提交 420ef2a3 编写于 作者: M mindspore-ci-bot 提交者: Gitee

!731 remove extra empty string from log text

Merge pull request !731 from fary86/remove_extra_empty_string_in_log
......@@ -345,7 +345,7 @@ TypePtr StringToNumberType(const std::string &type_name, const std::string &num_
auto bits = std::stoi(type_name.substr(num_type_name.size()));
type = std::make_shared<T>(bits);
} catch (const std::exception &e) {
MS_LOG(EXCEPTION) << "" << num_type_name << " convert from string error " << e.what();
MS_LOG(EXCEPTION) << num_type_name << " convert from string error " << e.what();
}
}
return type;
......@@ -389,7 +389,7 @@ TypePtr TensorStrToType(const std::string &type_name) {
}
type = std::make_shared<TensorType>(element_type);
} catch (const std::exception &e) {
MS_LOG(EXCEPTION) << "" << type_name << " convert from string error " << e.what();
MS_LOG(EXCEPTION) << type_name << " convert from string error " << e.what();
}
}
......@@ -416,7 +416,7 @@ TypePtr ListStrToType(const std::string &type_name) {
}
type = std::make_shared<List>(element_types);
} catch (const std::exception &e) {
MS_LOG(EXCEPTION) << "" << type_name << " convert from string error " << e.what();
MS_LOG(EXCEPTION) << type_name << " convert from string error " << e.what();
}
}
......@@ -443,7 +443,7 @@ TypePtr TupleStrToType(const std::string &type_name) {
}
type = std::make_shared<Tuple>(element_types);
} catch (const std::exception &e) {
MS_LOG(EXCEPTION) << "" << type_name << " convert from string error " << e.what();
MS_LOG(EXCEPTION) << type_name << " convert from string error " << e.what();
}
}
return type;
......@@ -484,7 +484,7 @@ TypePtr FunctionStrToType(const std::string &type_name) {
}
type = std::make_shared<Function>(args_type, retval);
} catch (const std::exception &e) {
MS_LOG(EXCEPTION) << "" << type_name << " convert from string error " << e.what();
MS_LOG(EXCEPTION) << type_name << " convert from string error " << e.what();
}
}
return type;
......
......@@ -888,7 +888,7 @@ void FuncGraphUserNodesCollector::OnMoveAllCNode(FuncGraphPtr src, FuncGraphPtr
void FuncGraphJDirectCollector::OnModEdge(AnfNodePtr node, int, AnfNodePtr inp, EdgeProcessDirection direction) {
if (IsValueNode<FuncGraph>(inp) && IsPrimitiveCNode(node, prim::kPrimJ)) {
(void)Mod(node->func_graph(), GetValueNode<FuncGraphPtr>(inp), direction);
MS_LOG(DEBUG) << "" << node->func_graph()->ToString() << " users func graph "
MS_LOG(DEBUG) << node->func_graph()->ToString() << " users func graph "
<< GetValueNode<FuncGraphPtr>(inp)->ToString() << " which contains J(func_graph), dir: " << direction;
}
}
......@@ -945,7 +945,7 @@ FuncGraphSetPtr FuncGraphParentsTotalComputer::SeekParents(const FuncGraphPtr &f
void FuncGraphParentsTotalComputer::RealRecompute(FuncGraphPtr fg) {
MS_EXCEPTION_IF_NULL(fg);
all_parents_direct_ = &(manager_->func_graph_parents_direct());
MS_LOG(DEBUG) << "" << fg->ToString() << " total func graph dep size:" << (*all_parents_direct_)[fg].size();
MS_LOG(DEBUG) << fg->ToString() << " total func graph dep size:" << (*all_parents_direct_)[fg].size();
func_graph_parents_total_analysis_[fg].update(SeekParents(fg));
MS_LOG(DEBUG) << "FuncGraphParentsTotalComputer end: " << func_graph_parents_total_analysis_[fg].size();
}
......@@ -1074,7 +1074,7 @@ void FuncGraphsUsedTotalComputer::RealRecompute(FuncGraphPtr fg) {
if (func_graph_used_total_analysis_[fg].count(used_fg) == 0) {
todo_new.push_back(used_fg);
}
MS_LOG(DEBUG) << "" << fg->ToString() << " add func graph " << used_fg->ToString();
MS_LOG(DEBUG) << fg->ToString() << " add func graph " << used_fg->ToString();
func_graph_used_total_analysis_[fg].add(used_fg);
}
}
......@@ -1138,7 +1138,7 @@ void RecursiveComputer::CheckRecursiveGraphs(const FuncGraphPtr &fg, std::list<F
bool FuncGraphJTotalComputer::SeekJ(const FuncGraphPtr &fg, const FuncGraphSetPtr &path) {
MS_EXCEPTION_IF_NULL(path);
if (path->contains(fg)) {
MS_LOG(DEBUG) << "" << fg->ToString() << " had been checked";
MS_LOG(DEBUG) << fg->ToString() << " had been checked";
return false;
}
MS_EXCEPTION_IF_NULL(manager_);
......@@ -1149,7 +1149,7 @@ bool FuncGraphJTotalComputer::SeekJ(const FuncGraphPtr &fg, const FuncGraphSetPt
std::find_if(func_graph_counter_map[fg].begin(), func_graph_counter_map[fg].end(),
[path](const std::pair<FuncGraphPtr, int> iter) { return !path->contains(iter.first); });
if (contains_j != func_graph_counter_map[fg].end()) {
MS_LOG(DEBUG) << "" << fg->ToString() << " contains J(" << contains_j->first->ToString() << ")";
MS_LOG(DEBUG) << fg->ToString() << " contains J(" << contains_j->first->ToString() << ")";
return true;
}
}
......@@ -1160,12 +1160,11 @@ bool FuncGraphJTotalComputer::SeekJ(const FuncGraphPtr &fg, const FuncGraphSetPt
for (auto &item : used[fg]) {
auto used_g = item.first;
if (SeekJ(used_g, path)) {
MS_LOG(DEBUG) << "" << fg->ToString() << " users func graph " << used_g->ToString()
<< " which contains J(func_graph)";
MS_LOG(DEBUG) << fg->ToString() << " users func graph " << used_g->ToString() << " which contains J(func_graph)";
return true;
}
}
MS_LOG(DEBUG) << "" << fg->ToString() << " doesn't contain J(func_graph)";
MS_LOG(DEBUG) << fg->ToString() << " doesn't contain J(func_graph)";
return false;
}
......
......@@ -145,14 +145,14 @@ py::function PrimitivePy::GetComputeFunction() {
static const char *const compute_func_name = "vm_impl";
if (py::hasattr(python_obj_, compute_func_name)) {
MS_LOG(INFO) << "" << name() << " compute_func_name";
MS_LOG(INFO) << name() << " compute_func_name";
py::function fn = python_obj_.attr(compute_func_name).cast<py::function>();
return fn;
}
static const std::string vm_module = "mindspore.ops.vm_impl_registry";
static const std::string get_vm_impl_fn = "get_vm_impl_fn";
MS_LOG(INFO) << "" << name() << ": get_vm_impl_fn";
MS_LOG(INFO) << name() << ": get_vm_impl_fn";
py::function get_fn = parse::python_adapter::GetPyFn(vm_module, get_vm_impl_fn);
py::function vm_fn = get_fn(python_obj_);
......
......@@ -676,7 +676,7 @@ void MultitypeFuncGraph::Register(const std::vector<std::string> &types_name, co
for (auto &type_name : types_name) {
auto type_ptr = StringToType(type_name);
if (type_ptr == nullptr) {
MS_LOG(EXCEPTION) << "" << type_name << " convert from string error ";
MS_LOG(EXCEPTION) << type_name << " convert from string error ";
}
types.push_back(type_ptr);
}
......@@ -955,8 +955,7 @@ int CheckSliceMember(const AbstractBasePtr &member, int default_value, const std
return default_value;
}
MS_LOG(EXCEPTION) << "" << member_name << " should be a AbstractScalar or AbstractNone, but got "
<< member->ToString();
MS_LOG(EXCEPTION) << member_name << " should be a AbstractScalar or AbstractNone, but got " << member->ToString();
}
void GenerateTupleSliceParameter(const AbstractTuplePtr &tuple, const AbstractSlicePtr &slice, int *start_index,
......
......@@ -246,7 +246,7 @@ AbstractBasePtr InferImplBiasAddGrad(const AnalysisEnginePtr &, const PrimitiveP
// Inputs: at least one tensor(y_backprop)
// Outputs: dbias
if (args_spec_list.empty()) {
MS_LOG(EXCEPTION) << "" << primitive->name() << " evaluator at least has 1 parameters, while the input size is "
MS_LOG(EXCEPTION) << primitive->name() << " evaluator at least has 1 parameters, while the input size is "
<< args_spec_list.size() << ".";
}
......@@ -255,8 +255,7 @@ AbstractBasePtr InferImplBiasAddGrad(const AnalysisEnginePtr &, const PrimitiveP
MS_EXCEPTION_IF_NULL(shape_y);
std::vector<int> y_dims = shape_y->shape();
if (y_dims.size() < 2) {
MS_LOG(EXCEPTION) << "" << primitive->name() << " input y backprop, dim should >= 2, while " << y_dims.size()
<< ".";
MS_LOG(EXCEPTION) << primitive->name() << " input y backprop, dim should >= 2, while " << y_dims.size() << ".";
}
std::vector<int> bias_dims = {y_dims[1]};
ShapePtr ret_shape = std::make_shared<Shape>(bias_dims);
......
......@@ -80,8 +80,7 @@ AbstractBasePtr InferImplDot(const AnalysisEnginePtr &, const PrimitivePtr &prim
auto y_shp_value = y_shp->shape();
// Should be matrix which shape size is 2.
if (x_shp_value.size() != 2 || y_shp_value.size() != 2) {
MS_LOG(EXCEPTION) << "" << op_name
<< " evaluator requires input two 2D tensors, while the dimensions of two tensors are "
MS_LOG(EXCEPTION) << op_name << " evaluator requires input two 2D tensors, while the dimensions of two tensors are "
<< x_shp_value.size() << ", " << y_shp_value.size() << " ";
}
if (x_shp_value[1] != y_shp_value[0] && x_shp_value[1] != Shape::SHP_ANY && y_shp_value[0] != Shape::SHP_ANY) {
......
......@@ -171,7 +171,7 @@ class Optimizer : public std::enable_shared_from_this<Optimizer> {
};
use_profile ? (WITH(MsProfile::GetProfile()->Step(pass_names_[i])) opt_func) : opt_func();
#ifdef DEBUG
MS_LOG(DEBUG) << "" << name_ << " round " << counter << " OptPass " << pass_names_[i] << " end.";
MS_LOG(DEBUG) << name_ << " round " << counter << " OptPass " << pass_names_[i] << " end.";
auto fg_name = name_ + "_r" + std::to_string(counter) + "_" + std::to_string(i) + "_" + pass_names_[i];
func_graph->DumpFuncGraph(fg_name);
DumpIR(fg_name + ".ir", func_graph);
......
......@@ -37,7 +37,7 @@ void FunctionBlock::AddPrevBlock(const FunctionBlockPtr &block) { prev_blocks_.p
// write variable records the variable name to corresponding node
void FunctionBlock::WriteVariable(const std::string &var_name, const AnfNodePtr &node) {
MS_LOG(DEBUG) << "" << func_graph_->ToString() << " write var " << var_name << " with node " << node->DebugString();
MS_LOG(DEBUG) << func_graph_->ToString() << " write var " << var_name << " with node " << node->DebugString();
vars_[var_name] = node;
}
......@@ -71,7 +71,7 @@ AnfNodePtr FunctionBlock::ReadVariable(const std::string &var) {
TraceManager::DebugTrace(std::make_shared<TracePhi>(debug_info));
ParameterPtr phi_param = std::make_shared<Parameter>(func_graph());
TraceManager::EndTrace();
MS_LOG(DEBUG) << "" << func_graph_->ToString() << " generate phi node " << phi_param->ToString() << " for " << var;
MS_LOG(DEBUG) << func_graph_->ToString() << " generate phi node " << phi_param->ToString() << " for " << var;
func_graph()->add_parameter(phi_param);
phi_nodes_[phi_param] = var;
WriteVariable(var, phi_param);
......
......@@ -333,7 +333,7 @@ void ExecutorPy::GetGeBackendPolicy() const {
MS_EXCEPTION_IF_NULL(ms_context);
std::string backend = ms_context->backend_policy();
if (backend != "ge") {
MS_LOG(EXCEPTION) << "" << backend << " backend policy is not supported under ge backend!";
MS_LOG(EXCEPTION) << backend << " backend policy is not supported under ge backend!";
}
}
......@@ -491,10 +491,10 @@ void RunPipelineAction(const ActionItem &action, pipeline::ResourcePtr resource,
// load MindSpore IR from file
if (action.first == "symbol_resolve") {
MS_LOG(DEBUG) << "" << action.first << " read ir file: " << ir_file;
MS_LOG(DEBUG) << action.first << " read ir file: " << ir_file;
std::vector<FuncGraphPtr> graphs = ImportIR(ir_file);
if (graphs.size() == 0) {
MS_LOG(EXCEPTION) << "" << action.first << " read ir file " << ir_file << " failed as no graph found";
MS_LOG(EXCEPTION) << action.first << " read ir file " << ir_file << " failed as no graph found";
}
auto manager = resource->manager();
MS_EXCEPTION_IF_NULL(manager);
......
......@@ -78,7 +78,7 @@ AnalysisContextPtr AnalysisContext::Filter(const FuncGraphPtr &func_graph) {
oss << ", context: " << iter.second.lock()->ToString() << "]";
}
oss << "}";
MS_LOG(EXCEPTION) << "" << oss.str() << " NodeInfo: " << trace::GetDebugInfo(func_graph->debug_info());
MS_LOG(EXCEPTION) << oss.str() << " NodeInfo: " << trace::GetDebugInfo(func_graph->debug_info());
}
return parent_context;
}
......
......@@ -33,8 +33,7 @@ void InferEntryLogging(const EvaluatorPtr &evaluator, const AbstractBasePtrList
MS_LOG(DEBUG) << "Evaluator " << evaluator->ToString() << " run for " << out_conf->node()->scope()->name();
}
for (size_t i = 0; i < arg_spec_list.size(); i++) {
MS_LOG(DEBUG) << "" << evaluator->ToString() << " input[" << i
<< "] abstract value: " << arg_spec_list[i]->ToString();
MS_LOG(DEBUG) << evaluator->ToString() << " input[" << i << "] abstract value: " << arg_spec_list[i]->ToString();
}
}
......@@ -137,7 +136,7 @@ AbstractBasePtrList FuncGraphEvaluator::NormalizeArgs(const AbstractBasePtrList
MS_EXCEPTION_IF_NULL(arg);
return arg->Broaden();
});
MS_LOG(DEBUG) << "" << func_graph_->ToString() << " original: " << mindspore::ToString(args_spec_list)
MS_LOG(DEBUG) << func_graph_->ToString() << " original: " << mindspore::ToString(args_spec_list)
<< ", broaded: " << mindspore::ToString(broaded_list);
return broaded_list;
}
......@@ -230,20 +229,20 @@ AbstractBasePtr Evaluator::Run(AnalysisEnginePtr engine, const ConfigPtrList &ar
MS_EXCEPTION_IF_NULL(cache_);
auto iter = cache_->find(args_spec_list);
if (iter == cache_->end()) {
MS_LOG(DEBUG) << "" << evaluator_name << " cache miss, call Infer().";
MS_LOG(DEBUG) << evaluator_name << " cache miss, call Infer().";
AbstractBasePtr ret = Infer(engine, args_spec_list);
if (ret == nullptr) {
InferFailLogging(shared_from_base<Evaluator>(), args_spec_list, out_conf);
MS_LOG(EXCEPTION) << "Evaluator " << evaluator_name << " result is nullptr.";
}
MS_EXCEPTION_IF_NULL(ret);
MS_LOG(DEBUG) << "" << evaluator_name << " set cache. return: " << ret->ToString() << ".";
MS_LOG(DEBUG) << evaluator_name << " set cache. return: " << ret->ToString() << ".";
(*cache_)[args_spec_list] = ret;
trace::TraceGraphInferLeave(shared_from_base<Evaluator>());
return ret;
} else {
MS_EXCEPTION_IF_NULL(iter->second);
MS_LOG(DEBUG) << "" << evaluator_name << " cache hit. return: " << iter->second->ToString() << ".";
MS_LOG(DEBUG) << evaluator_name << " cache hit. return: " << iter->second->ToString() << ".";
trace::TraceGraphInferLeave(shared_from_base<Evaluator>());
return iter->second;
}
......
......@@ -103,7 +103,7 @@ ShapePtr CheckShapeSame(const std::string &op, const AbstractTensorPtr &tensor_b
ShapePtr shape_base = tensor_base->shape();
ShapePtr shape = tensor->shape();
if (*shape != *shape_base) {
MS_LOG(EXCEPTION) << "" << op << " evaluator first arg shape " << tensor->shape()->ToString()
MS_LOG(EXCEPTION) << op << " evaluator first arg shape " << tensor->shape()->ToString()
<< " are not consistent with second arg shape " << tensor_base->shape()->ToString();
}
return shape_base;
......@@ -113,7 +113,7 @@ TypePtr CheckDtypeSame(const std::string &op, const AbstractTensorPtr &tensor_ba
TypePtr type_base = tensor_base->element()->BuildType();
TypePtr type = tensor->element()->BuildType();
if (*type != *type_base) {
MS_LOG(EXCEPTION) << "" << op << " evaluator first arg dtype " << type_base->ToString()
MS_LOG(EXCEPTION) << op << " evaluator first arg dtype " << type_base->ToString()
<< " are not consistent with second arg dtype " << type->ToString();
}
return type_base;
......@@ -121,14 +121,14 @@ TypePtr CheckDtypeSame(const std::string &op, const AbstractTensorPtr &tensor_ba
int CheckAxis(const std::string &op, const ValuePtr &axis, int minimum, int max) {
if (axis == nullptr) {
MS_LOG(EXCEPTION) << "" << op << " evaluator axis is null";
MS_LOG(EXCEPTION) << op << " evaluator axis is null";
}
if (!axis->isa<Int32Imm>()) {
MS_LOG(EXCEPTION) << "" << op << " evaluator axis should be int, but got " << axis->type_name();
MS_LOG(EXCEPTION) << op << " evaluator axis should be int, but got " << axis->type_name();
}
int axis_value = GetValue<int>(axis);
if (axis_value > max || axis_value < minimum) {
MS_LOG(EXCEPTION) << "" << op << " evaluator axis value should be in the range [" << minimum << ", " << max
MS_LOG(EXCEPTION) << op << " evaluator axis value should be in the range [" << minimum << ", " << max
<< "], but get " << axis_value;
}
return axis_value;
......@@ -136,8 +136,7 @@ int CheckAxis(const std::string &op, const ValuePtr &axis, int minimum, int max)
void CheckArgsSize(const std::string &op, const mindspore::abstract::AbstractBasePtrList &args_spec_list,
size_t size_expect) {
if (args_spec_list.size() != size_expect) {
MS_LOG(EXCEPTION) << "" << op << " input args size should be " << size_expect << ", but got "
<< args_spec_list.size();
MS_LOG(EXCEPTION) << op << " input args size should be " << size_expect << ", but got " << args_spec_list.size();
}
for (size_t i = 0; i < size_expect; i++) {
......
......@@ -70,7 +70,7 @@ ABSTRACT_REPORT_NAME_TRAITS(Class)
template <typename T>
std::shared_ptr<T> CheckArg(const std::string &op, const AbstractBasePtrList &args_spec_list, size_t index) {
if (index >= args_spec_list.size()) {
MS_EXCEPTION(ValueError) << "" << op << " evaluator args list index out of bound, size " << args_spec_list.size()
MS_EXCEPTION(ValueError) << op << " evaluator args list index out of bound, size " << args_spec_list.size()
<< ", index " << index;
}
auto arg = dyn_cast<T>(args_spec_list[index]);
......
......@@ -122,7 +122,7 @@ AnalysisResult AnalysisEngine::Run(const FuncGraphPtr &func_graph, const Abstrac
MS_EXCEPTION_IF_NULL(root_context->func_graph());
AnfNodeConfigPtr output_conf = MakeConfig(root_context->func_graph()->get_return(), root_context);
MS_EXCEPTION_IF_NULL(func_graph);
MS_LOG(INFO) << "" << func_graph->ToString() << ": Run finished.";
MS_LOG(INFO) << func_graph->ToString() << ": Run finished.";
AnalysisResult result;
MS_EXCEPTION_IF_NULL(output_conf);
......@@ -167,7 +167,7 @@ AbstractBasePtr AnalysisEngine::Eval(const AnfNodeConfigPtr &conf) {
for (auto iter : compute_conf_stack_) {
buffer << " -> " << iter->DebugString();
}
MS_LOG(DEBUG) << "" << buffer.str();
MS_LOG(DEBUG) << buffer.str();
#endif
MS_LOG(DEBUG) << "Begin Eval NodeConfig " << conf->ToString();
MS_EXCEPTION_IF_NULL(node);
......
......@@ -175,7 +175,7 @@ std::vector<int> RealBroadcast(const std::string &op, std::vector<int> x_shape,
output_i = x_i;
} else {
MS_LOG(EXCEPTION)
<< "" << op
<< op
<< " evaluator the shape of first tensor and the shape of second tensor do not meet the broadcasting "
"requirements";
}
......
......@@ -623,7 +623,7 @@ void DfGraphConvertor::InitParamWithData(const TensorOrderMap &tensors) {
auto node_itor = params_.find(name);
// if name not in params_, create a node in graph
if (node_itor == params_.end()) {
MS_LOG(WARNING) << "" << name << " is not in params, and create a new node.";
MS_LOG(WARNING) << name << " is not in params, and create a new node.";
ParameterPtr param = anf_graph_->add_parameter();
name = name + "_temp";
param->set_name(name);
......
......@@ -216,8 +216,8 @@ void FinalVM::InstCall(const VectorRef &args) {
MS_LOG(DEBUG) << "Start";
const size_t args_size = 1;
if (args.size() != args_size) {
MS_LOG(ERROR) << "" << __FUNCTION__ << " requires " << args_size << " parameter, while the input size is "
<< args.size() << ".";
MS_LOG(ERROR) << __FUNCTION__ << " requires " << args_size << " parameter, while the input size is " << args.size()
<< ".";
return;
}
......@@ -232,8 +232,8 @@ void FinalVM::InstTailCall(const VectorRef &args) {
MS_LOG(DEBUG) << "Start";
const size_t args_size = 3;
if (args.size() != args_size) {
MS_LOG(ERROR) << "" << __FUNCTION__ << " requires " << args_size << " parameters, while the input size is "
<< args.size() << ".";
MS_LOG(ERROR) << __FUNCTION__ << " requires " << args_size << " parameters, while the input size is " << args.size()
<< ".";
return;
}
......@@ -261,7 +261,7 @@ void FinalVM::InstTailCall(const VectorRef &args) {
void FinalVM::InstSwitchReturn(const VectorRef &args) {
MS_LOG(DEBUG) << "Start";
if (args.size() != 1) {
MS_LOG(ERROR) << "" << __FUNCTION__ << " requires one parameter, while the input size is " << args.size() << ".";
MS_LOG(ERROR) << __FUNCTION__ << " requires one parameter, while the input size is " << args.size() << ".";
return;
}
Pop(1);
......@@ -272,8 +272,8 @@ void FinalVM::InstReturn(const VectorRef &args) {
MS_LOG(DEBUG) << "Start";
const size_t args_size = 2;
if (args.size() != args_size) {
MS_LOG(ERROR) << "" << __FUNCTION__ << " requires " << args_size << " parameters, while the input size is "
<< args.size() << ".";
MS_LOG(ERROR) << __FUNCTION__ << " requires " << args_size << " parameters, while the input size is " << args.size()
<< ".";
return;
}
......@@ -295,7 +295,7 @@ void FinalVM::InstPartial(const VectorRef &args) {
MS_LOG(DEBUG) << "Start";
const size_t args_size = 1;
if (args.size() < args_size) {
MS_LOG(ERROR) << "" << __FUNCTION__ << " requires " << args_size << " or more parameters, while the input size is "
MS_LOG(ERROR) << __FUNCTION__ << " requires " << args_size << " or more parameters, while the input size is "
<< args.size() << ".";
return;
}
......@@ -314,8 +314,8 @@ void FinalVM::InstPartial(const VectorRef &args) {
void FinalVM::InstSimuSwitch(const VectorRef &args) {
const size_t args_size = 4;
if (args.size() != args_size) {
MS_LOG(ERROR) << "" << __FUNCTION__ << " requires " << args_size << " parameters, while the input size is "
<< args.size() << ".";
MS_LOG(ERROR) << __FUNCTION__ << " requires " << args_size << " parameters, while the input size is " << args.size()
<< ".";
return;
}
bool cond = utils::cast<bool>(args[0]);
......@@ -368,8 +368,8 @@ void FinalVM::InstSimuSwitch(const VectorRef &args) {
void FinalVM::InstRealSwitch(const VectorRef &args) {
const size_t args_size = 3;
if (args.size() != args_size) {
MS_LOG(ERROR) << "" << __FUNCTION__ << " requires " << args_size << " parameters, while the input size is "
<< args.size() << ".";
MS_LOG(ERROR) << __FUNCTION__ << " requires " << args_size << " parameters, while the input size is " << args.size()
<< ".";
return;
}
......@@ -378,7 +378,7 @@ void FinalVM::InstRealSwitch(const VectorRef &args) {
int vfalse = utils::cast<int>(args[2]);
BaseRef c = Ref(cond);
MS_LOG(DEBUG) << "" << vtrue << " false:" << vfalse << " InstSwitch: " << c.ToString();
MS_LOG(DEBUG) << vtrue << " false:" << vfalse << " InstSwitch: " << c.ToString();
bool bool_value = false;
if (backend_->GetCond(c, &bool_value)) {
MS_LOG(DEBUG) << "Cond:" << bool_value;
......@@ -417,8 +417,8 @@ void FinalVM::InstPush(const VectorRef &args) {
MS_LOG(DEBUG) << "Start";
const size_t args_size = 1;
if (args.size() != args_size) {
MS_LOG(ERROR) << "" << __FUNCTION__ << " requires " << args_size << " parameter, while the input size is "
<< args.size() << ".";
MS_LOG(ERROR) << __FUNCTION__ << " requires " << args_size << " parameter, while the input size is " << args.size()
<< ".";
return;
}
......@@ -431,8 +431,8 @@ void FinalVM::InstInput(const VectorRef &args) {
MS_LOG(DEBUG) << "Start";
const size_t args_size = 1;
if (args.size() != args_size) {
MS_LOG(ERROR) << "" << __FUNCTION__ << " requires " << args_size << " parameter, while the input size is "
<< args.size() << ".";
MS_LOG(ERROR) << __FUNCTION__ << " requires " << args_size << " parameter, while the input size is " << args.size()
<< ".";
return;
}
......@@ -445,13 +445,13 @@ void FinalVM::InstPadStack(const VectorRef &args) {
MS_LOG(DEBUG) << "Start";
const size_t args_size = 1;
if (args.size() != args_size) {
MS_LOG(ERROR) << "" << __FUNCTION__ << " requires " << args_size << " parameter, while the input size is "
<< args.size() << ".";
MS_LOG(ERROR) << __FUNCTION__ << " requires " << args_size << " parameter, while the input size is " << args.size()
<< ".";
return;
}
int sz = utils::cast<int>(args[0]);
MS_LOG(DEBUG) << "" << insts_stack_.size() << " need padstack " << sz << " sp_ " << sp_;
MS_LOG(DEBUG) << insts_stack_.size() << " need padstack " << sz << " sp_ " << sp_;
size_t stack_size = insts_stack_.size();
int need = sz - (static_cast<int>(stack_size) - sp_);
if (need > 0) {
......@@ -501,7 +501,7 @@ void FinalVM::InstPushPrim(const VectorRef &args) {
MS_LOG(DEBUG) << "Start: " << args.size();
const size_t args_size = 2;
if (args.size() < args_size) {
MS_LOG(ERROR) << "" << __FUNCTION__ << " requires " << args_size << " or more parameters, while the input size is "
MS_LOG(ERROR) << __FUNCTION__ << " requires " << args_size << " or more parameters, while the input size is "
<< args.size() << ".";
return;
}
......
......@@ -445,7 +445,7 @@ BaseRef RunOperation(const PrimitivePtr &prim, const VectorRef &args) {
MS_LOG(DEBUG) << "operation start " << prim->name();
auto func = operation != nullptr ? operation->GetComputeFunction() : prim->GetComputeFunction();
if (py::isinstance<py::none>(func)) {
MS_LOG(EXCEPTION) << "" << prim->name() << " 's compute function is not implemented";
MS_LOG(EXCEPTION) << prim->name() << " 's compute function is not implemented";
}
py::tuple py_args = py::tuple(args.size());
......
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