remove addcmul (#28937)
* remove addcmul * remove unittest and other related code of addcmul * fix bug * fix merge conflictrevert-31562-mean
Wei Shengyu
5 years ago
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GitHub
parent
f459dd9634
commit
dc8bb76c68
@ -1,187 +0,0 @@
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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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import unittest
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import numpy as np
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import paddle
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import paddle.fluid as fluid
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import paddle.fluid.core as core
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from paddle.fluid.op import Operator
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from paddle.fluid import compiler, Program, program_guard
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from op_test import OpTest, skip_check_grad_ci
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class TestAddcmulLayer(unittest.TestCase):
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def setUp(self):
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self._dtype = "float64"
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self.input = np.random.uniform(0.1, 1, [3, 100]).astype(self._dtype)
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self.tensor1 = np.random.uniform(0.1, 1, [100]).astype(self._dtype)
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self.tensor2 = np.random.uniform(0.1, 1, [3, 100]).astype(self._dtype)
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def static(self, value=1.0):
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prog = fluid.Program()
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with fluid.program_guard(prog):
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input = fluid.data(name="input", dtype=self._dtype, shape=[3, 100])
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tensor1 = fluid.data(name="tensor1", dtype=self._dtype, shape=[100])
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tensor2 = fluid.data(
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name="tensor2", dtype=self._dtype, shape=[3, 100])
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out = paddle.tensor.math.addcmul(input, tensor1, tensor2, value)
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exe = fluid.Executor(self._place)
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return exe.run(feed={
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"input": self.input,
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"tensor1": self.tensor1,
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"tensor2": self.tensor2
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},
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program=prog,
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fetch_list=[out])[0]
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def dynamic(self, value=1.0):
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with fluid.dygraph.guard(self._place):
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input = fluid.dygraph.to_variable(self.input)
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tensor1 = fluid.dygraph.to_variable(self.tensor1)
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tensor2 = fluid.dygraph.to_variable(self.tensor2)
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out = paddle.tensor.math.addcmul(input, tensor1, tensor2, value)
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return out.numpy()
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def numpy(self, value=1.0):
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self.out = np.add(self.input,
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np.multiply(self.tensor1, self.tensor2) * value)
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return self.out
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def test_equal(self):
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places = []
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if fluid.core.is_compiled_with_cuda():
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places.append(fluid.CUDAPlace(0))
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for place in places:
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self._place = place
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self.assertTrue(np.allclose(self.numpy(), self.static()))
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self.assertTrue(
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np.allclose(
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self.numpy(value=0.9), self.dynamic(value=0.9)))
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self.assertTrue(
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np.allclose(
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self.numpy(value=0), self.dynamic(value=0)))
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class TestAddcmul(unittest.TestCase):
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def test_addcmul(self):
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program = Program()
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with program_guard(program):
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data_shape = [3, 64, 64]
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input = fluid.data(name='in', shape=data_shape, dtype='float32')
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tensor1 = fluid.data(name='t1', shape=data_shape, dtype='float32')
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tensor2 = fluid.data(name='t2', shape=data_shape, dtype='float32')
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out = paddle.tensor.math.addcmul(input, tensor1, tensor2)
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self.assertEqual(out.shape, input.shape)
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def test_addcmul_with_broadcast0(self):
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program = Program()
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with program_guard(program):
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input = fluid.data(name='in', shape=[3, 100], dtype='float32')
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tensor1 = fluid.data(name='t1', shape=[3, 100], dtype='float32')
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tensor2 = fluid.data(name='t2', shape=[100], dtype='float32')
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out = paddle.tensor.math.addcmul(input, tensor1, tensor2)
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self.assertEqual(out.shape, input.shape)
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def test_addcmul_with_broadcast1(self):
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program = Program()
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with program_guard(program):
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input = fluid.data(name='in', shape=[4, 100], dtype='float32')
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tensor1 = fluid.data(name='t1', shape=[100], dtype='float32')
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tensor2 = fluid.data(name='t2', shape=[4, 100], dtype='float32')
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out = paddle.tensor.math.addcmul(input, tensor1, tensor2)
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self.assertEqual(out.shape, input.shape)
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def test_addcmul_with_broadcast2(self):
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program = Program()
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with program_guard(program):
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input = fluid.data(name='in', shape=[4, 100], dtype='float32')
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tensor1 = fluid.data(name='t1', shape=[100], dtype='float32')
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tensor2 = fluid.data(name='t2', shape=[100], dtype='float32')
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out = paddle.tensor.math.addcmul(input, tensor1, tensor2)
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self.assertEqual(out.shape, input.shape)
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class InvalidInputTest(unittest.TestCase):
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def test_error(self):
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def test_invalid_input():
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program = Program()
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with program_guard(program):
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input = [20, 20]
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tensor1 = fluid.data(
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name='tensor1', shape=[20, 20], dtype='float32')
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tensor2 = fluid.data(
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name='tensor2', shape=[20, 20], dtype='float32')
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out = paddle.tensor.math.addcmul(input, tensor1, tensor2)
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self.assertRaises(TypeError, test_invalid_input)
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def test_invalid_tensor1():
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program = Program()
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with program_guard(program):
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input = fluid.data(
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name='input', shape=[20, 20], dtype='float32')
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tensor1 = [20, 20]
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tensor2 = fluid.data(
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name='tensor2', shape=[20, 20], dtype='float32')
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out = paddle.tensor.math.addcmul(input, tensor1, tensor2)
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self.assertRaises(TypeError, test_invalid_tensor1)
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def test_invalid_tensor2():
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program = Program()
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with program_guard(program):
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input = fluid.data(
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name='input', shape=[20, 20], dtype='float32')
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tensor1 = fluid.data(
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name='tensor1', shape=[20, 20], dtype='float32')
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tensor2 = [20, 20]
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out = paddle.tensor.math.addcmul(input, tensor1, tensor2)
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self.assertRaises(TypeError, test_invalid_tensor2)
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def test_invalid_value_int():
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program = Program()
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with program_guard(program):
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input = fluid.data(
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name='input', shape=[20, 20], dtype='float32')
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tensor1 = fluid.data(
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name='tensor1', shape=[20, 20], dtype='float32')
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tensor2 = fluid.data(
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name='tensor2', shape=[20, 20], dtype='float32')
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out = paddle.tensor.math.addcmul(input, tensor1, tensor2, value=1)
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self.assertRaises(TypeError, test_invalid_value_int)
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def test_invalid_value_float():
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program = Program()
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with program_guard(program):
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input = fluid.data(name='input', shape=[20, 20], dtype='int32')
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tensor1 = fluid.data(
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name='tensor1', shape=[20, 20], dtype='int32')
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tensor2 = fluid.data(
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name='tensor2', shape=[20, 20], dtype='int32')
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out = paddle.tensor.math.addcmul(input, tensor1, tensor2, value=1.0)
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self.assertRaises(TypeError, test_invalid_value_float)
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if __name__ == '__main__':
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unittest.main()
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