未验证 提交 a872eb90 编写于 作者: X Xin Pan 提交者: GitHub

Merge pull request #14959 from panyx0718/clean2

Further op RunImpl refactor
......@@ -110,22 +110,125 @@ class CompileTimeInferShapeContext : public InferShapeContext {
}
}
std::vector<InferShapeVarPtr> GetInputVarPtrs(
const std::string &name) override {
const std::vector<std::string> arg_names = Inputs(name);
std::vector<InferShapeVarPtr> res;
res.reserve(arg_names.size());
std::transform(arg_names.begin(), arg_names.end(), std::back_inserter(res),
[this](const std::string &name) {
return block_.FindVarRecursive(name);
});
return res;
}
std::vector<InferShapeVarPtr> GetOutputVarPtrs(
const std::string &name) override {
const std::vector<std::string> arg_names = Outputs(name);
std::vector<InferShapeVarPtr> res;
res.reserve(arg_names.size());
std::transform(arg_names.begin(), arg_names.end(), std::back_inserter(res),
[this](const std::string &name) {
return block_.FindVarRecursive(name);
});
return res;
}
DDim GetInputDim(const std::string &name) const override {
const std::vector<std::string> &arg_names = Inputs(name);
PADDLE_ENFORCE_EQ(arg_names.size(), 1UL,
"Input(%s) should hold one element, but now it holds %d",
name, arg_names.size());
return this->GetDim(arg_names[0]);
}
std::vector<DDim> GetInputsDim(const std::string &name) const override {
const std::vector<std::string> &arg_names = Inputs(name);
return GetDims(arg_names);
}
bool IsRuntime() const override;
std::vector<proto::VarType::Type> GetInputsVarType(
const std::string &name) const override {
return GetVarTypes(Inputs(name));
}
std::vector<proto::VarType::Type> GetOutputsVarType(
const std::string &name) const override {
return GetVarTypes(Outputs(name));
}
void SetOutputDim(const std::string &name, const DDim &dim) override {
auto &arg_names = Outputs(name);
PADDLE_ENFORCE_EQ(arg_names.size(), 1UL,
"Output(%s) should hold one element, but now it holds %d",
name, arg_names.size());
SetDim(arg_names[0], dim);
}
void SetOutputsDim(const std::string &name,
const std::vector<DDim> &dims) override {
auto &names = Outputs(name);
SetDims(names, dims);
}
protected:
proto::VarType::Type GetVarType(const std::string &name) const override;
std::vector<proto::VarType::Type> GetVarTypes(
const std::vector<std::string> &names) const {
std::vector<proto::VarType::Type> retv;
retv.resize(names.size());
std::transform(
names.begin(), names.end(), retv.begin(),
std::bind(std::mem_fn(&CompileTimeInferShapeContext::GetVarType), this,
std::placeholders::_1));
return retv;
}
proto::VarType::Type GetVarType(const std::string &name) const;
DDim GetDim(const std::string &name) const {
auto var = block_.FindVarRecursive(name);
PADDLE_ENFORCE(var != nullptr, "Cannot find variable %s", name);
DDim res;
try {
auto shape = var->GetShape();
res = shape.empty() ? make_ddim({0UL}) : make_ddim(shape);
} catch (...) {
VLOG(5) << "GetDim of variable " << name << " error";
std::rethrow_exception(std::current_exception());
}
return res;
}
DDim GetDim(const std::string &name) const override;
std::vector<DDim> GetDims(const std::vector<std::string> &names) const {
std::vector<DDim> ret;
ret.reserve(names.size());
std::transform(
names.begin(), names.end(), std::back_inserter(ret),
[this](const std::string &name) { return this->GetDim(name); });
return ret;
}
void SetDim(const std::string &name, const DDim &dim);
void SetDim(const std::string &name, const DDim &dim) override;
void SetDims(const std::vector<std::string> &names,
const std::vector<DDim> &dims) {
size_t length = names.size();
PADDLE_ENFORCE_EQ(length, dims.size());
for (size_t i = 0; i < length; ++i) {
if (names[i] == framework::kEmptyVarName) {
continue;
}
SetDim(names[i], dims[i]);
}
}
std::vector<DDim> GetRepeatedDims(const std::string &name) const override;
void SetRepeatedDims(const std::string &name,
const std::vector<DDim> &dims) override;
InferShapeVarPtr GetVarPtr(const std::string &name) override;
const OpDesc &op_;
const BlockDesc &block_;
};
......@@ -644,20 +747,6 @@ const std::vector<std::string> &CompileTimeInferShapeContext::Outputs(
return op_.Output(name);
}
DDim CompileTimeInferShapeContext::GetDim(const std::string &name) const {
auto var = block_.FindVarRecursive(name);
PADDLE_ENFORCE(var != nullptr, "Cannot find variable %s", name);
DDim res;
try {
auto shape = var->GetShape();
res = shape.empty() ? make_ddim({0UL}) : make_ddim(shape);
} catch (...) {
VLOG(5) << "GetDim of variable " << name << " error";
std::rethrow_exception(std::current_exception());
}
return res;
}
std::vector<DDim> CompileTimeInferShapeContext::GetRepeatedDims(
const std::string &name) const {
auto var = block_.FindVarRecursive(name);
......@@ -696,10 +785,5 @@ proto::VarType::Type CompileTimeInferShapeContext::GetVarType(
return block_.FindVarRecursive(name)->GetType();
}
InferShapeVarPtr CompileTimeInferShapeContext::GetVarPtr(
const std::string &name) {
return block_.FindVarRecursive(name);
}
} // namespace framework
} // namespace paddle
......@@ -142,12 +142,14 @@ RuntimeContext::RuntimeContext(const VariableNameMap& innames,
const Scope& scope) {
for (auto& var_name_item : innames) {
std::vector<Variable*>& input_vars = inputs[var_name_item.first];
input_vars.reserve(var_name_item.second.size());
for (auto& var_name : var_name_item.second) {
input_vars.push_back(scope.FindVar(var_name));
}
}
for (auto& var_name_item : outnames) {
std::vector<Variable*>& output_vars = outputs[var_name_item.first];
output_vars.reserve(var_name_item.second.size());
for (auto& var_name : var_name_item.second) {
output_vars.push_back(scope.FindVar(var_name));
}
......@@ -556,30 +558,28 @@ class RuntimeInferShapeContext : public InferShapeContext {
bool HasOutput(const std::string& name) const override {
// has only one output
const auto& outs = op_.Outputs();
const auto& outs = ctx_.outputs;
auto it = outs.find(name);
if (it == outs.end()) {
return false;
}
const auto& out = it->second;
if (out.size() == 0 || out[0] == kEmptyVarName) {
if (out.size() == 0) {
return false;
}
PADDLE_ENFORCE_EQ(out.size(), 1UL,
"Output %s should not have more than one outputs", name);
return scope_.FindVar(out[0]) != nullptr;
return out[0] != nullptr;
}
bool HasInputs(const std::string& name) const override {
if (!op_.HasInputs(name)) {
return false;
}
auto inputs = op_.Inputs(name);
if (inputs.empty()) {
const auto& ins = ctx_.inputs;
auto it = ins.find(name);
if (it == ins.end() || it->second.empty()) {
return false;
}
for (auto& input : inputs) {
if (scope_.FindVar(input) == nullptr) {
for (auto& input : it->second) {
if (input == nullptr) {
return false;
}
}
......@@ -587,15 +587,13 @@ class RuntimeInferShapeContext : public InferShapeContext {
}
bool HasOutputs(const std::string& name) const override {
if (!op_.HasOutputs(name)) {
return false;
}
auto outputs = op_.Outputs(name);
if (outputs.empty()) {
const auto& outs = ctx_.outputs;
auto it = outs.find(name);
if (it == outs.end() || it->second.empty()) {
return false;
}
for (auto& output : outputs) {
if (scope_.FindVar(output) == nullptr) {
for (auto& output : it->second) {
if (output == nullptr) {
return false;
}
}
......@@ -616,16 +614,18 @@ class RuntimeInferShapeContext : public InferShapeContext {
void ShareDim(const std::string& in, const std::string& out, size_t i = 0,
size_t j = 0) override {
PADDLE_ENFORCE_LT(i, Inputs(in).size());
PADDLE_ENFORCE_LT(j, Outputs(out).size());
const std::string& input_n = Inputs(in)[i];
const std::string& output_n = Outputs(out)[j];
auto in_it = ctx_.inputs.find(in);
auto out_it = ctx_.outputs.find(out);
PADDLE_ENFORCE(in_it != ctx_.inputs.end() && in_it->second.size() > i,
"Inputs %s should have %llu argument", in, i);
PADDLE_ENFORCE(out_it != ctx_.outputs.end() && out_it->second.size() > j,
"Outputs %s should have %llu argument", out, j);
Variable* in_var = in_it->second[i];
Variable* out_var = out_it->second[j];
Variable* in_var = scope_.FindVar(input_n);
Variable* out_var = scope_.FindVar(output_n);
PADDLE_ENFORCE(in_var->Type() == out_var->Type(),
"The type of %s and %s is not the same.", output_n,
GetDim(input_n));
"The type of %s and %s is not the same.", in, out);
if (in_var->IsType<framework::SelectedRows>()) {
auto& in_sele_rows = in_var->Get<framework::SelectedRows>();
......@@ -646,13 +646,16 @@ class RuntimeInferShapeContext : public InferShapeContext {
void ShareLoD(const std::string& in, const std::string& out, size_t i = 0,
size_t j = 0) const override {
const std::vector<std::string>& inputs = Inputs(in);
const std::vector<std::string>& outputs = Outputs(out);
PADDLE_ENFORCE_LT(i, inputs.size());
PADDLE_ENFORCE_LT(j, outputs.size());
Variable* in_var = scope_.FindVar(inputs.at(i));
auto in_it = ctx_.inputs.find(in);
auto out_it = ctx_.outputs.find(out);
PADDLE_ENFORCE(in_it != ctx_.inputs.end() && in_it->second.size() > i,
"Inputs %s should have %llu argument", in, i);
PADDLE_ENFORCE(out_it != ctx_.outputs.end() && out_it->second.size() > j,
"Outputs %s should have %llu argument", out, j);
Variable* in_var = in_it->second.at(i);
if (!in_var->IsType<LoDTensor>()) return;
Variable* out_var = scope_.FindVar(outputs.at(j));
Variable* out_var = out_it->second.at(j);
PADDLE_ENFORCE(out_var->IsType<LoDTensor>(),
"The %d-th output of Output(%s) must be LoDTensor.", j, out);
auto in_tensor = in_var->Get<LoDTensor>();
......@@ -687,9 +690,64 @@ class RuntimeInferShapeContext : public InferShapeContext {
bool IsRuntime() const override { return true; }
// TODO(paddle-dev): Can this be template?
std::vector<InferShapeVarPtr> GetInputVarPtrs(
const std::string& name) override {
const std::vector<Variable*>& vars = InputVars(name);
std::vector<InferShapeVarPtr> res;
res.reserve(vars.size());
res.insert(res.begin(), vars.begin(), vars.end());
return res;
}
std::vector<InferShapeVarPtr> GetOutputVarPtrs(
const std::string& name) override {
const std::vector<Variable*>& vars = OutputVars(name);
std::vector<InferShapeVarPtr> res;
res.reserve(vars.size());
res.insert(res.begin(), vars.begin(), vars.end());
return res;
}
DDim GetInputDim(const std::string& name) const override {
const std::vector<Variable*>& vars = InputVars(name);
PADDLE_ENFORCE_EQ(vars.size(), 1UL,
"Input(%s) should hold one element, but now it holds %d",
name, vars.size());
return this->GetDim(vars[0]);
}
std::vector<DDim> GetInputsDim(const std::string& name) const override {
const std::vector<Variable*>& vars = InputVars(name);
return GetDims(vars);
}
std::vector<proto::VarType::Type> GetInputsVarType(
const std::string& name) const override {
return GetVarTypes(InputVars(name));
}
std::vector<proto::VarType::Type> GetOutputsVarType(
const std::string& name) const override {
return GetVarTypes(OutputVars(name));
}
void SetOutputDim(const std::string& name, const DDim& dim) override {
auto& vars = OutputVars(name);
PADDLE_ENFORCE_EQ(vars.size(), 1UL,
"Output(%s) should hold one element, but now it holds %d",
name, vars.size());
SetDim(vars[0], dim);
}
void SetOutputsDim(const std::string& name,
const std::vector<DDim>& dims) override {
auto& vars = OutputVars(name);
SetDims(vars, dims);
}
protected:
DDim GetDim(const std::string& name) const override {
Variable* var = scope_.FindVar(name);
DDim GetDim(Variable* var) const {
PADDLE_ENFORCE_NOT_NULL(var);
if (var->IsType<LoDTensor>()) {
return var->Get<LoDTensor>().dims();
......@@ -697,25 +755,44 @@ class RuntimeInferShapeContext : public InferShapeContext {
return var->Get<SelectedRows>().GetCompleteDims();
} else {
PADDLE_THROW(
"Only LoDTensor/SelectedRows support 'GetDim', but Variable %s's "
"Only LoDTensor/SelectedRows support 'GetDim', but Variables "
"type_id is %s.",
name, var->Type().name());
var->Type().name());
}
}
std::vector<DDim> GetDims(const std::vector<Variable*>& vars) const {
std::vector<DDim> ret;
ret.reserve(vars.size());
std::transform(vars.begin(), vars.end(), std::back_inserter(ret),
[this](Variable* var) { return this->GetDim(var); });
return ret;
}
std::vector<DDim> GetRepeatedDims(const std::string& name) const override {
PADDLE_THROW("Only compile time support this method");
}
void SetDim(const std::string& name, const DDim& dim) override {
Variable* var = scope_.FindVar(name);
void SetDim(Variable* var, const DDim& dim) {
if (var->IsType<LoDTensor>()) {
var->GetMutable<LoDTensor>()->Resize(dim);
} else if (var->IsType<SelectedRows>()) {
var->GetMutable<SelectedRows>()->set_height(dim[0]);
} else {
PADDLE_THROW("Variable %s type_id %s, expect LoDTensor/SelectedRows.",
name, var->Type().name());
PADDLE_THROW("Variable type_id %s, expect LoDTensor/SelectedRows.",
var->Type().name());
}
}
void SetDims(const std::vector<Variable*>& vars,
const std::vector<DDim>& dims) {
size_t length = vars.size();
PADDLE_ENFORCE_EQ(length, dims.size());
for (size_t i = 0; i < length; ++i) {
if (vars[i] == nullptr) {
continue;
}
SetDim(vars[i], dims[i]);
}
}
......@@ -724,16 +801,36 @@ class RuntimeInferShapeContext : public InferShapeContext {
PADDLE_THROW("Only compile time support this method");
}
proto::VarType::Type GetVarType(const std::string& name) const override {
auto* var = scope_.FindVar(name);
return ToVarType(var->Type());
std::vector<proto::VarType::Type> GetVarTypes(
const std::vector<Variable*>& vars) const {
std::vector<proto::VarType::Type> retv;
retv.resize(vars.size());
std::transform(vars.begin(), vars.end(), retv.begin(),
std::bind(std::mem_fn(&RuntimeInferShapeContext::GetVarType),
this, std::placeholders::_1));
return retv;
}
InferShapeVarPtr GetVarPtr(const std::string& name) override {
return scope_.FindVar(name);
proto::VarType::Type GetVarType(Variable* var) const {
return ToVarType(var->Type());
}
private:
const std::vector<Variable*>& InputVars(const std::string& name) const {
auto it = ctx_.inputs.find(name);
PADDLE_ENFORCE(it != ctx_.inputs.end(),
"Operator %s does not have the input %s.", op_.Type(), name);
return it->second;
}
const std::vector<Variable*>& OutputVars(const std::string& name) const {
auto it = ctx_.outputs.find(name);
PADDLE_ENFORCE(it != ctx_.outputs.end(),
"Operator %s does not have the outputs %s.", op_.Type(),
name);
return it->second;
}
const OperatorBase& op_;
const Scope& scope_;
const RuntimeContext& ctx_;
......@@ -864,8 +961,7 @@ Scope* OperatorWithKernel::PrepareData(
for (size_t i = 0; i < var_name_item.second.size(); ++i) {
auto& var_name = var_name_item.second[i];
auto* var = scope.FindVar(var_name);
input_vars[i] = var;
auto* var = input_vars[i];
// Only tensor can be tranfer to another device.
if (var == nullptr || !VarIsTensor(*var)) {
......
......@@ -22,20 +22,6 @@ limitations under the License. */
namespace paddle {
namespace framework {
DDim InferShapeContext::GetInputDim(const std::string &name) const {
const std::vector<std::string> &arg_names = Inputs(name);
PADDLE_ENFORCE_EQ(arg_names.size(), 1UL,
"Input(%s) should hold one element, but now it holds %d",
name, arg_names.size());
return this->GetDim(arg_names[0]);
}
std::vector<DDim> InferShapeContext::GetInputsDim(
const std::string &name) const {
const std::vector<std::string> &arg_names = Inputs(name);
return GetDims(arg_names);
}
std::vector<DDim> InferShapeContext::GetReaderDims(
const std::string &name) const {
const std::vector<std::string> &arg_names = Inputs(name);
......@@ -46,26 +32,6 @@ std::vector<DDim> InferShapeContext::GetReaderDims(
return this->GetRepeatedDims(arg_names[0]);
}
DDim InferShapeContext::GetInputsElementDim(const std::string &name,
int idx) const {
const std::vector<std::string> &names = Inputs(name);
return this->GetDim(names[idx]);
}
void InferShapeContext::SetOutputDim(const std::string &name, const DDim &dim) {
auto &arg_names = Outputs(name);
PADDLE_ENFORCE_EQ(arg_names.size(), 1UL,
"Output(%s) should hold one element, but now it holds %d",
name, arg_names.size());
SetDim(arg_names[0], dim);
}
void InferShapeContext::SetOutputsDim(const std::string &name,
const std::vector<DDim> &dims) {
auto &names = Outputs(name);
SetDims(names, dims);
}
void InferShapeContext::SetReaderDims(const std::string &name,
const std::vector<DDim> &dims) {
const std::vector<std::string> &arg_names = Outputs(name);
......@@ -76,69 +42,5 @@ void InferShapeContext::SetReaderDims(const std::string &name,
return this->SetRepeatedDims(arg_names[0], dims);
}
std::vector<InferShapeVarPtr> InferShapeContext::GetInputVarPtrs(
const std::string &name) {
const std::vector<std::string> arg_names = Inputs(name);
std::vector<InferShapeVarPtr> res;
res.reserve(arg_names.size());
std::transform(
arg_names.begin(), arg_names.end(), std::back_inserter(res),
[this](const std::string &name) { return this->GetVarPtr(name); });
return res;
}
std::vector<InferShapeVarPtr> InferShapeContext::GetOutputVarPtrs(
const std::string &name) {
const std::vector<std::string> arg_names = Outputs(name);
std::vector<InferShapeVarPtr> res;
res.reserve(arg_names.size());
std::transform(
arg_names.begin(), arg_names.end(), std::back_inserter(res),
[this](const std::string &name) { return this->GetVarPtr(name); });
return res;
}
std::vector<DDim> InferShapeContext::GetDims(
const std::vector<std::string> &names) const {
std::vector<DDim> ret;
ret.reserve(names.size());
std::transform(
names.begin(), names.end(), std::back_inserter(ret),
[this](const std::string &name) { return this->GetDim(name); });
return ret;
}
void InferShapeContext::SetDims(const std::vector<std::string> &names,
const std::vector<DDim> &dims) {
size_t length = names.size();
PADDLE_ENFORCE_EQ(length, dims.size());
for (size_t i = 0; i < length; ++i) {
if (names[i] == framework::kEmptyVarName) {
continue;
}
SetDim(names[i], dims[i]);
}
}
std::vector<proto::VarType::Type> InferShapeContext::GetInputsVarType(
const std::string &name) const {
return GetVarTypes(Inputs(name));
}
std::vector<proto::VarType::Type> InferShapeContext::GetOutputsVarType(
const std::string &name) const {
return GetVarTypes(Outputs(name));
}
std::vector<proto::VarType::Type> InferShapeContext::GetVarTypes(
const std::vector<std::string> &names) const {
std::vector<proto::VarType::Type> retv;
retv.resize(names.size());
std::transform(names.begin(), names.end(), retv.begin(),
std::bind(std::mem_fn(&InferShapeContext::GetVarType), this,
std::placeholders::_1));
return retv;
}
} // namespace framework
} // namespace paddle
......@@ -33,22 +33,23 @@ class InferShapeContext {
virtual bool HasInput(const std::string &name) const = 0;
virtual bool HasOutput(const std::string &name) const = 0;
std::vector<proto::VarType::Type> GetInputsVarType(
const std::string &name) const;
std::vector<proto::VarType::Type> GetOutputsVarType(
const std::string &name) const;
virtual std::vector<proto::VarType::Type> GetInputsVarType(
const std::string &name) const = 0;
virtual std::vector<proto::VarType::Type> GetOutputsVarType(
const std::string &name) const = 0;
virtual bool HasInputs(const std::string &name) const = 0;
virtual bool HasOutputs(const std::string &name) const = 0;
DDim GetInputDim(const std::string &name) const;
std::vector<DDim> GetInputsDim(const std::string &name) const;
std::vector<DDim> GetReaderDims(const std::string &name) const;
DDim GetInputsElementDim(const std::string &name, int idx) const;
virtual DDim GetInputDim(const std::string &name) const = 0;
virtual std::vector<DDim> GetInputsDim(const std::string &name) const = 0;
virtual std::vector<DDim> GetReaderDims(const std::string &name) const;
void SetOutputDim(const std::string &name, const DDim &dim);
void SetOutputsDim(const std::string &name, const std::vector<DDim> &dims);
void SetReaderDims(const std::string &name, const std::vector<DDim> &dims);
virtual void SetOutputDim(const std::string &name, const DDim &dim) = 0;
virtual void SetOutputsDim(const std::string &name,
const std::vector<DDim> &dims) = 0;
virtual void SetReaderDims(const std::string &name,
const std::vector<DDim> &dims);
virtual AttrReader Attrs() const = 0;
virtual const std::vector<std::string> &Inputs(
......@@ -67,27 +68,15 @@ class InferShapeContext {
virtual bool IsRuntime() const = 0;
std::vector<InferShapeVarPtr> GetInputVarPtrs(const std::string &name);
std::vector<InferShapeVarPtr> GetOutputVarPtrs(const std::string &name);
virtual InferShapeVarPtr GetVarPtr(const std::string &name) = 0;
// Note: In while op, we need this to be public
void SetDims(const std::vector<std::string> &names,
const std::vector<DDim> &dims);
virtual std::vector<InferShapeVarPtr> GetInputVarPtrs(
const std::string &name) = 0;
virtual std::vector<InferShapeVarPtr> GetOutputVarPtrs(
const std::string &name) = 0;
protected:
virtual DDim GetDim(const std::string &name) const = 0;
virtual void SetDim(const std::string &name, const DDim &dim) = 0;
virtual std::vector<DDim> GetRepeatedDims(const std::string &name) const = 0;
virtual void SetRepeatedDims(const std::string &name,
const std::vector<DDim> &dims) = 0;
std::vector<DDim> GetDims(const std::vector<std::string> &names) const;
std::vector<proto::VarType::Type> GetVarTypes(
const std::vector<std::string> &names) const;
virtual proto::VarType::Type GetVarType(const std::string &name) const = 0;
};
} // namespace framework
......
......@@ -399,26 +399,41 @@ class WhileGradOpShapeInference : public framework::InferShapeBase {
ctx->HasInputs(kOutputs);
ctx->HasInputs(framework::GradVarName(kOutputs));
auto p_names = ctx->Inputs(kX);
auto pg_ig_names = ctx->Outputs(kXGRAD);
auto var_types = ctx->GetInputsVarType(kX);
std::vector<std::string> names_to_set;
std::vector<framework::DDim> dims_to_set;
for (size_t i = 0; i < p_names.size(); ++i) {
std::vector<framework::InferShapeVarPtr> in_var_ptrs =
ctx->GetInputVarPtrs(kX);
std::vector<framework::InferShapeVarPtr> out_var_ptrs =
ctx->GetOutputVarPtrs(kXGRAD);
PADDLE_ENFORCE(in_var_ptrs.size() == out_var_ptrs.size());
for (size_t i = 0; i < in_var_ptrs.size(); ++i) {
if (pg_ig_names[i] == framework::kEmptyVarName) {
continue;
}
auto dims = ctx->GetInputsElementDim(kX, i);
if (var_types[i] == framework::proto::VarType::LOD_TENSOR) {
names_to_set.push_back(pg_ig_names[i]);
dims_to_set.push_back(dims);
} else if (var_types[i] == framework::proto::VarType::LOD_TENSOR_ARRAY) {
// not sure how to set the dim of LOD_TENSOR_ARRAY
names_to_set.push_back(pg_ig_names[i]);
dims_to_set.push_back(dims);
if (ctx->IsRuntime()) {
framework::Variable *in_var =
boost::get<framework::Variable *>(in_var_ptrs[i]);
framework::Variable *out_var =
boost::get<framework::Variable *>(out_var_ptrs[i]);
auto type = framework::ToVarType(in_var->Type());
if (type == framework::proto::VarType::LOD_TENSOR) {
out_var->GetMutable<LoDTensor>()->Resize(
in_var->Get<framework::LoDTensor>().dims());
} else if (type == framework::proto::VarType::SELECTED_ROWS) {
out_var->GetMutable<framework::SelectedRows>()->set_height(
in_var->Get<framework::SelectedRows>().GetCompleteDims()[0]);
} else if (type == framework::proto::VarType::LOD_TENSOR_ARRAY) {
PADDLE_THROW("WhileGradOp doesn't support type %d",
static_cast<int>(type));
}
} else {
framework::VarDesc *in_var =
boost::get<framework::VarDesc *>(in_var_ptrs[i]);
boost::get<framework::VarDesc *>(out_var_ptrs[i])
->SetShape(in_var->GetShape());
}
}
ctx->SetDims(names_to_set, dims_to_set);
}
};
......
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册