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139 lines
4.8 KiB
139 lines
4.8 KiB
# Copyright (c) 2020 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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import paddle.fluid.core as core
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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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from paddle.fluid import Program, program_guard
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class TestCrossOp(OpTest):
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def setUp(self):
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self.op_type = "cross"
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self.initTestCase()
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self.inputs = {
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'X': np.random.random(self.shape).astype(self.dtype),
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'Y': np.random.random(self.shape).astype(self.dtype)
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}
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self.init_output()
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def initTestCase(self):
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self.attrs = {'dim': -2}
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self.dtype = np.float64
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self.shape = (1024, 3, 1)
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def init_output(self):
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x = np.squeeze(self.inputs['X'], 2)
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y = np.squeeze(self.inputs['Y'], 2)
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z_list = []
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for i in range(1024):
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z_list.append(np.cross(x[i], y[i]))
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self.outputs = {'Out': np.array(z_list).reshape(self.shape)}
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def test_check_output(self):
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self.check_output()
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def test_check_grad_normal(self):
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self.check_grad(['X', 'Y'], 'Out')
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class TestCrossOpCase1(TestCrossOp):
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def initTestCase(self):
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self.shape = (2048, 3)
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self.dtype = np.float32
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def init_output(self):
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z_list = []
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for i in range(2048):
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z_list.append(np.cross(self.inputs['X'][i], self.inputs['Y'][i]))
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self.outputs = {'Out': np.array(z_list).reshape(self.shape)}
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class TestCrossAPI(unittest.TestCase):
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def input_data(self):
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self.data_x = np.array(
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[[1.0, 1.0, 1.0], [2.0, 2.0, 2.0], [3.0, 3.0, 3.0]])
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self.data_y = np.array(
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[[1.0, 1.0, 1.0], [1.0, 1.0, 1.0], [1.0, 1.0, 1.0]])
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def test_cross_api(self):
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self.input_data()
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# case 1:
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with program_guard(Program(), Program()):
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x = fluid.layers.data(name='x', shape=[-1, 3])
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y = fluid.layers.data(name='y', shape=[-1, 3])
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z = paddle.cross(x, y, axis=1)
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exe = fluid.Executor(fluid.CPUPlace())
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res, = exe.run(feed={'x': self.data_x,
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'y': self.data_y},
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fetch_list=[z.name],
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return_numpy=False)
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expect_out = np.array([[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
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[0.0, 0.0, 0.0]])
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self.assertTrue(np.allclose(expect_out, np.array(res)))
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# case 2:
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with program_guard(Program(), Program()):
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x = fluid.layers.data(name='x', shape=[-1, 3])
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y = fluid.layers.data(name='y', shape=[-1, 3])
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z = paddle.cross(x, y)
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exe = fluid.Executor(fluid.CPUPlace())
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res, = exe.run(feed={'x': self.data_x,
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'y': self.data_y},
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fetch_list=[z.name],
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return_numpy=False)
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expect_out = np.array([[-1.0, -1.0, -1.0], [2.0, 2.0, 2.0],
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[-1.0, -1.0, -1.0]])
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self.assertTrue(np.allclose(expect_out, np.array(res)))
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# case 3:
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with program_guard(Program(), Program()):
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x = fluid.data(name="x", shape=[-1, 3], dtype="float32")
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y = fluid.data(name='y', shape=[-1, 3], dtype='float32')
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y_1 = paddle.cross(x, y, name='result')
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self.assertEqual(('result' in y_1.name), True)
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def test_dygraph_api(self):
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self.input_data()
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# case 1:
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with fluid.dygraph.guard():
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x = fluid.dygraph.to_variable(self.data_x)
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y = fluid.dygraph.to_variable(self.data_y)
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z = paddle.cross(x, y)
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np_z = z.numpy()
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expect_out = np.array([[-1.0, -1.0, -1.0], [2.0, 2.0, 2.0],
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[-1.0, -1.0, -1.0]])
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self.assertTrue(np.allclose(expect_out, np_z))
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# case 2:
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with fluid.dygraph.guard():
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x = fluid.dygraph.to_variable(self.data_x)
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y = fluid.dygraph.to_variable(self.data_y)
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z = paddle.cross(x, y, axis=1)
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np_z = z.numpy()
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expect_out = np.array([[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
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[0.0, 0.0, 0.0]])
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self.assertTrue(np.allclose(expect_out, np_z))
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if __name__ == '__main__':
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unittest.main()
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