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0c617377
编写于
3月 03, 2020
作者:
S
songyouwei
提交者:
GitHub
3月 03, 2020
浏览文件
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电子邮件补丁
差异文件
add case and switch_case unittests for dygraph mode (#22790)
test=develop
上级
ddb9b46f
变更
1
隐藏空白更改
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并排
Showing
1 changed file
with
104 addition
and
0 deletion
+104
-0
python/paddle/fluid/tests/unittests/test_layers.py
python/paddle/fluid/tests/unittests/test_layers.py
+104
-0
未找到文件。
python/paddle/fluid/tests/unittests/test_layers.py
浏览文件 @
0c617377
...
...
@@ -1564,6 +1564,110 @@ class TestLayer(LayerTest):
self
.
assertTrue
(
np
.
array_equal
(
static_res
,
dynamic_res
))
def
test_case
(
self
):
def
fn_1
():
return
layers
.
fill_constant
(
shape
=
[
1
,
2
],
dtype
=
'float32'
,
value
=
1
)
def
fn_2
():
return
layers
.
fill_constant
(
shape
=
[
2
,
2
],
dtype
=
'int32'
,
value
=
2
)
def
fn_3
():
return
layers
.
fill_constant
(
shape
=
[
3
],
dtype
=
'int32'
,
value
=
3
)
with
self
.
static_graph
():
x
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'float32'
,
value
=
0.3
)
y
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'float32'
,
value
=
0.1
)
z
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'float32'
,
value
=
0.2
)
pred_1
=
layers
.
less_than
(
z
,
x
)
# true: 0.2 < 0.3
pred_2
=
layers
.
less_than
(
x
,
y
)
# false: 0.3 < 0.1
pred_3
=
layers
.
equal
(
x
,
y
)
# false: 0.3 == 0.1
out_1
=
layers
.
case
(
pred_fn_pairs
=
[(
pred_1
,
fn_1
),
(
pred_2
,
fn_2
)],
default
=
fn_3
)
out_2
=
layers
.
case
(
pred_fn_pairs
=
[(
pred_2
,
fn_2
),
(
pred_3
,
fn_3
)])
place
=
fluid
.
CUDAPlace
(
0
)
if
core
.
is_compiled_with_cuda
(
)
else
fluid
.
CPUPlace
()
exe
=
fluid
.
Executor
(
place
)
static_res1
,
static_res2
=
exe
.
run
(
fetch_list
=
[
out_1
,
out_2
])
with
self
.
dynamic_graph
():
x
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'float32'
,
value
=
0.3
)
y
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'float32'
,
value
=
0.1
)
z
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'float32'
,
value
=
0.2
)
pred_1
=
layers
.
less_than
(
z
,
x
)
# true: 0.2 < 0.3
pred_2
=
layers
.
less_than
(
x
,
y
)
# false: 0.3 < 0.1
pred_3
=
layers
.
equal
(
x
,
y
)
# false: 0.3 == 0.1
out_1
=
layers
.
case
(
pred_fn_pairs
=
[(
pred_1
,
fn_1
),
(
pred_2
,
fn_2
)],
default
=
fn_3
)
out_2
=
layers
.
case
(
pred_fn_pairs
=
[(
pred_2
,
fn_2
),
(
pred_3
,
fn_3
)])
dynamic_res1
=
out_1
.
numpy
()
dynamic_res2
=
out_2
.
numpy
()
self
.
assertTrue
(
np
.
array_equal
(
static_res1
,
dynamic_res1
))
self
.
assertTrue
(
np
.
array_equal
(
static_res2
,
dynamic_res2
))
def
test_switch_case
(
self
):
def
fn_1
():
return
layers
.
fill_constant
(
shape
=
[
1
,
2
],
dtype
=
'float32'
,
value
=
1
)
def
fn_2
():
return
layers
.
fill_constant
(
shape
=
[
2
,
2
],
dtype
=
'int32'
,
value
=
2
)
def
fn_3
():
return
layers
.
fill_constant
(
shape
=
[
3
],
dtype
=
'int32'
,
value
=
3
)
with
self
.
static_graph
():
index_1
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'int32'
,
value
=
1
)
index_2
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'int32'
,
value
=
2
)
out_1
=
layers
.
switch_case
(
branch_index
=
index_1
,
branch_fns
=
{
1
:
fn_1
,
2
:
fn_2
},
default
=
fn_3
)
out_2
=
layers
.
switch_case
(
branch_index
=
index_2
,
branch_fns
=
[(
1
,
fn_1
),
(
2
,
fn_2
)],
default
=
fn_3
)
out_3
=
layers
.
switch_case
(
branch_index
=
index_2
,
branch_fns
=
[(
0
,
fn_1
),
(
4
,
fn_2
),
(
7
,
fn_3
)])
place
=
fluid
.
CUDAPlace
(
0
)
if
core
.
is_compiled_with_cuda
(
)
else
fluid
.
CPUPlace
()
exe
=
fluid
.
Executor
(
place
)
static_res1
,
static_res2
,
static_res3
=
exe
.
run
(
fetch_list
=
[
out_1
,
out_2
,
out_3
])
with
self
.
dynamic_graph
():
index_1
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'int32'
,
value
=
1
)
index_2
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'int32'
,
value
=
2
)
out_1
=
layers
.
switch_case
(
branch_index
=
index_1
,
branch_fns
=
{
1
:
fn_1
,
2
:
fn_2
},
default
=
fn_3
)
out_2
=
layers
.
switch_case
(
branch_index
=
index_2
,
branch_fns
=
[(
1
,
fn_1
),
(
2
,
fn_2
)],
default
=
fn_3
)
out_3
=
layers
.
switch_case
(
branch_index
=
index_2
,
branch_fns
=
[(
0
,
fn_1
),
(
4
,
fn_2
),
(
7
,
fn_3
)])
dynamic_res1
=
out_1
.
numpy
()
dynamic_res2
=
out_2
.
numpy
()
dynamic_res3
=
out_3
.
numpy
()
self
.
assertTrue
(
np
.
array_equal
(
static_res1
,
dynamic_res1
))
self
.
assertTrue
(
np
.
array_equal
(
static_res2
,
dynamic_res2
))
self
.
assertTrue
(
np
.
array_equal
(
static_res3
,
dynamic_res3
))
def
test_crop_tensor
(
self
):
with
self
.
static_graph
():
x
=
fluid
.
layers
.
data
(
name
=
"x1"
,
shape
=
[
6
,
5
,
8
])
...
...
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