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体验新版 GitCode,发现更多精彩内容 >>
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4b95f85e
编写于
9月 19, 2022
作者:
Z
zhangkaihuo
提交者:
GitHub
9月 19, 2022
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差异文件
[Sparse] Add infer meta (#46016)
* sparse infer_meta
上级
b2262461
变更
38
隐藏空白更改
内联
并排
Showing
38 changed file
with
1047 addition
and
104 deletion
+1047
-104
paddle/phi/api/lib/CMakeLists.txt
paddle/phi/api/lib/CMakeLists.txt
+4
-2
paddle/phi/api/lib/api_gen_utils.cc
paddle/phi/api/lib/api_gen_utils.cc
+20
-0
paddle/phi/api/lib/api_gen_utils.h
paddle/phi/api/lib/api_gen_utils.h
+8
-0
paddle/phi/api/lib/tensor_method.cc
paddle/phi/api/lib/tensor_method.cc
+11
-2
paddle/phi/api/yaml/generator/intermediate_api_gen.py
paddle/phi/api/yaml/generator/intermediate_api_gen.py
+4
-0
paddle/phi/api/yaml/generator/sparse_api_gen.py
paddle/phi/api/yaml/generator/sparse_api_gen.py
+52
-3
paddle/phi/api/yaml/generator/sparse_bw_api_gen.py
paddle/phi/api/yaml/generator/sparse_bw_api_gen.py
+8
-0
paddle/phi/api/yaml/sparse_backward.yaml
paddle/phi/api/yaml/sparse_backward.yaml
+109
-0
paddle/phi/api/yaml/sparse_ops.yaml
paddle/phi/api/yaml/sparse_ops.yaml
+93
-0
paddle/phi/core/meta_tensor.cc
paddle/phi/core/meta_tensor.cc
+33
-2
paddle/phi/core/sparse_coo_tensor.cc
paddle/phi/core/sparse_coo_tensor.cc
+51
-10
paddle/phi/core/sparse_coo_tensor.h
paddle/phi/core/sparse_coo_tensor.h
+31
-9
paddle/phi/core/sparse_csr_tensor.cc
paddle/phi/core/sparse_csr_tensor.cc
+41
-11
paddle/phi/core/sparse_csr_tensor.h
paddle/phi/core/sparse_csr_tensor.h
+30
-11
paddle/phi/core/tensor_meta.cc
paddle/phi/core/tensor_meta.cc
+12
-0
paddle/phi/core/tensor_meta.h
paddle/phi/core/tensor_meta.h
+20
-0
paddle/phi/core/tensor_utils.cc
paddle/phi/core/tensor_utils.cc
+1
-1
paddle/phi/core/tensor_utils.h
paddle/phi/core/tensor_utils.h
+8
-0
paddle/phi/infermeta/CMakeLists.txt
paddle/phi/infermeta/CMakeLists.txt
+1
-0
paddle/phi/infermeta/sparse/CMakeLists.txt
paddle/phi/infermeta/sparse/CMakeLists.txt
+9
-0
paddle/phi/infermeta/sparse/backward.cc
paddle/phi/infermeta/sparse/backward.cc
+35
-0
paddle/phi/infermeta/sparse/backward.h
paddle/phi/infermeta/sparse/backward.h
+33
-0
paddle/phi/infermeta/sparse/binary.cc
paddle/phi/infermeta/sparse/binary.cc
+147
-0
paddle/phi/infermeta/sparse/binary.h
paddle/phi/infermeta/sparse/binary.h
+52
-0
paddle/phi/infermeta/sparse/multiary.cc
paddle/phi/infermeta/sparse/multiary.cc
+32
-0
paddle/phi/infermeta/sparse/multiary.h
paddle/phi/infermeta/sparse/multiary.h
+32
-0
paddle/phi/infermeta/sparse/unary.cc
paddle/phi/infermeta/sparse/unary.cc
+36
-0
paddle/phi/infermeta/sparse/unary.h
paddle/phi/infermeta/sparse/unary.h
+28
-0
paddle/phi/kernels/CMakeLists.txt
paddle/phi/kernels/CMakeLists.txt
+2
-1
paddle/phi/kernels/sparse/cpu/elementwise_grad_kernel.cc
paddle/phi/kernels/sparse/cpu/elementwise_grad_kernel.cc
+5
-2
paddle/phi/kernels/sparse/cpu/elementwise_kernel.cc
paddle/phi/kernels/sparse/cpu/elementwise_kernel.cc
+13
-20
paddle/phi/kernels/sparse/cpu/sparse_utils_kernel.cc
paddle/phi/kernels/sparse/cpu/sparse_utils_kernel.cc
+24
-14
paddle/phi/kernels/sparse/elementwise_grad_kernel.h
paddle/phi/kernels/sparse/elementwise_grad_kernel.h
+10
-0
paddle/phi/kernels/sparse/elementwise_kernel.h
paddle/phi/kernels/sparse/elementwise_kernel.h
+9
-4
paddle/phi/kernels/sparse/empty_kernel.cc
paddle/phi/kernels/sparse/empty_kernel.cc
+4
-6
paddle/phi/kernels/sparse/gpu/sparse_utils_kernel.cu
paddle/phi/kernels/sparse/gpu/sparse_utils_kernel.cu
+18
-2
paddle/phi/kernels/sparse/impl/unary_kernel_impl.h
paddle/phi/kernels/sparse/impl/unary_kernel_impl.h
+0
-4
paddle/phi/kernels/sparse/sparse_utils_kernel.h
paddle/phi/kernels/sparse/sparse_utils_kernel.h
+21
-0
未找到文件。
paddle/phi/api/lib/CMakeLists.txt
浏览文件 @
4b95f85e
...
...
@@ -370,7 +370,6 @@ cc_library(
SRCS api_custom_impl.cc
DEPS phi_tensor_raw phi kernel_dispatch api_gen_utils backward_infermeta
phi_data_transform
)
cc_library
(
phi_function_api
SRCS
${
api_source_file
}
...
...
@@ -384,6 +383,7 @@ cc_library(
kernel_dispatch
api_gen_utils
backward_infermeta
sparse_backward_infermeta
phi_data_transform
phi_function_api
api_custom_impl
...
...
@@ -395,7 +395,8 @@ cc_library(
cc_library
(
sparse_bw_api
SRCS
${
sparse_bw_api_source_file
}
DEPS phi_tensor_raw phi kernel_dispatch api_gen_utils sparse_api
)
DEPS phi_tensor_raw phi kernel_dispatch api_gen_utils sparse_api
sparse_backward_infermeta
)
cc_library
(
phi_dygraph_api
SRCS
${
dygraph_api_source_file
}
...
...
@@ -418,6 +419,7 @@ cc_library(
api_gen_utils
kernel_dispatch
infermeta
sparse_infermeta
sparse_api
strings_api
)
cc_library
(
...
...
paddle/phi/api/lib/api_gen_utils.cc
浏览文件 @
4b95f85e
...
...
@@ -88,6 +88,10 @@ std::shared_ptr<phi::StringTensor> TensorToStringTensor(const Tensor& tensor) {
return
std
::
dynamic_pointer_cast
<
phi
::
StringTensor
>
(
tensor
.
impl
());
}
std
::
shared_ptr
<
phi
::
SparseCooTensor
>
TensorToSparseCooTensor
(
const
Tensor
&
tensor
)
{
return
std
::
static_pointer_cast
<
phi
::
SparseCooTensor
>
(
tensor
.
impl
());
}
/* ----------------- for infer_meta --------------------- */
phi
::
MetaTensor
MakeMetaTensor
(
const
phi
::
TensorBase
&
tensor
)
{
...
...
@@ -150,6 +154,22 @@ phi::MetaTensor MakeMetaTensor(
return
phi
::
MetaTensor
();
}
phi
::
MetaTensor
MakeMetaTensor
(
const
paddle
::
optional
<
phi
::
SparseCooTensor
>&
tensor
)
{
if
(
tensor
)
{
return
{
phi
::
MetaTensor
(
*
tensor
)};
}
return
phi
::
MetaTensor
();
}
phi
::
MetaTensor
MakeMetaTensor
(
const
paddle
::
optional
<
phi
::
SparseCsrTensor
>&
tensor
)
{
if
(
tensor
)
{
return
{
phi
::
MetaTensor
(
*
tensor
)};
}
return
phi
::
MetaTensor
();
}
std
::
vector
<
phi
::
MetaTensor
>
MakeMetaTensor
(
const
paddle
::
optional
<
std
::
vector
<
const
phi
::
DenseTensor
*>>&
tensors
)
{
std
::
vector
<
phi
::
MetaTensor
>
meta_tensors
;
...
...
paddle/phi/api/lib/api_gen_utils.h
浏览文件 @
4b95f85e
...
...
@@ -52,6 +52,8 @@ paddle::optional<phi::SelectedRows> TensorToSelectedRows(
std
::
shared_ptr
<
phi
::
StringTensor
>
TensorToStringTensor
(
const
Tensor
&
tensor
);
std
::
shared_ptr
<
phi
::
SparseCooTensor
>
TensorToSparseCooTensor
(
const
Tensor
&
tensor
);
/* ----------------- for infer_meta --------------------- */
phi
::
MetaTensor
MakeMetaTensor
(
const
phi
::
TensorBase
&
tensor
);
...
...
@@ -71,6 +73,12 @@ std::vector<phi::MetaTensor> MakeMetaTensor(
phi
::
MetaTensor
MakeMetaTensor
(
const
paddle
::
optional
<
phi
::
SelectedRows
>&
tensor
);
phi
::
MetaTensor
MakeMetaTensor
(
const
paddle
::
optional
<
phi
::
SparseCooTensor
>&
tensor
);
phi
::
MetaTensor
MakeMetaTensor
(
const
paddle
::
optional
<
phi
::
SparseCsrTensor
>&
tensor
);
std
::
vector
<
phi
::
MetaTensor
>
MakeMetaTensor
(
const
paddle
::
optional
<
std
::
vector
<
const
phi
::
DenseTensor
*>>&
tensors
);
...
...
paddle/phi/api/lib/tensor_method.cc
浏览文件 @
4b95f85e
...
...
@@ -24,6 +24,7 @@ limitations under the License. */
#include "paddle/phi/api/lib/kernel_dispatch.h"
#include "paddle/phi/core/tensor_utils.h"
#include "paddle/phi/infermeta/unary.h"
// clang-format off
namespace
paddle
{
namespace
experimental
{
...
...
@@ -165,7 +166,11 @@ void Tensor::copy_(const Tensor &src,
static_cast
<
phi
::
SelectedRows
*>
(
impl_
.
get
()));
}
else
if
(
kernel_type
==
KernelType
::
SPARSE_COO_KERNEL
)
{
SetSparseKernelOutput
(
this
,
TensorType
::
SPARSE_COO
);
// TODO(zhangkaihuo) add sparse infer_meta
phi
::
MetaTensor
meta_out
(
impl_
.
get
());
phi
::
UnchangedInferMeta
(
MakeMetaTensor
(
*
(
std
::
static_pointer_cast
<
phi
::
SparseCooTensor
>
(
src
.
impl_
))),
&
meta_out
);
phi
::
Copy
(
*
dev_ctx
,
(
*
(
std
::
static_pointer_cast
<
phi
::
SparseCooTensor
>
(
src
.
impl_
))),
target_place
,
...
...
@@ -173,7 +178,11 @@ void Tensor::copy_(const Tensor &src,
static_cast
<
phi
::
SparseCooTensor
*>
(
impl_
.
get
()));
}
else
if
(
kernel_type
==
KernelType
::
SPARSE_CSR_KERNEL
)
{
SetSparseKernelOutput
(
this
,
TensorType
::
SPARSE_CSR
);
// TODO(zhangkaihuo) add sparse infer_meta
phi
::
MetaTensor
meta_out
(
impl_
.
get
());
phi
::
UnchangedInferMeta
(
MakeMetaTensor
(
*
(
std
::
static_pointer_cast
<
phi
::
SparseCsrTensor
>
(
src
.
impl_
))),
&
meta_out
);
phi
::
Copy
(
*
dev_ctx
,
(
*
(
std
::
static_pointer_cast
<
phi
::
SparseCsrTensor
>
(
src
.
impl_
))),
target_place
,
...
...
paddle/phi/api/yaml/generator/intermediate_api_gen.py
浏览文件 @
4b95f85e
...
...
@@ -50,6 +50,10 @@ def source_include(header_file_path):
#include "paddle/phi/infermeta/unary.h"
#include "paddle/phi/infermeta/ternary.h"
#include "paddle/phi/infermeta/sparse/unary.h"
#include "paddle/phi/infermeta/sparse/binary.h"
#include "paddle/phi/infermeta/sparse/multiary.h"
#include "paddle/fluid/platform/profiler/event_tracing.h"
#include "paddle/fluid/platform/profiler/supplement_tracing.h"
"""
...
...
paddle/phi/api/yaml/generator/sparse_api_gen.py
浏览文件 @
4b95f85e
...
...
@@ -18,6 +18,7 @@ import argparse
import
re
from
api_gen
import
ForwardAPI
from
api_base
import
PREFIX_TENSOR_NAME
class
SparseAPI
(
ForwardAPI
):
...
...
@@ -136,6 +137,36 @@ class SparseAPI(ForwardAPI):
return
kernel_context_code
def
prepare_input
(
self
):
input_names
=
self
.
inputs
[
'names'
]
input_types
=
self
.
inputs
[
'tensor_type'
]
attr_names
=
self
.
attrs
[
'names'
]
infer_meta
=
self
.
infer_meta
infer_meta_params
=
infer_meta
[
'param'
]
if
infer_meta
[
'param'
]
is
not
None
else
input_names
+
attr_names
create_input_var_code
=
""
tensor_type_map
=
{
'dense'
:
'phi::DenseTensor'
,
'sparse_coo'
:
'phi::SparseCooTensor'
,
'sparse_csr'
:
'phi::SparseCsrTensor'
}
for
param
in
infer_meta_params
:
if
param
in
input_names
:
var_name
=
"auto "
+
PREFIX_TENSOR_NAME
+
param
+
" = "
if
self
.
inputs
[
'input_info'
][
param
]
==
"const Tensor&"
:
create_input_var_code
=
create_input_var_code
+
var_name
+
param
+
".impl();
\n
"
elif
param
in
self
.
optional_vars
:
tensor_type
=
'phi::DenseTensor'
for
name
,
input_type
in
zip
(
input_names
,
input_types
):
if
param
==
name
:
tensor_type
=
tensor_type_map
[
input_type
]
break
optional_var
=
"paddle::optional<"
+
tensor_type
+
">("
create_input_var_code
=
create_input_var_code
+
var_name
+
param
+
" ? "
+
optional_var
+
"*static_cast<"
+
tensor_type
+
"*>((*"
+
param
+
").impl().get())) : "
+
optional_var
+
"paddle::none);
\n
"
return
f
"""
{
create_input_var_code
}
"""
def
gen_sparse_kernel_code
(
self
,
kernel_name
,
inplace_flag
=
False
):
_
,
kernel_output_names
,
output_create
=
self
.
gene_output
(
self
.
kernel
[
'dispatch'
][
kernel_name
][
1
],
None
,
''
,
inplace_flag
)
...
...
@@ -154,6 +185,8 @@ class SparseAPI(ForwardAPI):
auto* dev_ctx = GetDeviceContextByBackend(kernel_result.has_fallback_cpu ? Backend::CPU : kernel_backend);
auto kernel_context = phi::KernelContext(dev_ctx);
{
output_create
}
{
self
.
prepare_input
()
}
{
self
.
gene_infer_meta
(
kernel_output_names
,
''
)
}
{
kernel_context_code
}
phi_kernel(&kernel_context);
{
return_code
}
"""
...
...
@@ -167,6 +200,7 @@ class SparseAPI(ForwardAPI):
'sparse_csr'
:
'DataLayout::SPARSE_CSR'
}
condition_list
=
[]
tensor_type_list
=
[]
for
i
,
in_type
in
enumerate
(
input_types
):
if
in_type
==
"dense"
:
if
self
.
inputs
[
'names'
][
i
]
in
self
.
optional_vars
:
...
...
@@ -178,9 +212,15 @@ class SparseAPI(ForwardAPI):
f
"phi::DenseTensor::classof(
{
self
.
inputs
[
'names'
][
i
]
}
.impl().get())"
)
else
:
condition_list
.
append
(
f
"
{
self
.
inputs
[
'names'
][
i
]
}
.layout() ==
{
sparse_type_map
[
in_type
]
}
"
)
if
in_type
==
'sparse_coo'
:
condition_list
.
append
(
f
"
{
self
.
inputs
[
'names'
][
i
]
}
.is_sparse_coo_tensor()"
)
else
:
condition_list
.
append
(
f
"
{
self
.
inputs
[
'names'
][
i
]
}
.is_sparse_csr_tensor()"
)
tensor_type_list
.
append
(
in_type
)
self
.
inputs
[
'tensor_type'
]
=
tensor_type_list
return
" && "
.
join
(
condition_list
)
def
gene_dispatch_code
(
self
,
kernel_name
,
inplace_flag
=
False
):
...
...
@@ -230,6 +270,15 @@ def source_include(header_file_path):
#include "paddle/phi/api/lib/data_transform.h"
#include "paddle/phi/api/lib/kernel_dispatch.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/infermeta/unary.h"
#include "paddle/phi/infermeta/binary.h"
#include "paddle/phi/infermeta/ternary.h"
#include "paddle/phi/infermeta/multiary.h"
#include "paddle/utils/none.h"
#include "paddle/phi/infermeta/sparse/unary.h"
#include "paddle/phi/infermeta/sparse/binary.h"
#include "paddle/phi/infermeta/sparse/multiary.h"
"""
...
...
paddle/phi/api/yaml/generator/sparse_bw_api_gen.py
浏览文件 @
4b95f85e
...
...
@@ -112,6 +112,14 @@ def source_include(header_file_path):
#include "paddle/phi/api/lib/api_gen_utils.h"
#include "paddle/phi/api/lib/kernel_dispatch.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/infermeta/unary.h"
#include "paddle/phi/infermeta/binary.h"
#include "paddle/phi/infermeta/backward.h"
#include "paddle/phi/infermeta/sparse/unary.h"
#include "paddle/phi/infermeta/sparse/binary.h"
#include "paddle/phi/infermeta/sparse/backward.h"
"""
...
...
paddle/phi/api/yaml/sparse_backward.yaml
浏览文件 @
4b95f85e
...
...
@@ -2,6 +2,9 @@
forward
:
tanh(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
abs_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
abs_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -10,6 +13,9 @@
forward
:
acos(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
acos_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
acos_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -18,6 +24,9 @@
forward
:
acosh(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
acosh_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
acosh_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -26,6 +35,9 @@
forward
:
add(Tensor x, Tensor y) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(y_grad)
infer_meta
:
func
:
GeneralBinaryGradInferMeta
param
:
[
x
,
y
]
kernel
:
func
:
add_coo_coo_grad{sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo},
add_csr_csr_grad{sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr}
...
...
@@ -34,6 +46,9 @@
forward
:
addmm(Tensor input, Tensor x, Tensor y, float alpha=1.0, float beta=1.0) -> Tensor(out)
args
:
(Tensor input, Tensor x, Tensor y, Tensor out_grad, float alpha=1.0, float beta=1.0)
output
:
Tensor(input_grad), Tensor(x_grad), Tensor(y_grad)
infer_meta
:
func
:
GeneralTernaryGradInferMeta
param
:
[
input
,
x
,
y
]
kernel
:
func
:
addmm_csr_dense_grad {dense, sparse_csr, dense, dense -> dense, sparse_csr, dense},
addmm_csr_csr_grad {sparse_csr, sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr, sparse_csr},
...
...
@@ -44,6 +59,9 @@
forward
:
asin(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
asin_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
asin_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -52,6 +70,9 @@
forward
:
asinh(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
asinh_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
asinh_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -60,6 +81,9 @@
forward
:
atan(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
atan_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
atan_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -68,6 +92,9 @@
forward
:
atanh(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
atanh_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
atanh_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -76,6 +103,9 @@
forward
:
cast(Tensor x, DataType index_dtype, DataType value_dtype) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad, DataType value_dtype)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
cast_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
cast_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -85,6 +115,9 @@
forward
:
conv3d_coo (Tensor x, Tensor kernel, int[] paddings, int[] dilations, int[] strides, int groups, bool subm, str key) -> Tensor(out), Tensor(rulebook), Tensor(counter)
args
:
(Tensor x, Tensor kernel, Tensor out, Tensor rulebook, Tensor counter, Tensor out_grad, int[] paddings, int[] dilations, int[] strides, int groups, bool subm, str key)
output
:
Tensor(x_grad), Tensor(kernel_grad)
infer_meta
:
func
:
GeneralBinaryGradInferMeta
param
:
[
x
,
kernel
]
kernel
:
func
:
conv3d_coo_grad{sparse_coo, dense, sparse_coo, dense, dense, sparse_coo -> sparse_coo, dense}
...
...
@@ -92,6 +125,9 @@
forward
:
divide(Tensor x, Tensor y) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(y_grad)
infer_meta
:
func
:
GeneralBinaryGradInferMeta
param
:
[
x
,
y
]
kernel
:
func
:
divide_coo_coo_grad{sparse_coo, sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo},
divide_csr_csr_grad{sparse_csr, sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr}
...
...
@@ -106,6 +142,9 @@
forward
:
expm1(Tensor x) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
out
]
kernel
:
func
:
expm1_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
expm1_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -114,6 +153,9 @@
forward
:
leaky_relu(Tensor x, float alpha) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad, float alpha)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
leaky_relu_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
leaky_relu_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -122,6 +164,9 @@
forward
:
log1p(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
log1p_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
log1p_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -130,6 +175,9 @@
forward
:
masked_matmul(Tensor x, Tensor y, Tensor mask) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(y_grad)
infer_meta
:
func
:
GeneralBinaryGradInferMeta
param
:
[
x
,
y
]
kernel
:
func
:
masked_matmul_csr_grad{dense, dense, sparse_csr -> dense, dense}
...
...
@@ -137,6 +185,9 @@
forward
:
matmul(Tensor x, Tensor y) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(y_grad)
infer_meta
:
func
:
GeneralBinaryGradInferMeta
param
:
[
x
,
y
]
kernel
:
func
:
matmul_csr_dense_grad {sparse_csr, dense, dense -> sparse_csr, dense},
matmul_csr_csr_grad {sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr},
...
...
@@ -147,6 +198,9 @@
forward
:
maxpool(Tensor x, int[] kernel_sizes, int[] paddings, int[] dilations, int[] strides) -> Tensor(out), Tensor(rulebook), Tensor(counter)
args
:
(Tensor x, Tensor rulebook, Tensor counter, Tensor out, Tensor out_grad, int[] kernel_sizes)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
maxpool_coo_grad {sparse_coo, dense, dense, sparse_coo, sparse_coo -> sparse_coo}
...
...
@@ -154,6 +208,9 @@
forward
:
multiply(Tensor x, Tensor y) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(y_grad)
infer_meta
:
func
:
GeneralBinaryGradInferMeta
param
:
[
x
,
y
]
kernel
:
func
:
multiply_coo_coo_grad{sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo},
multiply_csr_csr_grad{sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr}
...
...
@@ -162,6 +219,9 @@
forward
:
mv(Tensor x, Tensor vec) -> Tensor(out)
args
:
(Tensor x, Tensor vec, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(vec_grad)
infer_meta
:
func
:
GeneralBinaryGradInferMeta
param
:
[
x
,
vec
]
kernel
:
func
:
mv_coo_grad{sparse_coo, dense, dense -> sparse_coo, dense},
mv_csr_grad{sparse_csr, dense, dense -> sparse_csr, dense}
...
...
@@ -170,6 +230,9 @@
forward
:
pow(Tensor x, float factor) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad, float factor)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
pow_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
pow_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -178,6 +241,9 @@
forward
:
relu6(Tensor x, float threshold) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad, float threshold)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
out
]
kernel
:
func
:
relu6_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
relu6_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -186,6 +252,9 @@
forward
:
relu(Tensor x) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
out
]
kernel
:
func
:
relu_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
relu_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -194,12 +263,18 @@
forward
:
scale(Tensor x, float scale, float bias, bool bias_after_scale) -> Tensor(out)
args
:
(Tensor out_grad, float scale)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
out_grad
]
invoke
:
scale(out_grad, scale, 0.0,
true
)
-
backward_op
:
sin_grad
forward
:
sin(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
sin_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
sin_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -208,6 +283,9 @@
forward
:
sinh(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
sinh_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
sinh_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -216,6 +294,9 @@
forward
:
softmax(Tensor x, int axis=-1) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad, int axis)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
out
]
kernel
:
func
:
softmax_csr_grad{sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -223,6 +304,9 @@
forward
:
sparse_coo_tensor(Tensor values, Tensor indices, IntArray dense_shape) -> Tensor(out)
args
:
(Tensor indices, Tensor out_grad)
output
:
Tensor(values_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
out_grad
]
kernel
:
func
:
sparse_coo_tensor_grad{dense, sparse_coo -> dense}
...
...
@@ -230,6 +314,9 @@
forward
:
sqrt(Tensor x) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
out
]
kernel
:
func
:
sqrt_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
sqrt_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -238,6 +325,9 @@
forward
:
square(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
square_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
square_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -246,6 +336,9 @@
forward
:
subtract(Tensor x, Tensor y) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(y_grad)
infer_meta
:
func
:
GeneralBinaryGradInferMeta
param
:
[
x
,
y
]
kernel
:
func
:
subtract_coo_coo_grad{sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo},
subtract_csr_csr_grad{sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr}
...
...
@@ -254,6 +347,9 @@
forward
:
tan(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
tan_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
tan_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -262,6 +358,9 @@
forward
:
tanh(Tensor x) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
out
]
kernel
:
func
:
tanh_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
tanh_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -270,6 +369,9 @@
forward
:
to_dense(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
coo_to_dense_grad{sparse_coo, dense -> sparse_coo}
...
...
@@ -277,6 +379,8 @@
forward
:
to_sparse_coo(Tensor x, int64_t sparse_dim) -> Tensor(out)
args
:
(Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
coo_to_dense { sparse_coo -> dense }
...
...
@@ -284,6 +388,9 @@
forward
:
values_coo(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
values_coo_grad{sparse_coo, dense-> sparse_coo}
...
...
@@ -291,6 +398,8 @@
forward
:
fused_attention_csr(Tensor query, Tensor key, Tensor value, Tensor sparse_mask, Tensor key_padding_mask, Tensor attn_mask) -> Tensor(out), Tensor(softmax)
args
:
(Tensor query, Tensor key, Tensor value, Tensor softmax, Tensor out_grad)
output
:
Tensor(query_grad), Tensor(key_grad), Tensor(value_grad)
infer_meta
:
func
:
sparse::FusedAttentionGradInferMeta
kernel
:
func
:
fused_attention_csr_grad{dense, dense, dense, sparse_csr, dense -> dense, dense, dense}
layout
:
softmax
...
...
paddle/phi/api/yaml/sparse_ops.yaml
浏览文件 @
4b95f85e
-
op
:
abs
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
abs_coo{sparse_coo -> sparse_coo},
abs_csr{sparse_csr -> sparse_csr}
...
...
@@ -10,6 +12,8 @@
-
op
:
acos
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
acos_coo{sparse_coo -> sparse_coo},
acos_csr{sparse_csr -> sparse_csr}
...
...
@@ -19,6 +23,8 @@
-
op
:
acosh
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
acosh_coo{sparse_coo -> sparse_coo},
acosh_csr{sparse_csr -> sparse_csr}
...
...
@@ -28,6 +34,8 @@
-
op
:
add
args
:
(Tensor x, Tensor y)
output
:
Tensor(out)
infer_meta
:
func
:
ElementwiseInferMeta
kernel
:
func
:
add_coo_coo{sparse_coo, sparse_coo -> sparse_coo},
add_csr_csr{sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -37,6 +45,8 @@
-
op
:
asin
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
asin_coo{sparse_coo -> sparse_coo},
asin_csr{sparse_csr -> sparse_csr}
...
...
@@ -46,6 +56,8 @@
-
op
:
asinh
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
asinh_coo{sparse_coo -> sparse_coo},
asinh_csr{sparse_csr -> sparse_csr}
...
...
@@ -55,6 +67,8 @@
-
op
:
atan
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
atan_coo{sparse_coo -> sparse_coo},
atan_csr{sparse_csr -> sparse_csr}
...
...
@@ -64,6 +78,8 @@
-
op
:
atanh
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
atanh_coo{sparse_coo -> sparse_coo},
atanh_csr{sparse_csr -> sparse_csr}
...
...
@@ -73,6 +89,9 @@
-
op
:
cast
args
:
(Tensor x, DataType index_dtype=DataType::UNDEFINED, DataType value_dtype=DataType::UNDEFINED)
output
:
Tensor(out)
infer_meta
:
func
:
CastInferMeta
param
:
[
x
,
value_dtype
]
kernel
:
func
:
cast_coo{sparse_coo -> sparse_coo},
cast_csr{sparse_csr -> sparse_csr}
...
...
@@ -83,6 +102,8 @@
-
op
:
conv3d
args
:
(Tensor x, Tensor kernel, int[] paddings, int[] dilations, int[] strides, int groups, bool subm, str key)
output
:
Tensor(out), Tensor(rulebook), Tensor(counter)
infer_meta
:
func
:
sparse::Conv3dInferMeta
kernel
:
func
:
conv3d_coo{sparse_coo, dense -> sparse_coo, dense, dense}
layout
:
x
...
...
@@ -92,6 +113,8 @@
-
op
:
divide
args
:
(Tensor x, Tensor y)
output
:
Tensor(out)
infer_meta
:
func
:
ElementwiseInferMeta
kernel
:
func
:
divide_coo_coo{sparse_coo, sparse_coo -> sparse_coo},
divide_csr_csr{sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -101,6 +124,9 @@
-
op
:
divide_scalar
args
:
(Tensor x, float scalar)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
divide_coo_scalar{sparse_coo -> sparse_coo},
divide_csr_scalar{sparse_csr -> sparse_csr}
...
...
@@ -109,6 +135,8 @@
-
op
:
expm1
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
expm1_coo{sparse_coo -> sparse_coo},
expm1_csr{sparse_csr -> sparse_csr}
...
...
@@ -118,6 +146,9 @@
-
op
:
leaky_relu
args
:
(Tensor x, float alpha)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
leaky_relu_coo{sparse_coo -> sparse_coo},
leaky_relu_csr{sparse_csr -> sparse_csr}
...
...
@@ -127,6 +158,8 @@
-
op
:
log1p
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
log1p_coo{sparse_coo -> sparse_coo},
log1p_csr{sparse_csr -> sparse_csr}
...
...
@@ -136,6 +169,8 @@
-
op
:
multiply
args
:
(Tensor x, Tensor y)
output
:
Tensor(out)
infer_meta
:
func
:
ElementwiseInferMeta
kernel
:
func
:
multiply_coo_coo{sparse_coo, sparse_coo -> sparse_coo},
multiply_csr_csr{sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -145,6 +180,9 @@
-
op
:
pow
args
:
(Tensor x, float factor)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
pow_coo{sparse_coo -> sparse_coo},
pow_csr{sparse_csr -> sparse_csr}
...
...
@@ -154,6 +192,8 @@
-
op
:
relu
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
relu_coo{sparse_coo -> sparse_coo},
relu_csr{sparse_csr -> sparse_csr}
...
...
@@ -163,6 +203,9 @@
-
op
:
relu6
args
:
(Tensor x, float threshold)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
relu6_coo{sparse_coo -> sparse_coo},
relu6_csr{sparse_csr -> sparse_csr}
...
...
@@ -172,6 +215,9 @@
-
op
:
scale
args
:
(Tensor x, float scale, float bias, bool bias_after_scale)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
scale_coo{sparse_coo -> sparse_coo},
scale_csr{sparse_csr -> sparse_csr}
...
...
@@ -180,6 +226,8 @@
-
op
:
sin
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
sin_coo{sparse_coo -> sparse_coo},
sin_csr{sparse_csr -> sparse_csr}
...
...
@@ -189,6 +237,8 @@
-
op
:
sinh
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
sinh_coo{sparse_coo -> sparse_coo},
sinh_csr{sparse_csr -> sparse_csr}
...
...
@@ -198,6 +248,9 @@
-
op
:
softmax
args
:
(Tensor x, int axis=-1)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
softmax_csr{sparse_csr -> sparse_csr}
layout
:
x
...
...
@@ -206,6 +259,8 @@
-
op
:
sparse_coo_tensor
args
:
(Tensor values, Tensor indices, IntArray dense_shape)
output
:
Tensor(out)
infer_meta
:
func
:
sparse::SparseCooTensorInferMeta
kernel
:
func
:
sparse_coo_tensor{dense, dense -> sparse_coo}
layout
:
values
...
...
@@ -215,6 +270,8 @@
-
op
:
sqrt
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
sqrt_coo{sparse_coo -> sparse_coo},
sqrt_csr{sparse_csr -> sparse_csr}
...
...
@@ -224,6 +281,8 @@
-
op
:
square
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
square_coo{sparse_coo -> sparse_coo},
square_csr{sparse_csr -> sparse_csr}
...
...
@@ -233,6 +292,8 @@
-
op
:
subtract
args
:
(Tensor x, Tensor y)
output
:
Tensor(out)
infer_meta
:
func
:
ElementwiseInferMeta
kernel
:
func
:
subtract_coo_coo{sparse_coo, sparse_coo -> sparse_coo},
subtract_csr_csr{sparse_csr, sparse_csr -> sparse_csr}
...
...
@@ -242,6 +303,8 @@
-
op
:
tan
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
tan_coo{sparse_coo -> sparse_coo},
tan_csr{sparse_csr -> sparse_csr}
...
...
@@ -251,6 +314,8 @@
-
op
:
tanh
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
tanh_coo{sparse_coo -> sparse_coo},
tanh_csr{sparse_csr -> sparse_csr}
...
...
@@ -260,6 +325,8 @@
-
op
:
to_dense
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
coo_to_dense {sparse_coo -> dense},
csr_to_dense {sparse_csr -> dense}
...
...
@@ -268,6 +335,9 @@
-
op
:
to_sparse_coo
args
:
(Tensor x, int64_t sparse_dim)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
dense_to_coo { dense -> sparse_coo },
csr_to_coo { sparse_csr -> sparse_coo}
...
...
@@ -276,6 +346,8 @@
-
op
:
to_sparse_csr
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
dense_to_csr {dense -> sparse_csr},
coo_to_csr {sparse_coo -> sparse_csr}
...
...
@@ -283,6 +355,8 @@
-
op
:
values
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
sparse::ValuesInferMeta
kernel
:
func
:
values_coo{sparse_coo -> dense},
values_csr{sparse_csr -> dense}
...
...
@@ -292,6 +366,8 @@
-
op
:
addmm
args
:
(Tensor input, Tensor x, Tensor y, float alpha=1.0, float beta=1.0)
output
:
Tensor(out)
infer_meta
:
func
:
AddmmInferMeta
kernel
:
func
:
addmm_csr_dense {dense, sparse_csr, dense -> dense},
addmm_csr_csr {sparse_csr, sparse_csr, sparse_csr -> sparse_csr},
...
...
@@ -303,6 +379,8 @@
-
op
:
coalesce
args
:
(Tensor x)
output
:
Tensor(out)
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
coalesce{sparse_coo -> sparse_coo}
layout
:
x
...
...
@@ -310,6 +388,9 @@
-
op
:
full_like
args
:
(Tensor x, Scalar value, DataType dtype=DataType::UNDEFINED)
output
:
Tensor(out)
infer_meta
:
func
:
CreateLikeInferMeta
param
:
[
x
,
dtype
]
kernel
:
func
:
coo_full_like{sparse_coo -> sparse_coo},
csr_full_like{sparse_csr -> sparse_csr}
...
...
@@ -319,6 +400,8 @@
-
op
:
fused_attention
args
:
(Tensor query, Tensor key, Tensor value, Tensor sparse_mask, Tensor key_padding_mask, Tensor attn_mask)
output
:
Tensor(out), Tensor(softmax)
infer_meta
:
func
:
sparse::FusedAttentionInferMeta
kernel
:
func
:
fused_attention_csr{dense, dense, dense, sparse_csr, dense, dense -> dense, sparse_csr}
layout
:
sparse_mask
...
...
@@ -330,6 +413,9 @@
-
op
:
masked_matmul
args
:
(Tensor x, Tensor y, Tensor mask)
output
:
Tensor(out)
infer_meta
:
func
:
MatmulInferMeta
param
:
[
x
,
y
,
false
,
false
]
kernel
:
func
:
masked_matmul_csr{dense, dense, sparse_csr -> sparse_csr}
layout
:
x
...
...
@@ -338,6 +424,9 @@
-
op
:
matmul
args
:
(Tensor x, Tensor y)
output
:
Tensor(out)
infer_meta
:
func
:
MatmulInferMeta
param
:
[
x
,
y
,
false
,
false
]
kernel
:
func
:
matmul_csr_dense {sparse_csr, dense -> dense},
matmul_csr_csr {sparse_csr, sparse_csr -> sparse_csr},
...
...
@@ -349,6 +438,8 @@
-
op
:
maxpool
args
:
(Tensor x, int[] kernel_sizes, int[] paddings, int[] dilations, int[] strides)
output
:
Tensor(out), Tensor(rulebook), Tensor(counter)
infer_meta
:
func
:
sparse::Pool3dInferMeta
kernel
:
func
:
maxpool_coo{sparse_coo -> sparse_coo, dense, dense}
layout
:
x
...
...
@@ -358,6 +449,8 @@
-
op
:
mv
args
:
(Tensor x, Tensor vec)
output
:
Tensor(out)
infer_meta
:
func
:
MvInferMeta
kernel
:
func
:
mv_coo{sparse_coo, dense -> dense},
mv_csr{sparse_csr, dense -> dense}
...
...
paddle/phi/core/meta_tensor.cc
浏览文件 @
4b95f85e
...
...
@@ -64,6 +64,12 @@ void MetaTensor::set_dims(const DDim& dims) {
DenseTensorUtils
::
GetMutableMeta
(
static_cast
<
SelectedRows
*>
(
tensor_
)
->
mutable_value
())
->
dims
=
dims
;
}
else
if
(
phi
::
SparseCooTensor
::
classof
(
tensor_
))
{
DenseTensorUtils
::
GetMutableMeta
(
static_cast
<
SparseCooTensor
*>
(
tensor_
))
->
dims
=
dims
;
}
else
if
(
phi
::
SparseCsrTensor
::
classof
(
tensor_
))
{
DenseTensorUtils
::
GetMutableMeta
(
static_cast
<
SparseCsrTensor
*>
(
tensor_
))
->
dims
=
dims
;
}
else
{
PADDLE_THROW
(
phi
::
errors
::
Unimplemented
(
"Unsupported setting dims for `%s`."
,
tensor_
->
type_info
().
name
()));
...
...
@@ -81,6 +87,13 @@ void MetaTensor::set_dtype(DataType dtype) {
DenseTensorUtils
::
GetMutableMeta
(
static_cast
<
SelectedRows
*>
(
tensor_
)
->
mutable_value
())
->
dtype
=
dtype
;
}
else
if
(
phi
::
SparseCooTensor
::
classof
(
tensor_
))
{
DenseTensorUtils
::
GetMutableMeta
(
static_cast
<
SparseCooTensor
*>
(
tensor_
))
->
dtype
=
dtype
;
}
else
if
(
phi
::
SparseCsrTensor
::
classof
(
tensor_
))
{
DenseTensorUtils
::
GetMutableMeta
(
static_cast
<
SparseCsrTensor
*>
(
tensor_
))
->
dtype
=
dtype
;
// No need to set dtype
}
else
{
PADDLE_THROW
(
phi
::
errors
::
Unimplemented
(
"Unsupported settting dtype for `%s`."
,
tensor_
->
type_info
().
name
()));
...
...
@@ -98,6 +111,12 @@ void MetaTensor::set_layout(DataLayout layout) {
DenseTensorUtils
::
GetMutableMeta
(
static_cast
<
SelectedRows
*>
(
tensor_
)
->
mutable_value
())
->
layout
=
layout
;
}
else
if
(
phi
::
SparseCooTensor
::
classof
(
tensor_
))
{
DenseTensorUtils
::
GetMutableMeta
(
static_cast
<
SparseCooTensor
*>
(
tensor_
))
->
layout
=
layout
;
}
else
if
(
phi
::
SparseCsrTensor
::
classof
(
tensor_
))
{
DenseTensorUtils
::
GetMutableMeta
(
static_cast
<
SparseCsrTensor
*>
(
tensor_
))
->
layout
=
layout
;
}
else
{
PADDLE_THROW
(
phi
::
errors
::
Unimplemented
(
"Unsupported settting layout for `%s`."
,
tensor_
->
type_info
().
name
()));
...
...
@@ -107,6 +126,10 @@ void MetaTensor::set_layout(DataLayout layout) {
void
MetaTensor
::
share_lod
(
const
MetaTensor
&
meta_tensor
)
{
ValidCheck
(
*
this
);
ValidCheck
(
meta_tensor
);
if
(
phi
::
SparseCooTensor
::
classof
(
tensor_
)
||
phi
::
SparseCsrTensor
::
classof
(
tensor_
))
{
return
;
}
if
(
meta_tensor
.
lod
().
size
()
==
0
)
{
// no need share
return
;
...
...
@@ -128,7 +151,9 @@ void MetaTensor::share_lod(const MetaTensor& meta_tensor) {
void
MetaTensor
::
share_meta
(
const
MetaTensor
&
meta_tensor
)
{
ValidCheck
(
*
this
);
if
(
phi
::
DenseTensor
::
classof
(
tensor_
)
||
phi
::
SelectedRows
::
classof
(
tensor_
))
{
phi
::
SelectedRows
::
classof
(
tensor_
)
||
phi
::
SparseCooTensor
::
classof
(
tensor_
)
||
phi
::
SparseCsrTensor
::
classof
(
tensor_
))
{
share_dims
(
meta_tensor
);
set_dtype
(
meta_tensor
.
dtype
());
set_layout
(
meta_tensor
.
layout
());
...
...
@@ -151,7 +176,9 @@ void MetaTensor::share_dims(const MetaTensor& meta_tensor) {
ValidCheck
(
*
this
);
bool
is_dense_tensor
=
phi
::
DenseTensor
::
classof
(
tensor_
);
bool
is_selected_rows
=
phi
::
SelectedRows
::
classof
(
tensor_
);
if
(
is_dense_tensor
||
is_selected_rows
)
{
bool
is_sparse_coo
=
phi
::
SparseCooTensor
::
classof
(
tensor_
);
bool
is_sparse_csr
=
phi
::
SparseCsrTensor
::
classof
(
tensor_
);
if
(
is_dense_tensor
||
is_selected_rows
||
is_sparse_coo
||
is_sparse_csr
)
{
set_dims
(
meta_tensor
.
dims
());
if
(
is_selected_rows
)
{
const
auto
in_tensor_base
=
meta_tensor
.
tensor
();
...
...
@@ -180,6 +207,10 @@ const LoD& MetaTensor::lod() const {
return
static_cast
<
DenseTensor
*>
(
tensor_
)
->
lod
();
}
else
if
(
phi
::
SelectedRows
::
classof
(
tensor_
))
{
return
static_cast
<
SelectedRows
*>
(
tensor_
)
->
value
().
lod
();
}
else
if
(
phi
::
SparseCooTensor
::
classof
(
tensor_
))
{
return
static_cast
<
SparseCooTensor
*>
(
tensor_
)
->
non_zero_elements
().
lod
();
}
else
if
(
phi
::
SparseCsrTensor
::
classof
(
tensor_
))
{
return
static_cast
<
SparseCsrTensor
*>
(
tensor_
)
->
non_zero_elements
().
lod
();
}
else
{
PADDLE_THROW
(
phi
::
errors
::
Unimplemented
(
"Unsupported getting lod of `%s`."
,
tensor_
->
type_info
().
name
()));
...
...
paddle/phi/core/sparse_coo_tensor.cc
浏览文件 @
4b95f85e
...
...
@@ -21,34 +21,47 @@ SparseCooTensor::SparseCooTensor() {
this
->
SetMember
(
non_zero_indices
,
non_zero_elements
,
{
1
},
true
);
}
SparseCooTensor
::
SparseCooTensor
(
SparseCooTensor
&&
other
)
{
this
->
non_zero_elements_
=
other
.
non_zero_elements_
;
this
->
non_zero_indices_
=
other
.
non_zero_indices_
;
this
->
coalesced_
=
other
.
coalesced_
;
set_meta
(
other
.
meta
());
}
SparseCooTensor
::
SparseCooTensor
(
const
DenseTensor
&
non_zero_indices
,
const
DenseTensor
&
non_zero_elements
,
const
DDim
&
dims
)
:
non_zero_indices_
(
non_zero_indices
),
non_zero_elements_
(
non_zero_elements
),
coalesced_
(
false
),
dims_
(
dims
)
{}
coalesced_
(
false
)
{
meta_
.
dims
=
dims
;
meta_
.
layout
=
DataLayout
::
NCHW
;
meta_
.
dtype
=
non_zero_elements
.
dtype
();
}
SparseCooTensor
::
SparseCooTensor
(
DenseTensor
&&
non_zero_indices
,
DenseTensor
&&
non_zero_elements
,
const
DDim
&
dims
)
:
non_zero_indices_
(
non_zero_indices
),
non_zero_elements_
(
non_zero_elements
),
coalesced_
(
false
),
dims_
(
dims
)
{}
coalesced_
(
false
)
{
meta_
.
dims
=
dims
;
meta_
.
layout
=
DataLayout
::
NCHW
;
meta_
.
dtype
=
non_zero_elements
.
dtype
();
}
SparseCooTensor
::
SparseCooTensor
(
const
SparseCooTensor
&
other
)
:
non_zero_indices_
(
other
.
non_zero_indices_
),
non_zero_elements_
(
other
.
non_zero_elements_
),
dims_
(
other
.
dims_
)
{
non_zero_elements_
(
other
.
non_zero_elements_
)
{
this
->
coalesced_
=
other
.
coalesced_
;
set_meta
(
other
.
meta
());
}
SparseCooTensor
SparseCooTensor
::
operator
=
(
const
SparseCooTensor
&
other
)
{
this
->
dims_
=
other
.
dims_
;
this
->
non_zero_indices_
=
other
.
non_zero_indices_
;
this
->
non_zero_elements_
=
other
.
non_zero_elements_
;
this
->
non_zero_indices_
=
other
.
non_zero_indices_
;
this
->
coalesced_
=
other
.
coalesced_
;
set_meta
(
other
.
meta
());
return
*
this
;
}
...
...
@@ -111,8 +124,18 @@ void SparseCooTensor::SetMember(const DenseTensor& non_zero_indices,
const
bool
coalesced
)
{
this
->
non_zero_indices_
=
non_zero_indices
;
this
->
non_zero_elements_
=
non_zero_elements
;
this
->
dims_
=
dims
;
this
->
meta_
.
dims
=
dims
;
this
->
coalesced_
=
coalesced
;
}
void
SparseCooTensor
::
SetMember
(
const
DenseTensor
&
non_zero_indices
,
const
DenseTensor
&
non_zero_elements
,
const
SparseTensorMeta
&
meta
,
const
bool
coalesced
)
{
this
->
non_zero_indices_
=
non_zero_indices
;
this
->
non_zero_elements_
=
non_zero_elements
;
this
->
coalesced_
=
coalesced
;
set_meta
(
meta
);
}
int32_t
SparseCooTensor
::
sparse_dim
()
const
{
...
...
@@ -120,7 +143,25 @@ int32_t SparseCooTensor::sparse_dim() const {
}
int32_t
SparseCooTensor
::
dense_dim
()
const
{
return
dims_
.
size
()
-
sparse_dim
();
return
meta_
.
dims
.
size
()
-
sparse_dim
();
}
void
SparseCooTensor
::
set_meta
(
SparseTensorMeta
&&
meta
)
{
PADDLE_ENFORCE
(
!
meta_
.
valid
(),
phi
::
errors
::
InvalidArgument
(
"Only when the original attribute of Tensor is "
"incomplete, can it be reset."
));
meta_
=
std
::
move
(
meta
);
}
void
SparseCooTensor
::
set_meta
(
const
SparseTensorMeta
&
meta
)
{
PADDLE_ENFORCE
(
meta
.
valid
(),
phi
::
errors
::
InvalidArgument
(
"Input meta is invalid, please check the meta attribute."
));
meta_
.
dims
=
meta
.
dims
;
meta_
.
dtype
=
meta
.
dtype
;
meta_
.
layout
=
meta
.
layout
;
}
}
// namespace phi
paddle/phi/core/sparse_coo_tensor.h
浏览文件 @
4b95f85e
...
...
@@ -20,6 +20,8 @@ limitations under the License. */
namespace
phi
{
class
DenseTensorUtils
;
/// \brief The SparseCooTensor uses two DenseTensors to represent
/// the non zero elements and the indices of non zero elements of
/// original DenseTensor.
...
...
@@ -93,21 +95,19 @@ class SparseCooTensor : public TensorBase,
/// \brief Return the number of elements contained in original dense tensor
/// \return The number of elements contained in original dense tensor
int64_t
numel
()
const
override
{
return
product
(
dims_
);
}
int64_t
numel
()
const
override
{
return
product
(
meta_
.
dims
);
}
/// \brief Returns the dims of the original dense tensor.
/// \return The dims of the original dense tensor.
const
DDim
&
dims
()
const
noexcept
override
{
return
dims_
;
}
const
DDim
&
dims
()
const
noexcept
override
{
return
meta_
.
dims
;
}
/// \brief Returns the data type of the tensor.
/// \return The data type of the tensor.
DataType
dtype
()
const
noexcept
override
{
return
non_zero_elements_
.
dtype
();
}
DataType
dtype
()
const
noexcept
override
{
return
meta_
.
dtype
;
}
/// \brief Returns the data layout of the tensor.
/// \return The data layout of the tensor.
DataLayout
layout
()
const
noexcept
override
{
return
DataLayout
::
SPARSE_COO
;
}
DataLayout
layout
()
const
noexcept
override
{
return
meta_
.
layout
;
}
/// \brief Returns the data place of the tensor.
/// \return The data place of the tensor.
...
...
@@ -140,6 +140,17 @@ class SparseCooTensor : public TensorBase,
const
DDim
&
dims
,
const
bool
coalesced
=
false
);
/// \brief set the member of sparse coo tensor.
/// \param non_zero_indices The indices of non zero elements in original dense
/// tensor.
/// \param non_zero_elements The non zero elements of original dense tensor.
/// \param meta The meta of original dense tensor.
/// \param coalesced whether the indices has coalesced.
void
SetMember
(
const
DenseTensor
&
non_zero_indices
,
const
DenseTensor
&
non_zero_elements
,
const
SparseTensorMeta
&
meta
,
const
bool
coalesced
=
false
);
/// \brief Get a mutable pointer of non_zero_indices_.
/// return a mutable pointer of non_zero_indices_.
DenseTensor
*
mutable_indices
()
{
return
&
non_zero_indices_
;
}
...
...
@@ -161,15 +172,22 @@ class SparseCooTensor : public TensorBase,
DataType
dtype
,
size_t
requested_size
=
0
)
override
;
/// \brief set the dims of original dense tensor
void
set_dims
(
const
DDim
&
dims
)
{
this
->
dims_
=
dims
;
}
/// \brief get the sparse dim
int32_t
sparse_dim
()
const
;
/// \brief get the dnese dim
int32_t
dense_dim
()
const
;
/// \brief Returns the meta information of the tensor.
/// \return The meta information of the tensor.
const
SparseTensorMeta
&
meta
()
const
noexcept
{
return
meta_
;
}
void
set_meta
(
SparseTensorMeta
&&
meta
);
void
set_meta
(
const
SparseTensorMeta
&
meta
);
void
set_dims
(
const
DDim
&
dims
)
{
meta_
.
dims
=
dims
;
}
/// \brief query table according to key
const
std
::
pair
<
DenseTensor
,
DenseTensor
>*
IndicesPairs
(
const
std
::
string
&
key
)
const
{
...
...
@@ -213,6 +231,10 @@ class SparseCooTensor : public TensorBase,
}
private:
friend
class
DenseTensorUtils
;
SparseTensorMeta
meta_
;
// save the indices of non zero elements in original dense tensor
DenseTensor
non_zero_indices_
;
// save the non zero elements of original dense tensor
...
...
paddle/phi/core/sparse_csr_tensor.cc
浏览文件 @
4b95f85e
...
...
@@ -21,7 +21,6 @@ SparseCsrTensor::SparseCsrTensor() {
this
->
non_zero_crows_
=
crows
;
this
->
non_zero_cols_
=
cols
;
this
->
non_zero_elements_
=
values
;
this
->
dims_
=
phi
::
make_ddim
({
1
,
1
});
}
inline
void
check_shape
(
const
DDim
&
dims
)
{
...
...
@@ -54,27 +53,30 @@ SparseCsrTensor::SparseCsrTensor(const DenseTensor& non_zero_crows,
const
DDim
&
dims
)
:
non_zero_crows_
(
non_zero_crows
),
non_zero_cols_
(
non_zero_cols
),
non_zero_elements_
(
non_zero_elements
),
dims_
(
dims
)
{
non_zero_elements_
(
non_zero_elements
)
{
if
(
non_zero_crows
.
initialized
())
{
Check
(
non_zero_crows_
,
non_zero_cols_
,
non_zero_elements_
,
dims
_
);
Check
(
non_zero_crows_
,
non_zero_cols_
,
non_zero_elements_
,
dims
);
}
else
{
// create a empty tensor
check_shape
(
dims
);
}
meta_
.
dims
=
dims
;
meta_
.
layout
=
DataLayout
::
NCHW
;
meta_
.
dtype
=
non_zero_elements
.
dtype
();
}
SparseCsrTensor
::
SparseCsrTensor
(
const
SparseCsrTensor
&
other
)
:
non_zero_crows_
(
other
.
non_zero_crows_
),
non_zero_cols_
(
other
.
non_zero_cols_
),
non_zero_elements_
(
other
.
non_zero_elements_
),
dims_
(
other
.
dims_
)
{}
non_zero_elements_
(
other
.
non_zero_elements_
)
{
set_meta
(
other
.
meta
());
}
SparseCsrTensor
&
SparseCsrTensor
::
operator
=
(
const
SparseCsrTensor
&
other
)
{
this
->
dims_
=
other
.
dim
s
();
this
->
non_zero_c
rows_
=
other
.
crow
s
();
this
->
non_zero_
cols_
=
other
.
col
s
();
this
->
non_zero_elements_
=
other
.
values
(
);
this
->
non_zero_crows_
=
other
.
non_zero_crow
s
();
this
->
non_zero_c
ols_
=
other
.
non_zero_col
s
();
this
->
non_zero_
elements_
=
other
.
non_zero_element
s
();
set_meta
(
other
.
meta
()
);
return
*
this
;
}
...
...
@@ -114,7 +116,35 @@ void SparseCsrTensor::SetMember(const DenseTensor& non_zero_crows,
this
->
non_zero_crows_
=
non_zero_crows
;
this
->
non_zero_cols_
=
non_zero_cols
;
this
->
non_zero_elements_
=
non_zero_elements
;
this
->
dims_
=
dims
;
meta_
.
dims
=
dims
;
}
void
SparseCsrTensor
::
SetMember
(
const
DenseTensor
&
non_zero_crows
,
const
DenseTensor
&
non_zero_cols
,
const
DenseTensor
&
non_zero_elements
,
const
SparseTensorMeta
&
meta
)
{
Check
(
non_zero_crows
,
non_zero_cols
,
non_zero_elements
,
meta
.
dims
);
this
->
non_zero_crows_
=
non_zero_crows
;
this
->
non_zero_cols_
=
non_zero_cols
;
this
->
non_zero_elements_
=
non_zero_elements
;
set_meta
(
meta
);
}
void
SparseCsrTensor
::
set_meta
(
SparseTensorMeta
&&
meta
)
{
PADDLE_ENFORCE
(
!
meta_
.
valid
(),
phi
::
errors
::
InvalidArgument
(
"Only when the original attribute of Tensor is "
"incomplete, can it be reset."
));
meta_
=
std
::
move
(
meta
);
}
void
SparseCsrTensor
::
set_meta
(
const
SparseTensorMeta
&
meta
)
{
PADDLE_ENFORCE
(
meta
.
valid
(),
phi
::
errors
::
InvalidArgument
(
"Input meta is invalid, please check the meta attribute."
));
meta_
.
dims
=
meta
.
dims
;
meta_
.
dtype
=
meta
.
dtype
;
meta_
.
layout
=
meta
.
layout
;
}
}
// namespace phi
paddle/phi/core/sparse_csr_tensor.h
浏览文件 @
4b95f85e
...
...
@@ -14,14 +14,13 @@ limitations under the License. */
#pragma once
#include "paddle/phi/core/allocator.h"
#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/core/tensor_base.h"
#include "paddle/phi/core/tensor_meta.h"
namespace
phi
{
class
Compatible
DenseTensorUtils
;
class
DenseTensorUtils
;
/// \brief The SparseCsrTensor uses three 1-D DenseTensors to represent
/// the row index , column index and non zero elements of the original
...
...
@@ -100,21 +99,19 @@ class SparseCsrTensor : public TensorBase,
/// \brief Return the number of elements contained in original dense tensor
/// \return The number of elements contained in original dense tensor
int64_t
numel
()
const
override
{
return
product
(
dims_
);
}
int64_t
numel
()
const
override
{
return
product
(
meta_
.
dims
);
}
/// \brief Returns the dims of the original dense tensor.
/// \return The dims of the original dense tensor.
const
DDim
&
dims
()
const
noexcept
override
{
return
dims_
;
}
const
DDim
&
dims
()
const
noexcept
override
{
return
meta_
.
dims
;
}
/// \brief Returns the data type of the tensor.
/// \return The data type of the tensor.
DataType
dtype
()
const
noexcept
override
{
return
non_zero_elements_
.
dtype
();
}
DataType
dtype
()
const
noexcept
override
{
return
meta_
.
dtype
;
}
/// \brief Returns the data layout of the tensor.
/// \return The data layout of the tensor.
DataLayout
layout
()
const
noexcept
override
{
return
DataLayout
::
SPARSE_CSR
;
}
DataLayout
layout
()
const
noexcept
override
{
return
meta_
.
layout
;
}
/// \brief Returns the data place of the tensor.
/// \return The data place of the tensor.
...
...
@@ -145,6 +142,18 @@ class SparseCsrTensor : public TensorBase,
const
DenseTensor
&
non_zero_elements
,
const
DDim
&
dims
);
/// \brief set the member of sparse csr tensor.
/// \param non_zero_crows The compresessed row index of non zero elements in
/// original dense tensor.
/// \param non_zero_cols The column index of non zero elements in original
/// dense tensor.
/// \param non_zero_elements The non zero elements of original dense tensor.
/// \param meta The meta of original dense tensor.
void
SetMember
(
const
DenseTensor
&
non_zero_crows
,
const
DenseTensor
&
non_zero_cols
,
const
DenseTensor
&
non_zero_elements
,
const
SparseTensorMeta
&
meta
);
/// \brief Get a mutable pointer of non_zero_crows.
/// return a mutable pointer of non_zero_crows.
DenseTensor
*
mutable_crows
()
{
return
&
non_zero_crows_
;
}
...
...
@@ -169,18 +178,28 @@ class SparseCsrTensor : public TensorBase,
/// mutable_values()
DenseTensor
*
mutable_non_zero_elements
()
{
return
&
non_zero_elements_
;
}
/// \brief Returns the meta information of the tensor.
/// \return The meta information of the tensor.
const
SparseTensorMeta
&
meta
()
const
noexcept
{
return
meta_
;
}
void
set_meta
(
SparseTensorMeta
&&
meta
);
void
set_meta
(
const
SparseTensorMeta
&
meta
);
/// \brief set the dims of original dense tensor
void
set_dims
(
const
DDim
&
dims
)
{
this
->
dims_
=
dims
;
}
void
set_dims
(
const
DDim
&
dims
)
{
meta_
.
dims
=
dims
;
}
protected:
SparseTensorMeta
meta_
;
private:
friend
class
DenseTensorUtils
;
// save the compressed rows information of non zero elements
DenseTensor
non_zero_crows_
;
// save the columns information of non zero elements
DenseTensor
non_zero_cols_
;
// save the non zero elements
DenseTensor
non_zero_elements_
;
// save the number of non zero elements in each batch
DDim
dims_
;
/* --------------------------- */
/* example: 2-D Tensor */
/* --------------------------- */
...
...
paddle/phi/core/tensor_meta.cc
浏览文件 @
4b95f85e
...
...
@@ -48,4 +48,16 @@ bool StringTensorMeta::valid() const noexcept {
return
valid
;
}
SparseTensorMeta
::
SparseTensorMeta
(
const
DDim
&
dims
)
:
dims
(
dims
)
{}
SparseTensorMeta
::
SparseTensorMeta
(
const
DDim
&
dims
,
const
DataLayout
&
layout
)
:
dims
(
dims
),
layout
(
layout
)
{}
bool
SparseTensorMeta
::
valid
()
const
noexcept
{
bool
valid
{
true
};
valid
=
valid
&&
(
layout
!=
DataLayout
::
UNDEFINED
);
valid
=
valid
&&
(
product
(
dims
)
>=
0
);
return
valid
;
}
}
// namespace phi
paddle/phi/core/tensor_meta.h
浏览文件 @
4b95f85e
...
...
@@ -99,4 +99,24 @@ inline bool operator==(const StringTensorMeta& lhs,
(
lhs
.
offset
==
rhs
.
offset
);
}
struct
SparseTensorMeta
{
using
DataLayout
=
paddle
::
experimental
::
DataLayout
;
SparseTensorMeta
()
=
default
;
explicit
SparseTensorMeta
(
const
DDim
&
dims
);
explicit
SparseTensorMeta
(
const
DDim
&
dims
,
const
DataLayout
&
layout
);
/// \brief Test whether the metadata is valid. Does not throw exceptions.
/// \return Whether the metadata is valid.
bool
valid
()
const
noexcept
;
DDim
dims
;
DataType
dtype
;
DataLayout
layout
{
DataLayout
::
NCHW
};
};
inline
bool
operator
==
(
const
SparseTensorMeta
&
lhs
,
const
SparseTensorMeta
&
rhs
)
{
return
(
lhs
.
dims
==
rhs
.
dims
)
&&
(
lhs
.
layout
==
rhs
.
layout
);
}
}
// namespace phi
paddle/phi/core/tensor_utils.cc
浏览文件 @
4b95f85e
...
...
@@ -296,7 +296,7 @@ void Copy(const Context& dev_ctx,
dst_place
,
blocking
,
dst
->
mutable_non_zero_elements
());
dst
->
set_
dims
(
src
.
dims
());
dst
->
set_
meta
(
src
.
meta
());
dst
->
SetCoalesced
(
src
.
coalesced
());
}
...
...
paddle/phi/core/tensor_utils.h
浏览文件 @
4b95f85e
...
...
@@ -28,6 +28,14 @@ class DenseTensorUtils {
return
&
(
tensor
->
meta_
);
}
static
SparseTensorMeta
*
GetMutableMeta
(
SparseCooTensor
*
tensor
)
{
return
&
(
tensor
->
meta_
);
}
static
SparseTensorMeta
*
GetMutableMeta
(
SparseCsrTensor
*
tensor
)
{
return
&
(
tensor
->
meta_
);
}
static
const
std
::
shared_ptr
<
phi
::
Allocation
>&
GetHolder
(
const
DenseTensor
&
tensor
)
{
return
tensor
.
holder_
;
...
...
paddle/phi/infermeta/CMakeLists.txt
浏览文件 @
4b95f85e
...
...
@@ -7,3 +7,4 @@ cc_library(
SRCS backward.cc
DEPS meta_tensor convert_utils
)
add_subdirectory
(
strings
)
add_subdirectory
(
sparse
)
paddle/phi/infermeta/sparse/CMakeLists.txt
0 → 100644
浏览文件 @
4b95f85e
cc_library
(
sparse_infermeta
SRCS unary.cc binary.cc multiary.cc
DEPS convert_utils infermeta_utils
)
cc_library
(
sparse_backward_infermeta
SRCS backward.cc
DEPS meta_tensor convert_utils
)
paddle/phi/infermeta/sparse/backward.cc
0 → 100644
浏览文件 @
4b95f85e
/* 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/phi/infermeta/sparse/backward.h"
#include "paddle/phi/infermeta/unary.h"
#include "paddle/phi/core/infermeta_utils.h"
namespace
phi
{
namespace
sparse
{
void
FusedAttentionGradInferMeta
(
const
MetaTensor
&
query
,
const
MetaTensor
&
key
,
const
MetaTensor
&
value
,
const
MetaTensor
&
softmax
,
const
MetaTensor
&
out_grad
,
MetaTensor
*
query_grad
,
MetaTensor
*
key_grad
,
MetaTensor
*
value_grad
)
{
// TODO(zhouwei, zhangkaihuo) add correct infer meta
}
}
// namespace sparse
}
// namespace phi
paddle/phi/infermeta/sparse/backward.h
0 → 100644
浏览文件 @
4b95f85e
/* 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/meta_tensor.h"
#include "paddle/phi/core/tensor_meta.h"
namespace
phi
{
namespace
sparse
{
void
FusedAttentionGradInferMeta
(
const
MetaTensor
&
query
,
const
MetaTensor
&
key
,
const
MetaTensor
&
value
,
const
MetaTensor
&
softmax
,
const
MetaTensor
&
out_grad
,
MetaTensor
*
query_grad
,
MetaTensor
*
key_grad
,
MetaTensor
*
value_grad
);
}
// namespace sparse
}
// namespace phi
paddle/phi/infermeta/sparse/binary.cc
0 → 100644
浏览文件 @
4b95f85e
/* 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/phi/infermeta/sparse/binary.h"
namespace
phi
{
namespace
sparse
{
inline
void
GetOutShape
(
const
DDim
&
x_dims
,
const
std
::
vector
<
int
>&
kernel_sizes
,
const
std
::
vector
<
int
>&
paddings
,
const
std
::
vector
<
int
>&
dilations
,
const
std
::
vector
<
int
>&
strides
,
DDim
*
out_dims
)
{
PADDLE_ENFORCE_EQ
(
x_dims
.
size
(),
5
,
phi
::
errors
::
InvalidArgument
(
"the shape of x should be (N, D, H, W, C)"
));
PADDLE_ENFORCE_EQ
(
kernel_sizes
.
size
(),
5
,
phi
::
errors
::
InvalidArgument
(
"the shape of kernel should be (D, H, W, C, OC)"
));
// infer out shape
(
*
out_dims
)[
0
]
=
x_dims
[
0
];
(
*
out_dims
)[
4
]
=
kernel_sizes
[
4
];
for
(
int
i
=
1
;
i
<
4
;
i
++
)
{
(
*
out_dims
)[
i
]
=
(
x_dims
[
i
]
+
2
*
paddings
[
i
-
1
]
-
dilations
[
i
-
1
]
*
(
kernel_sizes
[
i
-
1
]
-
1
)
-
1
)
/
strides
[
i
-
1
]
+
1
;
}
}
inline
void
ResetSubmKernelSizeAndStrides
(
const
DDim
&
kernel_dims
,
std
::
vector
<
int
>*
paddings
,
std
::
vector
<
int
>*
strides
)
{
for
(
uint64_t
i
=
0
;
i
<
paddings
->
size
();
i
++
)
{
(
*
paddings
)[
i
]
=
kernel_dims
[
i
]
/
2
;
(
*
strides
)[
i
]
=
1
;
}
}
void
Conv3dInferMeta
(
const
MetaTensor
&
x
,
const
MetaTensor
&
kernel
,
const
std
::
vector
<
int
>&
paddings
,
const
std
::
vector
<
int
>&
dilations
,
const
std
::
vector
<
int
>&
strides
,
const
int
groups
,
const
bool
subm
,
const
std
::
string
&
key
,
MetaTensor
*
out
,
MetaTensor
*
rulebook
,
MetaTensor
*
counter
)
{
const
auto
&
x_dims
=
x
.
dims
();
const
auto
&
kernel_dims
=
kernel
.
dims
();
DDim
out_dims
=
{
1
,
1
,
1
,
1
,
1
};
std
::
vector
<
int
>
kernel_sizes
(
kernel_dims
.
size
());
for
(
int
i
=
0
;
i
<
kernel_dims
.
size
();
i
++
)
{
kernel_sizes
[
i
]
=
kernel_dims
[
i
];
}
std
::
vector
<
int
>
subm_paddings
(
paddings
),
subm_strides
(
strides
);
if
(
subm
)
{
// the out shape of subm_conv is same as input shape
// reset the padding=kernel_size/2 and strides=1
ResetSubmKernelSizeAndStrides
(
kernel
.
dims
(),
&
subm_paddings
,
&
subm_strides
);
}
GetOutShape
(
x_dims
,
kernel_sizes
,
subm_paddings
,
dilations
,
subm_strides
,
&
out_dims
);
out
->
set_dtype
(
x
.
dtype
());
out
->
set_dims
(
out_dims
);
out
->
set_layout
(
x
.
layout
());
rulebook
->
set_dtype
(
DataType
::
INT32
);
rulebook
->
set_layout
(
DataLayout
::
NCHW
);
rulebook
->
set_dims
({
1
});
counter
->
set_dtype
(
DataType
::
INT32
);
counter
->
set_layout
(
DataLayout
::
NCHW
);
counter
->
set_dims
({
1
});
}
inline
const
std
::
vector
<
int
>
PoolResetKernel
(
const
std
::
vector
<
int
>&
kernel_sizes
,
const
int
in_channels
,
const
int
out_channels
)
{
std
::
vector
<
int
>
res
(
kernel_sizes
);
res
.
resize
(
5
);
res
[
3
]
=
in_channels
;
res
[
4
]
=
out_channels
;
return
res
;
}
void
Pool3dInferMeta
(
const
MetaTensor
&
x
,
const
std
::
vector
<
int
>&
kernel_sizes
,
const
std
::
vector
<
int
>&
paddings
,
const
std
::
vector
<
int
>&
dilations
,
const
std
::
vector
<
int
>&
strides
,
MetaTensor
*
out
,
MetaTensor
*
rulebook
,
MetaTensor
*
counter
)
{
const
auto
&
x_dims
=
x
.
dims
();
DDim
out_dims
=
{
1
,
1
,
1
,
1
,
1
};
const
std
::
vector
<
int
>&
real_kernel_sizes
=
PoolResetKernel
(
kernel_sizes
,
x_dims
[
4
],
x_dims
[
4
]);
GetOutShape
(
x_dims
,
real_kernel_sizes
,
paddings
,
dilations
,
strides
,
&
out_dims
);
out
->
set_dtype
(
x
.
dtype
());
out
->
set_dims
(
out_dims
);
out
->
set_layout
(
x
.
layout
());
rulebook
->
set_dtype
(
DataType
::
INT32
);
rulebook
->
set_layout
(
DataLayout
::
NCHW
);
rulebook
->
set_dims
({
1
});
counter
->
set_dtype
(
DataType
::
INT32
);
counter
->
set_layout
(
DataLayout
::
NCHW
);
counter
->
set_dims
({
1
});
}
void
SparseCooTensorInferMeta
(
const
MetaTensor
&
values
,
const
MetaTensor
&
indices
,
const
IntArray
&
dense_shape
,
MetaTensor
*
out
)
{
out
->
set_dims
(
phi
::
make_ddim
(
dense_shape
.
GetData
()));
out
->
set_dtype
(
values
.
dtype
());
out
->
set_layout
(
values
.
layout
());
}
}
// namespace sparse
}
// namespace phi
paddle/phi/infermeta/sparse/binary.h
0 → 100644
浏览文件 @
4b95f85e
/* 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/common/int_array.h"
#include "paddle/phi/core/infermeta_utils.h"
#include "paddle/phi/core/meta_tensor.h"
#include "paddle/phi/core/tensor_meta.h"
namespace
phi
{
namespace
sparse
{
void
Conv3dInferMeta
(
const
MetaTensor
&
x
,
const
MetaTensor
&
kernel
,
const
std
::
vector
<
int
>&
paddings
,
const
std
::
vector
<
int
>&
dilations
,
const
std
::
vector
<
int
>&
strides
,
const
int
groups
,
const
bool
subm
,
const
std
::
string
&
key
,
MetaTensor
*
out
,
MetaTensor
*
rulebook
,
MetaTensor
*
counter
);
void
Pool3dInferMeta
(
const
MetaTensor
&
x
,
const
std
::
vector
<
int
>&
kernel_sizes
,
const
std
::
vector
<
int
>&
paddings
,
const
std
::
vector
<
int
>&
dilations
,
const
std
::
vector
<
int
>&
strides
,
MetaTensor
*
out
,
MetaTensor
*
rulebook
,
MetaTensor
*
counter
);
void
SparseCooTensorInferMeta
(
const
MetaTensor
&
values
,
const
MetaTensor
&
indices
,
const
IntArray
&
dense_shape
,
MetaTensor
*
out
);
}
// namespace sparse
}
// namespace phi
paddle/phi/infermeta/sparse/multiary.cc
0 → 100644
浏览文件 @
4b95f85e
/* 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/phi/infermeta/sparse/multiary.h"
namespace
phi
{
namespace
sparse
{
void
FusedAttentionInferMeta
(
const
MetaTensor
&
query
,
const
MetaTensor
&
key
,
const
MetaTensor
&
value
,
const
MetaTensor
&
sparse_mask
,
const
MetaTensor
&
key_padding_mask
,
const
MetaTensor
&
attn_mask
,
MetaTensor
*
out
,
MetaTensor
*
softmax
)
{
// TODO(zhouwei,zhangkaihuo) add correct infer meta
}
}
// namespace sparse
}
// namespace phi
paddle/phi/infermeta/sparse/multiary.h
0 → 100644
浏览文件 @
4b95f85e
/* 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/meta_tensor.h"
namespace
phi
{
namespace
sparse
{
void
FusedAttentionInferMeta
(
const
MetaTensor
&
query
,
const
MetaTensor
&
key
,
const
MetaTensor
&
value
,
const
MetaTensor
&
sparse_mask
,
const
MetaTensor
&
key_padding_mask
,
const
MetaTensor
&
attn_mask
,
MetaTensor
*
out
,
MetaTensor
*
softmax
);
}
// namespace sparse
}
// namespace phi
paddle/phi/infermeta/sparse/unary.cc
0 → 100644
浏览文件 @
4b95f85e
/* 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/phi/infermeta/sparse/unary.h"
#include "paddle/phi/core/infermeta_utils.h"
namespace
phi
{
namespace
sparse
{
void
IndicesInferMeta
(
const
MetaTensor
&
x
,
MetaTensor
*
out
)
{
out
->
set_dims
({
-
1
});
out
->
set_dtype
(
DataType
::
INT32
);
out
->
set_layout
(
DataLayout
::
NCHW
);
}
void
ValuesInferMeta
(
const
MetaTensor
&
x
,
MetaTensor
*
out
)
{
const
auto
&
x_dims
=
x
.
dims
();
out
->
set_dims
({
-
1
,
x_dims
[
x_dims
.
size
()
-
1
]});
out
->
set_dtype
(
x
.
dtype
());
out
->
set_layout
(
x
.
layout
());
}
}
// namespace sparse
}
// namespace phi
paddle/phi/infermeta/sparse/unary.h
0 → 100644
浏览文件 @
4b95f85e
/* 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/meta_tensor.h"
#include "paddle/phi/core/tensor_meta.h"
namespace
phi
{
namespace
sparse
{
void
IndicesInferMeta
(
const
MetaTensor
&
x
,
MetaTensor
*
out
);
void
ValuesInferMeta
(
const
MetaTensor
&
x
,
MetaTensor
*
out
);
}
// namespace sparse
}
// namespace phi
paddle/phi/kernels/CMakeLists.txt
浏览文件 @
4b95f85e
...
...
@@ -45,7 +45,8 @@ set(COMMON_KERNEL_DEPS
selected_rows_functor
)
# remove this dep after removing fluid deps on tensor creation
set
(
COMMON_KERNEL_DEPS
${
COMMON_KERNEL_DEPS
}
phi_api_utils
)
set
(
COMMON_KERNEL_DEPS
${
COMMON_KERNEL_DEPS
}
infermeta infermeta_utils
)
set
(
COMMON_KERNEL_DEPS
${
COMMON_KERNEL_DEPS
}
infermeta infermeta_utils
sparse_infermeta
)
set
(
COMMON_KERNEL_DEPS
${
COMMON_KERNEL_DEPS
}
switch_autotune
)
set
(
COMMON_KERNEL_DEPS
...
...
paddle/phi/kernels/sparse/cpu/elementwise_grad_kernel.cc
浏览文件 @
4b95f85e
...
...
@@ -12,6 +12,9 @@ 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/phi/kernels/sparse/elementwise_grad_kernel.h"
#include "paddle/phi/kernels/sparse/elementwise_kernel.h"
#include "glog/logging.h"
#include "paddle/phi/backends/cpu/cpu_context.h"
...
...
@@ -24,7 +27,7 @@ limitations under the License. */
#include "paddle/phi/kernels/elementwise_kernel.h"
#include "paddle/phi/kernels/empty_kernel.h"
#include "paddle/phi/kernels/funcs/eigen/common.h"
#include "paddle/phi/kernels/sparse/e
lementwise
_kernel.h"
#include "paddle/phi/kernels/sparse/e
mpty
_kernel.h"
namespace
phi
{
namespace
sparse
{
...
...
@@ -45,7 +48,7 @@ void AllocCooPtr(const Context& dev_ctx,
SparseCooTensor
*
dx
)
{
DenseTensor
dx_indices
=
phi
::
EmptyLike
<
IntT
>
(
dev_ctx
,
x
.
indices
());
DenseTensor
dx_values
=
phi
::
EmptyLike
<
T
>
(
dev_ctx
,
x
.
values
());
dx
->
SetMember
(
dx_indices
,
dx_values
,
x
.
dims
(),
true
);
dx
->
SetMember
(
dx_indices
,
dx_values
,
x
.
dims
(),
x
.
coalesced
()
);
}
template
<
typename
T
,
typename
IntT
,
typename
Context
>
...
...
paddle/phi/kernels/sparse/cpu/elementwise_kernel.cc
浏览文件 @
4b95f85e
...
...
@@ -13,14 +13,15 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/phi/kernels/sparse/elementwise_kernel.h"
#include "paddle/phi/core/enforce.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/core/tensor_meta.h"
#include "paddle/phi/core/visit_type.h"
#include "paddle/phi/kernels/elementwise_add_kernel.h"
#include "paddle/phi/kernels/elementwise_kernel.h"
#include "paddle/phi/kernels/funcs/elementwise_functor.h"
#include "paddle/phi/kernels/funcs/sparse/flatten_indices.h"
#include "paddle/phi/kernels/sparse/empty_kernel.h"
#include "paddle/phi/kernels/sparse/sparse_utils_kernel.h"
namespace
phi
{
...
...
@@ -246,9 +247,7 @@ void ElementWiseCooKernelImpl(const Context& dev_ctx,
vectorize
(
slice_ddim
(
x
.
values
().
dims
(),
1
,
x
.
values
().
dims
().
size
()));
indeces_dim
.
insert
(
indeces_dim
.
begin
(),
nnz
);
DenseTensorMeta
values_meta
(
paddle
::
experimental
::
CppTypeToDataType
<
T
>::
Type
(),
phi
::
make_ddim
(
indeces_dim
),
DataLayout
::
NCHW
);
x
.
dtype
(),
phi
::
make_ddim
(
indeces_dim
),
DataLayout
::
NCHW
);
phi
::
DenseTensor
out_indices
=
phi
::
Empty
(
dev_ctx
,
std
::
move
(
indices_meta
));
phi
::
DenseTensor
out_values
=
phi
::
Empty
(
dev_ctx
,
std
::
move
(
values_meta
));
...
...
@@ -263,22 +262,16 @@ void ElementWiseCooKernelImpl(const Context& dev_ctx,
}
}
#define DEFINE_CSR_ELEMENTWISE_CPU_KERNEL(name) \
template <typename T, typename IntT, typename Context> \
void ElementWise##name##CsrCPUKernel(const Context& dev_ctx, \
const SparseCsrTensor& x, \
const SparseCsrTensor& y, \
SparseCsrTensor* out) { \
funcs::name##Functor<T> functor; \
auto coo_x = CsrToCoo<T>(dev_ctx, x); \
auto coo_y = CsrToCoo<T>(dev_ctx, y); \
DenseTensor indeces; \
DenseTensor values; \
SparseCooTensor coo_out; \
coo_out.SetMember(indeces, values, x.dims()); \
ElementWiseCooKernelImpl<T, IntT, Context, funcs::name##Functor<T>>( \
dev_ctx, coo_x, coo_y, &coo_out, functor); \
*out = CooToCsr<T>(dev_ctx, coo_out); \
#define DEFINE_CSR_ELEMENTWISE_CPU_KERNEL(name) \
template <typename T, typename IntT, typename Context> \
void ElementWise##name##CsrCPUKernel(const Context& dev_ctx, \
const SparseCsrTensor& x, \
const SparseCsrTensor& y, \
SparseCsrTensor* out) { \
auto coo_x = CsrToCoo<T>(dev_ctx, x); \
auto coo_y = CsrToCoo<T>(dev_ctx, y); \
auto coo_out = ElementWise##name##Coo<T, Context>(dev_ctx, coo_x, coo_y); \
CooToCsrKernel<T>(dev_ctx, coo_out, out); \
}
#define DEFINE_CSR_ELEMENTWISE_KERNEL(name) \
...
...
paddle/phi/kernels/sparse/cpu/sparse_utils_kernel.cc
浏览文件 @
4b95f85e
...
...
@@ -103,6 +103,7 @@ void DenseToCooKernel(const Context& dev_ctx,
++
index
;
}
}
out
->
SetMember
(
indices
,
values
,
x_dims
,
true
);
}
...
...
@@ -181,17 +182,12 @@ void CooToCsrCPUKernel(const CPUContext& dev_ctx,
int
batchs
=
x_dims
.
size
()
==
2
?
1
:
x_dims
[
0
];
int
rows
=
x_dims
.
size
()
==
2
?
x_dims
[
0
]
:
x_dims
[
1
];
phi
::
DenseTensor
crows
;
crows
.
Resize
({
batchs
*
(
rows
+
1
)});
IntT
*
csr_crows_data
=
dev_ctx
.
template
Alloc
<
IntT
>(
&
crows
);
phi
::
DenseTensor
cols
;
cols
.
Resize
({
non_zero_num
});
IntT
*
csr_cols_data
=
dev_ctx
.
template
Alloc
<
IntT
>(
&
cols
);
phi
::
DenseTensor
values
;
values
.
Resize
({
non_zero_num
});
T
*
csr_values_data
=
dev_ctx
.
template
Alloc
<
T
>(
&
values
);
phi
::
DenseTensor
crows
=
phi
::
Empty
<
IntT
>
(
dev_ctx
,
{
batchs
*
(
rows
+
1
)});
phi
::
DenseTensor
cols
=
phi
::
Empty
<
IntT
>
(
dev_ctx
,
{
non_zero_num
});
phi
::
DenseTensor
values
=
phi
::
EmptyLike
<
T
,
CPUContext
>
(
dev_ctx
,
x
.
values
());
IntT
*
csr_crows_data
=
crows
.
data
<
IntT
>
();
IntT
*
csr_cols_data
=
cols
.
data
<
IntT
>
();
T
*
csr_values_data
=
values
.
data
<
T
>
();
const
auto
&
coo_indices
=
x
.
indices
();
const
auto
&
coo_values
=
x
.
values
();
...
...
@@ -270,8 +266,7 @@ void CooToDenseCPUKernel(const CPUContext& dev_ctx,
const
int64_t
dense_dim
=
x
.
dense_dim
();
const
T
*
x_data
=
values
.
data
<
T
>
();
*
out
=
phi
::
Empty
(
dev_ctx
,
DenseTensorMeta
(
x
.
dtype
(),
x
.
dims
(),
x
.
values
().
layout
()));
dev_ctx
.
template
Alloc
<
T
>(
out
);
T
*
out_data
=
out
->
data
<
T
>
();
int64_t
base_offset
=
1
;
for
(
int64_t
i
=
0
;
i
<
dense_dim
;
i
++
)
{
...
...
@@ -403,6 +398,21 @@ PD_REGISTER_KERNEL(values_coo,
kernel
->
InputAt
(
0
).
SetDataLayout
(
phi
::
DataLayout
::
SPARSE_COO
);
}
PD_REGISTER_KERNEL
(
indices_coo
,
CPU
,
ALL_LAYOUT
,
phi
::
sparse
::
IndicesCooKernel
,
float
,
double
,
phi
::
dtype
::
float16
,
uint8_t
,
int8_t
,
int16_t
,
int
,
int64_t
)
{
kernel
->
InputAt
(
0
).
SetDataLayout
(
phi
::
DataLayout
::
SPARSE_COO
);
}
PD_REGISTER_KERNEL
(
values_csr
,
CPU
,
ALL_LAYOUT
,
...
...
@@ -415,7 +425,7 @@ PD_REGISTER_KERNEL(values_csr,
int16_t
,
int
,
int64_t
)
{
kernel
->
InputAt
(
0
).
SetDataLayout
(
phi
::
DataLayout
::
SPARSE_C
OO
);
kernel
->
InputAt
(
0
).
SetDataLayout
(
phi
::
DataLayout
::
SPARSE_C
SR
);
}
PD_REGISTER_KERNEL
(
sparse_coo_tensor
,
...
...
paddle/phi/kernels/sparse/elementwise_grad_kernel.h
浏览文件 @
4b95f85e
...
...
@@ -17,6 +17,7 @@ limitations under the License. */
#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/core/sparse_coo_tensor.h"
#include "paddle/phi/core/sparse_csr_tensor.h"
#include "paddle/phi/infermeta/sparse/unary.h"
#include "paddle/phi/kernels/empty_kernel.h"
namespace
phi
{
...
...
@@ -50,6 +51,9 @@ namespace sparse {
const Sparse##type##Tensor& dout) { \
Sparse##type##Tensor dx; \
Sparse##type##Tensor dy; \
MetaTensor meta_dx(&dx), meta_dy(&dy); \
phi::UnchangedInferMeta(x, &meta_dx); \
phi::UnchangedInferMeta(y, &meta_dy); \
ElementWise##name##type##GradKernel<T, Context>( \
dev_ctx, x, y, dout, &dx, &dy); \
return std::vector<Sparse##type##Tensor>{dx, dy}; \
...
...
@@ -90,6 +94,9 @@ std::vector<SparseCsrTensor> ElementWiseDivideCsrGrad(
const
SparseCsrTensor
&
dout
)
{
SparseCsrTensor
dx
;
SparseCsrTensor
dy
;
MetaTensor
meta_dx
(
&
dx
),
meta_dy
(
&
dy
);
phi
::
UnchangedInferMeta
(
x
,
&
meta_dx
);
phi
::
UnchangedInferMeta
(
y
,
&
meta_dy
);
ElementWiseDivideCsrGradKernel
<
T
,
Context
>
(
dev_ctx
,
x
,
y
,
out
,
dout
,
&
dx
,
&
dy
);
return
std
::
vector
<
SparseCsrTensor
>
{
dx
,
dy
};
...
...
@@ -104,6 +111,9 @@ std::vector<SparseCooTensor> ElementWiseDivideCooGrad(
const
SparseCooTensor
&
dout
)
{
SparseCooTensor
dx
;
SparseCooTensor
dy
;
MetaTensor
meta_dx
(
&
dx
),
meta_dy
(
&
dy
);
phi
::
UnchangedInferMeta
(
x
,
&
meta_dx
);
phi
::
UnchangedInferMeta
(
y
,
&
meta_dy
);
ElementWiseDivideCooGradKernel
<
T
,
Context
>
(
dev_ctx
,
x
,
y
,
out
,
dout
,
&
dx
,
&
dy
);
return
std
::
vector
<
SparseCooTensor
>
{
dx
,
dy
};
...
...
paddle/phi/kernels/sparse/elementwise_kernel.h
浏览文件 @
4b95f85e
...
...
@@ -17,6 +17,7 @@ limitations under the License. */
#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/core/sparse_coo_tensor.h"
#include "paddle/phi/core/sparse_csr_tensor.h"
#include "paddle/phi/infermeta/binary.h"
namespace
phi
{
namespace
sparse
{
...
...
@@ -45,8 +46,10 @@ namespace sparse {
const SparseCsrTensor& y) { \
DenseTensor crows; \
DenseTensor cols; \
DenseTensor non_zero_elements; \
SparseCsrTensor out(crows, cols, non_zero_elements, x.dims()); \
DenseTensor values; \
SparseCsrTensor out(crows, cols, values, x.dims()); \
MetaTensor meta_out(out); \
phi::ElementwiseInferMeta(x, y, &meta_out); \
ElementWise##name##CsrKernel<T, Context>(dev_ctx, x, y, &out); \
return out; \
}
...
...
@@ -57,8 +60,10 @@ namespace sparse {
const SparseCooTensor& x, \
const SparseCooTensor& y) { \
DenseTensor indices; \
DenseTensor non_zero_elements; \
SparseCooTensor out(indices, non_zero_elements, x.dims()); \
DenseTensor values; \
SparseCooTensor out(indices, values, x.dims()); \
MetaTensor meta_out(out); \
phi::ElementwiseInferMeta(x, y, &meta_out); \
ElementWise##name##CooKernel<T, Context>(dev_ctx, x, y, &out); \
return out; \
}
...
...
paddle/phi/kernels/sparse/empty_kernel.cc
浏览文件 @
4b95f85e
...
...
@@ -26,11 +26,10 @@ template <typename T, typename Context>
void
EmptyLikeCooKernel
(
const
Context
&
dev_ctx
,
const
SparseCooTensor
&
x
,
SparseCooTensor
*
out
)
{
out
->
set_dims
(
x
.
dims
());
*
(
out
->
mutable_indices
())
=
x
.
indices
();
const
DenseTensor
&
x_values
=
x
.
non_zero_element
s
();
DenseTensor
*
out_values
=
out
->
mutable_
non_zero_element
s
();
const
DenseTensor
&
x_values
=
x
.
value
s
();
DenseTensor
*
out_values
=
out
->
mutable_
value
s
();
out_values
->
Resize
(
x_values
.
dims
());
dev_ctx
.
template
Alloc
<
T
>(
out_values
);
}
...
...
@@ -39,12 +38,11 @@ template <typename T, typename Context>
void
EmptyLikeCsrKernel
(
const
Context
&
dev_ctx
,
const
SparseCsrTensor
&
x
,
SparseCsrTensor
*
out
)
{
out
->
set_dims
(
x
.
dims
());
*
(
out
->
mutable_crows
())
=
x
.
crows
();
*
(
out
->
mutable_cols
())
=
x
.
cols
();
const
DenseTensor
&
x_values
=
x
.
non_zero_element
s
();
DenseTensor
*
out_values
=
out
->
mutable_
non_zero_element
s
();
const
DenseTensor
&
x_values
=
x
.
value
s
();
DenseTensor
*
out_values
=
out
->
mutable_
value
s
();
out_values
->
Resize
(
x_values
.
dims
());
dev_ctx
.
template
Alloc
<
T
>(
out_values
);
}
...
...
paddle/phi/kernels/sparse/gpu/sparse_utils_kernel.cu
浏览文件 @
4b95f85e
...
...
@@ -172,6 +172,7 @@ void DenseToCooKernel(const Context& dev_ctx,
temp_indexs_ptr
,
indices_data
,
sparse_data
);
out
->
SetMember
(
indices
,
values
,
x_dims
,
true
);
}
...
...
@@ -461,8 +462,8 @@ void CooToDenseGPUKernel(const GPUContext& dev_ctx,
const
auto
place
=
dev_ctx
.
GetPlace
();
const
T
*
x_data
=
values
.
data
<
T
>
();
*
out
=
phi
::
Empty
(
dev_ctx
,
phi
::
DenseTensorMeta
(
x
.
dtype
(),
x
.
dims
(),
x
.
values
().
layout
()));
dev_ctx
.
template
Alloc
<
T
>(
out
);
T
*
out_data
=
out
->
data
<
T
>
();
int64_t
base_offset
=
1
;
for
(
int64_t
i
=
0
;
i
<
dense_dim
;
i
++
)
{
...
...
@@ -619,6 +620,21 @@ PD_REGISTER_KERNEL(values_csr,
int16_t
,
int
,
int64_t
)
{
kernel
->
InputAt
(
0
).
SetDataLayout
(
phi
::
DataLayout
::
SPARSE_CSR
);
}
PD_REGISTER_KERNEL
(
indices_coo
,
GPU
,
ALL_LAYOUT
,
phi
::
sparse
::
IndicesCooKernel
,
float
,
double
,
phi
::
dtype
::
float16
,
uint8_t
,
int8_t
,
int16_t
,
int
,
int64_t
)
{
kernel
->
InputAt
(
0
).
SetDataLayout
(
phi
::
DataLayout
::
SPARSE_COO
);
}
...
...
paddle/phi/kernels/sparse/impl/unary_kernel_impl.h
浏览文件 @
4b95f85e
...
...
@@ -129,8 +129,6 @@ void CastCooKernel(const Context& dev_ctx,
DataType
index_dtype
,
DataType
value_dtype
,
SparseCooTensor
*
out
)
{
out
->
set_dims
(
x
.
dims
());
const
DenseTensor
&
x_indices
=
x
.
indices
();
const
DenseTensor
&
x_values
=
x
.
non_zero_elements
();
DenseTensor
*
out_indices
=
out
->
mutable_indices
();
...
...
@@ -165,8 +163,6 @@ void CastCsrKernel(const Context& dev_ctx,
DataType
index_dtype
,
DataType
value_dtype
,
SparseCsrTensor
*
out
)
{
out
->
set_dims
(
x
.
dims
());
const
DenseTensor
&
x_crows
=
x
.
crows
();
const
DenseTensor
&
x_cols
=
x
.
cols
();
const
DenseTensor
&
x_values
=
x
.
non_zero_elements
();
...
...
paddle/phi/kernels/sparse/sparse_utils_kernel.h
浏览文件 @
4b95f85e
...
...
@@ -18,6 +18,7 @@ limitations under the License. */
#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/core/sparse_coo_tensor.h"
#include "paddle/phi/core/sparse_csr_tensor.h"
#include "paddle/phi/infermeta/unary.h"
#include "paddle/phi/kernels/empty_kernel.h"
namespace
phi
{
...
...
@@ -36,6 +37,8 @@ SparseCooTensor DenseToCoo(const Context& dev_ctx,
DenseTensor
indices
;
DenseTensor
values
;
SparseCooTensor
coo
(
indices
,
values
,
x
.
dims
());
MetaTensor
meta_out
(
&
coo
);
phi
::
UnchangedInferMeta
(
x
,
&
meta_out
);
DenseToCooKernel
<
T
,
Context
>
(
dev_ctx
,
x
,
sparse_dim
,
&
coo
);
return
coo
;
}
...
...
@@ -50,6 +53,8 @@ SparseCooTensor CsrToCoo(const Context& dev_ctx, const SparseCsrTensor& x) {
DenseTensor
indices
;
DenseTensor
values
;
SparseCooTensor
coo
(
indices
,
values
,
x
.
dims
());
MetaTensor
meta_out
(
&
coo
);
phi
::
UnchangedInferMeta
(
x
,
&
meta_out
);
CsrToCooKernel
<
T
,
Context
>
(
dev_ctx
,
x
,
&
coo
);
return
coo
;
}
...
...
@@ -65,6 +70,8 @@ SparseCsrTensor CooToCsr(const Context& dev_ctx, const SparseCooTensor& x) {
DenseTensor
cols
;
DenseTensor
non_zero_elements
;
SparseCsrTensor
csr
(
crows
,
cols
,
non_zero_elements
,
x
.
dims
());
MetaTensor
meta_out
(
&
csr
);
phi
::
UnchangedInferMeta
(
x
,
&
meta_out
);
CooToCsrKernel
<
T
,
Context
>
(
dev_ctx
,
x
,
&
csr
);
return
csr
;
}
...
...
@@ -79,10 +86,13 @@ void DenseToCsrKernel(const Context& dev_ctx,
true
,
phi
::
errors
::
InvalidArgument
(
"SparseCsrTensor only support 2-D or 3-D Tensor."
));
const
int64_t
sparse_dim
=
x_dims
.
size
()
==
2
?
2
:
3
;
DenseTensor
indices
;
DenseTensor
values
;
SparseCooTensor
coo
(
indices
,
values
,
x
.
dims
());
MetaTensor
meta_out
(
&
coo
);
phi
::
UnchangedInferMeta
(
x
,
&
meta_out
);
DenseToCooKernel
<
T
,
Context
>
(
dev_ctx
,
x
,
sparse_dim
,
&
coo
);
CooToCsrKernel
<
T
,
Context
>
(
dev_ctx
,
coo
,
out
);
}
...
...
@@ -93,6 +103,8 @@ SparseCsrTensor DenseToCsr(const Context& dev_ctx, const DenseTensor& x) {
DenseTensor
cols
;
DenseTensor
non_zero_elements
;
SparseCsrTensor
csr
(
crows
,
cols
,
non_zero_elements
,
x
.
dims
());
MetaTensor
meta_out
(
&
csr
);
phi
::
UnchangedInferMeta
(
x
,
&
meta_out
);
DenseToCsrKernel
<
T
,
Context
>
(
dev_ctx
,
x
,
&
csr
);
return
csr
;
}
...
...
@@ -117,6 +129,8 @@ void CsrToDenseKernel(const Context& dev_ctx,
DenseTensor
indices
;
DenseTensor
values
;
SparseCooTensor
coo
(
indices
,
values
,
x
.
dims
());
MetaTensor
meta_out
(
&
coo
);
phi
::
UnchangedInferMeta
(
x
,
&
meta_out
);
CsrToCooKernel
<
T
,
Context
>
(
dev_ctx
,
x
,
&
coo
);
CooToDenseKernel
<
T
,
Context
>
(
dev_ctx
,
coo
,
out
);
}
...
...
@@ -143,6 +157,13 @@ void ValuesCsrKernel(const Context& dev_ctx,
*
out
=
x
.
non_zero_elements
();
}
template
<
typename
T
,
typename
Context
>
void
IndicesCooKernel
(
const
Context
&
dev_ctx
,
const
SparseCooTensor
&
x
,
DenseTensor
*
out
)
{
*
out
=
x
.
indices
();
}
template
<
typename
T
,
typename
Context
>
void
SparseCooTensorKernel
(
const
Context
&
dev_ctx
,
const
DenseTensor
&
values
,
...
...
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