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Padding style fixes.

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This commit is contained in:
fchollet 2016-10-12 18:02:39 -07:00
parent 169c0896d6
commit 5dd8c5c10c
2 changed files with 39 additions and 26 deletions
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51
keras/layers/convolutional.py
View File

@ -1412,14 +1412,15 @@ class ZeroPadding1D(Layer):
'''Zero-padding layer for 1D input (e.g. temporal sequence).
# Arguments
padding: int or tuple of int (length 2) or dictionary
For symmetric padding: int
padding: int, or tuple of int (length 2), or dictionary.
- If int:
How many zeros to add at the beginning and end of
the padding dimension (axis 1).
For asymmetric padding: tuple of int (length 2)
- If tuple of int (length 2)
How many zeros to add at the beginning and at the end of
the padding dimension '(left_pad, right_pad)' or
'{'left_pad': left_pad, 'right_pad': right_pad}'.
the padding dimension, in order '(left_pad, right_pad)'.
- If dictionary: should contain the keys
{'left_pad', 'right_pad'}.
If any key is missing, default value of 0 will be used for the missing key.
# Input shape
@ -1436,15 +1437,21 @@ class ZeroPadding1D(Layer):
if isinstance(padding, int):
self.left_pad = padding
self.right_pad = padding
elif isinstance(padding, dict):
if set(padding.keys()) <= {'left_pad', 'right_pad'}:
self.left_pad = padding.get('left_pad', 0)
self.right_pad = padding.get('right_pad', 0)
else:
raise ValueError('Unexpected key is found in the padding argument. '
'Keys have to be in {"left_pad", "right_pad"}')
raise ValueError('Unexpected key found in `padding` dictionary. '
'Keys have to be in {"left_pad", "right_pad"}. '
'Found: ' + str(padding.keys()))
else:
padding = tuple(padding)
if len(padding) != 2:
raise ValueError('`padding` should be int, or dict with keys '
'{"left_pad", "right_pad"}, or tuple of length 2. '
'Found: ' + str(padding))
self.left_pad = padding[0]
self.right_pad = padding[1]
self.input_spec = [InputSpec(ndim=3)]
@ -1468,15 +1475,16 @@ class ZeroPadding2D(Layer):
'''Zero-padding layer for 2D input (e.g. picture).
# Arguments
padding: tuple of int (length 2) or tuple of int (length 4) or dictionary
For symmetric padding tuple of int (length 2)
padding: tuple of int (length 2), or tuple of int (length 4), or dictionary.
- If tuple of int (length 2):
How many zeros to add at the beginning and end of
the 2 padding dimensions (rows and cols).
For asymmetric padding tuple of int (length 4)
- If tuple of int (length 4):
How many zeros to add at the beginning and at the end of
the 2 padding dimensions (rows and cols).
'(top_pad, bottom_pad, left_pad, right_pad)' or
'{'top_pad': top_pad, 'bottom_pad': bottom_pad, 'left_pad': left_pad, 'right_pad': right_pad}'
the 2 padding dimensions (rows and cols), in the order
'(top_pad, bottom_pad, left_pad, right_pad)'.
- If dictionary: should contain the keys
{'top_pad', 'bottom_pad', 'left_pad', 'right_pad'}.
If any key is missing, default value of 0 will be used for the missing key.
dim_ordering: 'th' or 'tf'.
In 'th' mode, the channels dimension (the depth)
@ -1507,16 +1515,18 @@ class ZeroPadding2D(Layer):
dim_ordering = K.image_dim_ordering()
self.padding = padding
try:
if isinstance(padding, dict):
if set(padding.keys()) <= {'top_pad', 'bottom_pad', 'left_pad', 'right_pad'}:
self.top_pad = padding.get('top_pad', 0)
self.bottom_pad = padding.get('bottom_pad', 0)
self.left_pad = padding.get('left_pad', 0)
self.right_pad = padding.get('right_pad', 0)
else:
raise ValueError('Unexpected key is found in the padding argument. '
'Keys have to be in {"top_pad", "bottom_pad", "left_pad", "right_pad"}')
except AttributeError:
raise ValueError('Unexpected key found in `padding` dictionary. '
'Keys have to be in {"top_pad", "bottom_pad", '
'"left_pad", "right_pad"}.'
'Found: ' + str(padding.keys()))
else:
padding = tuple(padding)
if len(padding) == 2:
self.top_pad = padding[0]
@ -1529,9 +1539,11 @@ class ZeroPadding2D(Layer):
self.left_pad = padding[2]
self.right_pad = padding[3]
else:
raise TypeError('padding should be tuple of int of length 2 or 4, or dict')
raise TypeError('`padding` should be tuple of int '
'of length 2 or 4, or dict. '
'Found: ' + str(padding))
assert dim_ordering in {'tf', 'th'}, 'dim_ordering must be in {tf, th}'
assert dim_ordering in {'tf', 'th'}, '`dim_ordering` must be in {"tf", "th"}.'
self.dim_ordering = dim_ordering
self.input_spec = [InputSpec(ndim=4)]
@ -1574,6 +1586,7 @@ class ZeroPadding3D(Layer):
padding: tuple of int (length 3)
How many zeros to add at the beginning and end of
the 3 padding dimensions (axis 3, 4 and 5).
Currentl only symmetric padding is supported.
dim_ordering: 'th' or 'tf'.
In 'th' mode, the channels dimension (the depth)
is at index 1, in 'tf' mode is it at index 4.

14
tests/keras/layers/test_convolutional.py
View File

@ -381,7 +381,7 @@ def test_averagepooling_3d():
def test_zero_padding_1d():
nb_samples = 2
input_dim = 2
nb_steps = 11
nb_steps = 5
input = np.ones((nb_samples, nb_steps, input_dim))
# basic test
@ -420,8 +420,8 @@ def test_zero_padding_1d():
def test_zero_padding_2d():
nb_samples = 2
stack_size = 2
input_nb_row = 11
input_nb_col = 12
input_nb_row = 4
input_nb_col = 5
dim_ordering = K.image_dim_ordering()
assert dim_ordering in {'tf', 'th'}, 'dim_ordering must be in {tf, th}'
@ -487,9 +487,9 @@ def test_zero_padding_2d():
def test_zero_padding_3d():
nb_samples = 2
stack_size = 2
input_len_dim1 = 10
input_len_dim2 = 11
input_len_dim3 = 12
input_len_dim1 = 4
input_len_dim2 = 5
input_len_dim3 = 3
input = np.ones((nb_samples,
input_len_dim1, input_len_dim2, input_len_dim3,
@ -608,7 +608,7 @@ def test_upsampling_3d():
@keras_test
def test_cropping_1d():
nb_samples = 2
time_length = 10
time_length = 4
input_len_dim1 = 2
input = np.random.rand(nb_samples, time_length, input_len_dim1)