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c8fc3379
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体验新版 GitCode,发现更多精彩内容 >>
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c8fc3379
编写于
10月 31, 2022
作者:
zhouweiwei2014
提交者:
GitHub
10月 31, 2022
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
[Zero-Dim] support input 0D Tensor for reduce_sum/reduce_mean (#47219)
上级
81b93ebb
变更
12
隐藏空白更改
内联
并排
Showing
12 changed file
with
160 addition
and
116 deletion
+160
-116
paddle/phi/infermeta/unary.cc
paddle/phi/infermeta/unary.cc
+5
-4
paddle/phi/kernels/funcs/broadcast_function.h
paddle/phi/kernels/funcs/broadcast_function.h
+4
-4
paddle/phi/kernels/funcs/reduce_function.h
paddle/phi/kernels/funcs/reduce_function.h
+8
-0
paddle/phi/kernels/gpu/reduce_mean_grad_kernel.cu
paddle/phi/kernels/gpu/reduce_mean_grad_kernel.cu
+21
-10
paddle/phi/kernels/gpu/reduce_sum_grad_kernel.cu
paddle/phi/kernels/gpu/reduce_sum_grad_kernel.cu
+13
-23
paddle/phi/kernels/reduce_mean_kernel.cc
paddle/phi/kernels/reduce_mean_kernel.cc
+3
-0
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+0
-3
python/paddle/fluid/tests/unittests/test_mean_op.py
python/paddle/fluid/tests/unittests/test_mean_op.py
+15
-0
python/paddle/fluid/tests/unittests/test_reduce_op.py
python/paddle/fluid/tests/unittests/test_reduce_op.py
+15
-0
python/paddle/fluid/tests/unittests/test_zero_dim_shape.py
python/paddle/fluid/tests/unittests/test_zero_dim_shape.py
+51
-0
python/paddle/tensor/math.py
python/paddle/tensor/math.py
+23
-55
python/paddle/tensor/stat.py
python/paddle/tensor/stat.py
+2
-17
未找到文件。
paddle/phi/infermeta/unary.cc
浏览文件 @
c8fc3379
...
...
@@ -2685,7 +2685,7 @@ DDim ReduceInferDim(const MetaTensor& x,
bool
full_dim
=
true
;
std
::
set
<
int64_t
>
dims_set
(
formated_axis
.
begin
(),
formated_axis
.
end
());
for
(
int64_t
i
=
0
;
i
<
x
.
dims
().
size
()
;
++
i
)
{
for
(
int64_t
i
=
0
;
i
<
x
_rank
;
++
i
)
{
if
(
dims_set
.
find
(
i
)
==
dims_set
.
end
())
{
full_dim
=
false
;
break
;
...
...
@@ -2695,7 +2695,7 @@ DDim ReduceInferDim(const MetaTensor& x,
std
::
vector
<
int64_t
>
out_dim_vector
;
if
(
keep_dim
)
{
for
(
int64_t
i
=
0
;
i
<
x
.
dims
().
size
()
;
++
i
)
{
for
(
int64_t
i
=
0
;
i
<
x
_rank
;
++
i
)
{
if
(
reduce_all
||
dims_set
.
find
(
i
)
!=
dims_set
.
end
())
{
out_dim_vector
.
push_back
(
1
);
}
else
{
...
...
@@ -2703,7 +2703,7 @@ DDim ReduceInferDim(const MetaTensor& x,
}
}
}
else
{
for
(
int64_t
i
=
0
;
i
<
x
.
dims
().
size
()
;
++
i
)
{
for
(
int64_t
i
=
0
;
i
<
x
_rank
;
++
i
)
{
if
(
reduce_all
||
dims_set
.
find
(
i
)
!=
dims_set
.
end
())
{
continue
;
}
else
{
...
...
@@ -2711,7 +2711,7 @@ DDim ReduceInferDim(const MetaTensor& x,
}
}
if
(
out_dim_vector
.
size
()
==
0
)
{
if
(
x_rank
>
0
&&
out_dim_vector
.
size
()
==
0
)
{
out_dim_vector
.
push_back
(
1
);
}
}
...
...
@@ -3013,6 +3013,7 @@ void SetValueInferMeta(const MetaTensor& x, MetaTensor* out) {
phi
::
errors
::
InvalidArgument
(
"The rank of input should be less than 7, but received %d."
,
in_dims
.
size
()));
out
->
set_dims
(
in_dims
);
}
void
ShapeInferMeta
(
const
MetaTensor
&
input
,
MetaTensor
*
out
)
{
...
...
paddle/phi/kernels/funcs/broadcast_function.h
浏览文件 @
c8fc3379
...
...
@@ -44,7 +44,7 @@ struct DimensionsTransform {
int64_t
in_idx
=
0
;
if
(
in_dim
.
size
()
<
dim_size
)
{
DimVector
tmp_dim
(
dim_size
,
1
);
do
{
for
(;
in_idx
<
in_dim
.
size
();)
{
if
(
in_dim
[
in_idx
]
==
out_dims
[
axis
]
||
in_dim
[
in_idx
]
==
1
)
{
tmp_dim
[
axis
]
=
in_dim
[
in_idx
];
in_idx
++
;
...
...
@@ -59,11 +59,11 @@ struct DimensionsTransform {
out_dims
[
axis
],
in_dim
[
in_idx
]));
}
}
while
(
in_idx
<
in_dim
.
size
());
}
in_dim
.
resize
(
dim_size
);
std
::
copy
(
tmp_dim
.
begin
(),
tmp_dim
.
end
(),
in_dim
.
begin
());
}
else
{
do
{
for
(;
in_idx
<
dim_size
;)
{
if
(
in_dim
[
in_idx
]
==
out_dims
[
in_idx
]
||
in_dim
[
in_idx
]
==
1
)
{
in_idx
++
;
}
else
{
...
...
@@ -76,7 +76,7 @@ struct DimensionsTransform {
out_dims
[
in_idx
],
in_dim
[
in_idx
]));
}
}
while
(
in_idx
<
dim_size
);
}
}
std
::
reverse
(
in_dim
.
begin
(),
in_dim
.
end
());
}
...
...
paddle/phi/kernels/funcs/reduce_function.h
浏览文件 @
c8fc3379
...
...
@@ -1063,6 +1063,14 @@ void ReduceKernel(const KPDevice& dev_ctx,
dev_ctx
.
Alloc
<
Ty
>
(
y
);
auto
x_dim
=
phi
::
vectorize
<
int
>
(
x
.
dims
());
if
(
x_dim
.
size
()
==
0
)
{
std
::
vector
<
const
DenseTensor
*>
inputs
=
{
&
x
};
std
::
vector
<
DenseTensor
*>
outputs
=
{
y
};
funcs
::
ElementwiseKernel
<
Ty
>
(
dev_ctx
,
inputs
,
&
outputs
,
transform
);
return
;
}
auto
config
=
ReduceConfig
<
Ty
>
(
origin_reduce_dims
,
x_dim
);
config
.
Run
(
dev_ctx
);
int
numel
=
x
.
numel
();
...
...
paddle/phi/kernels/gpu/reduce_mean_grad_kernel.cu
浏览文件 @
c8fc3379
...
...
@@ -16,8 +16,8 @@
#include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/funcs/broadcast_function.h"
#include "paddle/phi/kernels/funcs/reduce_function.h"
#include "paddle/phi/kernels/gpu/reduce_grad.h"
namespace
phi
{
...
...
@@ -29,23 +29,34 @@ void ReduceMeanGradKernel(const Context& dev_ctx,
bool
keep_dim
,
bool
reduce_all
,
DenseTensor
*
x_grad
)
{
// get reduce_dim and reduce_num for reduce_mean_grad
int
dim_size
=
x
.
dims
().
size
();
if
(
dims
.
size
()
==
0
)
{
reduce_all
=
true
;
}
std
::
vector
<
int
>
reduce_dims
=
funcs
::
details
::
GetReduceDim
(
dims
.
GetData
(),
dim_size
,
reduce_all
);
auto
update_dims
=
vectorize
(
x
.
dims
());
int
reduce_num
=
1
;
for
(
auto
i
:
reduce_dims
)
{
reduce_num
*=
(
x
.
dims
())[
i
];
update_dims
[
i
]
=
1
;
}
// make new tensor
DenseTensor
new_out_grad
(
out_grad
.
dtype
());
new_out_grad
.
ShareDataWith
(
out_grad
);
new_out_grad
.
Resize
(
phi
::
make_ddim
(
update_dims
));
// call BroadcastKernel
dev_ctx
.
Alloc
(
x_grad
,
x
.
dtype
());
std
::
vector
<
const
DenseTensor
*>
inputs
=
{
&
new_out_grad
};
std
::
vector
<
DenseTensor
*>
outputs
=
{
x_grad
};
using
MPType
=
typename
kps
::
details
::
MPTypeTrait
<
T
>::
Type
;
ReduceGradKernel
<
T
,
T
,
Context
,
kps
::
DivideFunctor
<
T
,
MPType
>>
(
dev_ctx
,
x
,
out_grad
,
dims
.
GetData
(),
keep_dim
,
reduce_all
,
x_grad
,
kps
::
DivideFunctor
<
T
,
MPType
>
(
reduce_num
));
funcs
::
BroadcastKernel
<
phi
::
ElementwiseType
::
kUnary
,
T
,
T
>
(
dev_ctx
,
inputs
,
&
outputs
,
0
,
kps
::
DivideFunctor
<
T
,
MPType
>
(
reduce_num
));
}
}
// namespace phi
...
...
paddle/phi/kernels/gpu/reduce_sum_grad_kernel.cu
浏览文件 @
c8fc3379
...
...
@@ -29,42 +29,32 @@ void ReduceSumGradKernel(const Context& dev_ctx,
bool
keep_dim
,
bool
reduce_all
,
DenseTensor
*
x_grad
)
{
using
MPType
=
typename
kps
::
details
::
MPTypeTrait
<
T
>::
Type
;
auto
out_dtype
=
x
.
dtype
();
auto
*
in_x
=
&
x
;
auto
*
d_out
=
&
out_grad
;
auto
*
d_x
=
x_grad
;
// get reduce_dim and reduce_num for reduce_mean_grad
int
dim_size
=
in_x
->
dims
().
size
();
// get reduce_dim for reduce_mean_grad
int
dim_size
=
x
.
dims
().
size
();
if
(
dims
.
size
()
==
0
)
{
reduce_all
=
true
;
}
std
::
vector
<
int
>
reduce_dims
=
funcs
::
details
::
GetReduceDim
(
dims
.
GetData
(),
dim_size
,
reduce_all
);
auto
update_dims
=
vectorize
(
d_x
->
dims
());
int
reduce_num
=
1
;
auto
update_dims
=
vectorize
(
x
.
dims
());
for
(
auto
i
:
reduce_dims
)
{
reduce_num
*=
(
in_x
->
dims
())[
i
];
update_dims
[
i
]
=
1
;
}
// make new tensor
DenseTensor
new_
d_out
(
d_out
->
dtype
());
new_
d_out
.
ShareDataWith
(
*
d_out
);
new_
d_out
.
Resize
(
phi
::
make_ddim
(
update_dims
));
DenseTensor
new_
out_grad
(
out_grad
.
dtype
());
new_
out_grad
.
ShareDataWith
(
out_grad
);
new_
out_grad
.
Resize
(
phi
::
make_ddim
(
update_dims
));
dev_ctx
.
Alloc
(
d_x
,
x
.
dtype
());
auto
pt_out_dtype
=
x
.
dtype
();
auto
pt_d_out
=
new_d_out
;
auto
pt_d_x
=
*
d_x
;
std
::
vector
<
const
DenseTensor
*>
inputs
=
{
&
pt_d_out
};
std
::
vector
<
DenseTensor
*>
outputs
=
{
&
pt_d_x
};
// call ReduceGrad
dev_ctx
.
Alloc
(
x_grad
,
x
.
dtype
());
using
MPType
=
typename
kps
::
details
::
MPTypeTrait
<
T
>::
Type
;
phi
::
ReduceGrad
<
T
,
kps
::
IdentityFunctor
<
T
,
MPType
>>
(
dev_ctx
,
&
pt_d_out
,
&
pt_d_x
,
pt_out_dtype
,
&
new_out_grad
,
x_grad
,
x
.
dtype
()
,
kps
::
IdentityFunctor
<
T
,
MPType
>
());
}
...
...
paddle/phi/kernels/reduce_mean_kernel.cc
浏览文件 @
c8fc3379
...
...
@@ -26,6 +26,9 @@ void MeanKernel(const Context& dev_ctx,
bool
keep_dim
,
DenseTensor
*
out
)
{
bool
reduce_all
=
false
;
if
(
dims
.
size
()
==
0
)
{
reduce_all
=
true
;
}
MeanRawKernel
<
T
>
(
dev_ctx
,
x
,
dims
,
keep_dim
,
reduce_all
,
out
);
}
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
c8fc3379
...
...
@@ -5096,9 +5096,6 @@ def reduce_sum(input, dim=None, keep_dim=False, name=None):
fluid.layers.reduce_sum(y, dim=[0, 1]) # [16, 20]
"""
if dim is not None and not isinstance(dim, list):
dim = [dim]
reduce_all, dim = _get_reduce_dim(dim, input)
if in_dygraph_mode():
...
...
python/paddle/fluid/tests/unittests/test_mean_op.py
浏览文件 @
c8fc3379
...
...
@@ -58,6 +58,21 @@ class TestMeanOp(OpTest):
self
.
check_grad
([
'X'
],
'Out'
,
check_eager
=
True
)
class
TestMeanOp_ZeroDim
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"mean"
self
.
python_api
=
paddle
.
mean
self
.
dtype
=
np
.
float64
self
.
inputs
=
{
'X'
:
np
.
random
.
random
([]).
astype
(
self
.
dtype
)}
self
.
outputs
=
{
'Out'
:
np
.
mean
(
self
.
inputs
[
"X"
])}
def
test_check_output
(
self
):
self
.
check_output
(
check_eager
=
True
)
def
test_checkout_grad
(
self
):
self
.
check_grad
([
'X'
],
'Out'
,
check_eager
=
True
)
class
TestMeanOpError
(
unittest
.
TestCase
):
def
test_errors
(
self
):
with
program_guard
(
Program
(),
Program
()):
...
...
python/paddle/fluid/tests/unittests/test_reduce_op.py
浏览文件 @
c8fc3379
...
...
@@ -37,6 +37,21 @@ class TestSumOp(OpTest):
self
.
check_grad
([
'X'
],
'Out'
,
check_eager
=
True
)
class
TestSumOp_ZeroDim
(
OpTest
):
def
setUp
(
self
):
self
.
python_api
=
paddle
.
sum
self
.
op_type
=
"reduce_sum"
self
.
inputs
=
{
'X'
:
np
.
random
.
random
([]).
astype
(
"float64"
)}
self
.
outputs
=
{
'Out'
:
self
.
inputs
[
'X'
].
sum
(
axis
=
None
)}
self
.
attrs
=
{
'dim'
:
[],
'reduce_all'
:
True
}
def
test_check_output
(
self
):
self
.
check_output
(
check_eager
=
True
)
def
test_check_grad
(
self
):
self
.
check_grad
([
'X'
],
'Out'
,
check_eager
=
True
)
class
TestSumOp_fp16
(
OpTest
):
def
setUp
(
self
):
self
.
python_api
=
paddle
.
sum
...
...
python/paddle/fluid/tests/unittests/test_zero_dim_shape.py
浏览文件 @
c8fc3379
...
...
@@ -17,6 +17,7 @@ import paddle.fluid as fluid
import
numpy
as
np
import
unittest
unary_api_list
=
[
paddle
.
nn
.
functional
.
elu
,
paddle
.
nn
.
functional
.
gelu
,
...
...
@@ -159,5 +160,55 @@ class TestUnaryAPI(unittest.TestCase):
paddle
.
disable_static
()
reduce_api_list
=
[
paddle
.
sum
,
paddle
.
mean
,
paddle
.
nansum
,
paddle
.
nanmean
,
]
class
TestReduceAPI
(
unittest
.
TestCase
):
def
test_dygraph
(
self
):
paddle
.
disable_static
()
fluid
.
set_flags
({
"FLAGS_retain_grad_for_all_tensor"
:
True
})
for
api
in
reduce_api_list
:
x
=
paddle
.
rand
([])
x
.
stop_gradient
=
False
out
=
api
(
x
,
None
)
out
.
backward
()
self
.
assertEqual
(
x
.
shape
,
[])
self
.
assertEqual
(
x
.
grad
.
shape
,
[])
self
.
assertEqual
(
out
.
shape
,
[])
self
.
assertEqual
(
out
.
grad
.
shape
,
[])
paddle
.
enable_static
()
def
test_static
(
self
):
paddle
.
enable_static
()
for
api
in
reduce_api_list
:
main_prog
=
fluid
.
Program
()
with
fluid
.
program_guard
(
main_prog
,
fluid
.
Program
()):
x
=
paddle
.
rand
([])
x
.
stop_gradient
=
False
out
=
api
(
x
,
None
)
fluid
.
backward
.
append_backward
(
out
)
# Test compile shape, grad is always [1]
self
.
assertEqual
(
x
.
shape
,
())
self
.
assertEqual
(
out
.
shape
,
())
exe
=
fluid
.
Executor
()
result
=
exe
.
run
(
main_prog
,
fetch_list
=
[
x
,
out
])
# Test runtime shape
self
.
assertEqual
(
result
[
0
].
shape
,
())
self
.
assertEqual
(
result
[
1
].
shape
,
())
paddle
.
disable_static
()
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/tensor/math.py
浏览文件 @
c8fc3379
...
...
@@ -1265,22 +1265,7 @@ def sum(x, axis=None, dtype=None, keepdim=False, name=None):
out8 = paddle.sum(x, axis=0) # [1, 1, 1, 1]
out9 = paddle.sum(x, axis=1) # [4, 0]
"""
if
isinstance
(
axis
,
Variable
):
reduce_all_flag
=
True
if
axis
.
shape
[
0
]
==
len
(
x
.
shape
)
else
False
else
:
if
axis
is
not
None
and
not
isinstance
(
axis
,
(
list
,
tuple
)):
axis
=
[
axis
]
if
not
axis
:
axis
=
[]
if
len
(
axis
)
==
0
:
reduce_all_flag
=
True
else
:
if
len
(
axis
)
==
len
(
x
.
shape
):
reduce_all_flag
=
True
else
:
reduce_all_flag
=
False
reduce_all
,
axis
=
_get_reduce_axis_with_tensor
(
axis
,
x
)
dtype_flag
=
False
if
dtype
is
not
None
:
...
...
@@ -1290,11 +1275,6 @@ def sum(x, axis=None, dtype=None, keepdim=False, name=None):
if
in_dygraph_mode
():
return
_C_ops
.
sum
(
x
,
axis
,
dtype
,
keepdim
)
if
not
isinstance
(
axis
,
Variable
):
axis
=
axis
if
axis
!=
None
and
axis
!=
[]
and
axis
!=
()
else
[
0
]
if
utils
.
_contain_var
(
axis
):
axis
=
utils
.
_convert_to_tensor_list
(
axis
)
if
_in_legacy_dygraph
():
if
dtype_flag
:
return
_legacy_C_ops
.
reduce_sum
(
...
...
@@ -1304,7 +1284,7 @@ def sum(x, axis=None, dtype=None, keepdim=False, name=None):
'keep_dim'
,
keepdim
,
'reduce_all'
,
reduce_all
_flag
,
reduce_all
,
'in_dtype'
,
x
.
dtype
,
'out_dtype'
,
...
...
@@ -1318,10 +1298,10 @@ def sum(x, axis=None, dtype=None, keepdim=False, name=None):
'keep_dim'
,
keepdim
,
'reduce_all'
,
reduce_all
_flag
,
reduce_all
,
)
attrs
=
{
'dim'
:
axis
,
'keep_dim'
:
keepdim
,
'reduce_all'
:
reduce_all
_flag
}
attrs
=
{
'dim'
:
axis
,
'keep_dim'
:
keepdim
,
'reduce_all'
:
reduce_all
}
if
dtype_flag
:
attrs
.
update
({
'in_dtype'
:
x
.
dtype
,
'out_dtype'
:
dtype
})
...
...
@@ -2304,13 +2284,13 @@ def inverse(x, name=None):
return
out
def
_get_reduce_axis
(
axis
):
def
_get_reduce_axis
(
axis
,
x
):
"""
Internal function for max, min, amax and amin.
It computes the attribute reduce_all value based on axis.
"""
if
axis
is
not
None
and
not
isinstance
(
axis
,
list
):
if
isinstance
(
axis
,
tuple
):
if
isinstance
(
axis
,
(
tuple
,
range
)
):
axis
=
list
(
axis
)
elif
isinstance
(
axis
,
int
):
axis
=
[
axis
]
...
...
@@ -2320,37 +2300,25 @@ def _get_reduce_axis(axis):
type
(
axis
)
)
)
reduce_all
=
True
if
axis
==
None
or
axis
==
[]
else
False
if
axis
==
None
:
if
axis
is
None
:
axis
=
[]
if
axis
==
[]
or
len
(
axis
)
==
len
(
x
.
shape
):
reduce_all
=
True
else
:
reduce_all
=
False
return
reduce_all
,
axis
def
_get_reduce_axis_with_tensor
(
axis
):
def
_get_reduce_axis_with_tensor
(
axis
,
x
):
if
isinstance
(
axis
,
Variable
):
return
False
,
axis
return
_get_reduce_axis
(
axis
)
def
_get_reduce_all_value
(
axis
):
"""
Internal function for max, min, amax and amin.
It computes the attribute reduce_all value based on axis.
"""
if
axis
is
not
None
and
not
isinstance
(
axis
,
list
):
if
isinstance
(
axis
,
tuple
):
axis
=
list
(
axis
)
elif
isinstance
(
axis
,
int
):
axis
=
[
axis
]
if
axis
.
shape
[
0
]
==
len
(
x
.
shape
):
reduce_all
=
True
else
:
raise
TypeError
(
"The type of axis must be int, list or tuple, but received {}"
.
format
(
type
(
axis
)
)
)
reduce_all
=
True
if
axis
==
None
or
axis
==
[]
else
False
axis
=
axis
if
axis
!=
None
and
axis
!=
[]
else
[
0
]
reduce_all
=
False
else
:
reduce_all
,
axis
=
_get_reduce_axis
(
axis
,
x
)
if
utils
.
_contain_var
(
axis
):
axis
=
utils
.
_convert_to_tensor_list
(
axis
)
return
reduce_all
,
axis
...
...
@@ -2432,7 +2400,7 @@ def max(x, axis=None, keepdim=False, name=None):
#[7., 8.], [[[0., 0.], [0., 0.]], [[0., 0.], [1., 1.]]]
"""
reduce_all
,
axis
=
_get_reduce_axis_with_tensor
(
axis
)
reduce_all
,
axis
=
_get_reduce_axis_with_tensor
(
axis
,
x
)
if
in_dygraph_mode
():
return
_C_ops
.
max
(
x
,
axis
,
keepdim
)
if
_in_legacy_dygraph
():
...
...
@@ -2534,7 +2502,7 @@ def min(x, axis=None, keepdim=False, name=None):
#[1., 2.], [[[1., 1.], [0., 0.]], [[0., 0.], [0., 0.]]]
"""
reduce_all
,
axis
=
_get_reduce_axis_with_tensor
(
axis
)
reduce_all
,
axis
=
_get_reduce_axis_with_tensor
(
axis
,
x
)
if
in_dygraph_mode
():
return
_C_ops
.
min
(
x
,
axis
,
keepdim
)
...
...
@@ -2650,7 +2618,7 @@ def amax(x, axis=None, keepdim=False, name=None):
#[0.9., 0.9], [[[0., 0.3333], [0.5, 0.3333]], [[0.5, 0.3333], [1., 1.]]]
"""
reduce_all
,
axis
=
_get_reduce_axis
(
axis
)
reduce_all
,
axis
=
_get_reduce_axis
(
axis
,
x
)
if
in_dygraph_mode
():
return
_C_ops
.
amax
(
x
,
axis
,
keepdim
)
if
_in_legacy_dygraph
():
...
...
@@ -2764,7 +2732,7 @@ def amin(x, axis=None, keepdim=False, name=None):
#[0.1., 0.1], [[[0., 0.3333], [0.5, 0.3333]], [[0.5, 0.3333], [1., 1.]]]
"""
reduce_all
,
axis
=
_get_reduce_axis
(
axis
)
reduce_all
,
axis
=
_get_reduce_axis
(
axis
,
x
)
if
in_dygraph_mode
():
return
_C_ops
.
amin
(
x
,
axis
,
keepdim
)
elif
_in_legacy_dygraph
():
...
...
python/paddle/tensor/stat.py
浏览文件 @
c8fc3379
...
...
@@ -20,9 +20,9 @@ from ..framework import core
from
paddle.fluid.framework
import
_in_legacy_dygraph
,
in_dygraph_mode
from
.search
import
where
from
..fluid.data_feeder
import
check_type
,
check_variable_and_dtype
from
..fluid.layers
import
utils
import
paddle
from
paddle
import
_C_ops
,
_legacy_C_ops
from
.math
import
_get_reduce_axis_with_tensor
__all__
=
[]
...
...
@@ -80,22 +80,9 @@ def mean(x, axis=None, keepdim=False, name=None):
# [ 8.5 12.5 16.5]
"""
if
isinstance
(
axis
,
Variable
):
reduce_all
=
True
if
axis
.
shape
[
0
]
==
len
(
x
.
shape
)
else
False
else
:
if
isinstance
(
axis
,
int
):
axis
=
[
axis
]
reduce_all
=
(
True
if
axis
is
None
or
len
(
axis
)
==
0
or
len
(
axis
)
==
len
(
x
.
shape
)
else
False
)
if
axis
is
None
or
len
(
axis
)
==
0
:
axis
=
[
0
]
reduce_all
,
axis
=
_get_reduce_axis_with_tensor
(
axis
,
x
)
if
in_dygraph_mode
():
if
reduce_all
:
axis
=
list
(
range
(
len
(
x
.
shape
)))
return
_C_ops
.
mean
(
x
,
axis
,
keepdim
)
if
_in_legacy_dygraph
():
return
_legacy_C_ops
.
reduce_mean
(
...
...
@@ -122,8 +109,6 @@ def mean(x, axis=None, keepdim=False, name=None):
helper
=
LayerHelper
(
'mean'
,
**
locals
())
if
not
isinstance
(
axis
,
Variable
)
and
utils
.
_contain_var
(
axis
):
axis
=
utils
.
_convert_to_tensor_list
(
axis
)
attrs
=
{
'dim'
:
axis
,
'keep_dim'
:
keepdim
,
'reduce_all'
:
reduce_all
}
out
=
helper
.
create_variable_for_type_inference
(
x
.
dtype
)
helper
.
append_op
(
...
...
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