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体验新版 GitCode,发现更多精彩内容 >>
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e6ca512a
编写于
1月 22, 2020
作者:
W
wangchaochaohu
提交者:
GitHub
1月 22, 2020
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
refine convert type for numpy type (#22386)
上级
20f30dd6
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
14 addition
and
4 deletion
+14
-4
python/paddle/fluid/data_feeder.py
python/paddle/fluid/data_feeder.py
+8
-2
python/paddle/fluid/tests/unittests/test_fill_constant_op.py
python/paddle/fluid/tests/unittests/test_fill_constant_op.py
+6
-2
未找到文件。
python/paddle/fluid/data_feeder.py
浏览文件 @
e6ca512a
...
...
@@ -15,7 +15,7 @@
from
__future__
import
print_function
from
.
import
core
import
numpy
import
numpy
as
np
import
os
import
six
from
six.moves
import
zip
,
range
,
xrange
...
...
@@ -47,6 +47,12 @@ def convert_dtype(dtype):
return
'int64'
elif
dtype
==
core
.
VarDesc
.
VarType
.
UINT8
:
return
'uint8'
elif
isinstance
(
dtype
,
type
):
if
dtype
in
[
np
.
bool
,
np
.
float16
,
np
.
float32
,
np
.
float64
,
np
.
int8
,
np
.
int16
,
np
.
int32
,
np
.
int64
,
np
.
uint8
]:
return
dtype
.
__name__
else
:
if
dtype
in
[
'bool'
,
'float16'
,
'float32'
,
'float64'
,
'int8'
,
'int16'
,
...
...
@@ -136,7 +142,7 @@ class DataToLoDTensorConverter(object):
format
(
self
.
shape
,
shape
))
def
done
(
self
):
arr
=
n
umpy
.
array
(
self
.
data
,
dtype
=
self
.
dtype
)
arr
=
n
p
.
array
(
self
.
data
,
dtype
=
self
.
dtype
)
if
self
.
shape
:
if
len
(
arr
.
shape
)
!=
len
(
self
.
shape
):
try
:
...
...
python/paddle/fluid/tests/unittests/test_fill_constant_op.py
浏览文件 @
e6ca512a
...
...
@@ -216,20 +216,24 @@ class TestFillConstantAPI(unittest.TestCase):
out_5
=
fluid
.
layers
.
fill_constant
(
shape
=
shape_tensor_int64
,
dtype
=
"float32"
,
value
=
1.1
)
out_6
=
fluid
.
layers
.
fill_constant
(
shape
=
shape_tensor_int64
,
dtype
=
np
.
float32
,
value
=
1.1
)
exe
=
fluid
.
Executor
(
place
=
fluid
.
CPUPlace
())
res_1
,
res_2
,
res_3
,
res_4
,
res_5
=
exe
.
run
(
res_1
,
res_2
,
res_3
,
res_4
,
res_5
,
res_6
=
exe
.
run
(
fluid
.
default_main_program
(),
feed
=
{
"shape_tensor_int32"
:
np
.
array
([
1
,
2
]).
astype
(
"int32"
),
"shape_tensor_int64"
:
np
.
array
([
1
,
2
]).
astype
(
"int64"
),
},
fetch_list
=
[
out_1
,
out_2
,
out_3
,
out_4
,
out_5
])
fetch_list
=
[
out_1
,
out_2
,
out_3
,
out_4
,
out_5
,
out_6
])
assert
np
.
array_equal
(
res_1
,
np
.
full
([
1
,
2
],
1.1
,
dtype
=
"float32"
))
assert
np
.
array_equal
(
res_2
,
np
.
full
([
1
,
2
],
1.1
,
dtype
=
"float32"
))
assert
np
.
array_equal
(
res_3
,
np
.
full
([
1
,
2
],
1.1
,
dtype
=
"float32"
))
assert
np
.
array_equal
(
res_4
,
np
.
full
([
1
,
2
],
1.1
,
dtype
=
"float32"
))
assert
np
.
array_equal
(
res_5
,
np
.
full
([
1
,
2
],
1.1
,
dtype
=
"float32"
))
assert
np
.
array_equal
(
res_6
,
np
.
full
([
1
,
2
],
1.1
,
dtype
=
"float32"
))
class
TestFillConstantOpError
(
unittest
.
TestCase
):
...
...
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