|
- # coding=utf-8
- # Copyright 2020 The HuggingFace Team. All rights reserved.
- #
- # 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_tf_available
- from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
-
-
- if is_tf_available():
- import numpy as np
- import tensorflow as tf
-
- from transformers import TFCamembertModel
-
-
- @require_tf
- @require_sentencepiece
- @require_tokenizers
- class TFCamembertModelIntegrationTest(unittest.TestCase):
- @slow
- def test_output_embeds_base_model(self):
- model = TFCamembertModel.from_pretrained("jplu/tf-camembert-base")
-
- input_ids = tf.convert_to_tensor(
- [[5, 121, 11, 660, 16, 730, 25543, 110, 83, 6]],
- dtype=tf.int32,
- ) # J'aime le camembert !"
-
- output = model(input_ids)["last_hidden_state"]
- expected_shape = tf.TensorShape((1, 10, 768))
- self.assertEqual(output.shape, expected_shape)
- # compare the actual values for a slice.
- expected_slice = tf.convert_to_tensor(
- [[[-0.0254, 0.0235, 0.1027], [0.0606, -0.1811, -0.0418], [-0.1561, -0.1127, 0.2687]]],
- dtype=tf.float32,
- )
- # camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
- # camembert.eval()
- # expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()
-
- self.assertTrue(np.allclose(output[:, :3, :3].numpy(), expected_slice.numpy(), atol=1e-4))
|