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.
127 lines
4.1 KiB
127 lines
4.1 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
|
|
|
|
|
|
class TestLodResetOpByAttr(OpTest):
|
|
def setUp(self):
|
|
self.op_type = "lod_reset"
|
|
x = np.random.random((10, 20)).astype("float32")
|
|
lod = [[3, 2, 5]]
|
|
# target_offset_lod and target_lod are the same lod info represented
|
|
# in offset-based format and length-based format, respectively.
|
|
target_offset_lod = [0, 7, 10]
|
|
target_lod = [7, 3]
|
|
self.inputs = {'X': (x, lod)}
|
|
# The `target_lod` attribute is still based on offset
|
|
self.attrs = {'target_lod': target_offset_lod}
|
|
self.outputs = {'Out': (x, [target_lod])}
|
|
|
|
def test_check_output(self):
|
|
self.check_output()
|
|
|
|
def test_check_grad(self):
|
|
self.check_grad(["X"], "Out")
|
|
|
|
|
|
class TestLodResetOpByInput(OpTest):
|
|
def setUp(self):
|
|
self.op_type = "lod_reset"
|
|
x = np.random.random((10, 20)).astype("float32")
|
|
lod = [[3, 2, 5]]
|
|
# target_offset_lod and target_lod are the same lod info represented
|
|
# in offset-based format and length-based format, respectively.
|
|
target_offset_lod = [0, 4, 7, 10]
|
|
target_lod = [4, 3, 3]
|
|
self.inputs = {
|
|
'X': (x, lod),
|
|
'Y': np.array([target_offset_lod]).astype('int32')
|
|
}
|
|
self.outputs = {'Out': (x, [target_lod])}
|
|
|
|
def test_check_output(self):
|
|
self.check_output()
|
|
|
|
def test_check_grad(self):
|
|
self.check_grad(["X"], "Out", no_grad_set=set("Y"))
|
|
|
|
|
|
class TestLodResetOpBoth(OpTest):
|
|
def setUp(self):
|
|
self.op_type = "lod_reset"
|
|
x = np.random.random((10, 20)).astype("float32")
|
|
lod = [[3, 2, 5]]
|
|
target_offset_lod_attr = [0, 7, 10]
|
|
target_offset_lod_in = [0, 4, 7, 10]
|
|
target_lod_in = [4, 3, 3]
|
|
self.inputs = {
|
|
'X': (x, lod),
|
|
'Y': np.array(target_offset_lod_in).astype('int32')
|
|
}
|
|
self.attrs = {'target_lod': target_offset_lod_attr}
|
|
self.outputs = {'Out': (x, [target_lod_in])}
|
|
|
|
def test_check_output(self):
|
|
self.check_output()
|
|
|
|
def test_check_grad(self):
|
|
self.check_grad(["X"], "Out", no_grad_set=set("Y"))
|
|
|
|
|
|
class TestLodResetOpYIsLoDTensor(OpTest):
|
|
def setUp(self):
|
|
self.op_type = "lod_reset"
|
|
x = np.random.random((10, 20)).astype("float32")
|
|
lod = [[3, 2, 5]]
|
|
y = np.random.random((10, 10)).astype("float32")
|
|
target_lod = [[4, 3, 3]]
|
|
self.inputs = {'X': (x, lod), 'Y': (y, target_lod)}
|
|
self.outputs = {'Out': (x, target_lod)}
|
|
|
|
def test_check_output(self):
|
|
self.check_output()
|
|
|
|
def test_check_grad(self):
|
|
self.check_grad(["X"], "Out", no_grad_set=set("Y"))
|
|
|
|
|
|
class TestLodAppendOpByAttr(OpTest):
|
|
def setUp(self):
|
|
self.op_type = "lod_reset"
|
|
x = np.random.random((10, 20)).astype("float32")
|
|
lod = [[3, 2, 5]]
|
|
# target_offset_lod and target_lod are the same lod info represented
|
|
# in offset-based format and length-based format, respectively.
|
|
target_offset_lod = [i for i in range(11)]
|
|
self.inputs = {'X': (x, lod)}
|
|
out_lod = [[3, 2, 5], [1] * 10]
|
|
# The `target_lod` attribute is still based on offset
|
|
self.attrs = {'target_lod': target_offset_lod, 'append': True}
|
|
self.outputs = {'Out': (x, out_lod)}
|
|
|
|
def test_check_output(self):
|
|
self.check_output()
|
|
|
|
def test_check_grad(self):
|
|
self.check_grad(["X"], "Out")
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|