text: #  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.
  
  from __future__ import print_function
  import unittest
  import numpy as np
  from op_test import OpTest
  import paddle.fluid.core as core
  from paddle.fluid.op import Operator
  
  
  class ElementwiseMulOp(OpTest):
      def init_kernel_type(self):
          self.use_mkldnn = False
  
      def setUp(self):
          self.op_type = "elementwise_mul"
          self.dtype = np.float32
          self.axis = -1
          self.init_dtype()
          self.init_input_output()
          self.init_kernel_type()
          self.init_axis()
  
          self.inputs = {
              'X': OpTest.np_dtype_to_fluid_dtype(self.x),
              'Y': OpTest.np_dtype_to_fluid_dtype(self.y)
          }
          self.outputs = {'Out': self.out}
          self.attrs = {'axis': self.axis, 'use_mkldnn': self.use_mkldnn}
  
      def test_check_output(self):
          self.check_output()
  
      def test_check_grad_normal(self):
          self.check_grad(['X', 'Y'], 'Out')
  
      def test_check_grad_ingore_x(self):
          self.check_grad(['Y'], 'Out', no_grad_set=set("X"))
  
      def test_check_grad_ingore_y(self):
          self.check_grad(['X'], 'Out', no_grad_set=set('Y'))
  
      def init_input_output(self):
          self.x = np.random.uniform(0.1, 1, [13, 17]).astype(self.dtype)
          self.y = np.random.uniform(0.1, 1, [13, 17]).astype(self.dtype)
          self.out = np.multiply(self.x, self.y)
  
      def init_dtype(self):
          pass
  
      def init_axis(self):
          pass
  
  
  class TestElementwiseMulOp_scalar(ElementwiseMulOp):
      def setUp(self):
          self.op_type = "elementwise_mul"
          self.inputs = {
              'X': np.random.rand(2, 3, 4).astype(np.float32),
              'Y': np.random.rand(1).astype(np.float32)
          }
          self.outputs = {'Out': self.inputs['X'] * self.inputs['Y']}
  
  
  class TestElementwiseMulOp_Vector(ElementwiseMulOp):
      def setUp(self):
          self.op_type = "elementwise_mul"
          self.inputs = {
              'X': np.random.random((32, )).astype("float64"),
              'Y': np.random.random((32, )).astype("float64")
          }
          self.outputs = {'Out': np.multiply(self.inputs['X'], self.inputs['Y'])}
  
  
  class TestElementwiseMulOp_broadcast_0(ElementwiseMulOp):
      def init_input_output(self):
          self.x = np.random.rand(2, 3, 4).astype(self.dtype)
          self.y = np.random.rand(2).astype(self.dtype)
          self.out = self.x * self.y.reshape(2, 1, 1)
  
      def init_axis(self):
          self.axis = 0
  
  
  class TestElementwiseMulOp_broadcast_1(ElementwiseMulOp):
      def setUp(self):
          self.op_type = "elementwise_mul"
          self.inputs = {
              'X': np.random.rand(2, 3, 4).astype(np.float64),
              'Y': np.random.rand(3).astype(np.float64)
          }
  
          self.attrs = {'axis': 1}
          self.outputs = {
              'Out': self.inputs['X'] * self.inputs['Y'].reshape(1, 3, 1)
          }
  
  
  class TestElementwiseMulOp_broadcast_2(ElementwiseMulOp):
      def setUp(self):
          self.op_type = "elementwise_mul"
          self.inputs = {
              'X': np.random.rand(2, 3, 4).astype(np.float64),
              'Y': np.random.rand(4).astype(np.float64)
          }
  
          self.outputs = {
              'Out': self.inputs['X'] * self.inputs['Y'].reshape(1, 1, 4)
          }
  
  
  class TestElementwiseMulOp_broadcast_3(ElementwiseMulOp):
      def setUp(self):
          self.op_type = "elementwise_mul"
          self.inputs = {
              'X': np.random.rand(2, 3, 4, 5).astype(np.float64),
              'Y': np.random.rand(3, 4).astype(np.float64)
          }
  
          self.attrs = {'axis': 1}
          self.outputs = {
              'Out': self.inputs['X'] * self.inputs['Y'].reshape(1, 3, 4, 1)
          }
  
  
  if __name__ == '__main__':
      unittest.main()
  