提交 2886245b 编写于 作者: M Megvii Engine Team

perf(imperative/src): improve pad host performance

GitOrigin-RevId: 05223deca753dd862e40f6f8a26c1fca56d8e216
上级 b55942a9
......@@ -1406,6 +1406,7 @@ public:
protected:
SmallVector<size_t> get_offsets();
MGE_WIN_DECLSPEC_FUC static SmallVector<size_t> get_offsets_impl(const Param& p);
void check_exec(const TensorLayout& src, const TensorLayout& dst);
};
......@@ -1421,6 +1422,9 @@ public:
const TensorLayout& src, const TensorLayout& dst) = 0;
void deduce_layout(const TensorLayout& src, TensorLayout& dst);
MGE_WIN_DECLSPEC_FUC static void deduce_layout_impl(
const TensorLayout& src, TensorLayout& dst, const Param& p);
protected:
void forward_check_exec(const TensorLayout& src, const TensorLayout& dst);
};
......
......@@ -7,6 +7,7 @@
namespace megdnn {
using padding_param = megdnn::param_enumv::Padding;
using Param = PaddingBase::Param;
void PaddingForward::forward_check_exec(
const TensorLayout& src, const TensorLayout& dst) {
......@@ -19,8 +20,9 @@ void PaddingForward::forward_check_exec(
"unsupported %s dtype for forward padding opr", src.dtype.name());
}
void PaddingForward::deduce_layout(const TensorLayout& src, TensorLayout& dst) {
SmallVector<size_t> offsets(get_offsets());
void PaddingForward::deduce_layout_impl(
const TensorLayout& src, TensorLayout& dst, const Param& p) {
SmallVector<size_t> offsets(get_offsets_impl(p));
TensorShape dst_shape;
switch (src.ndim) {
case 1:
......@@ -76,6 +78,10 @@ void PaddingForward::deduce_layout(const TensorLayout& src, TensorLayout& dst) {
dst = TensorLayout(dst_shape, src.dtype);
}
void PaddingForward::deduce_layout(const TensorLayout& src, TensorLayout& dst) {
return deduce_layout_impl(src, dst, param());
}
void PaddingBackward::backward_check_exec(
const TensorLayout& src, const TensorLayout& dst) {
check_exec(dst, src);
......@@ -86,17 +92,20 @@ void PaddingBackward::backward_check_exec(
"unsupported %s dtype for forward padding opr", src.dtype.name());
}
SmallVector<size_t> PaddingBase::get_offsets() {
SmallVector<size_t> offsets = {param().front_offset_dim0, param().back_offset_dim0,
param().front_offset_dim1, param().back_offset_dim1,
param().front_offset_dim2, param().back_offset_dim2,
param().front_offset_dim3, param().back_offset_dim3,
param().front_offset_dim4, param().back_offset_dim4,
param().front_offset_dim5, param().back_offset_dim5,
param().front_offset_dim6, param().back_offset_dim6};
SmallVector<size_t> PaddingBase::get_offsets_impl(const Param& p) {
SmallVector<size_t> offsets = {
p.front_offset_dim0, p.back_offset_dim0, p.front_offset_dim1,
p.back_offset_dim1, p.front_offset_dim2, p.back_offset_dim2,
p.front_offset_dim3, p.back_offset_dim3, p.front_offset_dim4,
p.back_offset_dim4, p.front_offset_dim5, p.back_offset_dim5,
p.front_offset_dim6, p.back_offset_dim6};
return offsets;
}
SmallVector<size_t> PaddingBase::get_offsets() {
return get_offsets_impl(param());
}
void PaddingBase::check_exec(const TensorLayout& src, const TensorLayout& dst) {
SmallVector<size_t> offsets(get_offsets());
// make sure the src and dst tensor not empty
......
#include "megbrain/graph/symbol_var.h"
#include "megbrain/imperative/ops/autogen.h"
#include "megbrain/imperative/physical_tensor.h"
#include "megbrain/imperative/proxy_graph_detail.h"
#include "megbrain/opr/basic_arith.h"
#include "megbrain/opr/internal/megdnn_opr_wrapper.h"
#include "megbrain/opr/io.h"
#include "megbrain/opr/tensor_manip.h"
#include "megdnn/dtype.h"
#include "../blob_manager_impl.h"
#include "../dnn_op_helper.h"
#include "../op_trait.h"
namespace mgb {
namespace imperative {
namespace {
namespace padding {
auto apply_on_var_node(const OpDef& def, const VarNodeArray& inputs) {
auto&& op = static_cast<const Padding&>(def);
mgb_assert(inputs.size() == 1);
return opr::Padding::make(inputs[0], op.param());
}
SmallVector<TensorPtr> apply_on_physical_tensor(
const OpDef& def, const SmallVector<TensorPtr>& inputs,
SmallVector<LogicalTensorDesc>& output_descs, const bool& validated) {
auto comp_node = inputs[0]->comp_node();
auto&& op_def = def.cast_final_safe<Padding>();
DnnOprCaller<megdnn::Padding> dnn_op(comp_node);
dnn_op.op->param() = op_def.param();
TensorLayout dst = output_descs[0].layout;
if (!validated) {
megdnn::Padding::deduce_layout_impl(
inputs[0]->dnn_tensor().layout, dst, op_def.param());
}
DeviceTensorND out =
BlobManager::inst()->alloc_workspace_with_defrag(comp_node, dst);
dnn_op.op->exec(inputs[0]->dnn_tensor(), out.as_megdnn());
return {Tensor::make(out)};
}
std::tuple<SmallVector<LogicalTensorDesc>, bool> infer_output_attrs_fallible(
const OpDef& def, const SmallVector<LogicalTensorDesc>& inputs) {
auto&& op_def = def.cast_final_safe<Padding>();
size_t nr_inp = inputs.size();
auto p = op_def.param();
auto&& inp = inputs[0];
auto& inp_cn = inp.comp_node;
if (inp.layout.ndim == 0) {
return {{{TensorLayout{inp.layout.dtype}, inp_cn, {}}}, false};
}
TensorLayout oup_layout;
megdnn::Padding::deduce_layout_impl(inp.layout, oup_layout, p);
return {{{oup_layout, inp_cn, {}}}, true};
}
OP_TRAIT_REG(Padding, Padding, opr::Padding)
.apply_on_var_node(apply_on_var_node)
.apply_on_physical_tensor(apply_on_physical_tensor)
.infer_output_attrs_fallible(infer_output_attrs_fallible)
.fallback();
} // namespace padding
} // namespace
} // namespace imperative
} // namespace mgb
// vim: syntax=cpp.doxygen foldmethod=marker foldmarker=f{{{,f}}}
\ No newline at end of file
......@@ -664,15 +664,6 @@ OP_TRAIT_REG(Cumsum, Cumsum).apply_on_var_node(apply_on_var_node).fallback();
} // namespace cumsum
} // namespace
namespace padding {
auto apply_on_var_node(const OpDef& def, const VarNodeArray& inputs) {
auto&& op = static_cast<const Padding&>(def);
mgb_assert(inputs.size() == 1);
return opr::Padding::make(inputs[0], op.param());
}
OP_TRAIT_REG(Padding, Padding).apply_on_var_node(apply_on_var_node).fallback();
} // namespace padding
namespace lrn {
auto apply_on_var_node(const OpDef& def, const VarNodeArray& inputs) {
auto&& op = static_cast<const LRN&>(def);
......
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