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127 lines
4.3 KiB
127 lines
4.3 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 paddle
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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.fluid as fluid
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from paddle.fluid import Program, program_guard
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class TestRollOp(OpTest):
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def setUp(self):
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self.op_type = "roll"
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self.init_dtype_type()
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self.inputs = {'X': np.random.random(self.x_shape).astype(self.dtype)}
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self.attrs = {'shifts': self.shifts, 'axis': self.axis}
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self.outputs = {
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'Out': np.roll(self.inputs['X'], self.attrs['shifts'],
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self.attrs['axis'])
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}
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def init_dtype_type(self):
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self.dtype = np.float64
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self.x_shape = (100, 4, 5)
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self.shifts = [101, -1]
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self.axis = [0, -2]
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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'], 'Out')
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class TestRollOpCase2(TestRollOp):
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def init_dtype_type(self):
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self.dtype = np.float32
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self.x_shape = (100, 10, 5)
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self.shifts = [8, -1]
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self.axis = [-1, -2]
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class TestRollAPI(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, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]])
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def test_roll_op_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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z = paddle.roll(x, shifts=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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fetch_list=[z.name],
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return_numpy=False)
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expect_out = np.array([[9.0, 1.0, 2.0], [3.0, 4.0, 5.0],
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[6.0, 7.0, 8.0]])
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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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z = paddle.roll(x, shifts=1, axis=0)
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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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fetch_list=[z.name],
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return_numpy=False)
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expect_out = np.array([[7.0, 8.0, 9.0], [1.0, 2.0, 3.0],
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[4.0, 5.0, 6.0]])
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self.assertTrue(np.allclose(expect_out, np.array(res)))
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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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z = paddle.roll(x, shifts=1)
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np_z = z.numpy()
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expect_out = np.array([[9.0, 1.0, 2.0], [3.0, 4.0, 5.0],
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[6.0, 7.0, 8.0]])
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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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z = paddle.roll(x, shifts=1, axis=0)
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np_z = z.numpy()
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expect_out = np.array([[7.0, 8.0, 9.0], [1.0, 2.0, 3.0],
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[4.0, 5.0, 6.0]])
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self.assertTrue(np.allclose(expect_out, np_z))
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def test_roll_op_false(self):
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self.input_data()
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def test_axis_out_range():
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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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z = paddle.roll(x, shifts=1, axis=10)
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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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fetch_list=[z.name],
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return_numpy=False)
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self.assertRaises(ValueError, test_axis_out_range)
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if __name__ == "__main__":
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unittest.main()
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