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143 lines
4.1 KiB
143 lines
4.1 KiB
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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from __future__ import print_function
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import unittest
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import numpy as np
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from op_test import OpTest
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import paddle
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import paddle.fluid as fluid
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class TestGatherOp(OpTest):
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def setUp(self):
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self.op_type = "gather"
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self.config()
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xnp = np.random.random(self.x_shape).astype(self.x_type)
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self.inputs = {
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'X': xnp,
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'Index': np.array(self.index).astype(self.index_type)
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}
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self.outputs = {'Out': self.inputs["X"][self.inputs["Index"]]}
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def test_check_output(self):
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self.check_output()
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def test_check_grad(self):
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self.check_grad(['X'], 'Out')
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def config(self):
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"""
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For multi-dimension input
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"""
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self.x_shape = (10, 20)
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self.x_type = "float64"
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self.index = [1, 3, 5]
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self.index_type = "int32"
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class TestCase1(TestGatherOp):
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def config(self):
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"""
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For one dimension input
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"""
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self.x_shape = (100)
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self.x_type = "float64"
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self.index = [1, 3, 5]
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self.index_type = "int32"
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class TestCase2(TestGatherOp):
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def config(self):
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"""
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For int64_t index type
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"""
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self.x_shape = (100)
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self.x_type = "float64"
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self.index = [1, 3, 5]
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self.index_type = "int64"
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class TestCase3(TestGatherOp):
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def config(self):
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"""
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For other input type
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"""
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self.x_shape = (10, 20)
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self.x_type = "float64"
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self.index = [1, 3, 5]
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self.index_type = "int64"
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class TestCase4(TestGatherOp):
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def config(self):
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self.x_shape = (10, 20)
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self.attrs = {'overwrite': False}
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self.x_type = "double"
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self.index = [1, 1]
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self.index_type = "int32"
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class TestCase5(TestGatherOp):
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def config(self):
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self.x_shape = (10, 20)
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self.attrs = {'overwrite': False}
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self.x_type = "float64"
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self.index = [1, 1, 3]
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self.index_type = "int32"
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class TestCase6(TestGatherOp):
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def config(self):
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self.x_shape = (10, 20)
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self.attrs = {'overwrite': True}
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self.x_type = "float64"
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self.index = [1, 3]
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self.index_type = "int32"
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class API_TestGather(unittest.TestCase):
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def test_out(self):
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with fluid.program_guard(fluid.Program(), fluid.Program()):
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data1 = fluid.layers.data('data1', shape=[-1, 2], dtype='float64')
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index = fluid.layers.data('index', shape=[-1, 1], dtype='float64')
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out = paddle.gather(data1, index)
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place = fluid.CPUPlace()
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exe = fluid.Executor(place)
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input = np.array([[1, 2], [3, 4], [5, 6]])
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index_1 = np.array([1, 2])
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result, = exe.run(feed={"data1": input,
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"index": index_1},
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fetch_list=[out])
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expected_output = np.array([[3, 4], [5, 6]])
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self.assertTrue(np.allclose(result, expected_output))
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class API_TestDygraphGather(unittest.TestCase):
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def test_out(self):
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with fluid.dygraph.guard():
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input_1 = np.array([[1, 2], [3, 4], [5, 6]])
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index_1 = np.array([1, 2])
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input = fluid.dygraph.to_variable(input_1)
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index = fluid.dygraph.to_variable(index_1)
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output = paddle.fluid.layers.gather(input, index)
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output_np = output.numpy()
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expected_output = np.array([[3, 4], [5, 6]])
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self.assertTrue(np.allclose(output_np, expected_output))
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if __name__ == "__main__":
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unittest.main()
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