diff --git a/mindspore/ccsrc/backend/kernel_compiler/host/host_kernel_metadata.cc b/mindspore/ccsrc/backend/kernel_compiler/host/host_kernel_metadata.cc
index 2417b61f60b..c8c575cea47 100644
--- a/mindspore/ccsrc/backend/kernel_compiler/host/host_kernel_metadata.cc
+++ b/mindspore/ccsrc/backend/kernel_compiler/host/host_kernel_metadata.cc
@@ -20,16 +20,24 @@
 #include "backend/kernel_compiler/oplib/oplib.h"
 #include "backend/kernel_compiler/common_utils.h"
 #include "backend/session/anf_runtime_algorithm.h"
+#include "base/core_ops.h"
 
 namespace mindspore {
 namespace kernel {
-constexpr auto kDynamicShape = "DynamicShape";
+static const std::set<std::string> host_kernel = {prim::kPrimDynamicShape->name(),
+                                                  prim::kPrimDynamicBroadcastGradientArgs->name()};
 
 void HostMetadataInfo(const CNodePtr &kernel_node, std::vector<std::shared_ptr<KernelBuildInfo>> *kernel_info_list) {
   MS_LOG(INFO) << "HostMetadataInfo.";
   MS_EXCEPTION_IF_NULL(kernel_node);
   MS_EXCEPTION_IF_NULL(kernel_info_list);
 
+  std::string op_name = AnfAlgo::GetCNodeName(kernel_node);
+  if (host_kernel.find(op_name) == host_kernel.end()) {
+    MS_LOG(DEBUG) << "Host dose not have op [" << op_name << "]";
+    return;
+  }
+
   std::vector<std::string> inputs_format{};
   std::vector<TypeId> inputs_type{};
   size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node);
diff --git a/mindspore/core/base/core_ops.h b/mindspore/core/base/core_ops.h
index 84a72a83d2d..fad1f174d34 100644
--- a/mindspore/core/base/core_ops.h
+++ b/mindspore/core/base/core_ops.h
@@ -61,6 +61,7 @@ constexpr auto kTile = "Tile";
 constexpr auto kBiasAddGrad = "BiasAddGrad";
 
 // Arrays
+constexpr auto kDynamicShape = "DynamicShape";
 constexpr auto kStack = "Stack";
 constexpr auto kUnstack = "Unstack";
 constexpr auto kTupleGetItem = "TupleGetItem";
@@ -167,7 +168,7 @@ inline const PrimitivePtr kPrimSparseGatherV2 = std::make_shared<Primitive>("Spa
 inline const PrimitivePtr kPrimSparseToDense = std::make_shared<Primitive>("SparseToDense");
 inline const PrimitivePtr kPrimShape = std::make_shared<Primitive>("Shape");
 inline const PrimitivePtr kPrimStridedSlice = std::make_shared<Primitive>(kStridedSlice);
-inline const PrimitivePtr kPrimDynamicShape = std::make_shared<Primitive>("DynamicShape");
+inline const PrimitivePtr kPrimDynamicShape = std::make_shared<Primitive>(kDynamicShape);
 inline const PrimitivePtr kPrimEmbeddingLookup = std::make_shared<Primitive>("EmbeddingLookup");
 inline const PrimitivePtr kPrimEmbeddingLookupCommGrad = std::make_shared<Primitive>("EmbeddingLookupCommGrad");
 inline const PrimitivePtr kPrimSize = std::make_shared<Primitive>("Size");
diff --git a/mindspore/nn/layer/conv.py b/mindspore/nn/layer/conv.py
index 404bc0c6e74..2b94a5b31d0 100644
--- a/mindspore/nn/layer/conv.py
+++ b/mindspore/nn/layer/conv.py
@@ -266,7 +266,7 @@ class Conv2d(_Conv):
     def extend_repr(self):
         s = 'input_channels={}, output_channels={}, kernel_size={},' \
             'stride={},  pad_mode={}, padding={}, dilation={}, ' \
-            'group={}, has_bias={}' \
+            'group={}, has_bias={}, ' \
             'weight_init={}, bias_init={}, format={}'.format(
                 self.in_channels,
                 self.out_channels,
diff --git a/mindspore/train/callback/_lr_scheduler_callback.py b/mindspore/train/callback/_lr_scheduler_callback.py
index db63b10cffc..df490a08acc 100644
--- a/mindspore/train/callback/_lr_scheduler_callback.py
+++ b/mindspore/train/callback/_lr_scheduler_callback.py
@@ -35,7 +35,7 @@ class LearningRateScheduler(Callback):
         learning_rate_function (Function): The function about how to change the learning rate during training.
 
     Examples:
-        >>> from _lr_scheduler_callback import LearningRateScheduler
+        >>> from mindspore.train.callback import LearningRateScheduler
         >>> import mindspore.nn as nn
         >>> from mindspore.train import Model
         ...