support not in and add check for grad_with_sens with no sense provide.

mindspore/_extends/parse/resources.py

@@ -107,7 +107,7 @@ convert_object_map = {
     T.is_:          F.is_,
     T.is_not:       F.is_not,
     T.contains:     multitype_ops.in_,
-    T.not_contains: F.not_in_dict,
+    T.not_contains: multitype_ops.not_in_,
 
     # system function
     T.len:          M.ms_len,

mindspore/ccsrc/frontend/operator/composite/composite.cc

@@ -641,7 +641,7 @@ void GradOperation::doGetGrad(const FuncGraphPtr &func_graph, AnfNodePtr out, An
 
 // Generate the graph.
 FuncGraphPtr GradOperation::GenerateFuncGraph(const AbstractBasePtrList &args_spec_list) {
-  if (args_spec_list.size() < 1) {
+  if (args_spec_list.empty()) {
     MS_LOG(EXCEPTION) << "GenerateGraph requires at least 1 parameters, while the input size is "
                       << args_spec_list.size() << ".";
   }

mindspore/ccsrc/pipeline/jit/static_analysis/prim.cc

@@ -138,7 +138,7 @@ EvalResultPtr UnpackGraphEvaluator::Run(AnalysisEnginePtr engine, const ConfigPt
   auto unpack_graph = prim_->cast<prim::UnpackGraphPrimitivePtr>();
   auto out_node = out_conf->node()->cast<CNodePtr>();
   const auto &out_node_inputs = out_node->inputs();
-  if (out_node->inputs().size() == 0 || (out_node_inputs.size() - 1) != args_conf_list.size()) {
+  if (out_node->inputs().empty() || (out_node_inputs.size() - 1) != args_conf_list.size()) {
     MS_LOG(EXCEPTION) << "UnpackGraphPrimitive"
                       << " args size should equal to inputs size minus 1, but args size " << args_conf_list.size()
                       << ", inputs size " << out_node_inputs.size();
@@ -149,7 +149,7 @@ EvalResultPtr UnpackGraphEvaluator::Run(AnalysisEnginePtr engine, const ConfigPt
                        [](const ConfigPtr &ref) -> AbstractBasePtr { return ref->GetEvaluatedValue()->abstract(); });
   // get the forward graph
   MS_EXCEPTION_IF_NULL(args_spec_list[0]);
-  AbstractFunctionPtr fn = args_spec_list[0]->cast<AbstractFunctionPtr>();
+  auto fn = args_spec_list[0]->cast<AbstractFunctionPtr>();
   if (fn == nullptr) {
     MS_LOG(EXCEPTION) << "UnpackGraphPrimitive arg0 must be AbstractFunction, but " << args_spec_list[0]->ToString();
   }
@@ -161,6 +161,9 @@ EvalResultPtr UnpackGraphEvaluator::Run(AnalysisEnginePtr engine, const ConfigPt
     GetUnpackGraphSpecArgsList(args_spec_list, unpack_graph->need_unpack_args());
 
   AbstractBasePtrList graph_specialize_args_without_sens;
+  if (unpack_graph->with_sens_in_args() && graph_specialize_args.empty()) {
+    MS_EXCEPTION(ValueError) << "Grad with sens, but the sens is not provided.";
+  }
   (void)std::transform(graph_specialize_args.begin(),
                        graph_specialize_args.end() - (unpack_graph->with_sens_in_args() ? 1 : 0),
                        std::back_inserter(graph_specialize_args_without_sens), [](AbstractBasePtr abs) { return abs; });
@@ -177,8 +180,8 @@ EvalResultPtr UnpackGraphEvaluator::Run(AnalysisEnginePtr engine, const ConfigPt
   return engine->ForwardConfig(out_conf, fn_conf);
 }
 
-AnfNodePtr MixedPrecisionCastHelper(AnfNodePtr source_node, AbstractBasePtr node_type, AnfNodePtr target_type,
-                                    FuncGraphPtr func_graph) {
+AnfNodePtr MixedPrecisionCastHelper(const AnfNodePtr &source_node, const AbstractBasePtr &node_type,
+                                    const AnfNodePtr &target_type, const FuncGraphPtr &func_graph) {
   AnfNodePtr target_node = source_node;
   if (node_type->isa<AbstractTensor>()) {
     auto x = node_type->cast<AbstractTensorPtr>();

mindspore/nn/layer/normalization.py

@@ -27,12 +27,12 @@ from mindspore._checkparam import check_int_positive
 from mindspore.ops import _selected_ops
 from ..cell import Cell
 
-
-
 __all__ = ['BatchNorm1d', 'BatchNorm2d', 'LayerNorm', 'GroupNorm', 'GlobalBatchNorm']
 
+
 class _BatchNorm(Cell):
     """Batch Normalization base class."""
+
     @cell_attr_register
     def __init__(self,
                  num_features,
@@ -132,7 +132,6 @@ class _BatchNorm(Cell):
         group_list = [list(i) for i in world_rank_list]
         return group_list
 
-
     def _global_sync(self, x, axes, re_shape):
         """calculate global batch normalization output"""
         x_mean = self.reduce_mean(x, axes)

mindspore/ops/composite/multitype_ops/__init__.py

@@ -38,6 +38,7 @@ from .logical_or_impl import logical_or
 from .logic_not_impl import logical_not
 from .uadd_impl import uadd
 from .in_impl import in_
+from .not_in_impl import not_in_
 __all__ = [
     'add',
     'sub',
@@ -61,5 +62,6 @@ __all__ = [
     'logical_and',
     'logical_or',
     'logical_not',
-    'in_'
+    'in_',
+    'not_in_'
 ]

mindspore/ops/composite/multitype_ops/add_impl.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ============================================================================
 
-"""add_impl"""
+"""Implementation for internal polymorphism `add` operations."""
 
 from ...composite import base
 from ... import functional as F

mindspore/ops/composite/multitype_ops/div_impl.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ============================================================================
 
-"""div_impl"""
+"""Implementation for internal polymorphism `div` operations."""
 
 from ...composite import base
 from ... import functional as F

mindspore/ops/composite/multitype_ops/equal_impl.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ============================================================================
 
-"""equal_impl"""
+"""Implementation for internal polymorphism `equal` operations."""
 from . import _constexpr_utils as const_utils
 from ...composite import base
 from ... import functional as F

mindspore/ops/composite/multitype_ops/getitem_impl.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ============================================================================
 
-"""Implementation for getitem."""
+"""Implementation for internal polymorphism `getitem` operations."""
 from . import _compile_utils as compile_utils
 from .. import base
 from ... import functional as F

mindspore/ops/composite/multitype_ops/greater_equal_impl.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ============================================================================
 
-"""greater_equal_impl"""
+"""Implementation for internal polymorphism `greater_equal` operations."""
 from mindspore.ops.composite import base
 from mindspore.ops import functional as F
 

mindspore/ops/composite/multitype_ops/greater_impl.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ============================================================================
 
-"""equal_impl"""
+"""Implementation for internal polymorphism `greater` operations."""
 from mindspore.ops.composite import base
 from mindspore.ops import functional as F
 

mindspore/ops/composite/multitype_ops/in_impl.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ============================================================================
 
-"""in_impl"""
+"""Implementation for internal polymorphism `in` operations."""
 
 from . import _constexpr_utils as const_utils
 from ... import functional as F
@@ -21,7 +21,7 @@ from ...composite import base
 
 in_ = base.MultitypeFuncGraph("in", True)
 """
-in_ is a metafuncgraph object which will determine if a in b
+"in_" is a multi type func graph  object which will determine if a in b
 using ".register" decorator
 """
 

mindspore/ops/composite/multitype_ops/less_equal_impl.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ============================================================================
 
-"""less_equal_impl"""
+"""Implementation for internal polymorphism `less_equal` operations."""
 from mindspore.ops.composite import base
 from mindspore.ops import functional as F
 

mindspore/ops/composite/multitype_ops/less_impl.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ============================================================================
 
-"""equal_impl"""
+"""Implementation for internal polymorphism `less` operations."""
 from mindspore.ops.composite import base
 from mindspore.ops import functional as F
 

mindspore/ops/composite/multitype_ops/logic_not_impl.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ============================================================================
 
-"""logical_not_impl"""
+"""Implementation for internal polymorphism `logical not` operations."""
 from mindspore.ops.composite import base
 from mindspore.ops import functional as F
 

mindspore/ops/composite/multitype_ops/logical_and_impl.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ============================================================================
 
-"""logical_and_impl"""
+"""Implementation for internal polymorphism `logical and` operations."""
 from mindspore.ops.composite import base
 from mindspore.ops import functional as F
 

mindspore/ops/composite/multitype_ops/logical_or_impl.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ============================================================================
 
-"""logical_or_impl"""
+"""Implementation for internal polymorphism `logical or` operations."""
 from mindspore.ops.composite import base
 from mindspore.ops import functional as F
 

mindspore/ops/composite/multitype_ops/not_equal_impl.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ============================================================================
 
-"""not_equal_impl"""
+"""Implementation for internal polymorphism `not equal` operations."""
 
 from ...composite import base
 from ... import functional as F

mindspore/ops/composite/multitype_ops/not_in_impl.py

@@ -0,0 +1,101 @@
+# 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.
+# ============================================================================
+
+"""Implementation for internal polymorphism `not in` operations."""
+
+from . import _constexpr_utils as const_utils
+from ... import functional as F
+from ...composite import base
+
+not_in_ = base.MultitypeFuncGraph("not_in", True)
+"""
+"not_in_" is a multi type func graph object which will determine if a not in b.
+using ".register" decorator
+"""
+
+
+@not_in_.register("Number", "Tuple")
+def _number_not_in_tuple(x, y):
+    """
+    Determine if a number not in tuple.
+
+    Args:
+       x (Number): x
+       y (tuple): y
+
+    Returns:
+       bool, if x not in y return true, x in y return false.
+   """
+    return not const_utils.scalar_in_sequence(x, y)
+
+
+@not_in_.register("Number", "List")
+def _number_not_in_list(x, y):
+    """
+    Determine if a number not in list.
+
+    Args:
+       x (Number): x
+       y (list): y
+
+    Returns:
+       bool, if x not in y return true, x in y return false.
+   """
+    return not const_utils.scalar_in_sequence(x, y)
+
+
+@not_in_.register("String", "Tuple")
+def _string_not_in_tuple(x, y):
+    """
+    Determine if a str not in a tuple.
+
+    Args:
+       x (str): x
+       y (tuple): y
+
+    Returns:
+       bool, if x not in y return true, x in y return false.
+   """
+    return not const_utils.scalar_in_sequence(x, y)
+
+
+@not_in_.register("String", "List")
+def _string_not_in_list(x, y):
+    """
+    Determine if a str not in a list.
+
+    Args:
+       x (str): x
+       y (list): y
+
+    Returns:
+       bool, if x not in y return true, x in y return false.
+   """
+    return not const_utils.scalar_in_sequence(x, y)
+
+
+@not_in_.register("String", "Dictionary")
+def _str_not_in_dict(x, y):
+    """
+    Determine if a str not in dict.
+
+    Args:
+       x: str
+       y: dict
+
+    Returns:
+       bool, if x not in y return true, x in y return false.
+   """
+    return F.not_in_dict(x, y)

mindspore/ops/composite/multitype_ops/setitem_impl.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ============================================================================
 
-"""Implementation for setitem."""
+"""Implementation for internal polymorphism `setitem` operations."""
 
 from . import _compile_utils as compile_utils
 from ... import functional as F

mindspore/ops/composite/multitype_ops/uadd_impl.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ============================================================================
 
-"""uadd_impl"""
+"""Implementation for internal polymorphism `uadd` operations."""
 from mindspore.ops.composite import base
 
 # uadd is a metagraph object which will return operation result regarding input

tests/ut/python/pipeline/infer/test_not_in.py

@@ -0,0 +1,56 @@
+# 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 not in"""
+import numpy as np
+
+import mindspore.nn as nn
+from mindspore import context, Tensor
+
+context.set_context(mode=context.GRAPH_MODE)
+
+
+def test_number_not_in_tuple():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+            self.tuple_ = (2, 3, 4)
+            self.list_ = [2, 3, 4]
+            self.dict_ = {"a": Tensor(np.ones([1, 2, 3], np.int32)),
+                          "b": Tensor(np.ones([1, 2, 3], np.int32)),
+                          "c": Tensor(np.ones([1, 2, 3], np.int32))}
+            self.number_in = 3
+            self.number_not_in = 5
+            self.str_in = "a"
+            self.str_not_in = "e"
+
+        def construct(self):
+            ret = 0
+            if self.number_in not in self.tuple_:
+                ret += 1
+            if self.number_not_in not in self.tuple_:
+                ret += 1
+            if self.number_in not in self.list_:
+                ret += 3
+            if self.number_not_in not in self.list_:
+                ret += 3
+            if self.str_in not in self.dict_:
+                ret += 5
+            if self.str_not_in not in self.dict_:
+                ret += 5
+            return ret
+
+    net = Net()
+    output = net()
+    assert output == 9