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paddlepaddle--paddle/test/legacy_test/test_fusion_seqpool_concat_op.py
2026-07-13 12:40:42 +08:00

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4.1 KiB
Python

# 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.
import sys
import unittest
import numpy as np
from op_test import OpTest
import paddle
sys.path.append("../sequence")
from test_sequence_pool import (
compute_seqpool_avg,
compute_seqpool_sqrt,
compute_seqpool_sum,
)
def convert_to_offset(lod):
offset = [[0] for i in lod]
for i, level in enumerate(lod):
for seq_len in level:
offset[i].append(offset[i][-1] + seq_len)
return offset
def api_wrapper(x, pooltype="SUM", axis=1):
if isinstance(x, paddle.Tensor):
x = [x]
return paddle._C_ops.fusion_seqpool_concat(x, pooltype, axis)
class TestFusionSeqPoolConcatOp(OpTest):
def setUp(self):
self.w = 11
self.lods = [[[2, 3, 5]], [[1, 5, 2]]]
self.set_conf()
self.set_pooltype()
self.op_type = 'fusion_seqpool_concat'
self.python_api = api_wrapper
self.axis = 1
bs = len(self.lods[0][0])
inputs = []
outs = []
i = 0
for lod in self.lods:
assert bs == len(lod[0]), 'All lod size should be equal'
x = np.random.uniform(0.1, 1, [sum(lod[0]), self.w]).astype(
'float32'
)
offset = convert_to_offset(lod)
out = np.zeros((bs, self.w)).astype('float32')
if self.pooltype == "SUM":
compute_seqpool_sum(x, offset, out)
elif self.pooltype == "AVERAGE":
compute_seqpool_avg(x, offset, out)
elif self.pooltype == "SQRT":
compute_seqpool_sqrt(x, offset, out)
else:
raise Exception("Unsupported pool type!")
inputs.append((f'x_{i}', (x, lod)))
outs.append(out)
i = i + 1
self.inputs = {'X': inputs}
self.outputs = {'Out': np.concatenate(outs, axis=self.axis)}
self.attrs = {
'pooltype': self.pooltype,
'axis': self.axis,
}
def set_pooltype(self):
self.pooltype = "SUM"
def set_conf(self):
pass
def test_check_output(self):
self.check_output()
class TestFusionSeqPoolConcatOpCase1(TestFusionSeqPoolConcatOp):
def set_conf(self):
self.lods = [[[1]]]
class TestFusionSeqPoolConcatOpCase2(TestFusionSeqPoolConcatOp):
def set_conf(self):
self.lods = [[[1]], [[1]], [[1]]]
class TestFusionSeqPoolConcatOpCase3(TestFusionSeqPoolConcatOp):
def set_conf(self):
self.lods = [[[1, 3, 4, 6]]]
self.w = 10
class TestFusionSeqPoolConcatOpCase4(TestFusionSeqPoolConcatOp):
def set_conf(self):
self.lods = [[[2, 13, 4]], [[1, 1, 1]], [[5, 3, 1]], [[9, 10, 3]]]
self.w = 3
# test avg pool and sqrt
def create_test_avg_sqrt_class(parent):
class TestSeqPoolAvgCase(parent):
def set_pooltype(self):
self.pooltype = "AVERAGE"
class TestSeqPoolSqrtCase(parent):
def set_pooltype(self):
self.pooltype = "SQRT"
cls_name_avg = "{}_{}".format(parent.__name__, "avg")
cls_name_sqrt = "{}_{}".format(parent.__name__, "sqrt")
TestSeqPoolAvgCase.__name__ = cls_name_avg
TestSeqPoolSqrtCase.__name__ = cls_name_sqrt
globals()[cls_name_avg] = TestSeqPoolAvgCase
globals()[cls_name_sqrt] = TestSeqPoolSqrtCase
create_test_avg_sqrt_class(TestFusionSeqPoolConcatOp)
create_test_avg_sqrt_class(TestFusionSeqPoolConcatOpCase1)
create_test_avg_sqrt_class(TestFusionSeqPoolConcatOpCase2)
create_test_avg_sqrt_class(TestFusionSeqPoolConcatOpCase3)
create_test_avg_sqrt_class(TestFusionSeqPoolConcatOpCase4)
if __name__ == '__main__':
unittest.main()