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835ea12c
编写于
12月 09, 2019
作者:
G
guofei
提交者:
Huihuang Zheng
12月 09, 2019
浏览文件
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电子邮件补丁
差异文件
Control flow API: while_loop (#21276)
Add basic while_loop
上级
4f81d1bd
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
294 addition
and
1 deletion
+294
-1
python/paddle/fluid/layers/control_flow.py
python/paddle/fluid/layers/control_flow.py
+89
-1
python/paddle/fluid/tests/unittests/test_while_loop_op.py
python/paddle/fluid/tests/unittests/test_while_loop_op.py
+205
-0
未找到文件。
python/paddle/fluid/layers/control_flow.py
浏览文件 @
835ea12c
...
...
@@ -33,7 +33,8 @@ __all__ = [
'While'
,
'Switch'
,
'increment'
,
'array_write'
,
'create_array'
,
'less_than'
,
'less_equal'
,
'greater_than'
,
'greater_equal'
,
'equal'
,
'not_equal'
,
'array_read'
,
'array_length'
,
'cond'
,
'IfElse'
,
'DynamicRNN'
,
'StaticRNN'
,
'reorder_lod_tensor_by_rank'
,
'Print'
,
'is_empty'
,
'case'
,
'switch_case'
'reorder_lod_tensor_by_rank'
,
'Print'
,
'is_empty'
,
'case'
,
'switch_case'
,
'while_loop'
]
...
...
@@ -918,6 +919,93 @@ class While(object):
"is_test"
:
self
.
is_test
})
def
while_loop
(
cond
,
body
,
loop_vars
,
name
=
None
):
"""
while_loop is one of the control flows. Repeats while_loop `body` until `cond` returns False.
Args:
cond(Callable): A callable returning a boolean tensor controlling whether to continue looping.
body(Callable): A callable returning a tuple or list of tensors of the same arity (length and structure)
and types as ``loops_vars`` .
loop_vars(list|tuple): A list or tuple of tensors that is passed to both ``cond`` and ``body`` .
name(str, optional): Normally there is no need for users to set this property. For more information, please
refer to :ref:`api_guide_Name`. Default is None.
Returns:
A list or tuple of tensors which returned by ``body`` .
Returen type:
list(Variable)|tuple(Variable).
Raises:
TypeError: If the type of ``cond`` is not callable.
TypeError: If the type of ``body`` is not callable.
TypeError: If the type of ``loop_vars`` is not list or tuple.
TypeError: If the type of ``cond`` returns is not Variable.
TypeError: If the type of ``cond`` returns is not a boolean variable.
TypeError: If the shape of ``cond`` returns is not equals 1.
ValueError: If the ``var_loops`` is empty.
Examples:
.. code-block:: python
import paddle.fluid as fluid
import paddle.fluid.layers as layers
def cond(i):
return layers.less_than(i, ten)
def body(i):
return layers.increment(x=i, value=1, in_place=True)
main_program = fluid.default_main_program()
startup_program = fluid.default_startup_program()
with fluid.program_guard(main_program, startup_program):
i = layers.fill_constant(shape=[1], dtype='int64', value=0) # loop counter
ten = layers.fill_constant(shape=[1], dtype='int64', value=10) # loop length
out = layers.while_loop(cond, body, [i])
exe = fluid.Executor(fluid.CPUPlace())
res = exe.run(main_program, feed={}, fetch_list=out)
print(res) # [array([10])]
"""
helper
=
LayerHelper
(
'while_loop'
,
**
locals
())
if
not
callable
(
cond
):
raise
TypeError
(
"cond in while_loop should be callable"
)
if
not
callable
(
body
):
raise
TypeError
(
"body in while_loop should be callable"
)
if
not
isinstance
(
loop_vars
,
(
list
,
tuple
)):
raise
TypeError
(
"loop_vars in while_loop should be a list or tuple"
)
if
len
(
loop_vars
)
==
0
:
raise
ValueError
(
"loop_vars in while_loop should not be empty"
)
pre_cond
=
cond
(
*
loop_vars
)
if
not
isinstance
(
pre_cond
,
Variable
):
raise
TypeError
(
"cond in while_loop should return a variable"
)
if
pre_cond
.
dtype
!=
core
.
VarDesc
.
VarType
.
BOOL
:
raise
TypeError
(
"cond in while_loop should return a boolean variable"
)
if
reduce
(
lambda
a
,
b
:
a
*
b
,
pre_cond
.
shape
,
1
)
!=
1
:
raise
TypeError
(
"the shape of the variable returned by cond should be [],"
"but given shape as {0}."
.
format
(
list
(
pre_cond
.
shape
)))
while_loop_block
=
While
(
pre_cond
)
with
while_loop_block
.
block
():
output_vars
=
body
(
*
loop_vars
)
if
len
(
loop_vars
)
==
1
:
assign
(
output_vars
,
loop_vars
[
0
])
now_cond
=
cond
(
output_vars
)
else
:
for
i
in
range
(
len
(
output_vars
)):
assign
(
output_vars
[
i
],
loop_vars
[
i
])
now_cond
=
cond
(
*
output_vars
)
assign
(
now_cond
,
pre_cond
)
return
loop_vars
def
lod_rank_table
(
x
,
level
=
0
):
"""
LoD Rank Table Operator. Given an input variable **x** and a level number
...
...
python/paddle/fluid/tests/unittests/test_while_loop_op.py
0 → 100644
浏览文件 @
835ea12c
# Copyright (c) 2018 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.
from
__future__
import
print_function
import
numpy
as
np
import
unittest
import
paddle.fluid
as
fluid
import
paddle.fluid.core
as
core
import
paddle.fluid.layers
as
layers
import
paddle.fluid.framework
as
framework
from
paddle.fluid.executor
import
Executor
from
paddle.fluid.framework
import
Program
,
program_guard
class
TestApiWhileLoop
(
unittest
.
TestCase
):
def
test_var_tuple
(
self
):
def
cond
(
i
):
return
layers
.
less_than
(
i
,
ten
)
def
body
(
i
):
return
layers
.
elementwise_add
(
x
=
i
,
y
=
one
)
main_program
=
Program
()
startup_program
=
Program
()
with
program_guard
(
main_program
,
startup_program
):
i
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'int64'
,
value
=
0
)
one
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'int64'
,
value
=
1
)
ten
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'int64'
,
value
=
10
)
out
=
layers
.
while_loop
(
cond
,
body
,
(
i
,
))
place
=
fluid
.
CPUPlace
()
exe
=
fluid
.
Executor
(
place
)
res
=
exe
.
run
(
main_program
,
fetch_list
=
out
)
self
.
assertTrue
(
np
.
allclose
(
np
.
asarray
(
res
[
0
]),
np
.
full
((
1
),
10
,
np
.
int64
)))
def
test_var_list
(
self
):
def
cond
(
i
,
mem
):
return
layers
.
less_than
(
i
,
ten
)
def
body
(
i
,
mem
):
mem
=
layers
.
elementwise_add
(
x
=
mem
,
y
=
one
)
i
=
layers
.
increment
(
i
)
return
[
i
,
mem
]
main_program
=
Program
()
startup_program
=
Program
()
with
program_guard
(
main_program
,
startup_program
):
i
=
layers
.
zeros
(
shape
=
[
1
],
dtype
=
'int64'
)
ten
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'int64'
,
value
=
10
)
mem
=
layers
.
data
(
name
=
"mem"
,
shape
=
[
10
],
dtype
=
'float32'
)
one
=
layers
.
fill_constant
(
shape
=
[
10
],
dtype
=
'float32'
,
value
=
1
)
out
=
layers
.
while_loop
(
cond
,
body
,
[
i
,
mem
])
data
=
np
.
random
.
rand
(
10
).
astype
(
'float32'
)
data_one
=
np
.
ones
(
10
).
astype
(
'float32'
)
place
=
fluid
.
CPUPlace
()
exe
=
fluid
.
Executor
(
place
)
res
=
exe
.
run
(
main_program
,
feed
=
{
'mem'
:
data
},
fetch_list
=
out
)
for
i
in
range
(
10
):
data
=
np
.
add
(
data
,
data_one
)
self
.
assertTrue
(
np
.
allclose
(
np
.
asarray
(
res
[
1
]),
data
))
class
TestApiWhileLoop_Nested
(
unittest
.
TestCase
):
def
test_nested_net
(
self
):
def
external_cond
(
i
,
j
,
init
,
sums
):
return
layers
.
less_than
(
i
,
loop_len1
)
def
external_body
(
i
,
j
,
init
,
sums
):
def
internal_cond
(
j
,
init
,
sums
):
return
layers
.
less_than
(
j
,
loop_len2
)
def
internal_body
(
j
,
init
,
sums
):
init
=
layers
.
elementwise_add
(
x
=
init
,
y
=
ones
)
sums
=
layers
.
elementwise_add
(
x
=
init
,
y
=
sums
)
j
=
layers
.
increment
(
j
)
return
[
j
,
init
,
sums
]
result
=
layers
.
while_loop
(
internal_cond
,
internal_body
,
[
j
,
init
,
sums
])
j
=
result
[
0
]
init
=
result
[
1
]
sums
=
result
[
2
]
sums
=
layers
.
elementwise_add
(
x
=
init
,
y
=
sums
)
i
=
layers
.
increment
(
i
)
return
[
i
,
j
,
init
,
sums
]
main_program
=
Program
()
startup_program
=
Program
()
with
program_guard
(
main_program
,
startup_program
):
i
=
layers
.
zeros
(
shape
=
[
1
],
dtype
=
'int64'
)
j
=
layers
.
zeros
(
shape
=
[
1
],
dtype
=
'int64'
)
init
=
layers
.
data
(
name
=
"init"
,
shape
=
[
3
,
3
],
dtype
=
'float32'
)
sums
=
layers
.
data
(
name
=
"sums"
,
shape
=
[
3
,
3
],
dtype
=
'float32'
)
loop_len1
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'int64'
,
value
=
2
)
loop_len2
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'int64'
,
value
=
3
)
ones
=
layers
.
fill_constant
(
shape
=
[
3
,
3
],
dtype
=
'float32'
,
value
=
1
)
res
=
layers
.
while_loop
(
external_cond
,
external_body
,
[
i
,
j
,
init
,
sums
])
data
=
np
.
random
.
rand
(
3
,
3
).
astype
(
'float32'
)
data_sums
=
np
.
zeros
([
3
,
3
]).
astype
(
'float32'
)
place
=
fluid
.
CPUPlace
()
exe
=
fluid
.
Executor
(
place
)
ret
=
exe
.
run
(
main_program
,
feed
=
{
'init'
:
data
,
'sums'
:
data_sums
},
fetch_list
=
res
)
for
i
in
range
(
3
):
data
=
np
.
add
(
data
,
1
)
data_sums
=
np
.
add
(
data
,
data_sums
)
for
j
in
range
(
2
):
data_sums
=
np
.
add
(
data
,
data_sums
)
self
.
assertTrue
(
np
.
allclose
(
np
.
asarray
(
ret
[
3
]),
data_sums
))
class
TestApiWhileLoop_Error
(
unittest
.
TestCase
):
def
test_error
(
self
):
def
cond_returns_constant
(
i
):
return
1
def
cond_returns_not_bool_tensor
(
i
):
return
layers
.
increment
(
i
)
def
cond_returns_bool_tensor
(
i
):
return
layers
.
less_than
(
i
,
ten
)
def
cond_returns_2d_tensor
(
i
):
return
layers
.
less_than
(
i
,
ten_2d
)
def
body
(
i
):
return
layers
.
increment
(
i
)
main_program
=
Program
()
startup_program
=
Program
()
with
program_guard
(
main_program
,
startup_program
):
data
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'int64'
,
value
=
1
)
data_1d
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'int64'
,
value
=
1
)
data_2d
=
layers
.
fill_constant
(
shape
=
[
2
,
2
],
dtype
=
'int64'
,
value
=
1
)
ten
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'int64'
,
value
=
10
)
ten_2d
=
layers
.
fill_constant
(
shape
=
[
2
,
2
],
dtype
=
'int64'
,
value
=
10
)
# The type of `cond` in Op(while_loop) must be callable
def
type_error_cond
():
out
=
layers
.
while_loop
(
data
,
body
,
[
data_1d
])
self
.
assertRaises
(
TypeError
,
type_error_cond
)
# The type of `body` in Op(while_loop) must be callable
def
type_error_body
():
out
=
layers
.
while_loop
(
cond_returns_bool_tensor
,
data
,
[
data_1d
])
self
.
assertRaises
(
TypeError
,
type_error_body
)
# The type of `loop_vars` in Op(while_loop) must be list or tuple
def
type_error_loop_vars
():
out
=
layers
.
while_loop
(
cond_returns_bool_tensor
,
body
,
data_1d
)
self
.
assertRaises
(
TypeError
,
type_error_loop_vars
)
# The value of `loop_vars` is empty
def
value_error_loop_vars
():
out
=
layers
.
while_loop
(
cond_returns_bool_tensor
,
body
,
[])
self
.
assertRaises
(
ValueError
,
value_error_loop_vars
)
# The type of `cond` returns in Op(while_loop) must be Variable
def
type_error_cond_returns_not_variable
():
out
=
layers
.
while_loop
(
cond_returns_constant
,
body
,
[
data_1d
])
self
.
assertRaises
(
TypeError
,
type_error_cond_returns_not_variable
)
# The type of `cond` returns in Op(while_loop) must be a bollean variable
def
type_error_cond_returns_not_boolean
():
out
=
layers
.
while_loop
(
cond_returns_not_bool_tensor
,
body
,
[
data_1d
])
self
.
assertRaises
(
TypeError
,
type_error_cond_returns_not_boolean
)
# The shape of `cond` returns in Op(while_loop) must be 1
def
type_error_shape_cond_returns_2d
():
out
=
layers
.
while_loop
(
cond_returns_2d_tensor
,
body
,
[
data_2d
])
self
.
assertRaises
(
TypeError
,
type_error_shape_cond_returns_2d
)
if
__name__
==
'__main__'
:
unittest
.
main
()
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