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Wire in dense gather. #921

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Aug 12, 2019
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Wire in dense gather. #921

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20 changes: 18 additions & 2 deletions torch_xla/csrc/ops/gather.cpp
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Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
#include "torch_xla/csrc/ops/gather.h"

#include "tensorflow/compiler/xla/client/lib/slicing.h"
#include "tensorflow/compiler/xla/shape_util.h"
#include "tensorflow/compiler/xla/xla_client/util.h"
#include "torch_xla/csrc/helpers.h"
#include "torch_xla/csrc/lowering_context.h"
Expand All @@ -11,11 +12,24 @@ namespace ir {
namespace ops {
namespace {

bool IsSparseGather(const xla::XlaOp& input, const xla::XlaOp& index,
xla::int64 dim) {
xla::Shape input_shape = XlaHelpers::ShapeOfXlaOp(input);
xla::Shape index_shape = XlaHelpers::ShapeOfXlaOp(index);
xla::int64 input_elements = xla::ShapeUtil::ElementsIn(input_shape);
xla::int64 index_elements = xla::ShapeUtil::ElementsIn(index_shape);
// Simple heuristic. Might need fine tuning.
return index_elements < input_elements / 3;
}

xla::Shape NodeOutputShape(const Value& input, const Value& index,
xla::int64 dim) {
auto lower_for_shape_fn =
[&](tensorflow::gtl::ArraySlice<const xla::XlaOp> operands)
-> xla::XlaOp { return TorchGather(operands[0], operands[1], dim); };
-> xla::XlaOp {
return TorchGather(operands[0], operands[1], dim,
IsSparseGather(operands[0], operands[1], dim));
};
return InferOutputShape({input.shape(), index.shape()}, lower_for_shape_fn);
}

Expand All @@ -34,7 +48,9 @@ NodePtr Gather::Clone(OpList operands) const {
XlaOpVector Gather::Lower(LoweringContext* loctx) const {
xla::XlaOp input = loctx->GetOutputOp(operand(0));
xla::XlaOp index = loctx->GetOutputOp(operand(1));
return ReturnOp(TorchGather(input, index, dim_), loctx);
return ReturnOp(
TorchGather(input, index, dim_, IsSparseGather(input, index, dim_)),
loctx);
}

std::string Gather::ToString() const {
Expand Down