remove addcmul (#28937) (#29640)

* remove addcmul

* remove unittest and other related code of addcmul

* fix bug

* fix merge conflict

python/paddle/__init__.py

@@ -187,7 +187,6 @@ from .tensor.math import logsumexp  #DEFINE_ALIAS
 from .tensor.math import inverse  #DEFINE_ALIAS
 from .tensor.math import log1p  #DEFINE_ALIAS
 from .tensor.math import erf  #DEFINE_ALIAS
-# from .tensor.math import addcmul  #DEFINE_ALIAS
 from .tensor.math import addmm  #DEFINE_ALIAS
 from .tensor.math import clip  #DEFINE_ALIAS
 from .tensor.math import trace  #DEFINE_ALIAS

python/paddle/fluid/tests/unittests/test_addcmul.py

-#  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
-import paddle
-import paddle.fluid as fluid
-import paddle.fluid.core as core
-from paddle.fluid.op import Operator
-from paddle.fluid import compiler, Program, program_guard
-from op_test import OpTest, skip_check_grad_ci
-
-
-class TestAddcmulLayer(unittest.TestCase):
-    def setUp(self):
-        self._dtype = "float64"
-        self.input = np.random.uniform(0.1, 1, [3, 100]).astype(self._dtype)
-        self.tensor1 = np.random.uniform(0.1, 1, [100]).astype(self._dtype)
-        self.tensor2 = np.random.uniform(0.1, 1, [3, 100]).astype(self._dtype)
-
-    def static(self, value=1.0):
-        prog = fluid.Program()
-        with fluid.program_guard(prog):
-            input = fluid.data(name="input", dtype=self._dtype, shape=[3, 100])
-            tensor1 = fluid.data(name="tensor1", dtype=self._dtype, shape=[100])
-            tensor2 = fluid.data(
-                name="tensor2", dtype=self._dtype, shape=[3, 100])
-            out = paddle.tensor.math.addcmul(input, tensor1, tensor2, value)
-
-        exe = fluid.Executor(self._place)
-        return exe.run(feed={
-            "input": self.input,
-            "tensor1": self.tensor1,
-            "tensor2": self.tensor2
-        },
-                       program=prog,
-                       fetch_list=[out])[0]
-
-    def dynamic(self, value=1.0):
-        with fluid.dygraph.guard(self._place):
-            input = fluid.dygraph.to_variable(self.input)
-            tensor1 = fluid.dygraph.to_variable(self.tensor1)
-            tensor2 = fluid.dygraph.to_variable(self.tensor2)
-            out = paddle.tensor.math.addcmul(input, tensor1, tensor2, value)
-            return out.numpy()
-
-    def numpy(self, value=1.0):
-        self.out = np.add(self.input,
-                          np.multiply(self.tensor1, self.tensor2) * value)
-        return self.out
-
-    def test_equal(self):
-        places = []
-        if fluid.core.is_compiled_with_cuda():
-            places.append(fluid.CUDAPlace(0))
-        for place in places:
-            self._place = place
-            self.assertTrue(np.allclose(self.numpy(), self.static()))
-            self.assertTrue(
-                np.allclose(
-                    self.numpy(value=0.9), self.dynamic(value=0.9)))
-            self.assertTrue(
-                np.allclose(
-                    self.numpy(value=0), self.dynamic(value=0)))
-
-
-class TestAddcmul(unittest.TestCase):
-    def test_addcmul(self):
-        program = Program()
-        with program_guard(program):
-            data_shape = [3, 64, 64]
-            input = fluid.data(name='in', shape=data_shape, dtype='float32')
-            tensor1 = fluid.data(name='t1', shape=data_shape, dtype='float32')
-            tensor2 = fluid.data(name='t2', shape=data_shape, dtype='float32')
-
-            out = paddle.tensor.math.addcmul(input, tensor1, tensor2)
-            self.assertEqual(out.shape, input.shape)
-
-    def test_addcmul_with_broadcast0(self):
-        program = Program()
-        with program_guard(program):
-            input = fluid.data(name='in', shape=[3, 100], dtype='float32')
-            tensor1 = fluid.data(name='t1', shape=[3, 100], dtype='float32')
-            tensor2 = fluid.data(name='t2', shape=[100], dtype='float32')
-
-            out = paddle.tensor.math.addcmul(input, tensor1, tensor2)
-            self.assertEqual(out.shape, input.shape)
-
-    def test_addcmul_with_broadcast1(self):
-        program = Program()
-        with program_guard(program):
-            input = fluid.data(name='in', shape=[4, 100], dtype='float32')
-            tensor1 = fluid.data(name='t1', shape=[100], dtype='float32')
-            tensor2 = fluid.data(name='t2', shape=[4, 100], dtype='float32')
-
-            out = paddle.tensor.math.addcmul(input, tensor1, tensor2)
-            self.assertEqual(out.shape, input.shape)
-
-    def test_addcmul_with_broadcast2(self):
-        program = Program()
-        with program_guard(program):
-            input = fluid.data(name='in', shape=[4, 100], dtype='float32')
-            tensor1 = fluid.data(name='t1', shape=[100], dtype='float32')
-            tensor2 = fluid.data(name='t2', shape=[100], dtype='float32')
-
-            out = paddle.tensor.math.addcmul(input, tensor1, tensor2)
-            self.assertEqual(out.shape, input.shape)
-
-
-class InvalidInputTest(unittest.TestCase):
-    def test_error(self):
-        def test_invalid_input():
-            program = Program()
-            with program_guard(program):
-                input = [20, 20]
-                tensor1 = fluid.data(
-                    name='tensor1', shape=[20, 20], dtype='float32')
-                tensor2 = fluid.data(
-                    name='tensor2', shape=[20, 20], dtype='float32')
-                out = paddle.tensor.math.addcmul(input, tensor1, tensor2)
-
-        self.assertRaises(TypeError, test_invalid_input)
-
-        def test_invalid_tensor1():
-            program = Program()
-            with program_guard(program):
-                input = fluid.data(
-                    name='input', shape=[20, 20], dtype='float32')
-                tensor1 = [20, 20]
-                tensor2 = fluid.data(
-                    name='tensor2', shape=[20, 20], dtype='float32')
-                out = paddle.tensor.math.addcmul(input, tensor1, tensor2)
-
-        self.assertRaises(TypeError, test_invalid_tensor1)
-
-        def test_invalid_tensor2():
-            program = Program()
-            with program_guard(program):
-                input = fluid.data(
-                    name='input', shape=[20, 20], dtype='float32')
-                tensor1 = fluid.data(
-                    name='tensor1', shape=[20, 20], dtype='float32')
-                tensor2 = [20, 20]
-                out = paddle.tensor.math.addcmul(input, tensor1, tensor2)
-
-        self.assertRaises(TypeError, test_invalid_tensor2)
-
-        def test_invalid_value_int():
-            program = Program()
-            with program_guard(program):
-                input = fluid.data(
-                    name='input', shape=[20, 20], dtype='float32')
-                tensor1 = fluid.data(
-                    name='tensor1', shape=[20, 20], dtype='float32')
-                tensor2 = fluid.data(
-                    name='tensor2', shape=[20, 20], dtype='float32')
-                out = paddle.tensor.math.addcmul(input, tensor1, tensor2, value=1)
-
-        self.assertRaises(TypeError, test_invalid_value_int)
-
-        def test_invalid_value_float():
-            program = Program()
-            with program_guard(program):
-                input = fluid.data(name='input', shape=[20, 20], dtype='int32')
-                tensor1 = fluid.data(
-                    name='tensor1', shape=[20, 20], dtype='int32')
-                tensor2 = fluid.data(
-                    name='tensor2', shape=[20, 20], dtype='int32')
-                out = paddle.tensor.math.addcmul(input, tensor1, tensor2, value=1.0)
-
-        self.assertRaises(TypeError, test_invalid_value_float)
-
-
-if __name__ == '__main__':
-    unittest.main()

python/paddle/tensor/__init__.py

@@ -156,7 +156,6 @@ from .math import log2  #DEFINE_ALIAS
 from .math import log10  #DEFINE_ALIAS
 from .math import log1p  #DEFINE_ALIAS
 from .math import erf  #DEFINE_ALIAS
-# from .math import addcmul  #DEFINE_ALIAS
 from .math import addmm  #DEFINE_ALIAS
 from .math import clip  #DEFINE_ALIAS
 from .math import trace  #DEFINE_ALIAS

python/paddle/tensor/math.py

@@ -117,7 +117,6 @@ __all__ = [
         'inverse',
         'log1p',
         'erf',
-        'addcmul',
         'addmm',
         'clip',
         'trace',
@@ -1454,50 +1453,6 @@ def log10(x, name=None):
     return out
 
 
-def addcmul(input, tensor1, tensor2, value=1.0, name=None):
-    """
-
-    Calculate the element-wise multiplication of tensor1 and tensor2,
-    then multiply the result by value, and add it to input. The shape of input,
-    tensor1, tensor2 should be broadcastable.
-    The equation is:
-    ..  math::
-
-        out = input + value * tensor1 * tensor2
-    Args:
-        input(Tensor): The input to be added. A Tensor with type float32, float64, int32, int64.
-        tensor1(Tensor): The tensor to be multiplied. A Tensor with type float32, float64, int32, int64.
-        tensor2(Tensor): The tensor to be multiplied. A Tensor with type float32, float64, int32, int64.
-        value(int|float): The multiplier for tensor1*tensor2. For float32 and float64 type input, value must be float, otherwise an integer.
-        name(str, Optional): For details, please refer to :ref:`api_guide_Name`.
-                        Generally, no setting is required. Default: None.
-    Returns:
-        out(Tensor): The output result. A Tensor with the same data type as input's.
-    Examples:
-        .. code-block:: python
-
-          import paddle
-          input = paddle.ones([2,2])
-          tensor1 = paddle.ones([2,2])
-          tensor2 = paddle.ones([2,2])
-          out = paddle.tensor.math.addcmul(input, tensor1, tensor2, value=0.5)
-          print(out)
-          # [[1.5 1.5]
-          # [1.5 1.5]]
-    """
-
-    check_variable_and_dtype(input, 'input', ['float32', 'float64', 'int32', 'int64'], 'addcmul')
-    check_variable_and_dtype(tensor1, 'tensor1', ['float32', 'float64', 'int32', 'int64'], 'addcmul')
-    check_variable_and_dtype(tensor2, 'tensor2', ['float32', 'float64', 'int32', 'int64'], 'addcmul')
-    if convert_dtype(input.dtype) in ['float32', 'float64']:
-        check_type(value, 'value', float, 'addcmul')
-    if convert_dtype(input.dtype) in ['int32', 'int64']:
-        check_type(value, 'value', int, 'addcmul')
-
-    out = layers.elementwise_add(input, layers.elementwise_mul(tensor1, tensor2) * value)
-    return out
-
-
 def clip(x, min=None, max=None, name=None):
     """
     This operator clip all elements in input into the range [ min, max ] and return

tools/static_mode_white_list.py

@@ -48,7 +48,6 @@ STATIC_MODE_TESTING_LIST = [
     'test_adaptive_max_pool1d',
     'test_add_position_encoding_op',
     'test_add_reader_dependency',
-    'test_addcmul',
     'test_addmm_op',
     'test_affine_grid_op',
     'test_allclose_layer',