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machine-learning
MLAir
Commits
a4644e7a
Commit
a4644e7a
authored
5 years ago
by
lukas leufen
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docs for paddings, updated docs requirements
parent
1bf8d5d6
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!125
Release v0.10.0
,
!124
Update Master to new version v0.10.0
,
!91
WIP: Resolve "create sphinx docu"
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#35385
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5 years ago
Stage: test
Stage: docs
Stage: pages
Stage: deploy
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docs/requirements_docs.txt
+3
-2
3 additions, 2 deletions
docs/requirements_docs.txt
src/model_modules/advanced_paddings.py
+63
-34
63 additions, 34 deletions
src/model_modules/advanced_paddings.py
with
66 additions
and
36 deletions
docs/requirements_docs.txt
+
3
−
2
View file @
a4644e7a
sphinx==3.0.
1
sphinx==3.0.
3
sphinx-autoapi==1.3.0
sphinx-rtd-theme==0.4.3
recommonmark==0.6.0
sphinx-autodoc-typehints==1.10.3
\ No newline at end of file
This diff is collapsed.
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src/model_modules/advanced_paddings.py
+
63
−
34
View file @
a4644e7a
"""
Collection of customised padding layers.
"""
__author__
=
'
Felix Kleinert
'
__date__
=
'
2020-03-02
'
import
tensorflow
as
tf
import
numpy
as
np
import
keras.backend
as
K
from
keras.layers.convolutional
import
_ZeroPadding
from
typing
import
Union
,
Tuple
import
numpy
as
np
import
tensorflow
as
tf
from
keras.backend.common
import
normalize_data_format
from
keras.layers
import
ZeroPadding2D
from
keras.layers.convolutional
import
_ZeroPadding
from
keras.legacy
import
interfaces
from
keras.utils
import
conv_utils
from
keras.utils.generic_utils
import
transpose_shape
from
keras.backend.common
import
normalize_data_format
class
PadUtils
:
"""
Helper class for advanced paddings
"""
"""
Helper class for advanced padding.
"""
@staticmethod
def
get_padding_for_same
(
kernel_size
,
strides
=
1
)
:
def
get_padding_for_same
(
kernel_size
:
Tuple
[
int
],
strides
:
int
=
1
)
->
Tuple
[
int
]
:
"""
This methods calculates the padding size to keep input and output dimensions equal for a given kernel size
(STRIDES HAVE TO BE EQUAL TO ONE!)
:param kernel_size:
:return:
Calculate padding size to keep input and output dimensions equal for a given kernel size.
.. hint:: custom paddings are currently only implemented for strides = 1
:param kernel_size: size of padding kernel size
:param strides: number of strides (default 1, currently only strides=1 supported)
:return: padding size
"""
if
strides
!=
1
:
raise
NotImplementedError
(
"
Strides other than 1 not implemented!
"
)
...
...
@@ -40,15 +45,15 @@ class PadUtils:
if
all
(
k
%
2
==
1
for
k
in
ks
):
# (d & 0x1 for d in ks):
pad
=
((
ks
-
1
)
/
2
).
astype
(
np
.
int64
)
# convert numpy int to base int
pad
=
[
np
.
asscalar
(
v
)
for
v
in
pad
]
pad
=
[
int
(
v
.
item
()
)
for
v
in
pad
]
return
tuple
(
pad
)
# return tuple(PadUtils.check_padding_format(pad))
else
:
raise
NotImplementedError
(
f
"
even kernel size not implemented. Got
{
kernel_size
}
"
)
@staticmethod
def
spatial_2d_padding
(
padding
=
((
1
,
1
),
(
1
,
1
)),
data_format
=
None
):
"""
Pads the 2nd and 3rd dimensions of a 4D tensor.
"""
Pad the 2nd and 3rd dimensions of a 4D tensor.
# Arguments
x: Tensor or variable.
...
...
@@ -75,6 +80,7 @@ class PadUtils:
@staticmethod
def
check_padding_format
(
padding
):
"""
Check padding format (int, 1D or 2D, >0).
"""
if
isinstance
(
padding
,
int
):
normalized_padding
=
((
padding
,
padding
),
(
padding
,
padding
))
elif
hasattr
(
padding
,
'
__len__
'
):
...
...
@@ -94,11 +100,13 @@ class PadUtils:
height_padding
=
conv_utils
.
normalize_tuple
(
padding
[
0
],
2
,
'
1st entry of padding
'
)
if
not
all
(
k
>=
0
for
k
in
height_padding
):
raise
ValueError
(
f
"
The `1st entry of padding` argument must be >= 0. Received:
{
padding
[
0
]
}
of type
{
type
(
padding
[
0
])
}
"
)
raise
ValueError
(
f
"
The `1st entry of padding` argument must be >= 0. Received:
{
padding
[
0
]
}
of type
{
type
(
padding
[
0
])
}
"
)
width_padding
=
conv_utils
.
normalize_tuple
(
padding
[
1
],
2
,
'
2nd entry of padding
'
)
if
not
all
(
k
>=
0
for
k
in
width_padding
):
raise
ValueError
(
f
"
The `2nd entry of padding` argument must be >= 0. Received:
{
padding
[
1
]
}
of type
{
type
(
padding
[
1
])
}
"
)
raise
ValueError
(
f
"
The `2nd entry of padding` argument must be >= 0. Received:
{
padding
[
1
]
}
of type
{
type
(
padding
[
1
])
}
"
)
normalized_padding
=
(
height_padding
,
width_padding
)
else
:
raise
ValueError
(
'
`padding` should be either an int,
'
...
...
@@ -112,9 +120,10 @@ class PadUtils:
class
ReflectionPadding2D
(
_ZeroPadding
):
"""
Reflection padding layer for 2D input. This custum padding layer is built on keras
'
zero padding layers. Doc is copy
pasted from the original functions/methods:
Reflection padding layer for 2D input.
This custom padding layer is built on keras
'
zero padding layers. Doc is copy and pasted from the original
functions/methods:
This layer can add rows and columns of reflected values
at the top, bottom, left and right side of an image like tensor.
...
...
@@ -129,7 +138,7 @@ class ReflectionPadding2D(_ZeroPadding):
'
# Arguments
# Arguments
padding: int, or tuple of 2 ints, or tuple of 2 tuples of 2 ints.
- If int: the same symmetric padding
is applied to height and width.
...
...
@@ -172,21 +181,24 @@ class ReflectionPadding2D(_ZeroPadding):
padding
=
(
1
,
1
),
data_format
=
None
,
**
kwargs
):
"""
Initialise ReflectionPadding2D.
"""
normalized_padding
=
PadUtils
.
check_padding_format
(
padding
=
padding
)
super
(
ReflectionPadding2D
,
self
).
__init__
(
normalized_padding
,
data_format
,
**
kwargs
)
def
call
(
self
,
inputs
,
mask
=
None
):
"""
Call ReflectionPadding2D.
"""
pattern
=
PadUtils
.
spatial_2d_padding
(
padding
=
self
.
padding
,
data_format
=
self
.
data_format
)
return
tf
.
pad
(
inputs
,
pattern
,
'
REFLECT
'
)
class
SymmetricPadding2D
(
_ZeroPadding
):
"""
Symmetric padding layer for 2D input. This custom padding layer is built on keras
'
zero padding layers. Doc is copy
pasted from the original functions/methods:
Symmetric padding layer for 2D input.
This custom padding layer is built on keras
'
zero padding layers. Doc is copy pasted from the original
functions/methods:
This layer can add rows and columns of symmetric values
at the top, bottom, left and right side of an image like tensor.
...
...
@@ -243,39 +255,57 @@ class SymmetricPadding2D(_ZeroPadding):
padding
=
(
1
,
1
),
data_format
=
None
,
**
kwargs
):
"""
Initialise SymmetricPadding2D.
"""
normalized_padding
=
PadUtils
.
check_padding_format
(
padding
=
padding
)
super
(
SymmetricPadding2D
,
self
).
__init__
(
normalized_padding
,
data_format
,
**
kwargs
)
def
call
(
self
,
inputs
,
mask
=
None
):
"""
Call SymmetricPadding2D.
"""
pattern
=
PadUtils
.
spatial_2d_padding
(
padding
=
self
.
padding
,
data_format
=
self
.
data_format
)
return
tf
.
pad
(
inputs
,
pattern
,
'
SYMMETRIC
'
)
class
Padding2D
:
'''
This class combines the implemented padding methods. You can call this method by defining a specific padding type.
The __call__ method will return the corresponding Padding layer.
'''
"""
Combine all implemented padding methods.
You can call this method by defining a specific padding type. The __call__ method will return the corresponding
Padding layer.
.. code-block:: python
input_x = ... # your input data
kernel_size = (5, 1)
padding_size = PadUtils.get_padding_for_same(kernel_size)
tower = layers.Conv2D(...)(input_x)
tower = layers.Activation(...)(tower)
tower = Padding2D(
'
ZeroPad2D
'
)(padding=padding_size, name=f
'
Custom_Pad
'
)(tower)
Padding type can either be set by a string or directly by using an instance of a valid padding class.
"""
allowed_paddings
=
{
**
dict
.
fromkeys
((
"
RefPad2D
"
,
"
ReflectionPadding2D
"
),
ReflectionPadding2D
),
**
dict
.
fromkeys
((
"
SymPad2D
"
,
"
SymmetricPadding2D
"
),
SymmetricPadding2D
),
**
dict
.
fromkeys
((
"
ZeroPad2D
"
,
"
ZeroPadding2D
"
),
ZeroPadding2D
)
}
padding_type
=
Union
[
ReflectionPadding2D
,
SymmetricPadding2D
,
ZeroPadding2D
]
def
__init__
(
self
,
padding_type
):
def
__init__
(
self
,
padding_type
:
Union
[
str
,
padding_type
]):
"""
Set padding type.
"""
self
.
padding_type
=
padding_type
def
_check_and_get_padding
(
self
):
if
isinstance
(
self
.
padding_type
,
str
):
try
:
pad2d
=
self
.
allowed_paddings
[
self
.
padding_type
]
except
KeyError
as
e
info
:
except
KeyError
as
e
:
raise
NotImplementedError
(
f
"
`
{
e
info
}
'
is not implemented as padding.
"
"
Use one of those: i) `RefPad2D
'
, ii) `SymPad2D
'
,
iii) `ZeroPad2D
'"
)
f
"
`
{
e
}
'
is not implemented as padding.
Use one of those: i) `RefPad2D
'
, ii) `SymPad2D
'
,
"
f
"
iii) `ZeroPad2D
'"
)
else
:
if
self
.
padding_type
in
self
.
allowed_paddings
.
values
():
pad2d
=
self
.
padding_type
...
...
@@ -286,6 +316,7 @@ class Padding2D:
return
pad2d
def
__call__
(
self
,
*
args
,
**
kwargs
):
"""
Call padding.
"""
return
self
.
_check_and_get_padding
()(
*
args
,
**
kwargs
)
...
...
@@ -318,5 +349,3 @@ if __name__ == '__main__':
model
.
compile
(
'
adam
'
,
loss
=
'
mse
'
)
model
.
summary
()
model
.
fit
(
x
,
y
,
epochs
=
10
)
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