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# 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 | |
class TFCamembertModelIntegrationTest(unittest.TestCase): | |
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)) | |