170 lines
5.0 KiB
170 lines
5.0 KiB
# Copyright (c) 2018 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
|
|
from op_test import OpTest
|
|
import paddle.fluid as fluid
|
|
import paddle.tensor as tensor
|
|
from paddle.fluid import compiler, Program, program_guard, core
|
|
|
|
|
|
class TestUnbind(unittest.TestCase):
|
|
def test_unbind(self):
|
|
|
|
x_1 = fluid.data(shape=[2, 3], dtype='float32', name='x_1')
|
|
[out_0, out_1] = tensor.unbind(input=x_1, axis=0)
|
|
input_1 = np.random.random([2, 3]).astype("float32")
|
|
axis = fluid.data(shape=[1], dtype='int32', name='axis')
|
|
exe = fluid.Executor(place=fluid.CPUPlace())
|
|
|
|
[res_1, res_2] = exe.run(fluid.default_main_program(),
|
|
feed={"x_1": input_1,
|
|
"axis": 0},
|
|
fetch_list=[out_0, out_1])
|
|
|
|
assert np.array_equal(res_1, input_1[0, 0:100])
|
|
assert np.array_equal(res_2, input_1[1, 0:100])
|
|
|
|
|
|
class TestLayersUnbind(unittest.TestCase):
|
|
def test_layers_unbind(self):
|
|
|
|
x_1 = fluid.data(shape=[2, 3], dtype='float32', name='x_1')
|
|
[out_0, out_1] = fluid.layers.unbind(input=x_1, axis=0)
|
|
input_1 = np.random.random([2, 3]).astype("float32")
|
|
axis = fluid.data(shape=[1], dtype='int32', name='axis')
|
|
exe = fluid.Executor(place=fluid.CPUPlace())
|
|
|
|
[res_1, res_2] = exe.run(fluid.default_main_program(),
|
|
feed={"x_1": input_1,
|
|
"axis": 0},
|
|
fetch_list=[out_0, out_1])
|
|
|
|
assert np.array_equal(res_1, input_1[0, 0:100])
|
|
assert np.array_equal(res_2, input_1[1, 0:100])
|
|
|
|
|
|
class TestUnbindOp(OpTest):
|
|
def initParameters(self):
|
|
pass
|
|
|
|
def outReshape(self):
|
|
pass
|
|
|
|
def setAxis(self):
|
|
pass
|
|
|
|
def setUp(self):
|
|
self._set_op_type()
|
|
self.dtype = self.get_dtype()
|
|
self.axis = 0
|
|
self.num = 3
|
|
self.initParameters()
|
|
x = np.arange(12).reshape(3, 2, 2).astype(self.dtype)
|
|
self.out = np.split(x, self.num, self.axis)
|
|
self.outReshape()
|
|
self.inputs = {'X': x}
|
|
self.attrs = {'axis': self.axis}
|
|
self.setAxis()
|
|
self.outputs = {'Out': [('out%d' % i, self.out[i]) \
|
|
for i in range(len(self.out))]}
|
|
|
|
def get_dtype(self):
|
|
return "float64"
|
|
|
|
def _set_op_type(self):
|
|
self.op_type = "unbind"
|
|
|
|
def test_check_output(self):
|
|
self.check_output()
|
|
|
|
def test_check_grad(self):
|
|
self.check_grad(['X'], ['out0', 'out1', 'out2'])
|
|
|
|
|
|
class TestUnbindOp1(TestUnbindOp):
|
|
def initParameters(self):
|
|
self.axis = 1
|
|
self.num = 2
|
|
|
|
def test_check_grad(self):
|
|
self.check_grad(['X'], ['out0', 'out1'])
|
|
|
|
def outReshape(self):
|
|
self.out[0] = self.out[0].reshape((3, 2))
|
|
self.out[1] = self.out[1].reshape((3, 2))
|
|
|
|
|
|
class TestUnbindOp2(TestUnbindOp):
|
|
def initParameters(self):
|
|
self.axis = 2
|
|
self.num = 2
|
|
|
|
def test_check_grad(self):
|
|
self.check_grad(['X'], ['out0', 'out1'])
|
|
|
|
def outReshape(self):
|
|
self.out[0] = self.out[0].reshape((3, 2))
|
|
self.out[1] = self.out[1].reshape((3, 2))
|
|
|
|
|
|
class TestUnbindOp3(TestUnbindOp):
|
|
def initParameters(self):
|
|
self.axis = 2
|
|
self.num = 2
|
|
|
|
def setAxis(self):
|
|
self.attrs = {'axis': -1}
|
|
|
|
def test_check_grad(self):
|
|
self.check_grad(['X'], ['out0', 'out1'])
|
|
|
|
def outReshape(self):
|
|
self.out[0] = self.out[0].reshape((3, 2))
|
|
self.out[1] = self.out[1].reshape((3, 2))
|
|
|
|
|
|
class TestUnbindOp4(TestUnbindOp):
|
|
def initParameters(self):
|
|
self.axis = 1
|
|
self.num = 2
|
|
|
|
def setAxis(self):
|
|
self.attrs = {'axis': -2}
|
|
|
|
def test_check_grad(self):
|
|
self.check_grad(['X'], ['out0', 'out1'])
|
|
|
|
def outReshape(self):
|
|
self.out[0] = self.out[0].reshape((3, 2))
|
|
self.out[1] = self.out[1].reshape((3, 2))
|
|
|
|
|
|
class TestUnbindAxisError(unittest.TestCase):
|
|
def test_errors(self):
|
|
with program_guard(Program(), Program()):
|
|
x = fluid.data(shape=[2, 3], dtype='float32', name='x')
|
|
|
|
def test_table_Variable():
|
|
tensor.unbind(input=x, axis=2.0)
|
|
|
|
self.assertRaises(TypeError, test_table_Variable)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|