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2026-07-13 12:40:42 +08:00

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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 unittest
from paddle.base import core
class TestInferShape(unittest.TestCase):
def test_sum_op(self):
prog = core.ProgramDesc()
self.assertIsNotNone(prog)
block = prog.block(0)
self.assertIsNotNone(block)
shape = [10, 20]
# prepare input/output
x1 = block.var(b'x1')
x1.set_type(core.VarDesc.VarType.DENSE_TENSOR)
x1.set_shape(shape)
x2 = block.var(b'x2')
x2.set_type(core.VarDesc.VarType.DENSE_TENSOR)
x2.set_shape(shape)
out = block.var(b'out')
out.set_type(core.VarDesc.VarType.DENSE_TENSOR)
# prepare the operator
sum_op_desc = block.append_op()
sum_op_desc.set_type("sum")
sum_op_desc.set_input("X", ["x1", "x2"])
sum_op_desc.set_output("Out", ["out"])
sum_op_desc.check_attrs()
sum_op_desc.infer_shape(block)
self.assertEqual(out.shape(), shape)
def test_mul_op(self):
prog = core.ProgramDesc()
self.assertIsNotNone(prog)
block = prog.block(0)
self.assertIsNotNone(block)
x_shape = [10, 20]
y_shape = [20, 30]
# prepare input/output
x1 = block.var(b'x')
x1.set_type(core.VarDesc.VarType.DENSE_TENSOR)
x1.set_shape(x_shape)
x2 = block.var(b'y')
x2.set_type(core.VarDesc.VarType.DENSE_TENSOR)
x2.set_shape(y_shape)
out = block.var(b'out')
out.set_type(core.VarDesc.VarType.DENSE_TENSOR)
# prepare the operator
mul_op_desc = block.append_op()
mul_op_desc.set_type("mul")
mul_op_desc.set_input("X", ["x"])
mul_op_desc.set_input("Y", ["y"])
mul_op_desc.set_output("Out", ["out"])
mul_op_desc._set_attr("x_num_col_dims", 1)
mul_op_desc._set_attr("y_num_col_dims", 1)
mul_op_desc.check_attrs()
mul_op_desc.infer_shape(block)
self.assertEqual(out.shape(), [x_shape[0], y_shape[1]])
if __name__ == '__main__':
unittest.main()