From cb391ba234e411234ea33e85a60df546efff8e09 Mon Sep 17 00:00:00 2001
From: yanzhenxiang2020 <yanzhenxiang@huawei.com>
Date: Fri, 27 Nov 2020 18:45:59 +0800
Subject: [PATCH] fix identity grad

---
 mindspore/ops/_grad/grad_array_ops.py | 10 ++++++++++
 mindspore/ops/operations/array_ops.py | 14 ++++++++------
 2 files changed, 18 insertions(+), 6 deletions(-)

diff --git a/mindspore/ops/_grad/grad_array_ops.py b/mindspore/ops/_grad/grad_array_ops.py
index 7788613452..4ef13eec44 100644
--- a/mindspore/ops/_grad/grad_array_ops.py
+++ b/mindspore/ops/_grad/grad_array_ops.py
@@ -456,6 +456,16 @@ def get_bprop_sparse_gather_v2(self):
     return bprop
 
 
+@bprop_getters.register(P.Identity)
+def get_bprop_identity(self):
+    """Generate bprop for Identity"""
+
+    def bprop(x, out, dout):
+        return (dout,)
+
+    return bprop
+
+
 @bprop_getters.register(inner.Range)
 def get_bprop_range(self):
     """Generate bprop for Range"""
diff --git a/mindspore/ops/operations/array_ops.py b/mindspore/ops/operations/array_ops.py
index a51729fa0e..86cae4b783 100644
--- a/mindspore/ops/operations/array_ops.py
+++ b/mindspore/ops/operations/array_ops.py
@@ -4104,14 +4104,14 @@ class Meshgrid(PrimitiveWithInfer):
         Tensors, A Tuple of N N-D Tensor objects.
 
     Examples:
-        >>> x = np.array([1, 2, 3, 4]).astype(np.int32)
-        >>> y = np.array([5, 6, 7]).astype(np.int32)
-        >>> z = np.array([8, 9, 0, 1, 2]).astype(np.int32)
+        >>> x = Tensor(np.array([1, 2, 3, 4]).astype(np.int32))
+        >>> y = Tensor(np.array([5, 6, 7]).astype(np.int32))
+        >>> z = Tensor(np.array([8, 9, 0, 1, 2]).astype(np.int32))
         >>> inputs = (x, y, z)
         >>> meshgrid = ops.Meshgrid(indexing="xy")
         >>> output = meshgrid(inputs)
         >>> print(output)
-        (Tensor(shape=[3, 4, 6], dtype=UInt32, value=
+        (Tensor(shape=[3, 4, 6], dtype=Int32, value=
          [[[1, 1, 1, 1, 1],
           [2, 2, 2, 2, 2],
           [3, 3, 3, 3, 3],
@@ -4124,7 +4124,7 @@ class Meshgrid(PrimitiveWithInfer):
           [2, 2, 2, 2, 2],
           [3, 3, 3, 3, 3],
           [4, 4, 4, 4, 4]]]),
-         Tensor(shape=[3, 4, 6], dtype=UInt32, value=
+         Tensor(shape=[3, 4, 6], dtype=Int32, value=
          [[[5, 5, 5, 5, 5],
           [5, 5, 5, 5, 5],
           [5, 5, 5, 5, 5],
@@ -4137,7 +4137,7 @@ class Meshgrid(PrimitiveWithInfer):
           [7, 7, 7, 7, 7],
           [7, 7, 7, 7, 7],
           [7, 7, 7, 7, 7]]]),
-         Tensor(shape=[3, 4, 6], dtype=UInt32, value=
+         Tensor(shape=[3, 4, 6], dtype=Int32, value=
          [[[8, 9, 0, 1, 2],
           [8, 9, 0, 1, 2],
           [8, 9, 0, 1, 2],
@@ -4611,6 +4611,8 @@ class Identity(PrimitiveWithInfer):
         """Initialize identity"""
 
     def __infer__(self, x):
+        validator.check_subclass("x", x['dtype'], mstype.tensor, self.name)
+        validator.check_tensor_dtype_valid('x', x['dtype'], mstype.number_type + (mstype.bool_,), self.name)
         out = {'shape': x['shape'],
                'dtype': x['dtype'],
                'value': None}