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Api conversions/zeropadding cropping (#5723)

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* Add ZeroPadding2/3D and Cropping2/3D API conversion interfaces.

* Add ZeroPadding2/3D and Cropping2/3D API conversion interfaces.
This commit is contained in:
Fred Schroeder 2017-03-11 18:43:31 -08:00 committed by François Chollet
parent 7696a13995
commit 84711475f8
3 changed files with 105 additions and 4 deletions
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4
keras/layers/convolutional.py
View File

@ -1289,6 +1289,7 @@ class ZeroPadding2D(Layer):
`(batch, channels, padded_rows, padded_cols)`
"""
@interfaces.legacy_zeropadding2d_support
def __init__(self,
padding=(1, 1),
data_format=None,
@ -1383,6 +1384,7 @@ class ZeroPadding3D(Layer):
`(batch, depth, first_padded_axis, second_padded_axis, third_axis_to_pad)`
"""
@interfaces.legacy_zeropadding3d_support
def __init__(self, padding=(1, 1, 1), data_format=None, **kwargs):
super(ZeroPadding3D, self).__init__(**kwargs)
self.data_format = conv_utils.normalize_data_format(data_format)
@ -1542,6 +1544,7 @@ class Cropping2D(Layer):
```
"""
@interfaces.legacy_cropping2d_support
def __init__(self, cropping=((0, 0), (0, 0)),
data_format=None, **kwargs):
super(Cropping2D, self).__init__(**kwargs)
@ -1669,6 +1672,7 @@ class Cropping3D(Layer):
`(batch, depth, first_cropped_axis, second_cropped_axis, third_cropped_axis)`
"""
@interfaces.legacy_cropping3d_support
def __init__(self, cropping=((1, 1), (1, 1), (1, 1)),
data_format=None, **kwargs):
super(Cropping3D, self).__init__(**kwargs)

58
keras/legacy/interfaces.py
View File

@ -406,7 +406,6 @@ def convlstm2d_args_preprocessor(args, kwargs):
args, kwargs, _converted = conv2d_args_preprocessor(args, kwargs)
return args, kwargs, converted + _converted
legacy_convlstm2d_support = generate_legacy_interface(
allowed_positional_args=['filters', 'kernel_size'],
conversions=[('nb_filter', 'filters'),
@ -427,9 +426,64 @@ legacy_convlstm2d_support = generate_legacy_interface(
'default': None}},
preprocessor=convlstm2d_args_preprocessor)
legacy_batchnorm_support = generate_legacy_interface(
allowed_positional_args=[],
conversions=[('beta_init', 'beta_initializer'),
('gamma_init', 'gamma_initializer')],
preprocessor=batchnorm_args_preprocessor)
def zeropadding2d_preprocessor(args, kwargs):
converted = []
if 'padding' in kwargs and isinstance(kwargs['padding'], dict):
if set(kwargs['padding'].keys()) <= {'top_pad', 'bottom_pad',
'left_pad', 'right_pad'}:
top_pad = kwargs['padding'].get('top_pad', 0)
bottom_pad = kwargs['padding'].get('bottom_pad', 0)
left_pad = kwargs['padding'].get('left_pad', 0)
right_pad = kwargs['padding'].get('right_pad', 0)
kwargs['padding'] = ((top_pad, bottom_pad), (left_pad, right_pad))
warnings.warn('The `padding` argument in the Keras 2 API no longer'
'accepts dict types. You can now input argument as: '
'`padding`=(top_pad, bottom_pad, left_pad, right_pad)')
elif len(args) == 2 and isinstance(args[1], dict):
if set(args[1].keys()) <= {'top_pad', 'bottom_pad',
'left_pad', 'right_pad'}:
top_pad = args[1].get('top_pad', 0)
bottom_pad = args[1].get('bottom_pad', 0)
left_pad = args[1].get('left_pad', 0)
right_pad = args[1].get('right_pad', 0)
args = (args[0], ((top_pad, bottom_pad), (left_pad, right_pad)))
warnings.warn('The `padding` argument in the Keras 2 API no longer'
'accepts dict types. You can now input argument as: '
'`padding`=((top_pad, bottom_pad), (left_pad, right_pad))')
return args, kwargs, converted
legacy_zeropadding2d_support = generate_legacy_interface(
allowed_positional_args=['padding'],
conversions=[('dim_ordering', 'data_format')],
value_conversions={'dim_ordering': {'tf': 'channels_last',
'th': 'channels_first',
'default': None}},
preprocessor=zeropadding2d_preprocessor)
legacy_zeropadding3d_support = generate_legacy_interface(
allowed_positional_args=['padding'],
conversions=[('dim_ordering', 'data_format')],
value_conversions={'dim_ordering': {'tf': 'channels_last',
'th': 'channels_first',
'default': None}})
legacy_cropping2d_support = generate_legacy_interface(
allowed_positional_args=['cropping'],
conversions=[('dim_ordering', 'data_format')],
value_conversions={'dim_ordering': {'tf': 'channels_last',
'th': 'channels_first',
'default': None}})
legacy_cropping3d_support = generate_legacy_interface(
allowed_positional_args=['cropping'],
conversions=[('dim_ordering', 'data_format')],
value_conversions={'dim_ordering': {'tf': 'channels_last',
'th': 'channels_first',
'default': None}})

47
tests/keras/legacy/interface_test.py
View File

@ -388,8 +388,12 @@ def test_upsampling2d_legacy_interface():
@keras_test
def test_upsampling3d_legacy_interface():
old_layer = keras.layers.UpSampling3D((2, 2, 2), dim_ordering='tf', name='us3d')
new_layer = keras.layers.UpSampling3D((2, 2, 2), data_format='channels_last', name='us3d')
old_layer = keras.layers.UpSampling3D((2, 2, 2),
dim_ordering='tf',
name='us3d')
new_layer = keras.layers.UpSampling3D((2, 2, 2),
data_format='channels_last',
name='us3d')
assert json.dumps(old_layer.get_config()) == json.dumps(new_layer.get_config())
@ -706,5 +710,44 @@ def test_atrousconv2d_legacy_interface():
assert json.dumps(old_layer.get_config()) == json.dumps(new_layer.get_config())
@keras_test
def test_zeropadding2d_legacy_interface():
old_layer = keras.layers.ZeroPadding2D(padding={'right_pad': 4,
'bottom_pad': 2,
'top_pad': 1,
'left_pad': 3},
dim_ordering='tf',
name='zp2d')
new_layer = keras.layers.ZeroPadding2D(((1, 2), (3, 4)),
data_format='channels_last',
name='zp2d')
assert json.dumps(old_layer.get_config()) == json.dumps(new_layer.get_config())
@keras_test
def test_zeropadding3d_legacy_interface():
old_layer = keras.layers.ZeroPadding3D((2, 2, 2),
dim_ordering='tf',
name='zp3d')
new_layer = keras.layers.ZeroPadding3D((2, 2, 2),
data_format='channels_last',
name='zp3d')
assert json.dumps(old_layer.get_config()) == json.dumps(new_layer.get_config())
@keras_test
def test_cropping2d_legacy_interface():
old_layer = keras.layers.Cropping2D(dim_ordering='tf', name='c2d')
new_layer = keras.layers.Cropping2D(data_format='channels_last', name='c2d')
assert json.dumps(old_layer.get_config()) == json.dumps(new_layer.get_config())
@keras_test
def test_cropping3d_legacy_interface():
old_layer = keras.layers.Cropping3D(dim_ordering='tf', name='c3d')
new_layer = keras.layers.Cropping3D(data_format='channels_last', name='c3d')
assert json.dumps(old_layer.get_config()) == json.dumps(new_layer.get_config())
if __name__ == '__main__':
pytest.main([__file__])