56 lines
1.8 KiB
Python
56 lines
1.8 KiB
Python
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# Copyright 2022 Google LLC
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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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"""Tests for transformer."""
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from absl.testing import parameterized
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from robotics_transformer import transformer
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import tensorflow as tf
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class TransformerTest(parameterized.TestCase):
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def setUp(self):
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self._vocab_size = 10
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batch_size = 8
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sequence_len = 12
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self._tokens = tf.random.uniform(
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[batch_size, sequence_len, self._vocab_size],
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minval=0,
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maxval=1,
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dtype=tf.dtypes.float32,
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)
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super(TransformerTest, self).setUp()
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@parameterized.parameters(True, False)
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def test_transformer_forwardpass(self, return_attention_scores):
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network = transformer.Transformer(
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num_layers=2,
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layer_size=512,
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num_heads=4,
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feed_forward_size=256,
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dropout_rate=0.1,
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vocab_size=self._vocab_size,
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return_attention_scores=return_attention_scores)
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output_tokens, attention_scores = network(self._tokens, attention_mask=None)
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self.assertSequenceEqual(self._tokens.shape.as_list(),
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output_tokens.shape.as_list())
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if return_attention_scores:
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self.assertNotEmpty(attention_scores)
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else:
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self.assertEmpty(attention_scores)
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if __name__ == '__main__':
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tf.test.main()
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