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#include "tensorflow/core/framework/fake_input.h"
#include "tensorflow/core/framework/node_def_util.h"
#include "tensorflow/core/framework/op_def.pb.h"
#include "tensorflow/core/framework/op_def_util.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/public/status.h"
namespace tensorflow {
namespace {
class FakeInputImpl {
public:
FakeInputImpl(const OpDef* op_def, int in_index, const NodeDef* node_def,
NodeDefBuilder* builder);
void SetN(int n);
void SetDataType(DataType dt);
void SetTypeList(DataTypeSlice dts);
Status AddInputToBuilder();
private:
static string FakeNodeName(int in_index);
Status GetN(int* n) const;
Status GetDataType(DataType* dt) const;
void NSources(int n, DataType dt) const;
void SourceList(DataTypeSlice dts) const;
const OpDef* const op_def_;
const OpDef::ArgDef* const arg_;
const string in_node_;
const NodeDef* const node_def_;
NodeDefBuilder* const builder_;
bool n_specified_;
int n_;
bool dt_specified_;
DataType dt_;
bool dts_specified_;
DataTypeSlice dts_;
};
FakeInputImpl::FakeInputImpl(const OpDef* op_def, int in_index,
const NodeDef* node_def, NodeDefBuilder* builder)
: op_def_(op_def),
arg_(&op_def->input_arg(in_index)),
in_node_(FakeNodeName(in_index)),
node_def_(node_def),
builder_(builder),
n_specified_(false),
dt_specified_(false),
dts_specified_(false) {}
void FakeInputImpl::SetN(int n) {
n_specified_ = true;
n_ = n;
}
void FakeInputImpl::SetDataType(DataType dt) {
dt_specified_ = true;
dt_ = dt;
}
void FakeInputImpl::SetTypeList(DataTypeSlice dts) {
dts_specified_ = true;
dts_ = dts;
}
Status FakeInputImpl::AddInputToBuilder() {
if (dts_specified_) {
SourceList(dts_);
} else if (n_specified_ || !arg_->number_attr().empty()) {
int n;
TF_RETURN_IF_ERROR(GetN(&n));
DataType dt;
if (n > 0) {
TF_RETURN_IF_ERROR(GetDataType(&dt));
} else {
dt = DT_FLOAT;
}
NSources(n, dt);
} else {
if (!dt_specified_ && !arg_->type_list_attr().empty()) {
DataTypeVector dts;
Status status =
GetNodeAttr(*node_def_, arg_->type_list_attr(), &dts);
if (!status.ok()) {
return errors::InvalidArgument(
"Could not infer list of types for input '", arg_->name(), "': ",
status.error_message());
}
SourceList(dts);
return Status::OK();
}
DataType dt;
TF_RETURN_IF_ERROR(GetDataType(&dt));
builder_->Input(in_node_, 0, dt);
}
return Status::OK();
}
// static
string FakeInputImpl::FakeNodeName(int in_index) {
char c = 'a' + (in_index % 26);
return string(&c, 1);
}
Status FakeInputImpl::GetN(int* n) const {
if (n_specified_) {
*n = n_;
} else {
Status status = GetNodeAttr(*node_def_, arg_->number_attr(), n);
if (!status.ok()) {
return errors::InvalidArgument("Could not infer length of input '",
arg_->name(), "': ",
status.error_message());
}
}
return Status::OK();
}
Status FakeInputImpl::GetDataType(DataType* dt) const {
if (dt_specified_) {
*dt = dt_;
} else if (arg_->type() != DT_INVALID) {
*dt = arg_->type();
} else if (!arg_->type_attr().empty()) {
Status status = GetNodeAttr(*node_def_, arg_->type_attr(), dt);
if (!status.ok()) {
return errors::InvalidArgument("Could not infer type for input '",
arg_->name(), "': ",
status.error_message());
}
} else {
return errors::InvalidArgument("No type or type_attr field in arg '",
arg_->name(), "'");
}
return Status::OK();
}
void FakeInputImpl::NSources(int n, DataType dt) const {
std::vector<NodeDefBuilder::NodeOut> srcs;
srcs.reserve(n);
for (int i = 0; i < n; ++i) {
srcs.emplace_back(in_node_, i, dt);
}
builder_->Input(srcs);
}
void FakeInputImpl::SourceList(DataTypeSlice dts) const {
std::vector<NodeDefBuilder::NodeOut> srcs;
srcs.reserve(dts.size());
for (size_t i = 0; i < dts.size(); ++i) {
srcs.emplace_back(in_node_, i, dts[i]);
}
builder_->Input(srcs);
}
} // namespace
// Public interface ------------------------------------------------------------
FakeInputFunctor FakeInput() {
return [](const OpDef& op_def, int in_index, const NodeDef& node_def,
NodeDefBuilder* builder) {
FakeInputImpl impl(&op_def, in_index, &node_def, builder);
return impl.AddInputToBuilder();
};
}
FakeInputFunctor FakeInput(DataType dt) {
return [dt](const OpDef& op_def, int in_index, const NodeDef& node_def,
NodeDefBuilder* builder) {
FakeInputImpl impl(&op_def, in_index, &node_def, builder);
impl.SetDataType(dt);
return impl.AddInputToBuilder();
};
}
FakeInputFunctor FakeInput(int n) {
return [n](const OpDef& op_def, int in_index, const NodeDef& node_def,
NodeDefBuilder* builder) {
FakeInputImpl impl(&op_def, in_index, &node_def, builder);
impl.SetN(n);
return impl.AddInputToBuilder();
};
}
FakeInputFunctor FakeInput(int n, DataType dt) {
return [n, dt](const OpDef& op_def, int in_index, const NodeDef& node_def,
NodeDefBuilder* builder) {
FakeInputImpl impl(&op_def, in_index, &node_def, builder);
impl.SetN(n);
impl.SetDataType(dt);
return impl.AddInputToBuilder();
};
}
FakeInputFunctor FakeInput(DataTypeSlice dts) {
// Make a copy to ensure the data will still be around when the lambda is
// called.
DataTypeVector dtv(dts.begin(), dts.end());
return [dtv](const OpDef& op_def, int in_index, const NodeDef& node_def,
NodeDefBuilder* builder) {
FakeInputImpl impl(&op_def, in_index, &node_def, builder);
impl.SetTypeList(dtv);
return impl.AddInputToBuilder();
};
}
} // namespace tensorflow
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