Move test model folders (#17034)
* move test model folders (TODO: fix imports and others) * fix (potentially partially) imports (in model test modules) * fix (potentially partially) imports (in tokenization test modules) * fix (potentially partially) imports (in feature extraction test modules) * fix import utils.test_modeling_tf_core * fix path ../fixtures/ * fix imports about generation.test_generation_flax_utils * fix more imports * fix fixture path * fix get_test_dir * update module_to_test_file * fix get_tests_dir from wrong transformers.utils * update config.yml (CircleCI) * fix style * remove missing imports * update new model script * update check_repo * update SPECIAL_MODULE_TO_TEST_MAP * fix style * add __init__ * update self-scheduled * fix add_new_model scripts * check one way to get location back * python setup.py build install * fix import in test auto * update self-scheduled.yml * update slack notification script * Add comments about artifact names * fix for yolos Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Yih-Dar
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tests/models/camembert/__init__.py
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tests/models/camembert/__init__.py
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tests/models/camembert/test_modeling_camembert.py
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tests/models/camembert/test_modeling_camembert.py
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# coding=utf-8
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# Copyright 2020 The HuggingFace Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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from transformers import is_torch_available
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from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
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if is_torch_available():
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import torch
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from transformers import CamembertModel
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@require_torch
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@require_sentencepiece
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@require_tokenizers
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class CamembertModelIntegrationTest(unittest.TestCase):
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@slow
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def test_output_embeds_base_model(self):
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model = CamembertModel.from_pretrained("camembert-base")
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model.to(torch_device)
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input_ids = torch.tensor(
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[[5, 121, 11, 660, 16, 730, 25543, 110, 83, 6]],
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device=torch_device,
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dtype=torch.long,
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) # J'aime le camembert !
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output = model(input_ids)["last_hidden_state"]
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expected_shape = torch.Size((1, 10, 768))
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self.assertEqual(output.shape, expected_shape)
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# compare the actual values for a slice.
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expected_slice = torch.tensor(
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[[[-0.0254, 0.0235, 0.1027], [0.0606, -0.1811, -0.0418], [-0.1561, -0.1127, 0.2687]]],
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device=torch_device,
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dtype=torch.float,
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)
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# camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
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# camembert.eval()
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# expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()
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self.assertTrue(torch.allclose(output[:, :3, :3], expected_slice, atol=1e-4))
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54
tests/models/camembert/test_modeling_tf_camembert.py
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tests/models/camembert/test_modeling_tf_camembert.py
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# coding=utf-8
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# Copyright 2020 The HuggingFace Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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from transformers import is_tf_available
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from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
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if is_tf_available():
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import numpy as np
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import tensorflow as tf
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from transformers import TFCamembertModel
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@require_tf
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@require_sentencepiece
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@require_tokenizers
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class TFCamembertModelIntegrationTest(unittest.TestCase):
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@slow
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def test_output_embeds_base_model(self):
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model = TFCamembertModel.from_pretrained("jplu/tf-camembert-base")
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input_ids = tf.convert_to_tensor(
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[[5, 121, 11, 660, 16, 730, 25543, 110, 83, 6]],
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dtype=tf.int32,
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) # J'aime le camembert !"
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output = model(input_ids)["last_hidden_state"]
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expected_shape = tf.TensorShape((1, 10, 768))
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self.assertEqual(output.shape, expected_shape)
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# compare the actual values for a slice.
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expected_slice = tf.convert_to_tensor(
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[[[-0.0254, 0.0235, 0.1027], [0.0606, -0.1811, -0.0418], [-0.1561, -0.1127, 0.2687]]],
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dtype=tf.float32,
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)
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# camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
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# camembert.eval()
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# expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()
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self.assertTrue(np.allclose(output[:, :3, :3].numpy(), expected_slice.numpy(), atol=1e-4))
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130
tests/models/camembert/test_tokenization_camembert.py
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tests/models/camembert/test_tokenization_camembert.py
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# coding=utf-8
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# Copyright 2018 HuggingFace Inc. team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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from transformers import CamembertTokenizer, CamembertTokenizerFast
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from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
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from transformers.utils import is_torch_available
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from ...test_tokenization_common import TokenizerTesterMixin
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SAMPLE_VOCAB = get_tests_dir("fixtures/test_sentencepiece.model")
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SAMPLE_BPE_VOCAB = get_tests_dir("fixtures/test_sentencepiece_bpe.model")
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FRAMEWORK = "pt" if is_torch_available() else "tf"
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@require_sentencepiece
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@require_tokenizers
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class CamembertTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
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tokenizer_class = CamembertTokenizer
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rust_tokenizer_class = CamembertTokenizerFast
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test_rust_tokenizer = True
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test_sentencepiece = True
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def setUp(self):
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super().setUp()
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# We have a SentencePiece fixture for testing
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tokenizer = CamembertTokenizer(SAMPLE_VOCAB)
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tokenizer.save_pretrained(self.tmpdirname)
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def test_convert_token_and_id(self):
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"""Test ``_convert_token_to_id`` and ``_convert_id_to_token``."""
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token = "<pad>"
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token_id = 1
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self.assertEqual(self.get_tokenizer()._convert_token_to_id(token), token_id)
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self.assertEqual(self.get_tokenizer()._convert_id_to_token(token_id), token)
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def test_get_vocab(self):
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vocab_keys = list(self.get_tokenizer().get_vocab().keys())
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self.assertEqual(vocab_keys[0], "<s>NOTUSED")
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self.assertEqual(vocab_keys[1], "<pad>")
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self.assertEqual(vocab_keys[-1], "<mask>")
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self.assertEqual(len(vocab_keys), 1_004)
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def test_vocab_size(self):
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self.assertEqual(self.get_tokenizer().vocab_size, 1_005)
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def test_rust_and_python_bpe_tokenizers(self):
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tokenizer = CamembertTokenizer(SAMPLE_BPE_VOCAB)
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tokenizer.save_pretrained(self.tmpdirname)
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rust_tokenizer = CamembertTokenizerFast.from_pretrained(self.tmpdirname)
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sequence = "I was born in 92000, and this is falsé."
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ids = tokenizer.encode(sequence)
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rust_ids = rust_tokenizer.encode(sequence)
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self.assertListEqual(ids, rust_ids)
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ids = tokenizer.encode(sequence, add_special_tokens=False)
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rust_ids = rust_tokenizer.encode(sequence, add_special_tokens=False)
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self.assertListEqual(ids, rust_ids)
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# <unk> tokens are not the same for `rust` than for `slow`.
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# Because spm gives back raw token instead of `unk` in EncodeAsPieces
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# tokens = tokenizer.tokenize(sequence)
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tokens = tokenizer.convert_ids_to_tokens(ids)
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rust_tokens = rust_tokenizer.tokenize(sequence)
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self.assertListEqual(tokens, rust_tokens)
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def test_rust_and_python_full_tokenizers(self):
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if not self.test_rust_tokenizer:
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return
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tokenizer = self.get_tokenizer()
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rust_tokenizer = self.get_rust_tokenizer()
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sequence = "I was born in 92000, and this is falsé."
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tokens = tokenizer.tokenize(sequence)
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rust_tokens = rust_tokenizer.tokenize(sequence)
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self.assertListEqual(tokens, rust_tokens)
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ids = tokenizer.encode(sequence, add_special_tokens=False)
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rust_ids = rust_tokenizer.encode(sequence, add_special_tokens=False)
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self.assertListEqual(ids, rust_ids)
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rust_tokenizer = self.get_rust_tokenizer()
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ids = tokenizer.encode(sequence)
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rust_ids = rust_tokenizer.encode(sequence)
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self.assertListEqual(ids, rust_ids)
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@slow
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def test_tokenizer_integration(self):
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# fmt: off
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expected_encoding = {'input_ids': [[5, 54, 7196, 297, 30, 23, 776, 18, 11, 3215, 3705, 8252, 22, 3164, 1181, 2116, 29, 16, 813, 25, 791, 3314, 20, 3446, 38, 27575, 120, 6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [5, 468, 17, 11, 9088, 20, 1517, 8, 22804, 18818, 10, 38, 629, 607, 607, 142, 19, 7196, 867, 56, 10326, 24, 2267, 20, 416, 5072, 15612, 233, 734, 7, 2399, 27, 16, 3015, 1649, 7, 24, 20, 4338, 2399, 27, 13, 3400, 14, 13, 6189, 8, 930, 9, 6]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]} # noqa: E501
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# fmt: on
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# camembert is a french model. So we also use french texts.
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sequences = [
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"Le transformeur est un modèle d'apprentissage profond introduit en 2017, "
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"utilisé principalement dans le domaine du traitement automatique des langues (TAL).",
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"À l'instar des réseaux de neurones récurrents (RNN), les transformeurs sont conçus "
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"pour gérer des données séquentielles, telles que le langage naturel, pour des tâches "
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"telles que la traduction et la synthèse de texte.",
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]
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self.tokenizer_integration_test_util(
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expected_encoding=expected_encoding,
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model_name="camembert-base",
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revision="3a0641d9a1aeb7e848a74299e7e4c4bca216b4cf",
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sequences=sequences,
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)
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