add new flatten op test=develop (#25393)
yaoxuefeng
5 years ago
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GitHub
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20c8432ae3
commit
224620071b
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# Copyright (c) 2019 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 as fluid
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import paddle
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from op_test import OpTest
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class TestFlattenOp(OpTest):
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def setUp(self):
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self.op_type = "flatten_contiguous_range"
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self.start_axis = 0
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self.stop_axis = -1
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self.init_test_case()
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self.inputs = {"X": np.random.random(self.in_shape).astype("float64")}
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self.init_attrs()
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self.outputs = {
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"Out": self.inputs["X"].reshape(self.new_shape),
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"XShape": np.random.random(self.in_shape).astype("float32")
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}
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def test_check_output(self):
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self.check_output(no_check_set=["XShape"])
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def test_check_grad(self):
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self.check_grad(["X"], "Out")
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def init_test_case(self):
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self.in_shape = (3, 2, 5, 4)
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self.start_axis = 0
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self.stop_axis = -1
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self.new_shape = (120)
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def init_attrs(self):
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self.attrs = {
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"start_axis": self.start_axis,
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"stop_axis": self.stop_axis
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}
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class TestFlattenOp_1(TestFlattenOp):
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def init_test_case(self):
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self.in_shape = (3, 2, 5, 4)
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self.start_axis = 1
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self.stop_axis = 2
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self.new_shape = (3, 10, 4)
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def init_attrs(self):
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self.attrs = {
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"start_axis": self.start_axis,
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"stop_axis": self.stop_axis
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}
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class TestFlattenOp_2(TestFlattenOp):
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def init_test_case(self):
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self.in_shape = (3, 2, 5, 4)
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self.start_axis = 0
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self.stop_axis = 1
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self.new_shape = (6, 5, 4)
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def init_attrs(self):
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self.attrs = {
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"start_axis": self.start_axis,
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"stop_axis": self.stop_axis
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}
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class TestFlattenOp_3(TestFlattenOp):
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def init_test_case(self):
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self.in_shape = (3, 2, 5, 4)
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self.start_axis = 0
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self.stop_axis = 2
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self.new_shape = (30, 4)
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def init_attrs(self):
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self.attrs = {
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"start_axis": self.start_axis,
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"stop_axis": self.stop_axis
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}
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class TestFlattenOp_4(TestFlattenOp):
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def init_test_case(self):
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self.in_shape = (3, 2, 5, 4)
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self.start_axis = -2
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self.stop_axis = -1
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self.new_shape = (3, 2, 20)
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def init_attrs(self):
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self.attrs = {
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"start_axis": self.start_axis,
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"stop_axis": self.stop_axis
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}
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class TestFlattenOp_5(TestFlattenOp):
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def init_test_case(self):
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self.in_shape = (3, 2, 5, 4)
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self.start_axis = 2
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self.stop_axis = 2
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self.new_shape = (3, 2, 5, 4)
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def init_attrs(self):
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self.attrs = {
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"start_axis": self.start_axis,
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"stop_axis": self.stop_axis
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}
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class TestFlattenOpSixDims(TestFlattenOp):
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def init_test_case(self):
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self.in_shape = (3, 2, 3, 2, 4, 4)
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self.start_axis = 3
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self.stop_axis = 5
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self.new_shape = (3, 2, 3, 32)
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def init_attrs(self):
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self.attrs = {
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"start_axis": self.start_axis,
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"stop_axis": self.stop_axis
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}
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class TestFlatten2OpError(unittest.TestCase):
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def test_errors(self):
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image_shape = (2, 3, 4, 4)
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x = np.arange(image_shape[0] * image_shape[1] * image_shape[2] *
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image_shape[3]).reshape(image_shape) / 100.
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x = x.astype('float32')
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def test_ValueError1():
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x_var = paddle.nn.data(name="x", shape=image_shape, dtype='float32')
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out = paddle.flatten(x_var, start_axis=2, stop_axis=1)
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self.assertRaises(ValueError, test_ValueError1)
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def test_ValueError2():
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x_var = paddle.nn.data(name="x", shape=image_shape, dtype='float32')
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paddle.flatten(x_var, start_axis=10, stop_axis=1)
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self.assertRaises(ValueError, test_ValueError2)
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def test_ValueError3():
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x_var = paddle.nn.data(name="x", shape=image_shape, dtype='float32')
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paddle.flatten(x_var, start_axis=2, stop_axis=10)
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self.assertRaises(ValueError, test_ValueError3)
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def test_type():
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# dtype must be float32, float64, int8, int32, int64.
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x2 = np.arange(image_shape[0] * image_shape[1] * image_shape[2] *
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image_shape[3]).reshape(image_shape) / 100.
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x2 = x2.astype('float16')
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x2_var = paddle.data(name='x2', shape=[3, 2, 4, 5], dtype='float16')
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paddle.flatten(x2_var)
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self.assertRaises(TypeError, test_type)
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def test_InputError():
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out = paddle.flatten(x)
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self.assertRaises(ValueError, test_InputError)
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class TestFlattenPython(unittest.TestCase):
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def test_python_api(self):
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image_shape = (2, 3, 4, 4)
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x = np.arange(image_shape[0] * image_shape[1] * image_shape[2] *
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image_shape[3]).reshape(image_shape) / 100.
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x = x.astype('float32')
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def test_InputError():
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out = paddle.flatten(x)
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self.assertRaises(ValueError, test_InputError)
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def test_Negative():
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paddle.enable_imperative()
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img = paddle.imperative.to_variable(x)
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out = paddle.flatten(img, start_axis=-2, stop_axis=-1)
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return out.numpy().shape
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res_shape = test_Negative()
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self.assertTrue((2, 3, 16) == res_shape)
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if __name__ == "__main__":
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unittest.main()
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