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Roberta tokenization + fixed tests (py3 + py2).

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This commit is contained in:
LysandreJik
2019-08-09 15:02:13 -04:00
parent 14e970c271
commit 75d5f98fd2
3 changed files with 138 additions and 224 deletions
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40
pytorch_transformers/tests/modeling_roberta_test.py
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@@ -157,42 +157,6 @@ class RobertaModelTest(CommonTestCases.CommonModelTester):
inputs_dict = {'input_ids': input_ids, 'token_type_ids': token_type_ids, 'attention_mask': input_mask}
return config, inputs_dict
def test_inference_masked_lm(self):
model = RobertaForMaskedLM.from_pretrained('roberta-base')
input_ids = torch.tensor([[0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]])
output = model(input_ids)[0]
expected_shape = torch.Size((1, 11, 50265))
self.assertEqual(
output.shape,
expected_shape
)
# compare the actual values for a slice.
expected_slice = torch.Tensor(
[[[33.8843, -4.3107, 22.7779],
[4.6533, -2.8099, 13.6252],
[1.8222, -3.6898, 8.8600]]]
)
self.assertTrue(
torch.allclose(output[:, :3, :3], expected_slice, atol=1e-3)
)
# @pytest.mark.slow
def test_inference_no_head(self):
model = RobertaModel.from_pretrained('roberta-base')
input_ids = torch.tensor([[0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]])
output = model(input_ids)[0]
# compare the actual values for a slice.
expected_slice = torch.Tensor(
[[[-0.0231, 0.0782, 0.0074],
[-0.1854, 0.0539, -0.0174],
[0.0548, 0.0799, 0.1687]]]
)
self.assertTrue(
torch.allclose(output[:, :3, :3], expected_slice, atol=1e-3)
)
def setUp(self):
self.model_tester = RobertaModelTest.RobertaModelTester(self)
self.config_tester = ConfigTester(self, config_class=RobertaConfig, hidden_size=37)
@@ -220,7 +184,7 @@ class RobertaModelTest(CommonTestCases.CommonModelTester):
class RobertaModelIntegrationTest(unittest.TestCase):
# @pytest.mark.slow
@pytest.mark.slow
def test_inference_masked_lm(self):
model = RobertaForMaskedLM.from_pretrained('roberta-base')
@@ -241,7 +205,7 @@ class RobertaModelIntegrationTest(unittest.TestCase):
torch.allclose(output[:, :3, :3], expected_slice, atol=1e-3)
)
# @pytest.mark.slow
@pytest.mark.slow
def test_inference_no_head(self):
model = RobertaModel.from_pretrained('roberta-base')

11
pytorch_transformers/tests/tokenization_roberta_test.py
View File

@@ -18,8 +18,7 @@ import os
import json
import unittest
from pytorch_transformers.tokenization_roberta import RobertaTokenizer, DICT_FILES_NAMES
from pytorch_transformers.tokenization_gpt2 import GPT2Tokenizer, VOCAB_FILES_NAMES
from pytorch_transformers.tokenization_roberta import RobertaTokenizer, VOCAB_FILES_NAMES
from .tokenization_tests_commons import CommonTestCases
@@ -45,8 +44,7 @@ class RobertaTokenizationTest(CommonTestCases.CommonTokenizerTester):
fp.write("\n".join(merges))
def get_tokenizer(self):
bpe_tokenizer = GPT2Tokenizer.from_pretrained(self.tmpdirname, **self.special_tokens_map)
return RobertaTokenizer.from_pretrained("roberta-base", bpe_tokenizer=bpe_tokenizer)
return RobertaTokenizer.from_pretrained(self.tmpdirname, **self.special_tokens_map)
def get_input_output_texts(self):
input_text = u"lower newer"
@@ -54,15 +52,14 @@ class RobertaTokenizationTest(CommonTestCases.CommonTokenizerTester):
return input_text, output_text
def test_full_tokenizer(self):
tokenizer = self.get_tokenizer()
tokenizer = RobertaTokenizer(self.vocab_file, self.merges_file, **self.special_tokens_map)
text = "lower"
bpe_tokens = ["low", "er"]
tokens = tokenizer.tokenize(text)
self.assertListEqual(tokens, bpe_tokens)
input_tokens = tokens + [tokenizer.unk_token]
input_bpe_tokens = [0, 4, 12, 176, 2]
tokenizer.convert_tokens_to_ids(input_tokens)
input_bpe_tokens = [13, 12, 17]
self.assertListEqual(
tokenizer.convert_tokens_to_ids(input_tokens), input_bpe_tokens)