Fix a bug after old side-effect flag removed

The problem:
After we removed old 'side_effect' flag from Push primtive,
CSE will incorrectly merge some Push nodes.

To fix this:
We change "_random_effect" flag to a more proper name "side_effect_hidden",
and add this flag to Push primitive to prevent it be merged by CSE.

mindspore/ccsrc/backend/common/pass/common_subexpression_elimination.cc

@@ -111,7 +111,7 @@ bool BackendCSE::CheckCNode(const CNodePtr &main, const CNodePtr &node) const {
   if (!context_ptr->get_param<bool>(MS_CTX_ENABLE_LOOP_SINK) && CheckIgnoreCase(main)) {
     return false;
   }
-  if (HasRandomEffect(main) || HasRandomEffect(node)) {
+  if (HasHiddenSideEffect(main) || HasHiddenSideEffect(node)) {
     return false;
   }
   if (!CheckEqualKernelBuildInfo(main, node)) {

mindspore/ccsrc/frontend/optimizer/cse.cc

@@ -133,13 +133,12 @@ bool CSE::BuildOrderGroupAndDoReplace(const FuncGraphManagerPtr manager) const {
   return changed;
 }
 
-bool CSE::HasRandomEffect(const AnfNodePtr &node) {
+bool CSE::HasHiddenSideEffect(const AnfNodePtr &node) {
   auto prim = GetCNodePrimitive(node);
   if (prim == nullptr) {
     return false;
   }
-  auto attr = prim->GetAttr(GRAPH_FLAG_RANDOM_EFFECT);
-  return (attr != nullptr) && attr->isa<BoolImm>() && GetValue<bool>(attr);
+  return prim->HasAttr(GRAPH_FLAG_SIDE_EFFECT_HIDDEN);
 }
 
 bool CSE::CheckReplace(const AnfNodePtr &main, const AnfNodePtr &node) const {
@@ -181,7 +180,7 @@ bool CSE::CheckReplace(const AnfNodePtr &main, const AnfNodePtr &node) const {
       return false;
     }
     // We don't merge primitive cnodes with random effect.
-    return !HasRandomEffect(c_main);
+    return !HasHiddenSideEffect(c_main);
   }
   // a parameter node.
   return false;

mindspore/ccsrc/frontend/optimizer/cse.h

@@ -38,7 +38,7 @@ class CSE {
 
   virtual bool Cse(const FuncGraphPtr root, const FuncGraphManagerPtr manager) const;
 
-  static bool HasRandomEffect(const AnfNodePtr &node);
+  static bool HasHiddenSideEffect(const AnfNodePtr &node);
 
  protected:
   bool BuildOrderGroupAndDoReplaceForOneGraph(const FuncGraphPtr &fg, const FuncGraphManagerPtr &manager) const;

mindspore/ccsrc/pipeline/pynative/pynative_execute.cc

@@ -357,7 +357,7 @@ void GetSingleOpGraphInfo(const OpExecInfoPtr &op_exec_info, const std::vector<t
   bool has_const_input = false;
   const auto &op_prim = op_exec_info->py_primitive;
   MS_EXCEPTION_IF_NULL(op_prim);
-  bool is_random_effect_op = op_prim->HasAttr(GRAPH_FLAG_RANDOM_EFFECT);
+  bool has_hidden_side_effect = op_prim->HasAttr(GRAPH_FLAG_SIDE_EFFECT_HIDDEN);
   for (size_t index = 0; index < input_tensors.size(); ++index) {
     MS_EXCEPTION_IF_NULL(input_tensors[index]);
     buf << input_tensors[index]->shape();
@@ -365,7 +365,7 @@ void GetSingleOpGraphInfo(const OpExecInfoPtr &op_exec_info, const std::vector<t
     buf << input_tensors[index]->padding_type();
     // In the case of the same shape, but dtype and format are inconsistent
     auto tensor_addr = input_tensors[index]->device_address();
-    if (tensor_addr != nullptr && !is_random_effect_op) {
+    if (tensor_addr != nullptr && !has_hidden_side_effect) {
       auto p_address = std::dynamic_pointer_cast<device::DeviceAddress>(tensor_addr);
       MS_EXCEPTION_IF_NULL(p_address);
       buf << p_address->type_id();
@@ -407,8 +407,8 @@ void GetSingleOpGraphInfo(const OpExecInfoPtr &op_exec_info, const std::vector<t
     buf << build_type->type_id();
   }
 
-  // Random effect operator
-  if (is_random_effect_op) {
+  // Operator with hidden side effect.
+  if (has_hidden_side_effect) {
     buf << "_" << std::to_string(op_prim->id());
   }
 

mindspore/core/utils/flags.h

@@ -22,9 +22,9 @@ namespace mindspore {
 inline const char GRAPH_FLAG_MIX_PRECISION_FP16[] = "fp16";
 inline const char GRAPH_FLAG_MIX_PRECISION_FP32[] = "fp32";
 inline const char GRAPH_FLAG_CACHE_ENABLE[] = "cache_enable";
-inline const char GRAPH_FLAG_RANDOM_EFFECT[] = "_random_effect";
 inline const char GRAPH_FLAG_SIDE_EFFECT_IO[] = "side_effect_io";
 inline const char GRAPH_FLAG_SIDE_EFFECT_MEM[] = "side_effect_mem";
+inline const char GRAPH_FLAG_SIDE_EFFECT_HIDDEN[] = "side_effect_hidden";
 inline const char GRAPH_FLAG_SIDE_EFFECT_EXCEPTION[] = "side_effect_exception";
 inline const char GRAPH_FLAG_SIDE_EFFECT_PROPAGATE[] = "side_effect_propagate";
 inline const char GRAPH_FLAG_SIDE_EFFECT_BACKPROP[] = "side_effect_backprop";

mindspore/python/mindspore/ops/operations/nn_ops.py

@@ -3178,7 +3178,7 @@ class DropoutGenMask(Primitive):
         self.init_prim_io_names(inputs=['shape', 'keep_prob'], outputs=['output'])
         validator.check_value_type("Seed0", Seed0, [int], self.name)
         validator.check_value_type("Seed1", Seed1, [int], self.name)
-        self.add_prim_attr("_random_effect", True)
+        self.add_prim_attr("side_effect_hidden", True)
 
 
 class DropoutDoMask(Primitive):

mindspore/python/mindspore/ops/operations/other_ops.py

@@ -678,6 +678,7 @@ class Push(PrimitiveWithInfer):
         """Initialize Push"""
         self.add_prim_attr("primitive_target", "CPU")
         self.init_prim_io_names(inputs=['optim_inputs', 'optim_input_shapes'], outputs=['key'])
+        self.add_prim_attr("side_effect_hidden", True)
 
     def infer_shape(self, inputs, shapes):
         return [1]

mindspore/python/mindspore/ops/operations/random_ops.py

@@ -1,4 +1,4 @@
-# Copyright 2020 Huawei Technologies Co., Ltd
+# Copyright 2020-2022 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.
@@ -62,7 +62,7 @@ class StandardNormal(PrimitiveWithInfer):
     def __init__(self, seed=0, seed2=0):
         """Initialize StandardNormal"""
         self.init_prim_io_names(inputs=['shape'], outputs=['output'])
-        self.add_prim_attr("_random_effect", True)
+        self.add_prim_attr("side_effect_hidden", True)
         Validator.check_non_negative_int(seed, "seed", self.name)
         Validator.check_non_negative_int(seed2, "seed2", self.name)
 
@@ -119,7 +119,7 @@ class StandardLaplace(PrimitiveWithInfer):
     def __init__(self, seed=0, seed2=0):
         """Initialize StandardLaplace"""
         self.init_prim_io_names(inputs=['shape'], outputs=['output'])
-        self.add_prim_attr("_random_effect", True)
+        self.add_prim_attr("side_effect_hidden", True)
         Validator.check_value_type('seed', seed, [int], self.name)
         Validator.check_value_type('seed2', seed2, [int], self.name)
 
@@ -196,7 +196,7 @@ class Gamma(PrimitiveWithInfer):
     def __init__(self, seed=0, seed2=0):
         """Initialize Gamma"""
         self.init_prim_io_names(inputs=['shape', 'alpha', 'beta'], outputs=['output'])
-        self.add_prim_attr("_random_effect", True)
+        self.add_prim_attr("side_effect_hidden", True)
         Validator.check_non_negative_int(seed, "seed", self.name)
         Validator.check_non_negative_int(seed2, "seed2", self.name)
 
@@ -262,7 +262,7 @@ class Poisson(PrimitiveWithInfer):
     def __init__(self, seed=0, seed2=0):
         """Initialize Poisson"""
         self.init_prim_io_names(inputs=['shape', 'mean'], outputs=['output'])
-        self.add_prim_attr("_random_effect", True)
+        self.add_prim_attr("side_effect_hidden", True)
         Validator.check_non_negative_int(seed, "seed", self.name)
         Validator.check_non_negative_int(seed2, "seed2", self.name)
 
@@ -334,7 +334,7 @@ class UniformInt(PrimitiveWithInfer):
     def __init__(self, seed=0, seed2=0):
         """Initialize UniformInt"""
         self.init_prim_io_names(inputs=['shape', 'minval', 'maxval'], outputs=['output'])
-        self.add_prim_attr("_random_effect", True)
+        self.add_prim_attr("side_effect_hidden", True)
         Validator.check_non_negative_int(seed, "seed", self.name)
         Validator.check_non_negative_int(seed2, "seed2", self.name)
 
@@ -451,7 +451,7 @@ class RandomChoiceWithMask(PrimitiveWithInfer):
         Validator.check_positive_int(count, "count", self.name)
         Validator.check_value_type('seed', seed, [int], self.name)
         Validator.check_value_type('seed2', seed2, [int], self.name)
-        self.add_prim_attr("_random_effect", True)
+        self.add_prim_attr("side_effect_hidden", True)
 
     def infer_shape(self, x_shape):
         Validator.check_int(len(x_shape), 1, Rel.GE, "input_x rank", self.name)
@@ -513,7 +513,7 @@ class RandomCategorical(PrimitiveWithInfer):
         Validator.check_type_name("dtype", dtype, valid_values, self.name)
         self.init_prim_io_names(inputs=['logits', 'num_samples', 'seed'],
                                 outputs=['output'])
-        self.add_prim_attr("_random_effect", True)
+        self.add_prim_attr("side_effect_hidden", True)
 
     def __infer__(self, logits, num_samples, seed):
         logits_dtype = logits['dtype']
@@ -580,7 +580,7 @@ class Multinomial(PrimitiveWithInfer):
         Validator.check_non_negative_int(seed, "seed", self.name)
         Validator.check_non_negative_int(seed2, "seed2", self.name)
         self.init_prim_io_names(inputs=['input', 'num_sample'], outputs=['output'])
-        self.add_prim_attr("_random_effect", True)
+        self.add_prim_attr("side_effect_hidden", True)
 
     def __infer__(self, inputs, num_samples):
         input_shape = inputs["shape"]