Commit 1b2680d4 authored by umangyadav's avatar umangyadav
Browse files

add option to use reduce_sum in parse_instancnorm

parent 66c91c9e
...@@ -44,7 +44,7 @@ struct parse_instancenorm : op_parser<parse_instancenorm> ...@@ -44,7 +44,7 @@ struct parse_instancenorm : op_parser<parse_instancenorm>
// y = scale * ( x - mean ) / sqrt ( variance + epsilon ) + bias // y = scale * ( x - mean ) / sqrt ( variance + epsilon ) + bias
// mean = reduce_mean({D1, D2, ... Dk}, x) // mean = reduce_mean({D1, D2, ... Dk}, x)
// variance = reduce_mean({D1, D2, ... Dk}, (x - mean)^2) // variance = reduce_mean({D1, D2, ... Dk}, (x - mean)^2)
bool convert_fp16 = true; bool convert_fp16 = false;
float epsilon = 1e-5f; float epsilon = 1e-5f;
if(contains(info.attributes, "epsilon")) if(contains(info.attributes, "epsilon"))
{ {
...@@ -82,13 +82,24 @@ struct parse_instancenorm : op_parser<parse_instancenorm> ...@@ -82,13 +82,24 @@ struct parse_instancenorm : op_parser<parse_instancenorm>
std::vector<int64_t> axes(kdims); std::vector<int64_t> axes(kdims);
std::iota(axes.begin(), axes.end(), 2); std::iota(axes.begin(), axes.end(), 2);
auto mean = info.add_instruction(make_op("reduce_mean", {{"axes", axes}}), x); auto mean = info.add_instruction(make_op("reduce_mean", {{"axes", axes}}), x);
auto mean_bcast = auto mean_bcast =
info.add_instruction(make_op("multibroadcast", {{"out_lens", dims}}), mean); info.add_instruction(make_op("multibroadcast", {{"out_lens", dims}}), mean);
auto l1 = info.add_instruction(make_op("sub"), x, mean_bcast);
std::string reduce_op_name = (dtype == shape::half_type) ? "reduce_sum" : "reduce_mean";
if(dtype == shape::half_type)
{
double n =
std::accumulate(dims.begin() + 2, dims.end(), 1, [&](const auto& i, const auto& j) {
return i * j;
});
n = 1.0 / std::sqrt(n);
auto n_literal = info.add_literal(literal{dtype, {n}});
mean_bcast = info.add_common_op("mul", {mean_bcast, n_literal});
x = info.add_common_op("mul", {x, n_literal});
}
auto l0 = info.add_instruction(make_op("sqdiff"), x, mean_bcast); auto l0 = info.add_instruction(make_op("sqdiff"), x, mean_bcast);
auto variance = info.add_instruction(make_op("reduce_mean", {{"axes", axes}}), l0); auto variance = info.add_instruction(make_op(reduce_op_name, {{"axes", axes}}), l0);
auto l1 = info.add_instruction(make_op("sub"), x, mean_bcast);
auto epsilon_literal = info.add_literal(literal{shape{literal_dtype}, {epsilon}}); auto epsilon_literal = info.add_literal(literal{shape{literal_dtype}, {epsilon}});
auto epsilon_bcast = auto epsilon_bcast =
info.add_instruction(make_op("multibroadcast", {{"out_lens", dims}}), epsilon_literal); info.add_instruction(make_op("multibroadcast", {{"out_lens", dims}}), epsilon_literal);
...@@ -99,7 +110,6 @@ struct parse_instancenorm : op_parser<parse_instancenorm> ...@@ -99,7 +110,6 @@ struct parse_instancenorm : op_parser<parse_instancenorm>
auto l4 = info.add_instruction(make_op("mul"), l1, l3); auto l4 = info.add_instruction(make_op("mul"), l1, l3);
auto scale_bcast = auto scale_bcast =
info.add_instruction(make_op("broadcast", {{"axis", 1}, {"out_lens", dims}}), scale); info.add_instruction(make_op("broadcast", {{"axis", 1}, {"out_lens", dims}}), scale);
;
auto bias_bcast = auto bias_bcast =
info.add_instruction(make_op("broadcast", {{"axis", 1}, {"out_lens", dims}}), bias); info.add_instruction(make_op("broadcast", {{"axis", 1}, {"out_lens", dims}}), bias);
auto l5 = info.add_instruction(make_op("mul"), l4, scale_bcast); auto l5 = info.add_instruction(make_op("mul"), l4, scale_bcast);
......
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