him for making such an accusation, Rasputin watches as the man is chased outside and beaten.
|
||||
# Twenty years later, Rasputin sees a vision of the Virgin Mary, prompting him to become a priest.
|
||||
# Rasputin quickly becomes famous, with people, even a bishop, begging for his blessing.
|
||||
# <sep><cls>, Rasputin is asked to perform magic.
|
||||
# He is not able to perform magic, and his father and
|
||||
# the men are forced to leave the monastery. Rasputin is forced to return to
|
||||
|
||||
output_ids = model.generate(input_ids, max_length=200, do_sample=False)
|
||||
|
||||
self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
|
||||
|
|
|
@ -218,7 +218,7 @@ class TransfoXLModelLanguageGenerationTest(unittest.TestCase):
|
|||
@slow
|
||||
def test_lm_generate_transfo_xl_wt103(self):
|
||||
model = TransfoXLLMHeadModel.from_pretrained("transfo-xl-wt103")
|
||||
input_ids = torch.Tensor(
|
||||
input_ids = torch.tensor(
|
||||
[
|
||||
[
|
||||
33,
|
||||
|
@ -363,8 +363,10 @@ class TransfoXLModelLanguageGenerationTest(unittest.TestCase):
|
|||
24,
|
||||
0,
|
||||
]
|
||||
]
|
||||
).long()
|
||||
],
|
||||
dtype=torch.long,
|
||||
device=torch_device,
|
||||
)
|
||||
# In 1991 , the remains of Russian Tsar Nicholas II and his family
|
||||
# ( except for Alexei and Maria ) are discovered .
|
||||
# The voice of Nicholas's young son , Tsarevich Alexei Nikolaevich , narrates the
|
||||
|
@ -545,14 +547,23 @@ class TransfoXLModelLanguageGenerationTest(unittest.TestCase):
|
|||
28,
|
||||
1110,
|
||||
3,
|
||||
57,
|
||||
629,
|
||||
38,
|
||||
3493,
|
||||
47,
|
||||
1094,
|
||||
7,
|
||||
1297,
|
||||
13,
|
||||
1041,
|
||||
4,
|
||||
24,
|
||||
603,
|
||||
490,
|
||||
2,
|
||||
71477,
|
||||
20098,
|
||||
104447,
|
||||
2,
|
||||
20961,
|
||||
1,
|
||||
2604,
|
||||
4,
|
||||
1,
|
||||
329,
|
||||
3,
|
||||
0,
|
||||
]
|
||||
|
@ -566,10 +577,9 @@ class TransfoXLModelLanguageGenerationTest(unittest.TestCase):
|
|||
# is chased outside and beaten. Twenty years later, Rasputin sees a vision
|
||||
# of the Virgin Mary, prompting him to become a priest.
|
||||
# Rasputin quickly becomes famous, with people, even a bishop, begging for
|
||||
# his blessing. Rasputin first appears as a priest in 1996, in the same year
|
||||
# that the remains of Russian Tsar Nicholas II and his family were discovered. H
|
||||
# his blessing. <unk> <unk> <eos> In the 1990s, the remains of Russian Tsar
|
||||
# Nicholas II and his family were discovered. The voice of <unk> young son,
|
||||
# Tsarevich Alexei Nikolaevich, narrates the remainder of the story.<eos>
|
||||
|
||||
torch.manual_seed(0)
|
||||
|
||||
output_ids = model.generate(input_ids, max_length=200)
|
||||
output_ids = model.generate(input_ids, max_length=200, do_sample=False)
|
||||
self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
|
||||
|
|
|
@ -403,7 +403,7 @@ class XLMModelLanguageGenerationTest(unittest.TestCase):
|
|||
@slow
|
||||
def test_lm_generate_xlm_mlm_en_2048(self):
|
||||
model = XLMWithLMHeadModel.from_pretrained("xlm-mlm-en-2048")
|
||||
input_ids = torch.Tensor([[1, 14, 2232, 26, 1]]).long() # The dog is cute
|
||||
input_ids = torch.tensor([[1, 14, 2232, 26, 1]], dtype=torch.long, device=torch_device) # The dog is cute
|
||||
expected_output_ids = [
|
||||
1,
|
||||
14,
|
||||
|
@ -426,8 +426,5 @@ class XLMModelLanguageGenerationTest(unittest.TestCase):
|
|||
149,
|
||||
149,
|
||||
] # The dog is nothing is it!!!!!!!!!!!! TODO (PVP): this sentence (and others I tried) does not make much sense, there seems to be a problem with xlm language generation.
|
||||
torch.manual_seed(0)
|
||||
|
||||
output_ids = model.generate(input_ids)
|
||||
|
||||
self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
|
||||
self.assertListEqual(output_ids[0].tolist(), expected_output_ids, do_sample=False)
|
||||
|
|
|
@ -517,7 +517,7 @@ class XLNetModelLanguageGenerationTest(unittest.TestCase):
|
|||
@slow
|
||||
def test_lm_generate_xlnet_base_cased(self):
|
||||
model = XLNetLMHeadModel.from_pretrained("xlnet-base-cased")
|
||||
input_ids = torch.Tensor(
|
||||
input_ids = torch.tensor(
|
||||
[
|
||||
[
|
||||
67,
|
||||
|
@ -682,8 +682,10 @@ class XLNetModelLanguageGenerationTest(unittest.TestCase):
|
|||
4,
|
||||
3,
|
||||
]
|
||||
]
|
||||
).long()
|
||||
],
|
||||
dtype=torch.long,
|
||||
device=torch_device,
|
||||
)
|
||||
# In 1991, the remains of Russian Tsar Nicholas II and his family
|
||||
# (except for Alexei and Maria) are discovered.
|
||||
# The voice of Nicholas's young son, Tsarevich Alexei Nikolaevich, narrates the
|
||||
|
@ -876,26 +878,36 @@ class XLNetModelLanguageGenerationTest(unittest.TestCase):
|
|||
22,
|
||||
2771,
|
||||
4901,
|
||||
25,
|
||||
18,
|
||||
2059,
|
||||
20,
|
||||
24,
|
||||
303,
|
||||
1775,
|
||||
691,
|
||||
9,
|
||||
1147,
|
||||
69,
|
||||
27,
|
||||
50,
|
||||
551,
|
||||
22,
|
||||
2771,
|
||||
4901,
|
||||
19,
|
||||
634,
|
||||
19,
|
||||
43,
|
||||
51,
|
||||
54,
|
||||
6157,
|
||||
2999,
|
||||
33,
|
||||
4185,
|
||||
21,
|
||||
45,
|
||||
668,
|
||||
21,
|
||||
18,
|
||||
416,
|
||||
41,
|
||||
1499,
|
||||
22,
|
||||
755,
|
||||
18,
|
||||
14285,
|
||||
9,
|
||||
12943,
|
||||
4354,
|
||||
153,
|
||||
27,
|
||||
1499,
|
||||
22,
|
||||
642,
|
||||
22,
|
||||
]
|
||||
# In 1991, the remains of Russian Tsar Nicholas II and his family (except for Alexei and Maria)
|
||||
# are discovered. The voice of Nicholas's young son, Tsarevich Alexei Nikolaevich,
|
||||
|
@ -905,11 +917,10 @@ class XLNetModelLanguageGenerationTest(unittest.TestCase):
|
|||
# him for making such an accusation, Rasputin watches as the man is chased outside and beaten.
|
||||
# Twenty years later, Rasputin sees a vision of the Virgin Mary, prompting him to become a priest.
|
||||
# Rasputin quickly becomes famous, with people, even a bishop, begging for his blessing.
|
||||
# 1990, a priest who cannot even walk with his wife, Maria, is asked to perform magic
|
||||
# in the presence of a local religious leader.
|
||||
# Since, however, he has had difficulty walking with Maria
|
||||
# <sep><cls>, Rasputin is asked to perform magic.
|
||||
# He is not able to perform magic, and his father and
|
||||
# the men are forced to leave the monastery. Rasputin is forced to return to
|
||||
|
||||
torch.manual_seed(0)
|
||||
output_ids = model.generate(input_ids, max_length=200)
|
||||
output_ids = model.generate(input_ids, max_length=200, do_sample=False)
|
||||
|
||||
self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
|
||||
|
|
|
@ -0,0 +1,430 @@
|
|||
# coding=utf-8
|
||||
# Copyright 2018 The Google AI Language Team Authors.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
|
||||
import unittest
|
||||
|
||||
from transformers import is_torch_available
|
||||
|
||||
from .test_configuration_common import ConfigTester
|
||||
from .test_modeling_common import ModelTesterMixin, ids_tensor
|
||||
from .utils import CACHE_DIR, require_torch, slow, torch_device
|
||||
|
||||
|
||||
if is_torch_available():
|
||||
import torch
|
||||
from transformers import (
|
||||
XLMConfig,
|
||||
XLMModel,
|
||||
XLMWithLMHeadModel,
|
||||
XLMForQuestionAnswering,
|
||||
XLMForSequenceClassification,
|
||||
XLMForQuestionAnsweringSimple,
|
||||
)
|
||||
from transformers.modeling_xlm import XLM_PRETRAINED_MODEL_ARCHIVE_MAP
|
||||
|
||||
|
||||
@require_torch
|
||||
class XLMModelTest(ModelTesterMixin, unittest.TestCase):
|
||||
|
||||
all_model_classes = (
|
||||
(
|
||||
XLMModel,
|
||||
XLMWithLMHeadModel,
|
||||
XLMForQuestionAnswering,
|
||||
XLMForSequenceClassification,
|
||||
XLMForQuestionAnsweringSimple,
|
||||
)
|
||||
if is_torch_available()
|
||||
else ()
|
||||
)
|
||||
all_generative_model_classes = (
|
||||
(XLMWithLMHeadModel,) if is_torch_available() else ()
|
||||
) # TODO (PVP): Check other models whether language generation is also applicable
|
||||
|
||||
class XLMModelTester(object):
|
||||
def __init__(
|
||||
self,
|
||||
parent,
|
||||
batch_size=13,
|
||||
seq_length=7,
|
||||
is_training=True,
|
||||
use_input_lengths=True,
|
||||
use_token_type_ids=True,
|
||||
use_labels=True,
|
||||
gelu_activation=True,
|
||||
sinusoidal_embeddings=False,
|
||||
causal=False,
|
||||
asm=False,
|
||||
n_langs=2,
|
||||
vocab_size=99,
|
||||
n_special=0,
|
||||
hidden_size=32,
|
||||
num_hidden_layers=5,
|
||||
num_attention_heads=4,
|
||||
hidden_dropout_prob=0.1,
|
||||
attention_probs_dropout_prob=0.1,
|
||||
max_position_embeddings=512,
|
||||
type_vocab_size=16,
|
||||
type_sequence_label_size=2,
|
||||
initializer_range=0.02,
|
||||
num_labels=3,
|
||||
num_choices=4,
|
||||
summary_type="last",
|
||||
use_proj=True,
|
||||
scope=None,
|
||||
bos_token_id=0,
|
||||
):
|
||||
self.parent = parent
|
||||
self.batch_size = batch_size
|
||||
self.seq_length = seq_length
|
||||
self.is_training = is_training
|
||||
self.use_input_lengths = use_input_lengths
|
||||
self.use_token_type_ids = use_token_type_ids
|
||||
self.use_labels = use_labels
|
||||
self.gelu_activation = gelu_activation
|
||||
self.sinusoidal_embeddings = sinusoidal_embeddings
|
||||
self.asm = asm
|
||||
self.n_langs = n_langs
|
||||
self.vocab_size = vocab_size
|
||||
self.n_special = n_special
|
||||
self.summary_type = summary_type
|
||||
self.causal = causal
|
||||
self.use_proj = use_proj
|
||||
self.hidden_size = hidden_size
|
||||
self.num_hidden_layers = num_hidden_layers
|
||||
self.num_attention_heads = num_attention_heads
|
||||
self.hidden_dropout_prob = hidden_dropout_prob
|
||||
self.attention_probs_dropout_prob = attention_probs_dropout_prob
|
||||
self.max_position_embeddings = max_position_embeddings
|
||||
self.n_langs = n_langs
|
||||
self.type_sequence_label_size = type_sequence_label_size
|
||||
self.initializer_range = initializer_range
|
||||
self.summary_type = summary_type
|
||||
self.num_labels = num_labels
|
||||
self.num_choices = num_choices
|
||||
self.scope = scope
|
||||
self.bos_token_id = bos_token_id
|
||||
|
||||
def prepare_config_and_inputs(self):
|
||||
input_ids = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)
|
||||
input_mask = ids_tensor([self.batch_size, self.seq_length], 2).float()
|
||||
|
||||
input_lengths = None
|
||||
if self.use_input_lengths:
|
||||
input_lengths = (
|
||||
ids_tensor([self.batch_size], vocab_size=2) + self.seq_length - 2
|
||||
) # small variation of seq_length
|
||||
|
||||
token_type_ids = None
|
||||
if self.use_token_type_ids:
|
||||
token_type_ids = ids_tensor([self.batch_size, self.seq_length], self.n_langs)
|
||||
|
||||
sequence_labels = None
|
||||
token_labels = None
|
||||
is_impossible_labels = None
|
||||
if self.use_labels:
|
||||
sequence_labels = ids_tensor([self.batch_size], self.type_sequence_label_size)
|
||||
token_labels = ids_tensor([self.batch_size, self.seq_length], self.num_labels)
|
||||
is_impossible_labels = ids_tensor([self.batch_size], 2).float()
|
||||
|
||||
config = XLMConfig(
|
||||
vocab_size=self.vocab_size,
|
||||
n_special=self.n_special,
|
||||
emb_dim=self.hidden_size,
|
||||
n_layers=self.num_hidden_layers,
|
||||
n_heads=self.num_attention_heads,
|
||||
dropout=self.hidden_dropout_prob,
|
||||
attention_dropout=self.attention_probs_dropout_prob,
|
||||
gelu_activation=self.gelu_activation,
|
||||
sinusoidal_embeddings=self.sinusoidal_embeddings,
|
||||
asm=self.asm,
|
||||
causal=self.causal,
|
||||
n_langs=self.n_langs,
|
||||
max_position_embeddings=self.max_position_embeddings,
|
||||
initializer_range=self.initializer_range,
|
||||
summary_type=self.summary_type,
|
||||
use_proj=self.use_proj,
|
||||
bos_token_id=self.bos_token_id,
|
||||
)
|
||||
|
||||
return (
|
||||
config,
|
||||
input_ids,
|
||||
token_type_ids,
|
||||
input_lengths,
|
||||
sequence_labels,
|
||||
token_labels,
|
||||
is_impossible_labels,
|
||||
input_mask,
|
||||
)
|
||||
|
||||
def check_loss_output(self, result):
|
||||
self.parent.assertListEqual(list(result["loss"].size()), [])
|
||||
|
||||
def create_and_check_xlm_model(
|
||||
self,
|
||||
config,
|
||||
input_ids,
|
||||
token_type_ids,
|
||||
input_lengths,
|
||||
sequence_labels,
|
||||
token_labels,
|
||||
is_impossible_labels,
|
||||
input_mask,
|
||||
):
|
||||
model = XLMModel(config=config)
|
||||
model.to(torch_device)
|
||||
model.eval()
|
||||
outputs = model(input_ids, lengths=input_lengths, langs=token_type_ids)
|
||||
outputs = model(input_ids, langs=token_type_ids)
|
||||
outputs = model(input_ids)
|
||||
sequence_output = outputs[0]
|
||||
result = {
|
||||
"sequence_output": sequence_output,
|
||||
}
|
||||
self.parent.assertListEqual(
|
||||
list(result["sequence_output"].size()), [self.batch_size, self.seq_length, self.hidden_size]
|
||||
)
|
||||
|
||||
def create_and_check_xlm_lm_head(
|
||||
self,
|
||||
config,
|
||||
input_ids,
|
||||
token_type_ids,
|
||||
input_lengths,
|
||||
sequence_labels,
|
||||
token_labels,
|
||||
is_impossible_labels,
|
||||
input_mask,
|
||||
):
|
||||
model = XLMWithLMHeadModel(config)
|
||||
model.to(torch_device)
|
||||
model.eval()
|
||||
|
||||
loss, logits = model(input_ids, token_type_ids=token_type_ids, labels=token_labels)
|
||||
|
||||
result = {
|
||||
"loss": loss,
|
||||
"logits": logits,
|
||||
}
|
||||
|
||||
self.parent.assertListEqual(list(result["loss"].size()), [])
|
||||
self.parent.assertListEqual(
|
||||
list(result["logits"].size()), [self.batch_size, self.seq_length, self.vocab_size]
|
||||
)
|
||||
|
||||
def create_and_check_xlm_simple_qa(
|
||||
self,
|
||||
config,
|
||||
input_ids,
|
||||
token_type_ids,
|
||||
input_lengths,
|
||||
sequence_labels,
|
||||
token_labels,
|
||||
is_impossible_labels,
|
||||
input_mask,
|
||||
):
|
||||
model = XLMForQuestionAnsweringSimple(config)
|
||||
model.to(torch_device)
|
||||
model.eval()
|
||||
|
||||
outputs = model(input_ids)
|
||||
|
||||
outputs = model(input_ids, start_positions=sequence_labels, end_positions=sequence_labels)
|
||||
loss, start_logits, end_logits = outputs
|
||||
|
||||
result = {
|
||||
"loss": loss,
|
||||
"start_logits": start_logits,
|
||||
"end_logits": end_logits,
|
||||
}
|
||||
self.parent.assertListEqual(list(result["start_logits"].size()), [self.batch_size, self.seq_length])
|
||||
self.parent.assertListEqual(list(result["end_logits"].size()), [self.batch_size, self.seq_length])
|
||||
self.check_loss_output(result)
|
||||
|
||||
def create_and_check_xlm_qa(
|
||||
self,
|
||||
config,
|
||||
input_ids,
|
||||
token_type_ids,
|
||||
input_lengths,
|
||||
sequence_labels,
|
||||
token_labels,
|
||||
is_impossible_labels,
|
||||
input_mask,
|
||||
):
|
||||
model = XLMForQuestionAnswering(config)
|
||||
model.to(torch_device)
|
||||
model.eval()
|
||||
|
||||
outputs = model(input_ids)
|
||||
start_top_log_probs, start_top_index, end_top_log_probs, end_top_index, cls_logits = outputs
|
||||
|
||||
outputs = model(
|
||||
input_ids,
|
||||
start_positions=sequence_labels,
|
||||
end_positions=sequence_labels,
|
||||
cls_index=sequence_labels,
|
||||
is_impossible=is_impossible_labels,
|
||||
p_mask=input_mask,
|
||||
)
|
||||
|
||||
outputs = model(
|
||||
input_ids,
|
||||
start_positions=sequence_labels,
|
||||
end_positions=sequence_labels,
|
||||
cls_index=sequence_labels,
|
||||
is_impossible=is_impossible_labels,
|
||||
)
|
||||
|
||||
(total_loss,) = outputs
|
||||
|
||||
outputs = model(input_ids, start_positions=sequence_labels, end_positions=sequence_labels)
|
||||
|
||||
(total_loss,) = outputs
|
||||
|
||||
result = {
|
||||
"loss": total_loss,
|
||||
"start_top_log_probs": start_top_log_probs,
|
||||
"start_top_index": start_top_index,
|
||||
"end_top_log_probs": end_top_log_probs,
|
||||
"end_top_index": end_top_index,
|
||||
"cls_logits": cls_logits,
|
||||
}
|
||||
|
||||
self.parent.assertListEqual(list(result["loss"].size()), [])
|
||||
self.parent.assertListEqual(
|
||||
list(result["start_top_log_probs"].size()), [self.batch_size, model.config.start_n_top]
|
||||
)
|
||||
self.parent.assertListEqual(
|
||||
list(result["start_top_index"].size()), [self.batch_size, model.config.start_n_top]
|
||||
)
|
||||
self.parent.assertListEqual(
|
||||
list(result["end_top_log_probs"].size()),
|
||||
[self.batch_size, model.config.start_n_top * model.config.end_n_top],
|
||||
)
|
||||
self.parent.assertListEqual(
|
||||
list(result["end_top_index"].size()),
|
||||
[self.batch_size, model.config.start_n_top * model.config.end_n_top],
|
||||
)
|
||||
self.parent.assertListEqual(list(result["cls_logits"].size()), [self.batch_size])
|
||||
|
||||
def create_and_check_xlm_sequence_classif(
|
||||
self,
|
||||
config,
|
||||
input_ids,
|
||||
token_type_ids,
|
||||
input_lengths,
|
||||
sequence_labels,
|
||||
token_labels,
|
||||
is_impossible_labels,
|
||||
input_mask,
|
||||
):
|
||||
model = XLMForSequenceClassification(config)
|
||||
model.to(torch_device)
|
||||
model.eval()
|
||||
|
||||
(logits,) = model(input_ids)
|
||||
loss, logits = model(input_ids, labels=sequence_labels)
|
||||
|
||||
result = {
|
||||
"loss": loss,
|
||||
"logits": logits,
|
||||
}
|
||||
|
||||
self.parent.assertListEqual(list(result["loss"].size()), [])
|
||||
self.parent.assertListEqual(
|
||||
list(result["logits"].size()), [self.batch_size, self.type_sequence_label_size]
|
||||
)
|
||||
|
||||
def prepare_config_and_inputs_for_common(self):
|
||||
config_and_inputs = self.prepare_config_and_inputs()
|
||||
(
|
||||
config,
|
||||
input_ids,
|
||||
token_type_ids,
|
||||
input_lengths,
|
||||
sequence_labels,
|
||||
token_labels,
|
||||
is_impossible_labels,
|
||||
input_mask,
|
||||
) = config_and_inputs
|
||||
inputs_dict = {"input_ids": input_ids, "token_type_ids": token_type_ids, "lengths": input_lengths}
|
||||
return config, inputs_dict
|
||||
|
||||
def setUp(self):
|
||||
self.model_tester = XLMModelTest.XLMModelTester(self)
|
||||
self.config_tester = ConfigTester(self, config_class=XLMConfig, emb_dim=37)
|
||||
|
||||
def test_config(self):
|
||||
self.config_tester.run_common_tests()
|
||||
|
||||
def test_xlm_model(self):
|
||||
config_and_inputs = self.model_tester.prepare_config_and_inputs()
|
||||
self.model_tester.create_and_check_xlm_model(*config_and_inputs)
|
||||
|
||||
def test_xlm_lm_head(self):
|
||||
config_and_inputs = self.model_tester.prepare_config_and_inputs()
|
||||
self.model_tester.create_and_check_xlm_lm_head(*config_and_inputs)
|
||||
|
||||
def test_xlm_simple_qa(self):
|
||||
config_and_inputs = self.model_tester.prepare_config_and_inputs()
|
||||
self.model_tester.create_and_check_xlm_simple_qa(*config_and_inputs)
|
||||
|
||||
def test_xlm_qa(self):
|
||||
config_and_inputs = self.model_tester.prepare_config_and_inputs()
|
||||
self.model_tester.create_and_check_xlm_qa(*config_and_inputs)
|
||||
|
||||
def test_xlm_sequence_classif(self):
|
||||
config_and_inputs = self.model_tester.prepare_config_and_inputs()
|
||||
self.model_tester.create_and_check_xlm_sequence_classif(*config_and_inputs)
|
||||
|
||||
@slow
|
||||
def test_model_from_pretrained(self):
|
||||
for model_name in list(XLM_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
|
||||
model = XLMModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
|
||||
self.assertIsNotNone(model)
|
||||
|
||||
|
||||
class XLMModelLanguageGenerationTest(unittest.TestCase):
|
||||
@slow
|
||||
def test_lm_generate_xlm_mlm_en_2048(self):
|
||||
model = XLMWithLMHeadModel.from_pretrained("xlm-mlm-en-2048")
|
||||
input_ids = torch.tensor([[1, 14, 2232, 26, 1]]).long() # The dog is cute
|
||||
expected_output_ids = [
|
||||
1,
|
||||
14,
|
||||
2232,
|
||||
26,
|
||||
1,
|
||||
567,
|
||||
26,
|
||||
32,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
149,
|
||||
] # The dog is nothing is it!!!!!!!!!!!! TODO (PVP): this sentence (and others I tried) does not make much sense, there seems to be a problem with xlm language generation.
|
||||
output_ids = model.generate(input_ids)
|
||||
self.assertListEqual(output_ids[0].tolist(), expected_output_ids, do_sample=False)
|
Loading…
Reference in New Issue