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8f09109a
编写于
9月 21, 2018
作者:
G
gongweibao
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
fix
上级
8fa1d84d
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
124 addition
and
163 deletion
+124
-163
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+70
-87
python/paddle/fluid/layers/ops.py
python/paddle/fluid/layers/ops.py
+0
-1
python/paddle/fluid/tests/unittests/op_test.py
python/paddle/fluid/tests/unittests/op_test.py
+3
-0
python/paddle/fluid/tests/unittests/test_layers.py
python/paddle/fluid/tests/unittests/test_layers.py
+8
-0
tools/test_generator.py
tools/test_generator.py
+43
-75
未找到文件。
python/paddle/fluid/layers/nn.py
浏览文件 @
8f09109a
...
...
@@ -29,93 +29,25 @@ from .. import unique_name
from
functools
import
reduce
__all__
=
[
'fc'
,
'embedding'
,
'dynamic_lstm'
,
'dynamic_lstmp'
,
'dynamic_gru'
,
'gru_unit'
,
'linear_chain_crf'
,
'crf_decoding'
,
'cos_sim'
,
'cross_entropy'
,
'square_error_cost'
,
'chunk_eval'
,
'sequence_conv'
,
'conv2d'
,
'conv3d'
,
'sequence_pool'
,
'sequence_softmax'
,
'softmax'
,
'pool2d'
,
'pool3d'
,
'batch_norm'
,
'beam_search_decode'
,
'conv2d_transpose'
,
'conv3d_transpose'
,
'sequence_expand'
,
'sequence_expand_as'
,
'sequence_pad'
,
'lstm_unit'
,
'reduce_sum'
,
'reduce_mean'
,
'reduce_max'
,
'reduce_min'
,
'reduce_prod'
,
'sequence_first_step'
,
'sequence_last_step'
,
'dropout'
,
'split'
,
'ctc_greedy_decoder'
,
'edit_distance'
,
'l2_normalize'
,
'matmul'
,
'topk'
,
'warpctc'
,
'sequence_reshape'
,
'transpose'
,
'im2sequence'
,
'nce'
,
'hsigmoid'
,
'beam_search'
,
'row_conv'
,
'multiplex'
,
'layer_norm'
,
'softmax_with_cross_entropy'
,
'smooth_l1'
,
'one_hot'
,
'autoincreased_step_counter'
,
'reshape'
,
'squeeze'
,
'unsqueeze'
,
'lod_reset'
,
'lrn'
,
'pad'
,
'pad_constant_like'
,
'label_smooth'
,
'roi_pool'
,
'dice_loss'
,
'image_resize'
,
'image_resize_short'
,
'resize_bilinear'
,
'gather'
,
'scatter'
,
'sequence_scatter'
,
'random_crop'
,
'mean_iou'
,
'relu'
,
'log'
,
'crop'
,
'rank_loss'
,
'prelu'
,
'flatten'
,
'sequence_mask'
,
'stack'
,
'pad2d'
,
'unstack'
,
'sequence_enumerate'
,
'expand'
,
'sequence_concat'
,
'fc'
,
'embedding'
,
'dynamic_lstm'
,
'dynamic_lstmp'
,
'dynamic_gru'
,
'gru_unit'
,
'linear_chain_crf'
,
'crf_decoding'
,
'cos_sim'
,
'cross_entropy'
,
'square_error_cost'
,
'chunk_eval'
,
'sequence_conv'
,
'conv2d'
,
'conv3d'
,
'sequence_pool'
,
'sequence_softmax'
,
'softmax'
,
'pool2d'
,
'pool3d'
,
'batch_norm'
,
'beam_search_decode'
,
'conv2d_transpose'
,
'conv3d_transpose'
,
'sequence_expand'
,
'sequence_expand_as'
,
'sequence_pad'
,
'lstm_unit'
,
'reduce_sum'
,
'reduce_mean'
,
'reduce_max'
,
'reduce_min'
,
'reduce_prod'
,
'sequence_first_step'
,
'sequence_last_step'
,
'dropout'
,
'split'
,
'ctc_greedy_decoder'
,
'edit_distance'
,
'l2_normalize'
,
'matmul'
,
'topk'
,
'warpctc'
,
'sequence_reshape'
,
'transpose'
,
'im2sequence'
,
'nce'
,
'hsigmoid'
,
'beam_search'
,
'row_conv'
,
'multiplex'
,
'layer_norm'
,
'softmax_with_cross_entropy'
,
'smooth_l1'
,
'one_hot'
,
'autoincreased_step_counter'
,
'reshape'
,
'squeeze'
,
'unsqueeze'
,
'lod_reset'
,
'lrn'
,
'pad'
,
'pad_constant_like'
,
'label_smooth'
,
'roi_pool'
,
'dice_loss'
,
'image_resize'
,
'image_resize_short'
,
'resize_bilinear'
,
'gather'
,
'scatter'
,
'sequence_scatter'
,
'random_crop'
,
'mean_iou'
,
'relu'
,
'log'
,
'crop'
,
'rank_loss'
,
'prelu'
,
'flatten'
,
'sequence_mask'
,
'stack'
,
'pad2d'
,
'unstack'
,
'sequence_enumerate'
,
'expand'
,
'sequence_concat'
,
'uniform_random_batch_size_like'
]
...
...
@@ -6234,3 +6166,54 @@ def expand(x, expand_times, name=None):
outputs
=
{
'Out'
:
out
},
attrs
=
{
'expand_times'
:
expand_times
})
return
out
from
paddle.fluid.framework
import
convert_np_dtype_to_dtype_
def
uniform_random_batch_size_like
(
input
,
shape
,
dtype
=
'float32'
,
input_dim_idx
=
0
,
output_dim_idx
=
0
,
min
=-
1.0
,
max
=
1.0
,
seed
=
0
):
"""
UniformRandomBatchSizeLike operator.
This operator initializes a tensor with the same batch_size as the Input tensor with random values sampled from a uniform distribution.
Args:
input (Variable): Tensor whose input_dim_idx'th dimension specifies the batch_size.
shape (tuple|list): the shape of the output.
input_dim_idx (Int): The index of input's batch size dimension.
output_dim_idx (Int): The index of output's batch size dimension.
min (Float): Minimum value of uniform random.
max (Float): Maximum value of uniform random.
seed (Int): Random seed used for generating samples. 0 means use a seed generated by the system.
Note that if seed is not 0, this operator will always generate the same random numbers every time.
dtype(np.dtype|core.VarDesc.VarType|str): The type of data : float32, float_16, int etc
Returns:
output(Variable): Output of this operator.
"""
helper
=
LayerHelper
(
'uniform_random_batch_size_like'
,
**
locals
())
out
=
helper
.
create_tmp_variable
(
dtype
)
c_dtype
=
convert_np_dtype_to_dtype_
(
dtype
)
helper
.
append_op
(
type
=
'uniform_random_batch_size_like'
,
inputs
=
{
'Input'
:
input
},
outputs
=
{
'Out'
:
out
},
attrs
=
{
'shape'
:
shape
,
'input_dim_idx'
:
input_dim_idx
,
'output_dim_idx'
:
output_dim_idx
,
'min'
:
min
,
'max'
:
max
,
'seed'
:
seed
,
'dtype'
:
c_dtype
})
return
out
python/paddle/fluid/layers/ops.py
浏览文件 @
8f09109a
...
...
@@ -62,7 +62,6 @@ __all__ = [
'logical_or'
,
'logical_xor'
,
'logical_not'
,
'uniform_random_batch_size_like'
,
'gaussian_random'
,
'sampling_id'
,
'gaussian_random_batch_size_like'
,
...
...
python/paddle/fluid/tests/unittests/op_test.py
浏览文件 @
8f09109a
...
...
@@ -252,6 +252,9 @@ class OpTest(unittest.TestCase):
block
=
program
.
global_block
()
self
.
_append_ops
(
block
)
from
paddle.fluid.transpiler.details
import
program_to_code
program_to_code
(
program
)
inputs
=
self
.
_get_inputs
(
block
)
outputs
=
self
.
_get_outputs
(
block
)
feed_map
=
self
.
feed_var
(
inputs
,
place
)
...
...
python/paddle/fluid/tests/unittests/test_layers.py
浏览文件 @
8f09109a
...
...
@@ -596,6 +596,14 @@ class TestBook(unittest.TestCase):
out
=
layers
.
expand
(
x
,
[
1
,
2
])
print
(
str
(
program
))
def
test_uniform_random_batch_size_like
(
self
):
program
=
Program
()
with
program_guard
(
program
):
input
=
layers
.
data
(
name
=
"input"
,
shape
=
[
500
,
2000
],
dtype
=
'float32'
)
out
=
layers
.
uniform_random_batch_size_like
(
input
,
[
-
1
,
2000
])
self
.
assertIsNotNone
(
out
)
if
__name__
==
'__main__'
:
unittest
.
main
()
tools/test_generator.py
浏览文件 @
8f09109a
...
...
@@ -23,7 +23,7 @@ from paddle.fluid.proto import framework_pb2
from
paddle.fluid.framework
import
OpProtoHolder
,
Variable
from
paddle.fluid.layer_helper
import
LayerHelper
g_filer_attrs
=
[
'op_role'
,
'op_role_var'
,
'op_namescope'
,
'dtype'
]
g_filer_attrs
=
[
'op_role'
,
'op_role_var'
,
'op_namescope'
]
def
_convert_
(
name
):
...
...
@@ -46,7 +46,7 @@ def _get_inputs(op_type):
op_proto
=
OpProtoHolder
.
instance
().
get_op_proto
(
op_type
)
inputs
=
dict
()
for
ipt
in
op_proto
.
inputs
:
inputs
[
ipt
.
name
]
=
""
inputs
[
ipt
.
name
]
=
ipt
.
comment
return
inputs
...
...
@@ -60,6 +60,34 @@ def _get_outputs(op_type):
return
outputs
_two_dollar_pattern_
=
re
.
compile
(
r
"\$\$([^\$]+)\$\$"
)
_single_dollar_pattern_
=
re
.
compile
(
r
"\$([^\$]+)\$"
)
_two_bang_pattern_
=
re
.
compile
(
r
"!!([^!]+)!!"
)
def
escape_math
(
text
):
return
_two_bang_pattern_
.
sub
(
r
'$$\1$$'
,
_single_dollar_pattern_
.
sub
(
r
':math:`\1`'
,
_two_dollar_pattern_
.
sub
(
r
"!!\1!!"
,
text
)))
def
get_comment
(
op_type
):
op_proto
=
OpProtoHolder
.
instance
().
get_op_proto
(
op_type
)
comment_lines
=
op_proto
.
comment
.
split
(
"
\n
"
)
comment
=
""
for
line
in
comment_lines
:
line
=
line
.
strip
()
if
len
(
line
)
!=
0
:
comment
+=
escape_math
(
line
)
comment
+=
" "
elif
len
(
comment
)
!=
0
:
comment
+=
"
\n
"
return
comment
def
_get_attrs
(
op_type
):
op_proto
=
OpProtoHolder
.
instance
().
get_op_proto
(
op_type
)
return
op_proto
.
attrs
...
...
@@ -77,14 +105,14 @@ def get_input_comments(op_type, indent=2):
ret
=
""
inputs
=
_get_inputs
(
op_type
)
for
t
in
inputs
:
ret
+=
get_indent_space
(
2
)
+
"
input(${%s_type}): ${%s_comment}
\n
"
%
(
_convert_
(
t
),
_convert_
(
t
)
)
ret
+=
get_indent_space
(
2
)
+
"
%s (Type): %s
\n
"
%
(
_convert_
(
t
),
inputs
[
t
]
)
for
t
in
_get_attrs
(
op_type
):
if
t
.
name
in
g_filer_attrs
:
continue
ret
+=
get_indent_space
(
2
)
+
"
input(${%s_type}): ${%s_comment}
\n
"
%
(
_convert_
(
t
.
name
),
_convert_
(
t
.
name
))
ret
+=
get_indent_space
(
2
)
+
"
%s (%s): %s
\n
"
%
(
_convert_
(
t
.
name
),
t
.
type
,
_convert_
(
t
.
comment
))
return
ret
...
...
@@ -122,7 +150,7 @@ def get_inputs(op_type):
ret
=
"inputs={"
inputs
=
_get_inputs
(
op_type
)
for
t
in
inputs
:
ret
+=
"
{}=
{},"
.
format
(
t
,
_convert_
(
t
))
ret
+=
"
'{}':
{},"
.
format
(
t
,
_convert_
(
t
))
ret
=
ret
.
strip
(
","
)
ret
+=
"}"
...
...
@@ -132,39 +160,11 @@ def get_inputs(op_type):
return
ret
"""
def get_input_dtype(op_type):
dtype = None
for ipt in _get_inputs():
name = _convert_(ipt.name)
val = kwargs.pop(name, [])
if not isinstance(val, list) and not isinstance(val, tuple):
val = [val]
if len(val) == 0:
val = [args[0]]
args = args[1:]
for each in val:
if not isinstance(each, Variable):
raise ValueError("input of {0} must be variable".format(
op_type))
if dtype is None:
dtype = each.dtype
elif dtype != each.dtype:
raise ValueError(
"operator {0} must input same dtype. {1} vs {2}".format(
op_type, dtype, each.dtype))
return dtype
"""
def
get_outputs
(
op_type
):
ret
=
"outputs={"
inputs
=
_get_outputs
(
op_type
)
for
t
in
inputs
:
ret
+=
"
{}=
{},"
.
format
(
t
,
_convert_
(
t
))
ret
+=
"
'{}':
{},"
.
format
(
t
,
_convert_
(
t
))
ret
=
ret
.
strip
(
","
)
ret
+=
"}"
...
...
@@ -174,44 +174,13 @@ def get_outputs(op_type):
return
ret
"""
attr_names = sorted(op.attr_names)
attrs_str = ""
for i in range(0, len(attr_names)):
name = attr_names[i]
attr_type = op.desc.attr_type(name)
if attr_type == core.AttrType.BLOCK:
a = "{name} = block[{value}]".format(
name=name, type=attr_type, value=op.block_attr_id(name))
attrs_str += a
if i != len(attr_names) - 1:
attrs_str += ", "
continue
if attr_type == core.AttrType.BLOCKS:
a = "{name} = blocks{value}".format(
name=name, type=attr_type, value=op.blocks_attr_ids(name))
attrs_str += a
if i != len(attr_names) - 1:
attrs_str += ", "
continue
a = "{name} = {value}".format(
name=name, type=attr_type, value=op.desc.attr(name))
attrs_str += a
if i != len(attr_names) - 1:
attrs_str += ", "
"""
def
get_attrs
(
op_type
):
ret
=
"attrs={"
for
t
in
_get_attrs
(
op_type
):
if
t
.
name
in
g_filer_attrs
:
continue
ret
+=
"
%s=
%s,"
%
(
t
.
name
,
_convert_
(
t
.
name
))
ret
+=
"
'%s':
%s,"
%
(
t
.
name
,
_convert_
(
t
.
name
))
ret
=
ret
.
strip
(
","
)
ret
+=
"}"
...
...
@@ -220,12 +189,13 @@ def get_attrs(op_type):
def
get_outvars
(
op_type
,
indent
=
1
):
inputs
=
_get_inputs
(
op_type
)
ret
=
""
for
t
in
_get_outputs
(
op_type
):
ret
+=
get_indent_space
(
indent
)
+
"%s = helper.create_tmp_variable(dtype=helper.input_dtype())
\n
"
%
(
_convert_
(
t
))
)
+
"%s = helper.create_tmp_variable(dtype=helper.input_dtype(
'%s'
))
\n
"
%
(
(
_convert_
(
t
),
list
(
inputs
)[
0
]
))
ret
=
ret
.
strip
(
'
\n
'
)
return
ret
...
...
@@ -238,17 +208,15 @@ def get_op_py(op_type):
outputs
=
get_outputs
(
op_type
)
attrs
=
get_attrs
(
op_type
)
out_vars
=
get_outvars
(
op_type
)
comment
=
get_comment
(
op_type
)
code
=
"""
@templatedoc()
def {op_type}({args}):
\"\"\"
{op_type}
{comment}
Args:
{input_comments}
Returns:
{output_comments}
\"\"\"
...
...
@@ -263,7 +231,7 @@ def {op_type}({args}):
return out
"""
.
format
(
comment
=
"${comment}"
,
comment
=
comment
,
input_comments
=
input_comments
.
strip
(
'
\n
'
),
output_comments
=
output_comments
,
args
=
args
,
...
...
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