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体验新版 GitCode,发现更多精彩内容 >>
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b77e20ac
编写于
3月 21, 2022
作者:
石
石晓伟
提交者:
GitHub
3月 21, 2022
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
add the map for dense tensor, test=develop (#40665)
上级
78fad09b
变更
23
隐藏空白更改
内联
并排
Showing
23 changed file
with
353 addition
and
65 deletion
+353
-65
paddle/infrt/api/infrt_api.cc
paddle/infrt/api/infrt_api.cc
+1
-1
paddle/infrt/dialect/dense_tensor.td
paddle/infrt/dialect/dense_tensor.td
+3
-3
paddle/infrt/dialect/infrt/ir/infrt_base.td
paddle/infrt/dialect/infrt/ir/infrt_base.td
+1
-1
paddle/infrt/dialect/infrt/ir/infrt_dialect.cc
paddle/infrt/dialect/infrt/ir/infrt_dialect.cc
+2
-8
paddle/infrt/dialect/phi/data_type.h
paddle/infrt/dialect/phi/data_type.h
+8
-8
paddle/infrt/dialect/phi/ir/infrt_phi_base.td
paddle/infrt/dialect/phi/ir/infrt_phi_base.td
+4
-0
paddle/infrt/dialect/phi/ir/infrt_phi_tensor.td
paddle/infrt/dialect/phi/ir/infrt_phi_tensor.td
+34
-0
paddle/infrt/host_context/mlir_to_runtime_translate.cc
paddle/infrt/host_context/mlir_to_runtime_translate.cc
+16
-8
paddle/infrt/host_context/paddle_mlir.cc
paddle/infrt/host_context/paddle_mlir.cc
+1
-1
paddle/infrt/host_context/value.h
paddle/infrt/host_context/value.h
+11
-8
paddle/infrt/kernel/phi/dense_tensor_kernels.cc
paddle/infrt/kernel/phi/dense_tensor_kernels.cc
+98
-0
paddle/infrt/kernel/phi/dense_tensor_kernels.h
paddle/infrt/kernel/phi/dense_tensor_kernels.h
+14
-0
paddle/infrt/kernel/phi/infershaped/infershape_launchers_test.cc
...infrt/kernel/phi/infershaped/infershape_launchers_test.cc
+15
-14
paddle/infrt/kernel/phi/registry.cc
paddle/infrt/kernel/phi/registry.cc
+13
-0
paddle/infrt/kernel/tensor_kernels.cc
paddle/infrt/kernel/tensor_kernels.cc
+3
-3
paddle/infrt/tensor/CMakeLists.txt
paddle/infrt/tensor/CMakeLists.txt
+2
-0
paddle/infrt/tensor/phi/CMakeLists.txt
paddle/infrt/tensor/phi/CMakeLists.txt
+3
-0
paddle/infrt/tensor/phi/tensor_map.cc
paddle/infrt/tensor/phi/tensor_map.cc
+47
-0
paddle/infrt/tensor/phi/tensor_map.h
paddle/infrt/tensor/phi/tensor_map.h
+37
-0
paddle/infrt/tests/dialect/tensor/tensor_map.mlir.in
paddle/infrt/tests/dialect/tensor/tensor_map.mlir.in
+27
-0
tools/infrt/fake_models/multi_fc.py
tools/infrt/fake_models/multi_fc.py
+3
-0
tools/infrt/get_phi_kernel_function.sh
tools/infrt/get_phi_kernel_function.sh
+2
-2
tools/infrt/get_phi_kernel_info.py
tools/infrt/get_phi_kernel_info.py
+8
-8
未找到文件。
paddle/infrt/api/infrt_api.cc
浏览文件 @
b77e20ac
...
...
@@ -129,7 +129,7 @@ class PredictExecutor : public MlirToRuntimeTranslator {
auto
arg
=
predict_func
.
getArgument
(
i
);
auto
type
=
arg
.
getType
();
// this param is TensorMap
if
(
type
.
isa
<
infrt
::
DenseTensorMapType
>
())
{
if
(
type
.
isa
<
infrt
::
Dense
Host
TensorMapType
>
())
{
auto
*
value
=
new
host_context
::
Value
(
std
::
move
(
*
map
));
arguments_
.
push_back
(
value
);
AddValue
(
predict_func
.
getArgument
(
i
),
value
);
...
...
paddle/infrt/dialect/dense_tensor.td
浏览文件 @
b77e20ac
...
...
@@ -106,7 +106,7 @@ def LoadParamsOp : DT_Op<"load_params", [NoSideEffect]> {
// input path of model params.
let arguments = (ins StrAttr:$path);
let results = (outs DenseTensorMap:$out);
let results = (outs Dense
Host
TensorMap:$out);
let assemblyFormat = "`(``)`attr-dict";
}
...
...
@@ -121,7 +121,7 @@ def TensorMapGetTensorOp : DT_Op<"tensor_map_get_tensor", [NoSideEffect]> {
// input path of model params.
let arguments = (ins
DenseTensorMap:$map,
Dense
Host
TensorMap:$map,
StrAttr:$name
);
let results = (outs DenseTensor:$output);
...
...
@@ -136,7 +136,7 @@ def TensorMapGetSizeOp : DT_Op<"tensor_map_get_size", [NoSideEffect]> {
An operation that get the size of a TensorMap.
}];
let arguments = (ins DenseTensorMap:$map);
let arguments = (ins Dense
Host
TensorMap:$map);
let results = (outs I32:$size);
let assemblyFormat = "`(` $map `)` attr-dict `->` type($size)";
}
...
...
paddle/infrt/dialect/infrt/ir/infrt_base.td
浏览文件 @
b77e20ac
...
...
@@ -83,7 +83,7 @@ def DenseTensor : Infrt_Type<"DenseTensor"> {
);
}
def Dense
TensorMap : Infrt_Type<"Dense
TensorMap"> {
def Dense
HostTensorMap : Infrt_Type<"DenseHost
TensorMap"> {
let summary = "infrt dense tensor map";
let description = [{dense_tensor map}];
let parameters = (ins);
...
...
paddle/infrt/dialect/infrt/ir/infrt_dialect.cc
浏览文件 @
b77e20ac
...
...
@@ -91,7 +91,7 @@ mlir::Type InfrtDialect::parseType(::mlir::DialectAsmParser &parser) const {
parser
.
getContext
(),
shape
,
elementType
,
lod_level
);
}
if
(
keyword
==
"dense_tensor_map"
)
{
return
DenseTensorMapType
::
get
(
parser
.
getContext
());
return
Dense
Host
TensorMapType
::
get
(
parser
.
getContext
());
}
if
(
keyword
==
"dense_tensor"
)
{
// parse DenseTensor, for example: !i=Infrt.tensor<X86, CUDA, F32>
...
...
@@ -162,7 +162,7 @@ void InfrtDialect::printType(::mlir::Type type,
<<
lod_tensor_type
.
getLod_level
()
<<
">"
;
return
;
}
if
(
type
.
isa
<
infrt
::
DenseTensorMapType
>
())
{
if
(
type
.
isa
<
infrt
::
Dense
Host
TensorMapType
>
())
{
os
<<
"dense_tensor_map"
;
return
;
}
...
...
@@ -180,12 +180,6 @@ void InfrtDialect::printType(::mlir::Type type,
os
<<
"tensor_list"
;
return
;
}
// print DenseTensorType, for example: !infrt.dense_tensor<CPU, FP32, NCHW>
if
(
type
.
isa
<
DenseTensorMapType
>
())
{
os
<<
"dense_tensor_map"
;
return
;
}
llvm_unreachable
(
"unknown infrt type."
);
}
...
...
paddle/infrt/dialect/phi/data_type.h
浏览文件 @
b77e20ac
...
...
@@ -23,16 +23,16 @@
namespace
infrt
{
phi
::
Backend
ConvertTargetToPhi
(
TargetType
target
);
TargetType
ConvertTargetFromPhi
(
phi
::
Backend
backend
);
::
phi
::
Backend
ConvertTargetToPhi
(
TargetType
target
);
TargetType
ConvertTargetFromPhi
(
::
phi
::
Backend
backend
);
phi
::
DataType
ConvertPrecisionToPhi
(
PrecisionType
precision
);
PrecisionType
ConvertPrecisionFromPhi
(
phi
::
DataType
datatype
);
::
phi
::
DataType
ConvertPrecisionToPhi
(
PrecisionType
precision
);
PrecisionType
ConvertPrecisionFromPhi
(
::
phi
::
DataType
datatype
);
phi
::
DataLayout
ConvertLayoutToPhi
(
LayoutType
layout
);
LayoutType
ConvertLayoutFromPhi
(
phi
::
DataLayout
layout
);
::
phi
::
DataLayout
ConvertLayoutToPhi
(
LayoutType
layout
);
LayoutType
ConvertLayoutFromPhi
(
::
phi
::
DataLayout
layout
);
phi
::
KernelKey
ConvertPlaceToPhi
(
const
Place
&
place
);
Place
ConvertPlaceFromPhi
(
phi
::
TensorArgDef
tensor_arg
);
::
phi
::
KernelKey
ConvertPlaceToPhi
(
const
Place
&
place
);
Place
ConvertPlaceFromPhi
(
::
phi
::
TensorArgDef
tensor_arg
);
}
// namespace infrt
paddle/infrt/dialect/phi/ir/infrt_phi_base.td
浏览文件 @
b77e20ac
...
...
@@ -37,4 +37,8 @@ def Allocator : PHI_Type<"Allocator"> {
let assemblyFormat = "`<` $target `>`";
}
def PD_DenseTensorMap : PHI_Type<"DenseTensorMap"> {
let mnemonic = "dense_tensor_map";
}
#endif
paddle/infrt/dialect/phi/ir/infrt_phi_tensor.td
浏览文件 @
b77e20ac
...
...
@@ -51,12 +51,46 @@ class CreateContextOp<string target>
let results = (outs Context:$output);
}
def PDT_LoadParamsOp : PDT_Op<"load_params", [NoSideEffect]> {
// input path of model params.
let arguments = (ins StrAttr:$path);
let results = (outs PD_DenseTensorMap:$out);
let assemblyFormat = "`(``)`attr-dict";
}
def PDT_LoadCombinedParamsOp : PDT_Op<"load_combined_params", [NoSideEffect]> {
// input path of model params.
let arguments = (ins StrAttr:$model_path, StrAttr:$params_path);
let results = (outs PD_DenseTensorMap:$out);
let assemblyFormat = "`(``)`attr-dict";
}
def PDT_TensorMapGetSizeOp : PDT_Op<"tensor_map_get_size", [NoSideEffect]> {
let arguments = (ins PD_DenseTensorMap:$map);
let results = (outs I32:$size);
let assemblyFormat = "`(` $map `)` attr-dict `->` type($size)";
}
class TensorMapGetTensorOp:
PDT_Op<"tensor_map_get_tensor"> {
let arguments = (ins
PD_DenseTensorMap:$map,
StrAttr:$name
);
let results = (outs DenseTensor:$output);
let assemblyFormat = "`(` operands `)` attr-dict `->` type($output)";
let verifier = ?;
}
def PDT_CreateCPUDenseTensorOp : CreateDenseTensorOp<"cpu">;
def PDT_CreateGPUDenseTensorOp : CreateDenseTensorOp<"gpu">;
def PDT_FillDenseTensorOp_f32 : FillDenseTensorOp<F32ArrayAttr, "f32">;
def PDT_CreateCPUContextOp : CreateContextOp<"cpu">;
def PDT_CreateGPUContextOp : CreateContextOp<"gpu">;
def PDT_PrintDenseTensor : PrintDenseTensorOp;
def PDT_TensorMapGetTensorOp: TensorMapGetTensorOp;
def FakeKernelOp : PDT_Op<"fake_phi_kernel"> {
let arguments = (ins Context:$dev_ctx, DenseTensor:$x, DenseTensor:$y, BoolAttr:$transpose_x, BoolAttr:$transpose_y);
...
...
paddle/infrt/host_context/mlir_to_runtime_translate.cc
浏览文件 @
b77e20ac
...
...
@@ -351,18 +351,26 @@ bool MlirToRuntimeTranslator::EmitGeneralOp(
auto
attrs
=
op
->
getAttrs
();
// MLIR's underlying attr storage type is `Builtin_Dictionary`, and its
// elements
// are sorted by name. The following code adapts the order of function
// signatures
// of the phi operator library.
// elements are sorted by name. The following code adapts the order of
// function signatures of the phi operator library.
llvm
::
SmallVector
<
Value
*
,
4
>
tmp
;
tmp
.
resize
(
attrs
.
size
());
const
std
::
string
&
kernel_name
=
op
->
getName
().
getStringRef
().
str
();
const
auto
&
attr_names
=
kernel_registry
.
GetAttrNameList
(
kernel_name
);
if
(
attrs
.
size
()
&&
attr_names
.
empty
())
{
LOG
(
WARNING
)
<<
"The kernel `"
<<
kernel_name
<<
"` has no specified attr order."
;
if
(
attrs
.
size
())
{
if
(
attr_names
.
empty
())
{
LOG
(
WARNING
)
<<
"The kernel `"
<<
kernel_name
<<
"` has not been registered with "
"`KernelRegistry::AddKernelWithAttrs()`."
;
}
else
{
CHECK_EQ
(
attr_names
.
size
(),
attrs
.
size
())
<<
"The number of kernel `"
<<
kernel_name
<<
"` attributes specified by mlir ("
<<
attrs
.
size
()
<<
") is inconsistent with the registration ("
<<
attr_names
.
size
()
<<
")."
;
}
}
auto
get_offset
=
[](
const
char
*
attr
,
const
std
::
vector
<
const
char
*>&
names
,
const
std
::
string
&
kernel_name
)
->
int
{
...
...
@@ -385,7 +393,7 @@ bool MlirToRuntimeTranslator::EmitGeneralOp(
}
else
{
offset
=
i
;
}
CHECK_
NE
(
offset
,
-
1
);
CHECK_
GT
(
offset
,
-
1
);
if
(
auto
v
=
EmitAttribute
<
int32_t
>
(
attr
.
getValue
()))
{
tmp
[
offset
]
=
new
Value
(
*
v
);
}
else
if
(
auto
v
=
EmitAttribute
<
int64_t
>
(
attr
.
getValue
()))
{
...
...
paddle/infrt/host_context/paddle_mlir.cc
浏览文件 @
b77e20ac
...
...
@@ -79,7 +79,7 @@ mlir::FuncOp MLIRModelGenImpl::UpdateModelModule(
llvm
::
SmallVector
<
mlir
::
Type
,
4
>
MLIRModelGenImpl
::
GetModelInputsType
(
const
infrt
::
paddle
::
framework_proto
::
ProgramDesc
&
program
)
{
llvm
::
SmallVector
<
mlir
::
Type
,
4
>
operandTypes
;
operandTypes
.
push_back
(
infrt
::
DenseTensorMapType
::
get
(
context_
));
operandTypes
.
push_back
(
infrt
::
Dense
Host
TensorMapType
::
get
(
context_
));
for
(
auto
&
op_desc
:
main_block_
.
ops
())
{
if
(
op_desc
.
type
()
!=
"feed"
)
continue
;
for
(
int
var_idx
=
0
;
var_idx
<
op_desc
.
outputs_size
();
++
var_idx
)
{
...
...
paddle/infrt/host_context/value.h
浏览文件 @
b77e20ac
...
...
@@ -34,6 +34,7 @@
#ifdef INFRT_WITH_PHI
#include "paddle/infrt/backends/host/phi_allocator.h"
#include "paddle/infrt/backends/host/phi_context.h"
#include "paddle/infrt/tensor/phi/tensor_map.h"
#include "paddle/phi/backends/all_context.h"
#include "paddle/phi/common/backend.h"
#include "paddle/phi/common/data_type.h"
...
...
@@ -84,22 +85,23 @@ using ValueVariantType =
#ifdef INFRT_WITH_GPU
backends
::
GpuPhiContext
,
::
phi
::
GPUContext
,
#endif
#endif
// INFRT_WITH_GPU
::
phi
::
CPUContext
,
std
::
vector
<
const
phi
::
DenseTensor
*>
,
std
::
vector
<
phi
::
DenseTensor
*>
,
paddle
::
experimental
::
ScalarBase
<
phi
::
DenseTensor
>
,
paddle
::
experimental
::
ScalarArrayBase
<
phi
::
DenseTensor
>
,
std
::
vector
<
phi
::
MetaTensor
*>
,
phi
::
MetaConfig
,
std
::
vector
<
const
::
phi
::
DenseTensor
*>
,
std
::
vector
<
::
phi
::
DenseTensor
*>
,
paddle
::
experimental
::
ScalarBase
<
::
phi
::
DenseTensor
>
,
paddle
::
experimental
::
ScalarArrayBase
<
::
phi
::
DenseTensor
>
,
std
::
vector
<
::
phi
::
MetaTensor
*>
,
::
phi
::
MetaConfig
,
paddle
::
experimental
::
Backend
,
paddle
::
experimental
::
DataLayout
,
paddle
::
experimental
::
DataType
,
::
infrt
::
phi
::
DenseTensorMap
,
#endif // INFRT_WITH_PHI
#ifdef INFRT_WITH_TRT
::
infrt
::
backends
::
tensorrt
::
TrtEngine
,
::
infrt
::
kernel
::
tensorrt
::
MlirOperationWithInfrtSymbol
,
#endif // INFRT_WITH_TRT
#endif
std
::
vector
<
int16_t
>
,
std
::
vector
<
int32_t
>
,
std
::
vector
<
int64_t
>
,
...
...
@@ -136,6 +138,7 @@ class Value : public common::Object {
explicit
Value
(
tensor
::
DenseHostTensor
&&
x
)
:
data
(
std
::
move
(
x
))
{}
explicit
Value
(
MlirFunctionExecutable
*
x
)
:
data
(
x
)
{}
#ifdef INFRT_WITH_PHI
explicit
Value
(
::
infrt
::
phi
::
DenseTensorMap
&&
x
)
:
data
(
std
::
move
(
x
))
{}
explicit
Value
(
::
phi
::
CPUContext
&&
x
)
:
data
(
std
::
move
(
x
))
{}
explicit
Value
(
backends
::
CpuPhiContext
&&
x
)
:
data
(
std
::
move
(
x
))
{}
#ifdef INFRT_WITH_GPU
...
...
paddle/infrt/kernel/phi/dense_tensor_kernels.cc
浏览文件 @
b77e20ac
...
...
@@ -13,8 +13,11 @@
// limitations under the License.
#include "paddle/infrt/kernel/phi/dense_tensor_kernels.h"
#include "paddle/infrt/common/string.h"
#include "paddle/infrt/dialect/phi/data_type.h"
#include "paddle/infrt/kernel/phi/context_kernels.h"
#include "paddle/infrt/paddle/model_parser.h"
#include "paddle/infrt/paddle/scope.h"
#include "paddle/phi/backends/all_context.h"
#include "paddle/phi/common/place.h"
...
...
@@ -22,6 +25,18 @@
#include <cuda_runtime.h>
#endif
namespace
paddle
{
namespace
platform
{
using
DeviceContext
=
::
phi
::
DeviceContext
;
}
// namespace platform
namespace
framework
{
using
LoDTensor
=
::
phi
::
DenseTensor
;
void
DeserializeFromStream
(
std
::
istream
&
is
,
LoDTensor
*
tensor
,
const
platform
::
DeviceContext
&
dev_ctx
);
}
}
// namespace paddle
namespace
infrt
{
namespace
kernel
{
namespace
phi
{
...
...
@@ -130,6 +145,89 @@ void PrintDenseTensor(::phi::DenseTensor* dense_tensor) {
std
::
cout
<<
"]
\n
"
;
#undef PRINT_META_DATA
}
::
infrt
::
phi
::
DenseTensorMap
LoadParams
(
host_context
::
Attribute
<
std
::
string
>
path
)
{
const
auto
&
file_path
=
path
.
get
();
std
::
cout
<<
"loading params from: "
<<
file_path
<<
std
::
endl
;
::
infrt
::
phi
::
DenseTensorMap
map
;
const
std
::
string
model_path
=
file_path
+
"/__model__"
;
auto
pb_proto_prog
=
paddle
::
LoadProgram
(
model_path
);
auto
main_block
=
pb_proto_prog
->
blocks
(
0
);
for
(
auto
&
var
:
main_block
.
vars
())
{
if
(
var
.
name
()
==
"feed"
||
var
.
name
()
==
"fetch"
||
!
var
.
persistable
())
continue
;
std
::
string
param_path
=
file_path
+
"/"
+
var
.
name
();
std
::
ifstream
param_file
(
param_path
,
std
::
ios
::
binary
);
switch
(
var
.
type
().
type
())
{
case
::
paddle
::
framework
::
proto
::
VarType_Type_LOD_TENSOR
:
{
std
::
unique_ptr
<::
phi
::
DenseTensor
>
tensor
{
std
::
make_unique
<::
phi
::
DenseTensor
>
()};
::
phi
::
CPUContext
ctx
;
::
paddle
::
framework
::
DeserializeFromStream
(
param_file
,
tensor
.
get
(),
ctx
);
map
.
SetDenseTensor
(
var
.
name
(),
std
::
move
(
tensor
));
}
break
;
default:
{
LOG
(
WARNING
)
<<
"Var `"
<<
var
.
name
()
<<
"` type `"
<<
static_cast
<
int
>
(
var
.
type
().
type
())
<<
"` has not been supported now."
;
}
}
}
return
map
;
}
::
infrt
::
phi
::
DenseTensorMap
LoadCombinedParams
(
host_context
::
Attribute
<
std
::
string
>
model_path
,
host_context
::
Attribute
<
std
::
string
>
params_path
)
{
const
auto
&
model
=
model_path
.
get
();
std
::
cout
<<
"loading params from: "
<<
model
<<
std
::
endl
;
::
infrt
::
phi
::
DenseTensorMap
map
;
auto
pb_proto_prog
=
paddle
::
LoadProgram
(
model
);
auto
main_block
=
pb_proto_prog
->
blocks
(
0
);
std
::
ifstream
param_file
(
params_path
.
get
(),
std
::
ios
::
binary
);
std
::
set
<
std
::
string
>
tmp
;
for
(
auto
&
var
:
main_block
.
vars
())
{
if
(
var
.
name
()
==
"feed"
||
var
.
name
()
==
"fetch"
||
!
var
.
persistable
())
{
continue
;
}
if
(
var
.
type
().
type
()
==
::
paddle
::
framework
::
proto
::
VarType_Type_LOD_TENSOR
)
{
tmp
.
emplace
(
var
.
name
());
}
else
{
llvm_unreachable
(
"the tensor type is illegal."
);
}
}
for
(
auto
&
var
:
tmp
)
{
std
::
unique_ptr
<::
phi
::
DenseTensor
>
tensor
{
std
::
make_unique
<::
phi
::
DenseTensor
>
()};
::
phi
::
CPUContext
ctx
;
::
paddle
::
framework
::
DeserializeFromStream
(
param_file
,
tensor
.
get
(),
ctx
);
map
.
SetDenseTensor
(
var
,
std
::
move
(
tensor
));
}
return
map
;
}
::
phi
::
DenseTensor
TensorMapGetTensor
(
const
::
infrt
::
phi
::
DenseTensorMap
&
map
,
host_context
::
Attribute
<
std
::
string
>
name
)
{
auto
*
tensor
=
map
.
GetDenseTensor
(
name
.
get
());
CHECK
(
tensor
);
return
*
tensor
;
}
int32_t
TensorMapGetSize
(
const
::
infrt
::
phi
::
DenseTensorMap
&
map
)
{
return
map
.
size
();
}
}
// namespace phi
}
// namespace kernel
}
// namespace infrt
paddle/infrt/kernel/phi/dense_tensor_kernels.h
浏览文件 @
b77e20ac
...
...
@@ -17,6 +17,7 @@
#include "paddle/infrt/backends/host/phi_allocator.h"
#include "paddle/infrt/dialect/infrt/common/types.h"
#include "paddle/infrt/host_context/kernel_utils.h"
#include "paddle/infrt/tensor/phi/tensor_map.h"
#include "paddle/phi/core/dense_tensor.h"
namespace
infrt
{
...
...
@@ -41,6 +42,19 @@ void FillDenseTensorF32(::phi::DenseTensor* dense_tensor,
host_context
::
Attribute
<
std
::
vector
<
float
>>
values
);
void
PrintDenseTensor
(
::
phi
::
DenseTensor
*
dense_tensor
);
infrt
::
phi
::
DenseTensorMap
LoadParams
(
host_context
::
Attribute
<
std
::
string
>
path
);
::
phi
::
DenseTensor
TensorMapGetTensor
(
const
::
infrt
::
phi
::
DenseTensorMap
&
map
,
host_context
::
Attribute
<
std
::
string
>
name
);
::
infrt
::
phi
::
DenseTensorMap
LoadCombinedParams
(
host_context
::
Attribute
<
std
::
string
>
model_path
,
host_context
::
Attribute
<
std
::
string
>
params_path
);
int32_t
TensorMapGetSize
(
const
::
infrt
::
phi
::
DenseTensorMap
&
map
);
}
// namespace phi
}
// namespace kernel
}
// namespace infrt
paddle/infrt/kernel/phi/infershaped/infershape_launchers_test.cc
浏览文件 @
b77e20ac
...
...
@@ -37,15 +37,16 @@ TEST(utils, registry) {
CHECK_EQ
(
count
,
2U
);
}
class
FancyAllocator
:
public
phi
::
Allocator
{
class
FancyAllocator
:
public
::
phi
::
Allocator
{
public:
static
void
Delete
(
phi
::
Allocation
*
allocation
)
{
static
void
Delete
(
::
phi
::
Allocation
*
allocation
)
{
::
operator
delete
(
allocation
->
ptr
());
}
AllocationPtr
Allocate
(
size_t
bytes_size
)
override
{
void
*
data
=
::
operator
new
(
bytes_size
);
auto
*
allocation
=
new
phi
::
Allocation
(
data
,
bytes_size
,
phi
::
CPUPlace
());
auto
*
allocation
=
new
::
phi
::
Allocation
(
data
,
bytes_size
,
::
phi
::
CPUPlace
());
return
AllocationPtr
(
allocation
,
Delete
);
}
};
...
...
@@ -56,20 +57,20 @@ TEST(ElementwiseAdd, launcher_registry) {
ASSERT_GE
(
registry
.
size
(),
1UL
);
auto
creator
=
registry
.
GetKernel
(
"phi_cpu.add.float32.any"
);
const
phi
::
DDim
dims
({
1
,
2
});
const
phi
::
DataType
dtype
{
phi
::
DataType
::
FLOAT32
};
const
phi
::
DataLayout
layout
{
phi
::
DataLayout
::
NHWC
};
const
phi
::
LoD
lod
{};
phi
::
DenseTensorMeta
meta
(
dtype
,
dims
,
layout
,
lod
);
const
::
phi
::
DDim
dims
({
1
,
2
});
const
::
phi
::
DataType
dtype
{
::
phi
::
DataType
::
FLOAT32
};
const
::
phi
::
DataLayout
layout
{
::
phi
::
DataLayout
::
NHWC
};
const
::
phi
::
LoD
lod
{};
::
phi
::
DenseTensorMeta
meta
(
dtype
,
dims
,
layout
,
lod
);
auto
fancy_allocator
=
std
::
unique_ptr
<
phi
::
Allocator
>
(
new
FancyAllocator
);
auto
fancy_allocator
=
std
::
unique_ptr
<
::
phi
::
Allocator
>
(
new
FancyAllocator
);
auto
*
alloc
=
fancy_allocator
.
get
();
phi
::
DenseTensor
a
(
alloc
,
meta
);
phi
::
DenseTensor
b
(
alloc
,
meta
);
phi
::
DenseTensor
c
(
alloc
,
meta
);
::
phi
::
DenseTensor
a
(
alloc
,
meta
);
::
phi
::
DenseTensor
b
(
alloc
,
meta
);
::
phi
::
DenseTensor
c
(
alloc
,
meta
);
auto
place
=
phi
::
CPUPlace
();
auto
place
=
::
phi
::
CPUPlace
();
float
*
a_data
=
a
.
mutable_data
<
float
>
(
place
);
float
*
b_data
=
b
.
mutable_data
<
float
>
(
place
);
float
*
c_data
=
c
.
mutable_data
<
float
>
(
place
);
...
...
@@ -78,7 +79,7 @@ TEST(ElementwiseAdd, launcher_registry) {
b_data
[
i
]
=
2.
f
;
}
phi
::
CPUContext
context
;
::
phi
::
CPUContext
context
;
context
.
SetAllocator
(
alloc
);
context
.
Init
();
...
...
paddle/infrt/kernel/phi/registry.cc
浏览文件 @
b77e20ac
...
...
@@ -53,6 +53,19 @@ void RegisterPhiKernels(host_context::KernelRegistry* registry) {
INFRT_KERNEL
(
infrt
::
kernel
::
phi
::
CreateGPUDenseTensor
),
{
"dims"
,
"lod"
,
"layout"
,
"precision"
});
#endif
registry
->
AddKernelWithAttrs
(
"phi_dt.load_params"
,
INFRT_KERNEL
(
infrt
::
kernel
::
phi
::
LoadParams
),
{
"path"
});
registry
->
AddKernelWithAttrs
(
"phi_dt.load_combined_params"
,
INFRT_KERNEL
(
infrt
::
kernel
::
phi
::
LoadCombinedParams
),
{
"model_path"
,
"params_path"
});
registry
->
AddKernelWithAttrs
(
"phi_dt.tensor_map_get_tensor"
,
INFRT_KERNEL
(
infrt
::
kernel
::
phi
::
TensorMapGetTensor
),
{
"name"
});
registry
->
AddKernel
(
"phi_dt.tensor_map_get_size"
,
INFRT_KERNEL
(
infrt
::
kernel
::
phi
::
TensorMapGetSize
));
}
}
// namespace kernel
...
...
paddle/infrt/kernel/tensor_kernels.cc
浏览文件 @
b77e20ac
...
...
@@ -68,14 +68,14 @@ int32_t TensorMapGetSize(TensorMap map) { return map.size(); }
// TODO(wilber): Maybe we should place TensorList type in dt dialect.
#ifdef INFRT_WITH_PHI
phi
::
DenseTensor
TensorListGetTensor
(
std
::
vector
<
phi
::
DenseTensor
*>
list
,
Attribute
<
int32_t
>
idx
)
{
::
phi
::
DenseTensor
TensorListGetTensor
(
std
::
vector
<::
phi
::
DenseTensor
*>
list
,
Attribute
<
int32_t
>
idx
)
{
CHECK_LT
(
idx
.
get
(),
static_cast
<
int
>
(
list
.
size
()))
<<
"idx should less than list size"
;
return
*
list
[
idx
.
get
()];
}
int32_t
TensorListGetSize
(
const
std
::
vector
<
phi
::
DenseTensor
*>
&
list
)
{
int32_t
TensorListGetSize
(
const
std
::
vector
<
::
phi
::
DenseTensor
*>
&
list
)
{
return
list
.
size
();
}
#endif
...
...
paddle/infrt/tensor/CMakeLists.txt
浏览文件 @
b77e20ac
core_gather_headers
()
add_subdirectory
(
phi
)
gather_srcs
(
infrt_src SRCS
tensor_map.cc
tensor_metadata.cc
...
...
paddle/infrt/tensor/phi/CMakeLists.txt
0 → 100644
浏览文件 @
b77e20ac
gather_srcs
(
infrt_src SRCS
tensor_map.cc
)
paddle/infrt/tensor/phi/tensor_map.cc
0 → 100644
浏览文件 @
b77e20ac
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "paddle/infrt/tensor/phi/tensor_map.h"
#include "llvm/Support/ErrorHandling.h"
namespace
infrt
{
namespace
phi
{
void
DenseTensorMap
::
SetDenseTensor
(
const
std
::
string
&
name
,
std
::
unique_ptr
<::
phi
::
DenseTensor
>&&
tensor
)
{
std
::
lock_guard
<
std
::
mutex
>
lock
(
mu_
);
auto
it
=
map_
.
emplace
(
std
::
make_pair
(
name
,
std
::
move
(
tensor
)));
if
(
!
it
.
second
)
{
llvm_unreachable
(
"dense tensor map insert failed."
);
}
}
::
phi
::
DenseTensor
*
DenseTensorMap
::
GetDenseTensor
(
const
std
::
string
&
name
)
const
{
std
::
lock_guard
<
std
::
mutex
>
lock
(
mu_
);
auto
it
=
map_
.
find
(
name
);
if
(
it
!=
map_
.
end
())
{
return
it
->
second
.
get
();
}
LOG
(
WARNING
)
<<
"can not find `"
<<
name
<<
"` in the tensor map."
;
return
nullptr
;
}
size_t
DenseTensorMap
::
size
()
const
{
std
::
lock_guard
<
std
::
mutex
>
lock
(
mu_
);
return
map_
.
size
();
}
}
// namespace phi
}
// namespace infrt
paddle/infrt/tensor/phi/tensor_map.h
0 → 100644
浏览文件 @
b77e20ac
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#pragma once
#include "paddle/phi/core/dense_tensor.h"
namespace
infrt
{
namespace
phi
{
class
DenseTensorMap
{
public:
DenseTensorMap
()
=
default
;
DenseTensorMap
(
DenseTensorMap
&&
other
)
:
map_
(
std
::
move
(
other
.
map_
))
{}
void
SetDenseTensor
(
const
std
::
string
&
name
,
std
::
unique_ptr
<::
phi
::
DenseTensor
>&&
tensor
);
::
phi
::
DenseTensor
*
GetDenseTensor
(
const
std
::
string
&
name
)
const
;
size_t
size
()
const
;
private:
mutable
std
::
mutex
mu_
;
std
::
unordered_map
<
std
::
string
,
std
::
unique_ptr
<::
phi
::
DenseTensor
>>
map_
;
};
}
// namespace phi
}
// namespace infrt
paddle/infrt/tests/dialect/tensor/tensor_map.mlir.in
浏览文件 @
b77e20ac
...
...
@@ -12,3 +12,30 @@ func @load_tensor_map() {
infrt.return
}
func @load_phi_tensor_map() {
%map = phi_dt.load_params(){path="@CMAKE_BINARY_DIR@/multi_fc_model"}
%size = phi_dt.tensor_map_get_size(%map) -> i32
infrt.print.i32 %size
%a = phi_dt.tensor_map_get_tensor(%map) {name="fc_bias"} -> !infrt.dense_tensor<CPU, FP32, NCHW>
// CHECK: dense_tensor: shape=shape[2], value=[0,0]
phi_dt.print_tensor (%a : !infrt.dense_tensor<CPU, FP32, NCHW>)
infrt.return
}
func @load_combined_phi_tensor_map() {
%map = phi_dt.load_combined_params(){model_path="@CMAKE_BINARY_DIR@/multi_fc_model/fc.pdmodel",
params_path="@CMAKE_BINARY_DIR@/multi_fc_model/fc.pdiparams"}
%size = phi_dt.tensor_map_get_size(%map) -> i32
infrt.print.i32 %size
%a = phi_dt.tensor_map_get_tensor(%map) {name="fc_bias"} -> !infrt.dense_tensor<CPU, FP32, NCHW>
// CHECK: dense_tensor: shape=shape[2], value=[0,0]
phi_dt.print_tensor (%a : !infrt.dense_tensor<CPU, FP32, NCHW>)
infrt.return
}
tools/infrt/fake_models/multi_fc.py
浏览文件 @
b77e20ac
...
...
@@ -52,4 +52,7 @@ loss = exe = fluid.Executor(cpu)
exe
.
run
(
fluid
.
default_startup_program
())
fluid
.
io
.
save_inference_model
(
"./multi_fc_model"
,
[
a
.
name
],
[
fc_out
],
exe
)
fluid
.
io
.
save_inference_model
(
"./multi_fc_model"
,
[
a
.
name
],
[
fc_out
],
exe
,
None
,
"fc.pdmodel"
,
"fc.pdiparams"
)
print
(
'output name'
,
fc_out
.
name
)
tools/infrt/get_phi_kernel_function.sh
浏览文件 @
b77e20ac
...
...
@@ -49,7 +49,7 @@ all_ir_name=`grep -Eo "PDTCPU_Kernel<.*\"" paddle/infrt/dialect/phi/ir/phi_cpu_k
for
ir
in
$all_ir_name
do
attr_name
=
`
grep
"<
\"
$ir
"
-A
3 paddle/infrt/dialect/phi/ir/phi_cpu_kernels.td |
grep
-Eo
"Attr:.*)"
\
|
awk
'{gsub(/F32Attr/,"");gsub(/F64Attr/,"");gsub(/StrAttr/,"");gsub(/B
OOL
Attr/,""); \
|
awk
'{gsub(/F32Attr/,"");gsub(/F64Attr/,"");gsub(/StrAttr/,"");gsub(/B
ool
Attr/,""); \
gsub(/SI1Attr/,"");gsub(/SI8Attr/,"");gsub(/SI16Attr/,"");gsub(/SI32Attr/,"");gsub(/SI64Attr/,""); \
gsub(/UI1Attr/,"");gsub(/UI8Attr/,"");gsub(/I16Attr/,"");gsub(/I32Attr/,"");gsub(/I64Attr/,""); \
gsub(/I1Attr/,"");gsub(/I8Attr/,"");gsub(/UI16Attr/,"");gsub(/UI32Attr/,"");gsub(/UI64Attr/,""); \
...
...
@@ -62,7 +62,7 @@ all_ir_name=`grep -Eo "PDTGPU_Kernel<.*\"" paddle/infrt/dialect/phi/ir/phi_gpu_k
for
ir
in
$all_ir_name
do
attr_name
=
`
grep
"<
\"
$ir
"
-A
3 paddle/infrt/dialect/phi/ir/phi_gpu_kernels.td |
grep
-Eo
"Attr:.*)"
\
|
awk
'{gsub(/F32Attr/,"");gsub(/F64Attr/,"");gsub(/StrAttr/,"");gsub(/B
OOL
Attr/,""); \
|
awk
'{gsub(/F32Attr/,"");gsub(/F64Attr/,"");gsub(/StrAttr/,"");gsub(/B
ool
Attr/,""); \
gsub(/SI1Attr/,"");gsub(/SI8Attr/,"");gsub(/SI16Attr/,"");gsub(/SI32Attr/,"");gsub(/SI64Attr/,""); \
gsub(/UI1Attr/,"");gsub(/UI8Attr/,"");gsub(/I16Attr/,"");gsub(/I32Attr/,"");gsub(/I64Attr/,""); \
gsub(/I1Attr/,"");gsub(/I8Attr/,"");gsub(/UI16Attr/,"");gsub(/UI32Attr/,"");gsub(/UI64Attr/,""); \
...
...
tools/infrt/get_phi_kernel_info.py
浏览文件 @
b77e20ac
...
...
@@ -133,11 +133,11 @@ namespace kernel {
def
gen_context
(
val
):
if
val
==
"CPU"
:
return
"phi::CPUContext"
,
"phi_cpu"
return
"
::
phi::CPUContext"
,
"phi_cpu"
elif
val
==
"GPU"
:
return
"phi::GPUContext"
,
"phi_gpu"
return
"
::
phi::GPUContext"
,
"phi_gpu"
# elif val == "XPU":
# return "phi::XPUContext", "phi_xpu"
# return "
::
phi::XPUContext", "phi_xpu"
else
:
# raise Exception(f"Unknown context type {val}")
return
""
,
""
...
...
@@ -157,12 +157,12 @@ def gen_kernel_func(val, ctx_name, dtype_name):
ed
=
val
.
index
(
'>'
)
func_name
=
val
[:
st
]
template_name
=
val
[
st
+
1
:
ed
]
if
'phi::'
in
template_name
:
return
"&phi::"
+
val
if
'
::
phi::'
in
template_name
:
return
"&
::
phi::"
+
val
else
:
return
"&
phi::"
+
func_name
+
"<
phi::"
+
template_name
+
">"
return
"&
::phi::"
+
func_name
+
"<::
phi::"
+
template_name
+
">"
else
:
return
"&phi::"
+
val
+
"<"
+
dtype_name
+
", "
+
ctx_name
+
">"
return
"&
::
phi::"
+
val
+
"<"
+
dtype_name
+
", "
+
ctx_name
+
">"
def
gen_dtype
(
vals
:
List
[
str
]):
...
...
@@ -227,7 +227,7 @@ def gen_register_code_info(item: List[str], attr_data: Dict[str, List[str]]):
return
""
item
[
2
]
=
gen_layout
(
item
[
2
])
ir_dtypes
,
origin_dtypes
=
gen_dtype
(
item
[
4
:
-
1
])
infer_shape_func
=
"&phi::"
+
item
[
-
1
]
infer_shape_func
=
"&
::
phi::"
+
item
[
-
1
]
res
=
""
...
...
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