diff --git a/tests/ut/python/parallel/test_fused_softmax.py b/tests/ut/python/parallel/test_fused_softmax.py
new file mode 100644
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+++ b/tests/ut/python/parallel/test_fused_softmax.py
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+
+# Copyright 2020 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)