fix code review

mindspore/lite/schema/ops.fbs

@@ -660,7 +660,7 @@ table NetOutput {
 }
 
 table MatMul {
-    broadcast : bool = false;
+    broadcast : bool = false;  // DEPRECATED
     transposeA : bool = false;
     transposeB : bool = false;
 }

mindspore/lite/src/ops/conv2d.cc

@@ -189,7 +189,7 @@ void Conv2D::PopulaterConv2DMultiGroup(const Primitive &prim, schema::PrimitiveT
   attr->channelMultiplier = channel_mutiplier;
 
   MS_ASSERT(inputs.size() == kAnfPopulaterInputNumTwo);
-  auto input_node = inputs[kAnfPopulaterInputNumOne];
+  auto input_node = inputs.at(kAnfPopulaterInputNumOne);
   MS_ASSERT(input_node != nullptr);
   if (input_node->isa<Parameter>()) {
     auto param_node = input_node->cast<ParameterPtr>();
@@ -201,7 +201,7 @@ void Conv2D::PopulaterConv2DMultiGroup(const Primitive &prim, schema::PrimitiveT
       MS_ASSERT(abstractTensor != nullptr);
       if (utils::isa<abstract::ShapePtr>(abstractTensor->BuildShape())) {
         auto dims = utils::cast<abstract::ShapePtr>(abstractTensor->BuildShape())->shape();
-        attr->channelIn = dims[kAnfPopulaterInputNumOne];
+        attr->channelIn = dims.at(kAnfPopulaterInputNumOne);
       }
     }
   } else if (input_node->isa<CNode>()) {

mindspore/lite/src/ops/depthwise_conv2d.cc

@@ -128,7 +128,7 @@ int DepthwiseConv2D::UnPackAttr(const Primitive &prim, const std::vector<AnfNode
   attr->channelMultiplier = channel_multiplier;
 
   MS_ASSERT(inputs.size() == kAnfPopulaterInputNumTwo);
-  auto inputNode = inputs[kAnfPopulaterInputNumOne];
+  auto inputNode = inputs.at(kAnfPopulaterInputNumOne);
   MS_ASSERT(inputNode != nullptr);
   if (inputNode->isa<Parameter>()) {
     auto paramNode = inputNode->cast<ParameterPtr>();
@@ -139,7 +139,7 @@ int DepthwiseConv2D::UnPackAttr(const Primitive &prim, const std::vector<AnfNode
       MS_ASSERT(abstractTensor != nullptr);
       if (utils::isa<abstract::ShapePtr>(abstractTensor->BuildShape())) {
         auto dims = utils::cast<abstract::ShapePtr>(abstractTensor->BuildShape())->shape();
-        attr->channelIn = dims[kAnfPopulaterInputNumOne];
+        attr->channelIn = dims.at(kAnfPopulaterInputNumOne);
       }
     }
   }

mindspore/lite/tools/converter/parser/onnx/onnx_matmul_parser.cc

@@ -42,9 +42,6 @@ STATUS OnnxMatmulParser::Parse(const onnx::GraphProto &onnx_graph, const onnx::N
   float beta = 1.0f;
   for (const auto &onnx_node_attr : onnx_node.attribute()) {
     const auto &attribute_name = onnx_node_attr.name();
-    if (attribute_name == "broadcast") {
-      attr->broadcast = static_cast<bool>(onnx_node_attr.i());
-    }
     if (attribute_name == "transA") {
       attr->transposeA = static_cast<bool>(onnx_node_attr.i());
     } else if (attribute_name == "transB") {

mindspore/lite/tools/converter/parser/tflite/tflite_custom_parser.cc

@@ -199,7 +199,6 @@ STATUS TfliteCustomParser::BatchMatMul(const std::vector<uint8_t> &custom_attr,
     MS_LOG(ERROR) << "new op failed";
     return RET_NULL_PTR;
   }
-  attr->broadcast = false;
   attr->transposeA = false;
   attr->transposeB = false;
   op->primitive->value.type = schema::PrimitiveType_MatMul;

mindspore/lite/tools/converter/parser/tflite/tflite_matmul_parser.cc

@@ -36,7 +36,6 @@ PrimitiveC *TfliteMatMulParser::ParseLitePrimitive(const std::unique_ptr<tflite:
   const auto &tflite_attr = tflite_op->builtin_options.AsBatchMatMulOptions();
   attr->transposeA = tflite_attr->adj_x;
   attr->transposeB = tflite_attr->adj_y;
-  attr->broadcast = false;
   primitive->value.type = schema::PrimitiveType_MatMul;
   primitive->value.value = attr.release();