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!25210 codecheck clean for r1.5 

Merge pull request !25210 from liuyang/code_check_r1_5
This commit is contained in:
i-robot 2021-10-22 02:26:01 +00:00 committed by Gitee
parent 8b6d8a4009 c07bfb4de5
commit d955dea6ad
1 changed files with 12 additions and 9 deletions
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21
mindspore/ccsrc/transform/express_ir/onnx_exporter.cc
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@ -34,6 +34,8 @@ const int kOneNum = 1;
const int kTwoNum = 2;
const int kThreeNum = 3;
const int kFourNum = 4;
const int64_t kOneNumLong = 1;
const float weight_for_mul = 0.5;
enum OpMergeMode {
OP_MERGE_UNDEFINED = 0, // undefined behavior
OP_MERGE_IGNORE = 1, // indicate an input op merged into other op in compute node list
@ -1016,7 +1018,7 @@ void OnnxExporter::ExportPrimExpandDims(const FuncGraphPtr &, const CNodePtr &no
new_shape.push_back(x_shape->shape()[i]);
}
if (axis < 0) {
axis = axis + IntToLong(kOneNum) + SizeToLong(x_shape->shape().size());
axis = axis + kOneNumLong + SizeToLong(x_shape->shape().size());
}
new_shape.insert(new_shape.begin() + axis, kOneNum);
auto new_shape_value = MakeValue<std::vector<int64_t>>(new_shape);
@ -1183,11 +1185,12 @@ void OnnxExporter::ExportPrimGeLU(const FuncGraphPtr &, const CNodePtr &node,
// Add Pow node
// Add input exponent node for Pow node
auto exp_node_idx = AllocateNodeIndex();
const float exponent_for_pow = 3.0;
onnx::NodeProto *exp_node_proto = graph_proto->add_node();
onnx::AttributeProto *exp_attr_proto = exp_node_proto->add_attribute();
onnx::TensorProto *exp_tensor_proto = exp_attr_proto->mutable_t();
SetConstantNodeProtoInfoForGeLU(exp_node_proto, std::to_string(exp_node_idx), exp_attr_proto, exp_tensor_proto,
"exponent", 3.0);
"exponent", exponent_for_pow);
// Add pow node
auto pow_idx = AllocateNodeIndex();
auto pow_name = std::to_string(pow_idx);
@ -1204,11 +1207,12 @@ void OnnxExporter::ExportPrimGeLU(const FuncGraphPtr &, const CNodePtr &node,
// Add first Mul node
// Add input node for first Mul node
auto fmul_input_node_idx = AllocateNodeIndex();
const float weight_for_fmul = 0.044715;
onnx::NodeProto *fmul_input_node_proto = graph_proto->add_node();
onnx::AttributeProto *fmul_input_attr_proto = fmul_input_node_proto->add_attribute();
onnx::TensorProto *fmul_input_tensor_proto = fmul_input_attr_proto->mutable_t();
SetConstantNodeProtoInfoForGeLU(fmul_input_node_proto, std::to_string(fmul_input_node_idx), fmul_input_attr_proto,
fmul_input_tensor_proto, "input_y_for_mul", 0.044715);
fmul_input_tensor_proto, "input_y_for_mul", weight_for_fmul);
// Add first Mul Node
auto fmul_name = std::to_string(AllocateNodeIndex());
onnx::NodeProto *fmul_node_proto = graph_proto->add_node();
@ -1227,11 +1231,12 @@ void OnnxExporter::ExportPrimGeLU(const FuncGraphPtr &, const CNodePtr &node,
// Add second Mul node
// Add input node for second Mul node
auto smul_input_node_idx = AllocateNodeIndex();
const float weight_for_smul = 0.79788456;
onnx::NodeProto *smul_input_node_proto = graph_proto->add_node();
onnx::AttributeProto *smul_input_attr_proto = smul_input_node_proto->add_attribute();
onnx::TensorProto *smul_input_tensor_proto = smul_input_attr_proto->mutable_t();
SetConstantNodeProtoInfoForGeLU(smul_input_node_proto, std::to_string(smul_input_node_idx), smul_input_attr_proto,
smul_input_tensor_proto, "input_y_for_smul", 0.79788456);
smul_input_tensor_proto, "input_y_for_smul", weight_for_smul);
// Add second Mul Node
auto smul_name = std::to_string(AllocateNodeIndex());
onnx::NodeProto *smul_node_proto = graph_proto->add_node();
@ -1262,7 +1267,7 @@ void OnnxExporter::ExportPrimGeLU(const FuncGraphPtr &, const CNodePtr &node,
onnx::AttributeProto *tmul_input_attr_proto = tmul_input_node_proto->add_attribute();
onnx::TensorProto *tmul_input_tensor_proto = tmul_input_attr_proto->mutable_t();
SetConstantNodeProtoInfoForGeLU(tmul_input_node_proto, std::to_string(tmul_input_node_idx), tmul_input_attr_proto,
tmul_input_tensor_proto, "input_y_for_tmul", 0.5);
tmul_input_tensor_proto, "input_y_for_tmul", weight_for_mul);
// Add third Mul Node
auto tmul_name = std::to_string(AllocateNodeIndex());
onnx::NodeProto *tmul_node_proto = graph_proto->add_node();
@ -1302,7 +1307,6 @@ void OnnxExporter::ExportPrimConcat(const FuncGraphPtr &, const CNodePtr &node,
auto op_value = dyn_cast<ValueNode>(op);
auto prim = dyn_cast<Primitive>(op_value->value());
auto input_node = node->input(kOneNum)->cast<CNodePtr>();
if (input_node->IsApply(prim::kPrimMakeTuple)) {
node_proto->set_op_type("ConcatFromSequence");
} else {
@ -1532,10 +1536,11 @@ void OnnxExporter::ExportPrimSquare(const FuncGraphPtr &, const CNodePtr &node,
attr_proto->set_name("value");
attr_proto->set_type(onnx::AttributeProto_AttributeType_TENSOR);
onnx::TensorProto *tensor_proto = attr_proto->mutable_t();
const float exponent_value = 2.0;
tensor_proto->set_name("exponent");
tensor_proto->add_dims(static_cast<::google::protobuf::int64>(1));
tensor_proto->set_data_type(GetOnnxDataType(kNumberTypeFloat32));
tensor_proto->add_float_data(2.0);
tensor_proto->add_float_data(exponent_value);
auto node_idx = AllocateNodeIndex();
(*node_map_ptr)[node] = node_idx;
@ -1671,7 +1676,6 @@ size_t OnnxExporter::ExportPrimitive(const FuncGraphPtr &, std::map<AnfNodePtr,
// Set inputs
for (const auto &input_name : input_list) {
// auto input_name = GetNodeInputName(input, node_map_ptr, graph_proto);
node_proto->add_input(input_name);
}
@ -1786,7 +1790,6 @@ void OnnxExporter::ExportMergeLayerNorm(const FuncGraphPtr &, const CNodePtr &no
auto shape_node = NewValueNode(new_shape_value)->cast<AnfNodePtr>();
auto shape_node_idx = AllocateNodeIndex();
// (*node_map_ptr)[shape_node] = shape_node_idx;
onnx::NodeProto *shape_node_proto = graph_proto->add_node();
shape_node_proto->add_output(std::to_string(shape_node_idx));
shape_node_proto->set_op_type("Constant");