Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Add half-precision datatype support #524

Open
wants to merge 8 commits into
base: master
Choose a base branch
from
Open

Add half-precision datatype support #524

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
8 commits
Select commit Hold shift + click to select a range
cc3d268
Initial - Add DT_HALF support
kanvi-nervana Jun 11, 2020
e3b742a
Fix half-precision cast issues
Jun 11, 2020
ed72cc0
Format
Jun 11, 2020
9ba5778
Treat DT_HALF as a float before converting it to ng::float16
Jun 12, 2020
0d42b63
Merge branch 'Kanvi/one_hot_debug' of github.com:tensorflow/ngraph-br…
Jun 12, 2020
fdc5a48
Code format
Jun 12, 2020
cfd71b0
Merge branch 'master' into Kanvi/one_hot_debug
adk9 Jun 30, 2020
dea4180
Merge branch 'master' into Kanvi/one_hot_debug
adk9 Jul 30, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
7 changes: 6 additions & 1 deletion ngraph_bridge/ngraph_builder.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -247,6 +247,9 @@ static Status TensorDataToVector(const Tensor& tensor, std::vector<T>* vector) {
// Else we have to convert.
else {
switch (dt) {
case DT_HALF:
ConvertTensorDataToVector<Eigen::half, T>(tensor, vector);
break;
case DT_FLOAT:
ConvertTensorDataToVector<float, T>(tensor, vector);
break;
Expand Down Expand Up @@ -350,7 +353,9 @@ Builder::TF_NGRAPH_CONST_MAP() {
{DataType::DT_UINT16,
make_pair(MakeConstOp<uint16>, ng::element::u16)},
{DataType::DT_BOOL,
make_pair(MakeConstOp<bool, char>, ng::element::boolean)}};
make_pair(MakeConstOp<bool, char>, ng::element::boolean)},
{DataType::DT_HALF,
make_pair(MakeConstOp<float, ng::float16>, ng::element::f16)}};
return the_map;
}

Expand Down
3 changes: 1 addition & 2 deletions ngraph_bridge/ngraph_mark_for_clustering.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -77,9 +77,7 @@ static Status TypeConstraintOk(Node* node,
for (const auto& name_and_set : itr->second) {
auto& type_attr_name = name_and_set.first;
auto& allowed_types = name_and_set.second;

DataType dt;

if (GetNodeAttr(node->attrs(), type_attr_name, &dt) != Status::OK() ||
std::find(allowed_types.begin(), allowed_types.end(), dt) ==
allowed_types.end()) {
Expand Down Expand Up @@ -566,6 +564,7 @@ const TypeConstraintMap& GetTypeConstraintMap() {
type_constraint_map["NonMaxSuppressionV4"]["T"] = {
DT_FLOAT}; // TF allows half too
type_constraint_map["OneHot"]["T"] = NGraphDTypes();
type_constraint_map["OneHot"]["TI"] = NGraphIndexDTypes();
type_constraint_map["Pack"]["T"] = NGraphDTypes();
type_constraint_map["Pad"]["T"] = NGraphDTypes();
type_constraint_map["Pad"]["Tpaddings"] = NGraphIndexDTypes();
Expand Down
17 changes: 9 additions & 8 deletions ngraph_bridge/ngraph_utils.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -293,23 +293,23 @@ void print_node_histogram(const std::unordered_map<string, int>& histogram,

const gtl::ArraySlice<DataType>& NGraphDTypes() {
static gtl::ArraySlice<DataType> result{
DT_FLOAT, DT_DOUBLE, DT_INT8, DT_INT16, DT_INT32,
DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32, DT_UINT64,
DT_BOOL, DT_QINT8, DT_QUINT8, DT_BFLOAT16};
DT_FLOAT, DT_DOUBLE, DT_INT8, DT_INT16, DT_INT32,
DT_INT64, DT_UINT8, DT_UINT16, DT_UINT32, DT_UINT64,
DT_BOOL, DT_QINT8, DT_QUINT8, DT_BFLOAT16, DT_HALF};
return result;
}

const gtl::ArraySlice<DataType>& NGraphNumericDTypes() {
static gtl::ArraySlice<DataType> result{
DT_FLOAT, DT_DOUBLE, DT_INT8, DT_INT16, DT_INT32, DT_INT64,
DT_UINT8, DT_UINT16, DT_UINT32, DT_UINT64, DT_BFLOAT16};
DT_FLOAT, DT_DOUBLE, DT_INT8, DT_INT16, DT_INT32, DT_INT64,
DT_UINT8, DT_UINT16, DT_UINT32, DT_UINT64, DT_BFLOAT16, DT_HALF};
return result;
}

const gtl::ArraySlice<DataType>& NGraphNumericAndQuantizedDTypes() {
static gtl::ArraySlice<DataType> result{
DT_FLOAT, DT_DOUBLE, DT_INT8, DT_INT16, DT_INT32, DT_INT64,
DT_UINT8, DT_UINT16, DT_UINT32, DT_UINT64, DT_QINT8, DT_QUINT8};
DT_FLOAT, DT_DOUBLE, DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8,
DT_UINT16, DT_UINT32, DT_UINT64, DT_QINT8, DT_QUINT8, DT_HALF};
return result;
}

Expand All @@ -330,7 +330,8 @@ const gtl::ArraySlice<DataType>& NGraphSupportedQuantizedDTypes() {
}

const gtl::ArraySlice<DataType>& NGraphRealDTypes() {
static gtl::ArraySlice<DataType> result{DT_FLOAT, DT_DOUBLE, DT_BFLOAT16};
static gtl::ArraySlice<DataType> result{DT_FLOAT, DT_DOUBLE, DT_BFLOAT16,
DT_HALF};
return result;
}

Expand Down
18 changes: 12 additions & 6 deletions ngraph_bridge/ngraph_utils.h
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -97,7 +97,9 @@ Status ValuesFromConstNode(const NodeDef& node,
return errors::InvalidArgument("Node not a Const");
}

if (node.attr().at("dtype").type() != DataTypeToEnum<T>::value) {
auto dt = node.attr().at("dtype").type();
if (node.attr().count("dtype") == 0 || node.attr().count("value") == 0 ||
(dt != DT_HALF && dt != DataTypeToEnum<T>::value)) {
std::stringstream ss;
ss << "Invalid data type defined for Const. Defined: "
<< node.attr().at("dtype").type();
Expand Down Expand Up @@ -151,25 +153,29 @@ Status ValuesFromConstNode(const NodeDef& node,
switch (dt) {
// TODO(amprocte/NGRAPH-2502): there are more element types to support
// here
case DT_HALF:
val_size = tensor.half_val_size();
if (val_size > 0) val_i = static_cast<T>(tensor.half_val()[i]);
break;
case DT_INT32:
val_size = tensor.int_val_size();
if (val_size > 0) val_i = tensor.int_val()[i];
if (val_size > 0) val_i = static_cast<T>(tensor.int_val()[i]);
break;
case DT_INT64:
val_size = tensor.int64_val_size();
if (val_size > 0) val_i = tensor.int64_val()[i];
if (val_size > 0) val_i = static_cast<T>(tensor.int64_val()[i]);
break;
case DT_FLOAT:
val_size = tensor.float_val_size();
if (val_size > 0) val_i = tensor.float_val()[i];
if (val_size > 0) val_i = static_cast<T>(tensor.float_val()[i]);
break;
case DT_BOOL:
val_size = tensor.bool_val_size();
if (val_size > 0) val_i = tensor.bool_val()[i];
if (val_size > 0) val_i = static_cast<T>(tensor.bool_val()[i]);
break;
case DT_DOUBLE:
val_size = tensor.double_val_size();
if (val_size > 0) val_i = tensor.double_val()[i];
if (val_size > 0) val_i = static_cast<T>(tensor.double_val()[i]);
break;
default:
NGRAPH_VLOG(0)
Expand Down