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Paddle/python/paddle/fluid/tests/unittests/test_bmm_op.py

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# 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
from op_test import OpTest
import paddle
import paddle.fluid as fluid
import paddle.tensor as tensor
from paddle.fluid import Program, program_guard
class TestBmmOp(OpTest):
def setUp(self):
self.op_type = "bmm"
X = np.random.random((10, 3, 4)).astype("float64")
Y = np.random.random((10, 4, 5)).astype("float64")
self.inputs = {'X': X, 'Y': Y}
Out = np.matmul(X, Y)
self.outputs = {'Out': Out}
def test_check_output(self):
self.check_output()
def test_checkout_grad(self):
self.check_grad(['X', 'Y'], 'Out')
class API_TestBmm(unittest.TestCase):
def test_out(self):
with fluid.program_guard(fluid.Program(), fluid.Program()):
data1 = fluid.layers.data(
'data1', shape=[-1, 3, 4], dtype='float64')
data2 = fluid.layers.data(
'data2', shape=[-1, 4, 5], dtype='float64')
result_bmm = paddle.bmm(data1, data2)
place = fluid.CPUPlace()
exe = fluid.Executor(place)
input1 = np.random.random([10, 3, 4]).astype('float64')
input2 = np.random.random([10, 4, 5]).astype('float64')
result, = exe.run(feed={"data1": input1,
"data2": input2},
fetch_list=[result_bmm])
expected_result = np.matmul(input1, input2)
self.assertTrue(np.allclose(expected_result, result))
class API_TestDygraphBmm(unittest.TestCase):
def test_out(self):
input1 = np.array([[[1.0, 1.0, 1.0], [2.0, 2.0, 2.0]],
[[3.0, 3.0, 3.0], [4.0, 4.0, 4.0]]])
input2 = np.array([[[1.0, 1.0], [2.0, 2.0], [3.0, 3.0]],
[[4.0, 4.0], [5.0, 5.0], [6.0, 6.0]]])
with fluid.dygraph.guard():
x = fluid.dygraph.to_variable(input1)
y = fluid.dygraph.to_variable(input2)
out = paddle.bmm(x, y)
out_np = out.numpy()
expected_result = np.matmul(input1, input2)
self.assertTrue(np.allclose(expected_result, out_np))
if __name__ == "__main__":
unittest.main()