Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
未来在这儿
X2Paddle
提交
a6235569
X
X2Paddle
项目概览
未来在这儿
/
X2Paddle
与 Fork 源项目一致
Fork自
PaddlePaddle / X2Paddle
通知
1
Star
1
Fork
0
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
0
列表
看板
标记
里程碑
合并请求
0
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
X
X2Paddle
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
0
Issue
0
列表
看板
标记
里程碑
合并请求
0
合并请求
0
Pages
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
提交
Issue看板
体验新版 GitCode,发现更多精彩内容 >>
提交
a6235569
编写于
7月 14, 2020
作者:
M
mamingjie-China
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
support for bert
上级
3be647ed
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
169 addition
and
8 deletion
+169
-8
x2paddle/core/op_mapper.py
x2paddle/core/op_mapper.py
+37
-1
x2paddle/decoder/tf_decoder.py
x2paddle/decoder/tf_decoder.py
+17
-4
x2paddle/op_mapper/tf_op_mapper_nhwc.py
x2paddle/op_mapper/tf_op_mapper_nhwc.py
+115
-3
未找到文件。
x2paddle/core/op_mapper.py
浏览文件 @
a6235569
...
...
@@ -55,6 +55,24 @@ def export_paddle_param(param, param_name, dir):
def
run_net
(
param_dir
=
"./"
):
import
os
inputs
,
outputs
=
x2paddle_net
()
ops
=
fluid
.
default_main_program
().
global_block
().
ops
used_vars
=
list
()
for
op
in
ops
:
used_vars
+=
op
.
input_arg_names
tmp
=
list
()
for
input
in
inputs
:
if
isinstance
(
input
,
list
):
for
ipt
in
input
:
if
ipt
.
name
not
in
used_vars
:
continue
tmp
.
append
(
ipt
)
else
:
if
input
.
name
not
in
used_vars
:
continue
tmp
.
append
(
input
)
inputs
=
tmp
for
i
,
out
in
enumerate
(
outputs
):
if
isinstance
(
out
,
list
):
for
out_part
in
out
:
...
...
@@ -122,12 +140,30 @@ class OpMapper(object):
import
model
try
:
inputs
,
outputs
=
model
.
x2paddle_net
()
ops
=
fluid
.
default_main_program
().
global_block
().
ops
used_vars
=
list
()
for
op
in
ops
:
used_vars
+=
op
.
input_arg_names
for
i
,
out
in
enumerate
(
outputs
):
if
isinstance
(
out
,
list
):
for
out_part
in
out
:
outputs
.
append
(
out_part
)
del
outputs
[
i
]
input_names
=
[
input
.
name
for
input
in
inputs
]
input_names
=
list
()
for
input
in
inputs
:
if
isinstance
(
input
,
list
):
for
ipt
in
input
:
if
ipt
.
name
not
in
used_vars
:
continue
input_names
.
append
(
ipt
.
name
)
else
:
if
input
.
name
not
in
used_vars
:
continue
input_names
.
append
(
input
.
name
)
exe
=
fluid
.
Executor
(
fluid
.
CPUPlace
())
exe
.
run
(
fluid
.
default_startup_program
())
...
...
x2paddle/decoder/tf_decoder.py
浏览文件 @
a6235569
...
...
@@ -48,7 +48,7 @@ class TFGraphNode(GraphNode):
@
property
def
out_shapes
(
self
):
if
self
.
layer_type
==
"OneShotIterator"
:
if
self
.
layer_type
==
"OneShotIterator"
or
self
.
layer_type
==
"IteratorV2"
:
values
=
self
.
layer
.
attr
[
"output_shapes"
].
list
.
shape
else
:
values
=
self
.
layer
.
attr
[
"_output_shapes"
].
list
.
shape
...
...
@@ -68,7 +68,8 @@ class TFGraphNode(GraphNode):
if
dtype
==
0
:
dtype
=
self
.
layer
.
attr
[
'output_types'
].
list
.
type
[
0
]
if
dtype
not
in
self
.
dtype_map
:
raise
Exception
(
"Dtype[{}] not in dtype_map"
.
format
(
dtype
))
raise
Exception
(
"Dtype[{}] of node({}) not in dtype_map"
.
format
(
dtype
,
self
.
layer
.
name
))
return
self
.
dtype_map
[
dtype
]
@
property
...
...
@@ -114,16 +115,20 @@ class TFGraph(Graph):
def
__init__
(
self
,
model
,
data_format
=
"NHWC"
):
super
(
TFGraph
,
self
).
__init__
(
model
)
self
.
identity_map
=
dict
()
self
.
multi_out_ops
=
[
'Split'
,
'SplitV'
]
self
.
multi_out_ops
=
[
'Split'
,
'SplitV'
,
'IteratorV2'
]
self
.
tf_data_format
=
data_format
def
build
(
self
):
for
layer
in
self
.
model
.
node
:
if
layer
.
op
==
'Assert'
:
continue
self
.
node_map
[
layer
.
name
.
replace
(
'/'
,
'_'
).
replace
(
'-'
,
'_'
)]
=
TFGraphNode
(
layer
,
data_format
=
self
.
tf_data_format
)
for
layer_name
,
node
in
self
.
node_map
.
items
():
if
node
.
layer_type
==
'Const'
:
continue
for
in_node
in
node
.
layer
.
input
:
in_node
=
in_node
.
replace
(
'/'
,
'_'
).
replace
(
'-'
,
'_'
).
replace
(
'^'
,
''
)
...
...
@@ -139,6 +144,14 @@ class TFGraph(Graph):
super
(
TFGraph
,
self
).
build
()
for
layer
in
self
.
model
.
node
:
if
layer
.
op
==
'Assert'
:
for
ipt
in
layer
.
input
:
ipt_name
=
ipt
.
replace
(
'-'
,
'_'
).
replace
(
'/'
,
'_'
)
if
ipt_name
in
self
.
output_nodes
:
idx
=
self
.
output_nodes
.
index
(
ipt_name
)
del
self
.
output_nodes
[
idx
]
# tensorflow graph optimize
self
.
_remove_isolated_node
()
self
.
_optimize_dialiation_conv
()
...
...
@@ -322,7 +335,7 @@ class TFDecoder(object):
graph_def
=
cp
.
deepcopy
(
graph_def
)
input_map
=
dict
()
for
layer
in
graph_def
.
node
:
if
layer
.
op
!=
"Placeholder"
and
layer
.
op
!=
"OneShotIterator"
:
if
layer
.
op
!=
"Placeholder"
and
layer
.
op
!=
"OneShotIterator"
and
layer
.
op
!=
"IteratorV2"
:
continue
graph_node
=
TFGraphNode
(
layer
)
dtype
=
graph_node
.
layer
.
attr
[
'dtype'
].
type
...
...
x2paddle/op_mapper/tf_op_mapper_nhwc.py
浏览文件 @
a6235569
...
...
@@ -15,6 +15,7 @@
from
x2paddle.decoder.tf_decoder
import
TFGraph
from
x2paddle.core.op_mapper
import
OpMapper
from
x2paddle.core.util
import
*
import
math
import
inspect
import
numpy
import
sys
...
...
@@ -47,7 +48,8 @@ class TFOpMapperNHWC(OpMapper):
'LeakyRelu'
:
[
'leaky_relu'
,
{
'alpha'
:
'alpha'
}],
'Floor'
:
[
'floor'
]
'Floor'
:
[
'floor'
],
'Erf'
:
[
'erf'
]
}
elementwise_ops
=
{
'Add'
:
'elementwise_add'
,
...
...
@@ -56,6 +58,7 @@ class TFOpMapperNHWC(OpMapper):
'Sub'
:
'elementwise_sub'
,
'Maximum'
:
'elementwise_max'
,
'Minimum'
:
'elementwise_min'
,
'LessEqual'
:
'less_equal'
,
'Mul'
:
'elementwise_mul'
,
'FloorDiv'
:
'elementwise_floordiv'
}
...
...
@@ -71,7 +74,11 @@ class TFOpMapperNHWC(OpMapper):
not_placeholder
=
list
()
for
name
in
self
.
graph
.
input_nodes
:
if
self
.
graph
.
get_node
(
name
).
layer_type
!=
"Placeholder"
:
if
self
.
graph
.
get_node
(
name
).
layer_type
!=
"Placeholder"
and
self
.
graph
.
get_node
(
name
).
layer_type
!=
"OneShotIterator"
and
self
.
graph
.
get_node
(
name
).
layer_type
!=
"IteratorV2"
:
not_placeholder
.
append
(
name
)
for
name
in
not_placeholder
:
idx
=
self
.
graph
.
input_nodes
.
index
(
name
)
...
...
@@ -81,6 +88,7 @@ class TFOpMapperNHWC(OpMapper):
sys
.
stderr
.
write
(
"Total nodes: {}
\n
"
.
format
(
len
(
self
.
graph
.
topo_sort
)))
for
i
,
node_name
in
enumerate
(
self
.
graph
.
topo_sort
):
sys
.
stderr
.
write
(
"
\r
Converting node {} ... "
.
format
(
i
+
1
))
# sys.stderr.write("\rConverting node {} name: {:50}... ".format(i + 1, node_name))
node
=
self
.
graph
.
get_node
(
node_name
)
op
=
node
.
layer_type
if
op
in
self
.
directly_map_ops
:
...
...
@@ -631,10 +639,20 @@ class TFOpMapperNHWC(OpMapper):
attr
=
{
"shape"
:
shape
}
node
.
fluid_code
.
add_layer
(
"reshape"
,
inputs
=
x
,
output
=
x
,
param_attr
=
attr
)
if
transpose_a
is
None
:
transpose_a
=
node
.
get_attr
(
'adj_x'
)
if
transpose_b
is
None
:
transpose_b
=
node
.
get_attr
(
'adj_y'
)
attr
=
{
"transpose_x"
:
transpose_a
,
"transpose_y"
:
transpose_b
}
node
.
fluid_code
.
add_layer
(
"matmul"
,
inputs
=
inputs
,
output
=
node
,
param_attr
=
attr
)
def
BatchMatMul
(
self
,
node
):
return
self
.
MatMul
(
node
)
def
BatchMatMulV2
(
self
,
node
):
return
self
.
MatMul
(
node
)
def
ArgMax
(
self
,
node
):
input
=
self
.
graph
.
get_node
(
node
.
layer
.
input
[
0
],
copy
=
True
)
axis
=
self
.
graph
.
get_node
(
node
.
layer
.
input
[
1
],
copy
=
True
)
...
...
@@ -957,7 +975,9 @@ class TFOpMapperNHWC(OpMapper):
if
y
.
layer_type
==
'Const'
:
self
.
add_omit_nodes
(
y
.
layer_name
,
node
.
layer_name
)
dim
=
y
.
value
.
tolist
()
attr
=
{
'axes'
:
[
dim
]}
if
not
isinstance
(
dim
,
list
):
dim
=
[
dim
]
attr
=
{
'axes'
:
dim
}
else
:
attr
=
{
'axes'
:
y
}
node
.
fluid_code
.
add_layer
(
...
...
@@ -980,3 +1000,95 @@ class TFOpMapperNHWC(OpMapper):
"="
,
inputs
=
x
,
output
=
node
,
param_attr
=
None
)
else
:
raise
Exception
(
"SpaceToBatchND is not supported"
)
def
OneHot
(
self
,
node
):
input
=
self
.
graph
.
get_node
(
node
.
layer
.
input
[
0
],
copy
=
True
)
depth
=
self
.
graph
.
get_node
(
node
.
layer
.
input
[
1
],
copy
=
True
)
on_value
=
self
.
graph
.
get_node
(
node
.
layer
.
input
[
2
],
copy
=
True
)
off_value
=
self
.
graph
.
get_node
(
node
.
layer
.
input
[
3
],
copy
=
True
)
assert
depth
.
layer_type
==
'Const'
,
'Parameter depth should be Const in OneHot'
assert
on_value
.
layer_type
==
'Const'
,
'Parameter on_value should be Const in OneHot'
assert
off_value
.
layer_type
==
'Const'
,
'Parameter off_value should be Const in OneHot'
self
.
add_omit_nodes
(
depth
.
layer_name
,
node
.
layer_name
)
self
.
add_omit_nodes
(
on_value
.
layer_name
,
node
.
layer_name
)
self
.
add_omit_nodes
(
off_value
.
layer_name
,
node
.
layer_name
)
depth
=
depth
.
value
on_value
=
on_value
.
value
off_value
=
off_value
.
value
assert
math
.
fabs
(
on_value
-
1.0
)
<
1e-06
,
"on_value should be 1 in OneHot"
assert
math
.
fabs
(
off_value
-
0.0
)
<
1e-06
,
"off_value should be 0 in OneHot"
attr
=
{
'depth'
:
depth
}
node
.
fluid_code
.
add_layer
(
"one_hot"
,
inputs
=
input
,
output
=
node
,
param_attr
=
attr
,
use_fluid
=
True
)
def
Pow
(
self
,
node
):
x
=
self
.
graph
.
get_node
(
node
.
layer
.
input
[
0
],
copy
=
True
)
factor
=
self
.
graph
.
get_node
(
node
.
layer
.
input
[
1
],
copy
=
True
)
self
.
add_omit_nodes
(
factor
.
layer_name
,
node
.
layer_name
)
if
factor
.
layer_type
==
'Const'
:
factor
=
factor
.
value
.
tolist
()
else
:
factor
=
self
.
decoder
.
infer_tensor
(
factor
)
attr
=
{
'factor'
:
factor
}
node
.
fluid_code
.
add_layer
(
"pow"
,
inputs
=
x
,
output
=
node
,
param_attr
=
attr
)
def
All
(
self
,
node
):
input
=
self
.
graph
.
get_node
(
node
.
layer
.
input
[
0
],
copy
=
True
)
reduce_idx
=
self
.
graph
.
get_node
(
node
.
layer
.
input
[
1
],
copy
=
True
)
self
.
add_omit_nodes
(
reduce_idx
.
layer_name
,
node
.
layer_name
)
assert
reduce_idx
.
layer_type
==
"Const"
,
"Only support Const parameter[reduce_idx]"
dims
=
reduce_idx
.
value
.
tolist
()
keep_dims
=
node
.
get_attr
(
"keep_dims"
)
attr
=
{
"dim"
:
dims
,
"keep_dim"
:
keep_dims
}
node
.
fluid_code
.
add_layer
(
"reduce_all"
,
inputs
=
input
,
output
=
node
,
param_attr
=
attr
)
def
GatherV2
(
self
,
node
):
embeddings
=
self
.
graph
.
get_node
(
node
.
layer
.
input
[
0
],
copy
=
True
)
index
=
self
.
graph
.
get_node
(
node
.
layer
.
input
[
1
],
copy
=
True
)
axis
=
self
.
graph
.
get_node
(
node
.
layer
.
input
[
2
],
copy
=
True
)
self
.
add_omit_nodes
(
axis
.
layer_name
,
node
.
layer_name
)
assert
axis
.
layer_type
==
'Const'
,
"Only support Const parameter[axis]"
axis
=
axis
.
value
.
tolist
()
assert
axis
==
0
,
"Only support axis=0 in GatherV2 OP"
attr
=
{
'overwrite'
:
False
}
if
len
(
index
.
out_shapes
[
0
])
!=
1
:
reshape_attr
=
{
"shape"
:
[
-
1
]}
node
.
fluid_code
.
add_layer
(
"reshape"
,
inputs
=
index
,
output
=
index
,
param_attr
=
reshape_attr
)
inputs
=
{
'input'
:
embeddings
,
'index'
:
index
}
node
.
fluid_code
.
add_layer
(
"gather"
,
inputs
=
inputs
,
output
=
node
,
param_attr
=
attr
)
def
OneShotIterator
(
self
,
node
):
return
self
.
Placeholder
(
node
)
def
IteratorV2
(
self
,
node
):
dtype_map
=
{
1
:
"float32"
,
3
:
"int32"
,
4
:
"uint8"
,
9
:
"int64"
,
10
:
"bool"
}
shapes
=
node
.
out_shapes
dtypes
=
node
.
layer
.
attr
[
'output_types'
].
list
.
type
node
.
fluid_code
.
add_note
(
"{} = [0] * {}"
.
format
(
node
.
layer_name
,
len
(
shapes
)))
for
i
,
shape
in
enumerate
(
shapes
):
attr
=
{
'dtype'
:
string
(
dtype_map
[
dtypes
[
i
]]),
'shape'
:
shape
,
'name'
:
string
(
"{}_{}"
.
format
(
node
.
layer_name
,
i
)),
'append_batch_size'
:
False
}
output
=
"{}[{}]"
.
format
(
node
.
layer_name
,
i
)
node
.
fluid_code
.
add_layer
(
"data"
,
inputs
=
None
,
output
=
output
,
param_attr
=
attr
)
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录