You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
128 lines
3.8 KiB
128 lines
3.8 KiB
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
|
|
#
|
|
# 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.
|
|
|
|
from __future__ import print_function
|
|
|
|
import unittest
|
|
import numpy as np
|
|
import paddle
|
|
import paddle.fluid as fluid
|
|
import paddle.fluid.core as core
|
|
from paddle.fluid import Program, program_guard
|
|
from op_test import OpTest
|
|
|
|
|
|
class TestFlipOp_API(unittest.TestCase):
|
|
"""Test flip api."""
|
|
|
|
def test_static_graph(self):
|
|
startup_program = fluid.Program()
|
|
train_program = fluid.Program()
|
|
with fluid.program_guard(train_program, startup_program):
|
|
axis = [0]
|
|
input = fluid.data(name='input', dtype='float32', shape=[2, 3])
|
|
output = paddle.flip(input, axis)
|
|
place = fluid.CPUPlace()
|
|
if fluid.core.is_compiled_with_cuda():
|
|
place = fluid.CUDAPlace(0)
|
|
exe = fluid.Executor(place)
|
|
exe.run(startup_program)
|
|
img = np.array([[1, 2, 3], [4, 5, 6]]).astype(np.float32)
|
|
res = exe.run(train_program,
|
|
feed={'input': img},
|
|
fetch_list=[output])
|
|
out_np = np.array(res[0])
|
|
out_ref = np.array([[4, 5, 6], [1, 2, 3]]).astype(np.float32)
|
|
self.assertTrue(
|
|
(out_np == out_ref).all(),
|
|
msg='flip output is wrong, out =' + str(out_np))
|
|
|
|
def test_dygraph(self):
|
|
img = np.array([[1, 2, 3], [4, 5, 6]]).astype(np.float32)
|
|
with fluid.dygraph.guard():
|
|
inputs = fluid.dygraph.to_variable(img)
|
|
ret = paddle.flip(inputs, [0])
|
|
out_ref = np.array([[4, 5, 6], [1, 2, 3]]).astype(np.float32)
|
|
self.assertTrue(
|
|
(ret.numpy() == out_ref).all(),
|
|
msg='flip output is wrong, out =' + str(ret.numpy()))
|
|
|
|
|
|
class TestFlipOp(OpTest):
|
|
def setUp(self):
|
|
self.op_type = 'flip'
|
|
self.init_test_case()
|
|
self.inputs = {'X': np.random.random(self.in_shape).astype('float64')}
|
|
self.init_attrs()
|
|
self.outputs = {'Out': self.calc_ref_res()}
|
|
|
|
def init_attrs(self):
|
|
self.attrs = {"axis": self.axis}
|
|
|
|
def test_check_output(self):
|
|
self.check_output()
|
|
|
|
def test_check_grad(self):
|
|
self.check_grad(["X"], "Out")
|
|
|
|
def init_test_case(self):
|
|
self.in_shape = (6, 4, 2, 3)
|
|
self.axis = [0, 1]
|
|
|
|
def calc_ref_res(self):
|
|
res = self.inputs['X']
|
|
for axis in self.axis:
|
|
res = np.flip(res, axis)
|
|
return res
|
|
|
|
|
|
class TestFlipOpAxis1(TestFlipOp):
|
|
def init_test_case(self):
|
|
self.in_shape = (2, 4, 4)
|
|
self.axis = [0]
|
|
|
|
|
|
class TestFlipOpAxis2(TestFlipOp):
|
|
def init_test_case(self):
|
|
self.in_shape = (4, 4, 6, 3)
|
|
self.axis = [0, 2]
|
|
|
|
|
|
class TestFlipOpAxis3(TestFlipOp):
|
|
def init_test_case(self):
|
|
self.in_shape = (4, 3, 1)
|
|
self.axis = [0, 1, 2]
|
|
|
|
|
|
class TestFlipOpAxis4(TestFlipOp):
|
|
def init_test_case(self):
|
|
self.in_shape = (6, 4, 2, 2)
|
|
self.axis = [0, 1, 2, 3]
|
|
|
|
|
|
class TestFlipOpEmptyAxis(TestFlipOp):
|
|
def init_test_case(self):
|
|
self.in_shape = (6, 4, 2, 2)
|
|
self.axis = []
|
|
|
|
|
|
class TestFlipOpNegAxis(TestFlipOp):
|
|
def init_test_case(self):
|
|
self.in_shape = (6, 4, 2, 2)
|
|
self.axis = [-1]
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|