text: 
  # Copyright 2022 Huawei Technologies Co., Ltd
  #
  # 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 numpy as np
  import pytest
  
  import mindspore as ms
  from mindspore import context, Tensor, Parameter
  from mindspore.common.api import _cell_graph_executor
  from mindspore.nn import Cell, TrainOneStepCell, Momentum
  from mindspore.ops import operations as P
  
  
  class Net(Cell):
      def __init__(self, mul_weight, strategy1=None, strategy2=None, strategy3=None):
          super().__init__()
          self.begin_norm_axis = 2
          self.begin_params_axis = 1
          self.mul = P.Mul().shard(strategy1)
          self.softmax = P.Softmax().shard(strategy2)
          self.mul2 = P.Mul().shard(strategy3)
          self.mul_weight = Parameter(mul_weight, "w1")
          self.normalized_shape = [64, 32, 16]
  
      def construct(self, x, b):
          out = self.mul(x, self.mul_weight)
          out = self.softmax(out)
          out = self.mul2(out, b)
          return out
  
  
  _x = Tensor(np.ones([16, 64, 32, 16]), dtype=ms.float32)
  _w = Tensor(np.ones([16, 64, 32, 16]), dtype=ms.float32)
  _b = Tensor(np.ones([16, 64, 32, 16]), dtype=ms.float32)
  
  
  def compile_net(net):
      optimizer = Momentum(net.trainable_params(),
                           learning_rate=0.1, momentum=0.9)
      train_net = TrainOneStepCell(net, optimizer)
      train_net.set_auto_parallel()
      train_net.set_train()
      _cell_graph_executor.compile(train_net, _x, _b)
      context.reset_auto_parallel_context()
  
  
  def test_softmax_data_parallel():
      """
      Feature: distribute operator softmax in auto parallel.
      Description: data parallel softmax net in auto parallel.
      Expectation: compile done without error.
      """
      context.set_auto_parallel_context(
          parallel_mode="semi_auto_parallel", device_num=16, global_rank=0)
      strategy1 = ((16, 1, 1, 1), (16, 1, 1, 1))
      strategy2 = ((16, 1, 1, 1),)
      strategy3 = ((16, 1, 1, 1), (16, 1, 1, 1))
      net = Net(_w, strategy1, strategy2, strategy3)
      compile_net(net)
  
  
  def test_softmax_data_parallel_with_half_repeat():
      """
      Feature: distribute operator softmax in auto parallel.
      Description: data parallel and half repeat softmax net in auto parallel.
      Expectation: compile done without error.
      """
      context.set_auto_parallel_context(
          parallel_mode="semi_auto_parallel", device_num=16, global_rank=0)
      strategy1 = ((16, 1, 1, 1), (16, 1, 1, 1))
      strategy2 = ((8, 1, 1, 1),)
      strategy3 = ((16, 1, 1, 1), (16, 1, 1, 1))
      net = Net(_w, strategy1, strategy2, strategy3)
      compile_net(net)
  
  
  def test_softmax_model_parallel():
      """
      Feature: distribute operator softmax in auto parallel.
      Description: model parallel softmax net in auto parallel.
      Expectation: compile done without error.
      """
      context.set_auto_parallel_context(
          parallel_mode="semi_auto_parallel", device_num=16, global_rank=0)
      strategy1 = ((1, 16, 1, 1), (1, 16, 1, 1))
      strategy2 = ((16, 1, 1, 1),)
      strategy3 = ((1, 16, 1, 1), (1, 16, 1, 1))
      net = Net(_w, strategy1, strategy2, strategy3)
      compile_net(net)
  
  
  def test_softmax_model_parallel_with_repeat():
      """
      Feature: distribute operator softmax in auto parallel.
      Description: model parallel with repeate softmax net in auto parallel.
      Expectation: compile done without error.
      """
      context.set_auto_parallel_context(
          parallel_mode="semi_auto_parallel", device_num=16, global_rank=0)
      strategy1 = ((1, 16, 1, 1), (1, 16, 1, 1))
      strategy2 = ((1, 1, 1, 1),)
      strategy3 = ((1, 16, 1, 1), (1, 16, 1, 1))
      net = Net(_w, strategy1, strategy2, strategy3)
      compile_net(net)
  
  
  def test_softmax_model_parallel_with_half_repeat():
      """
      Feature: distribute operator softmax in auto parallel.
      Description: model parallel with half repeate softmax net in auto parallel.
      Expectation: compile done without error.
      """
      context.set_auto_parallel_context(
          parallel_mode="semi_auto_parallel", device_num=16, global_rank=0)
      strategy1 = ((1, 16, 1, 1), (1, 16, 1, 1))
      strategy2 = ((8, 1, 1, 1),)
      strategy3 = ((1, 16, 1, 1), (1, 16, 1, 1))
      net = Net(_w, strategy1, strategy2, strategy3)
      compile_net(net)
  
  
  def test_softmax_hybrid_parallel():
      """
      Feature: distribute operator softmax in auto parallel.
      Description: hybrid parallel softmax net in auto parallel.
      Expectation: compile done without error.
      """
      context.set_auto_parallel_context(
          parallel_mode="semi_auto_parallel", device_num=16, global_rank=0)
      strategy1 = ((2, 8, 1, 1), (2, 8, 1, 1))
      strategy2 = ((16, 1, 1, 1),)
      strategy3 = ((2, 8, 1, 1), (2, 8, 1, 1))
      net = Net(_w, strategy1, strategy2, strategy3)
      compile_net(net)
  
  
  def test_softmax_hybrid_with_repeat_parallel():
      """
      Feature: distribute operator softmax in auto parallel.
      Description: hybrid parallel with repat softmax net in auto parallel.
      Expectation: compile done without error.
      """
      context.set_auto_parallel_context(
          parallel_mode="semi_auto_parallel", device_num=16, global_rank=0)
      strategy1 = ((2, 8, 1, 1), (2, 8, 1, 1))
      strategy2 = ((1, 1, 1, 1),)
      strategy3 = ((2, 8, 1, 1), (2, 8, 1, 1))
      net = Net(_w, strategy1, strategy2, strategy3)
      compile_net(net)
  
  
  def test_softmax_hybrid_with_half_repeat_parallel():
      """
      Feature: distribute operator softmax in auto parallel.
      Description: hybrid parallel with half repeate softmax net in auto parallel.
      Expectation: compile done without error.
      """
      context.set_auto_parallel_context(
          parallel_mode="semi_auto_parallel", device_num=16, global_rank=0)
      strategy1 = ((2, 8, 1, 1), (2, 8, 1, 1))
      strategy2 = ((8, 1, 1, 1),)
      strategy3 = ((2, 8, 1, 1), (2, 8, 1, 1))
      net = Net(_w, strategy1, strategy2, strategy3)
      compile_net(net)
  
  
  def test_softmax_hybrid_parallel_with_quater_repeate():
      """
      Feature: distribute operator softmax in auto parallel.
      Description: hybrid parallel softmax net in auto parallel.
      Expectation: compile done without error.
      """
      context.set_auto_parallel_context(
          parallel_mode="semi_auto_parallel", device_num=16, global_rank=0)
      strategy1 = ((2, 8, 1, 1), (2, 8, 1, 1))
      strategy2 = ((4, 1, 1, 1),)
      strategy3 = ((2, 8, 1, 1), (2, 8, 1, 1))
      net = Net(_w, strategy1, strategy2, strategy3)
      compile_net(net)
  
  
  def test_softmax_auto_parallel():
      """
      Feature: distribute operator softmax in auto parallel.
      Description: softmax net in auto parallel.
      Expectation: compile done without error.
      """
      context.set_auto_parallel_context(
          parallel_mode="auto_parallel", device_num=16, global_rank=0)
      net = Net(_w)
      compile_net(net)
  
  
  def test_softmax_repeat_calc():
      """
      Feature: distribute operator softmax in auto parallel.
      Description: repeated calculation softmax net in auto parallel.
      Expectation: compile done without error.
      """
      context.set_auto_parallel_context(
          parallel_mode="semi_auto_parallel", device_num=16, global_rank=0)
      strategy1 = ((2, 2, 4, 1), (2, 2, 4, 1))
      strategy2 = ((1, 1, 1, 1),)
      strategy3 = ((2, 2, 4, 1), (2, 2, 4, 1))
      net = Net(_w, strategy1, strategy2, strategy3)
      compile_net(net)
  
  
  def test_softmax_wrong_strategy():
      """
      Feature: distribute operator softmax in auto parallel.
      Description: wrong strategy net in auto parallel.
      Expectation: compile done without error.
      """
      context.set_auto_parallel_context(
          parallel_mode="semi_auto_parallel", device_num=16, global_rank=0)
      strategy1 = ((2, 2, 4, 1), (2, 2, 4, 1))
      strategy2 = ((1, 2, 1, 2),)
      strategy3 = ((2, 2, 4, 1), (2, 2, 4, 1))
      net = Net(_w, strategy1, strategy2, strategy3)
      with pytest.raises(RuntimeError):
          compile_net(net)
  