test_multihead_attention.py 3.0 KB
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#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
# 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
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import paddle
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import paddle.fluid as fluid
import paddle.fluid.core as core
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import numpy as np


class TestMultiheadAttention(unittest.TestCase):
    def gen_random_input(self):
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        """Generate random input data."""
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        # batch_size, max_sequence_length, hidden dimension
        self.input_shape = (3, 13, 16)
        self.queries = np.random.random(size=self.input_shape).astype("float32")
        self.keys = np.random.random(size=self.input_shape).astype("float32")

    def set_program(self):
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        """Build the test program."""
        queries = fluid.layers.data(
            name="queries",
            shape=self.input_shape,
            dtype="float32",
            append_batch_size=False,
        )
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        queries.stop_gradient = False
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        keys = fluid.layers.data(
            name="keys",
            shape=self.input_shape,
            dtype="float32",
            append_batch_size=False,
        )
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        keys.stop_gradient = False

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        contexts = fluid.nets.scaled_dot_product_attention(
            queries=queries,
            keys=keys,
            values=keys,
            num_heads=8,
            dropout_rate=0.0,
        )
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        out = paddle.sum(contexts, axis=None)
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        fluid.backward.append_backward(loss=out)

        self.fetch_list = [contexts]

    def run_program(self):
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        """Run the test program."""
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        places = [core.CPUPlace()]
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        if core.is_compiled_with_cuda():
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            places.append(core.CUDAPlace(0))

        for place in places:
            self.set_inputs(place)
            exe = fluid.Executor(place)

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            exe.run(fluid.default_startup_program())
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            output = exe.run(
                fluid.default_main_program(),
                feed=self.inputs,
                fetch_list=self.fetch_list,
                return_numpy=True,
            )
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            self.op_output = output

    def set_inputs(self, place):
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        """Set the randomly generated data to the test program."""
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        self.inputs = {}
        queries = fluid.Tensor()
        queries.set(self.queries, place)

        keys = fluid.Tensor()
        keys.set(self.keys, place)

        self.inputs["keys"] = keys
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        self.inputs["queries"] = queries
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    def test_multihead_attention(self):
        self.gen_random_input()

        self.set_program()
        self.run_program()

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        # fixme(caoying) add more meaningfull unittest.
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if __name__ == '__main__':
    unittest.main()