diff --git a/mindspore/_extends/parse/standard_method.py b/mindspore/_extends/parse/standard_method.py
index 27c4112d5f..7f80f65305 100644
--- a/mindspore/_extends/parse/standard_method.py
+++ b/mindspore/_extends/parse/standard_method.py
@@ -28,6 +28,7 @@ __all__ = ['MultitypeFuncGraph', 'env_get', 'hyper_add', 'zeros_like', 'ones_lik
 
 trans = P.Transpose()
 shape_ = P.Shape()
+reshape_ = P.Reshape()
 dtype_ = P.DType()
 
 def all_(x, axis=(), keep_dims=False):
@@ -162,6 +163,12 @@ def expand_tensor_as(x, y):
     return broadcast_to(x)
 
 
+def view(x, *shape):
+    """Reshape tensor, if shape is -1, reshape tensor into one dimension"""
+    shape = check_view_shape(shape)
+    return reshape_(x, shape)
+
+
 def isinstance_(x, base_type):
     """Determine whether x is an instance of base_type."""
     x_type = F.typeof(x)
@@ -232,6 +239,18 @@ def const_tensor_to_bool(x):
     raise ValueError("The truth value of an array with several elements is ambiguous.")
 
 
+@constexpr
+def check_view_shape(x):
+    """Check view function input shape"""
+    if not x:
+        raise ValueError("The shape variable should not be empty")
+    if isinstance(x[0], tuple):
+        if len(x) != 1:
+            raise ValueError(f"Only one tuple is needed, but got {x}")
+        x = x[0]
+    return x
+
+
 def tensor_bool(x):
     """tensor as conditon, if is constant, return immediate bool value"""
     is_cond = check_is_tensor_bool_cond(F.shape(x))
diff --git a/mindspore/ccsrc/pipeline/jit/resource.cc b/mindspore/ccsrc/pipeline/jit/resource.cc
index e970c0c2e9..03941f86ff 100644
--- a/mindspore/ccsrc/pipeline/jit/resource.cc
+++ b/mindspore/ccsrc/pipeline/jit/resource.cc
@@ -167,6 +167,7 @@ BuiltInTypeMap &GetMethodMap() {
                                          {"__le__", std::string("le")},                   // C.le
                                          {"__ge__", std::string("ge")},                   // C.ge
                                          {"expand_as", std::string("expand_tensor_as")},  // C.expand_as
+                                         {"view", std::string("view")},                   // C.view
                                          {"__matmul__", prim::kPrimDot},                  // P.dot,
                                          {"__len__", prim::kPrimArrayLen},                // P.array_len,
                                          {"__getitem__", prim::kPrimArrayGetItem},        // P.array_getitem,
diff --git a/tests/ut/python/pipeline/parse/test_view.py b/tests/ut/python/pipeline/parse/test_view.py
new file mode 100644
index 0000000000..13e085d93c
--- /dev/null
+++ b/tests/ut/python/pipeline/parse/test_view.py
@@ -0,0 +1,127 @@
+# 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.
+# ============================================================================
+""" test view"""
+import pytest
+
+import mindspore.nn as nn
+from mindspore import Tensor
+from mindspore import context
+
+context.set_context(mode=context.GRAPH_MODE)
+
+
+def test_view():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+            self.value = Tensor([[1, 2, 3], [4, 5, 6]])
+
+        def construct(self):
+            return self.value.view(-1)
+
+    net = Net()
+    net()
+
+
+def test_view_1():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+            self.value = Tensor([[1, 2, 3], [4, 5, 6]])
+
+        def construct(self):
+            return self.value.view((3, 2))
+
+    net = Net()
+    net()
+
+
+def test_view_2():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+            self.value = Tensor([[1, 2, 3], [4, 5, 6]])
+
+        def construct(self):
+            return self.value.view(3, 2)
+
+    net = Net()
+    net()
+
+
+def test_view_parameter():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def construct(self, x):
+            return x.view(-1)
+
+    net = Net()
+    net(Tensor([[1, 2, 3], [4, 5, 6]]))
+
+
+def test_view_parameter_1():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def construct(self, x):
+            return x.view((3, 2))
+
+    net = Net()
+    net(Tensor([[1, 2, 3], [4, 5, 6]]))
+
+
+def test_view_parameter_2():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def construct(self, x):
+            return x.view(3, 2)
+
+    net = Net()
+    net(Tensor([[1, 2, 3], [4, 5, 6]]))
+
+
+def test_view_shape_error():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+            self.value = Tensor([[1, 2, 3], [4, 5, 6]])
+
+        def construct(self):
+            return self.value.view()
+
+    net = Net()
+    with pytest.raises(ValueError) as ex:
+        net()
+    assert "The shape variable should not be empty" in str(ex.value)
+
+
+def test_view_shape_error_1():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+            self.value = Tensor([[1, 2, 3], [4, 5, 6]])
+
+        def construct(self):
+            return self.value.view((2, 3), (4, 5))
+
+    net = Net()
+    with pytest.raises(ValueError) as ex:
+        net()
+    assert "Only one tuple is needed" in str(ex.value)