# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve. # # 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 import paddle.v2.fluid as fluid import paddle.v2.fluid.core as core import numpy as np class TestMultiheadAttention(unittest.TestCase): def gen_random_input(self): """Generate random input data. """ # 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): """Build the test program. """ queries = fluid.layers.data( name="queries", shape=self.input_shape, dtype="float32", append_batch_size=False) queries.stop_gradient = False keys = fluid.layers.data( name="keys", shape=self.input_shape, dtype="float32", append_batch_size=False) keys.stop_gradient = False contexts = fluid.nets.scaled_dot_product_attention( queries=queries, keys=keys, values=keys, num_heads=8, dropout_rate=0.) out = fluid.layers.reduce_sum(contexts, dim=None) fluid.backward.append_backward(loss=out) self.fetch_list = [contexts] def run_program(self): """Run the test program. """ places = [core.CPUPlace()] if core.is_compile_gpu(): places.append(core.CUDAPlace(0)) for place in places: self.set_inputs(place) exe = fluid.Executor(place) exe.run(fluid.default_startup_program()) output = exe.run(fluid.default_main_program(), feed=self.inputs, fetch_list=self.fetch_list, return_numpy=True) self.op_output = output def set_inputs(self, place): """Set the randomly generated data to the test program. """ self.inputs = {} queries = fluid.Tensor() queries.set(self.queries, place) keys = fluid.Tensor() keys.set(self.keys, place) self.inputs["keys"] = keys self.inputs["queries"] = queries def test_multihead_attention(self): self.gen_random_input() self.set_program() self.run_program() #fixme(caoying) add more meaningfull unittest. if __name__ == '__main__': unittest.main()