diff --git a/src/model_modules/advanced_paddings.py b/src/model_modules/advanced_paddings.py
index 1d48dfc0a87c05183fc5b8b7755f48efaf7b5428..c24085ffae1939b8bc95eae0e500ef2d07f917ad 100644
--- a/src/model_modules/advanced_paddings.py
+++ b/src/model_modules/advanced_paddings.py
@@ -6,6 +6,7 @@ import numpy as np
import keras.backend as K
from keras.layers.convolutional import _ZeroPadding
+from keras.layers import ZeroPadding2D
from keras.legacy import interfaces
from keras.utils import conv_utils
from keras.utils.generic_utils import transpose_shape
@@ -109,6 +110,42 @@ class PadUtils:
return normalized_padding
+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.
+ '''
+ def __init__(self, padding_type):
+ self.padding_type = padding_type
+ self.allowed_paddings = {
+ 'RefPad2D': ReflectionPadding2D, 'ReflectionPadding2D': ReflectionPadding2D,
+ 'SymPad2D': SymmetricPadding2D, 'SymmetricPadding2D': SymmetricPadding2D,
+ 'ZeroPad2D': ZeroPadding2D, 'ZeroPadding2D': ZeroPadding2D
+ }
+
+ def _check_and_get_padding(self):
+ if isinstance(self.padding_type, str):
+ try:
+ pad2d = self.allowed_paddings[self.padding_type]
+ except KeyError as einfo:
+ raise NotImplementedError(
+ f"`{einfo}' is not implemented as padding. "
+ "Use one of those: i) `RefPad2D', ii) `SymPad2D', iii) `ZeroPad2D'")
+ else:
+ if self.padding_type in self.allowed_paddings.values():
+ pad2d = self.padding_type
+ else:
+ raise TypeError(f"`{self.padding_type.__name__}' is not a valid padding layer type. "
+ "Use one of those: "
+ "i) ReflectionPadding2D, ii) SymmetricPadding2D, iii) ZeroPadding2D")
+ return pad2d
+
+ def __call__(self, *args, **kwargs):
+ return self._check_and_get_padding()(*args, **kwargs)
+
+
+
+
class ReflectionPadding2D(_ZeroPadding):
"""
Reflection padding layer for 2D input. This custum padding layer is built on keras' zero padding layers. Doc is copy
@@ -258,6 +295,7 @@ if __name__ == '__main__':
kernel_1 = (3, 3)
kernel_2 = (5, 5)
+ kernel_3 = (3,3)
x = np.array(range(2000)).reshape(-1, 10, 10, 1)
y = x.mean(axis=(1, 2))
@@ -269,6 +307,10 @@ if __name__ == '__main__':
pad2 = PadUtils.get_padding_for_same(kernel_size=kernel_2)
x_out = SymmetricPadding2D(padding=pad2, name="SymPAD")(x_out)
x_out = Conv2D(2, kernel_size=kernel_2, activation='relu')(x_out)
+
+ pad3 = PadUtils.get_padding_for_same(kernel_size=kernel_3)
+ x_out = Padding2D('RefPad2D')(padding=pad3, name="Padding2D_RefPad")(x_out)
+ x_out = Conv2D(2, kernel_size=kernel_3, activation='relu')(x_out)
x_out = Flatten()(x_out)
x_out = Dense(1, activation='linear')(x_out)
diff --git a/src/model_modules/inception_model.py b/src/model_modules/inception_model.py
index 1cb7656335495f0261abb434e4a203cb4e63887e..6467b3245ad097af6ef17e596f85264eef383d7a 100644
--- a/src/model_modules/inception_model.py
+++ b/src/model_modules/inception_model.py
@@ -5,7 +5,7 @@ import logging
import keras
import keras.layers as layers
-from src.model_modules.advanced_paddings import PadUtils, ReflectionPadding2D, SymmetricPadding2D
+from src.model_modules.advanced_paddings import PadUtils, ReflectionPadding2D, SymmetricPadding2D, Padding2D
class InceptionModelBase:
@@ -75,7 +75,10 @@ class InceptionModelBase:
name=f'Block_{self.number_of_blocks}{self.block_part_name()}_1x1')(input_x)
tower = self.act(tower, activation, **act_settings)
- tower = self.padding_layer(padding)(padding=padding_size,
+ # tower = self.padding_layer(padding)(padding=padding_size,
+ # name=f'Block_{self.number_of_blocks}{self.block_part_name()}_Pad'
+ # )(tower)
+ tower = Padding2D(padding)(padding=padding_size,
name=f'Block_{self.number_of_blocks}{self.block_part_name()}_Pad'
)(tower)
@@ -108,28 +111,28 @@ class InceptionModelBase:
else:
return act_name.__name__
- @staticmethod
- def padding_layer(padding):
- allowed_paddings = {
- 'RefPad2D': ReflectionPadding2D, 'ReflectionPadding2D': ReflectionPadding2D,
- 'SymPad2D': SymmetricPadding2D, 'SymmetricPadding2D': SymmetricPadding2D,
- 'ZeroPad2D': keras.layers.ZeroPadding2D, 'ZeroPadding2D': keras.layers.ZeroPadding2D
- }
- if isinstance(padding, str):
- try:
- pad2d = allowed_paddings[padding]
- except KeyError as einfo:
- raise NotImplementedError(
- f"`{einfo}' is not implemented as padding. "
- "Use one of those: i) `RefPad2D', ii) `SymPad2D', iii) `ZeroPad2D'")
- else:
- if padding in allowed_paddings.values():
- pad2d = padding
- else:
- raise TypeError(f"`{padding.__name__}' is not a valid padding layer type. "
- "Use one of those: "
- "i) ReflectionPadding2D, ii) SymmetricPadding2D, iii) ZeroPadding2D")
- return pad2d
+ # @staticmethod
+ # def padding_layer(padding):
+ # allowed_paddings = {
+ # 'RefPad2D': ReflectionPadding2D, 'ReflectionPadding2D': ReflectionPadding2D,
+ # 'SymPad2D': SymmetricPadding2D, 'SymmetricPadding2D': SymmetricPadding2D,
+ # 'ZeroPad2D': keras.layers.ZeroPadding2D, 'ZeroPadding2D': keras.layers.ZeroPadding2D
+ # }
+ # if isinstance(padding, str):
+ # try:
+ # pad2d = allowed_paddings[padding]
+ # except KeyError as einfo:
+ # raise NotImplementedError(
+ # f"`{einfo}' is not implemented as padding. "
+ # "Use one of those: i) `RefPad2D', ii) `SymPad2D', iii) `ZeroPad2D'")
+ # else:
+ # if padding in allowed_paddings.values():
+ # pad2d = padding
+ # else:
+ # raise TypeError(f"`{padding.__name__}' is not a valid padding layer type. "
+ # "Use one of those: "
+ # "i) ReflectionPadding2D, ii) SymmetricPadding2D, iii) ZeroPadding2D")
+ # return pad2d
def create_pool_tower(self, input_x, pool_kernel, tower_filter, activation='relu', max_pooling=True, **kwargs):
"""
@@ -156,7 +159,8 @@ class InceptionModelBase:
block_type = "AvgPool"
pooling = layers.AveragePooling2D
- tower = self.padding_layer(padding)(padding=padding_size, name=block_name+'Pad')(input_x)
+ # tower = self.padding_layer(padding)(padding=padding_size, name=block_name+'Pad')(input_x)
+ tower = Padding2D(padding)(padding=padding_size, name=block_name+'Pad')(input_x)
tower = pooling(pool_kernel, strides=(1, 1), padding='valid', name=block_name+block_type)(tower)
# convolution block
@@ -262,7 +266,7 @@ if __name__ == '__main__':
'padding': 'SymPad2D'},
'tower_3': {'reduction_filter': 64,
'tower_filter': 64,
- 'tower_kernel': (1, 1),
+ 'tower_kernel': (7, 7),
'activation': ELU,
'padding': ReflectionPadding2D}
}
diff --git a/src/model_modules/model_class.py b/src/model_modules/model_class.py
index 84f98690754a5d21a579270f4357636db692747d..7796ea4fbb529d4eaaa819f28804b034db596dfd 100644
--- a/src/model_modules/model_class.py
+++ b/src/model_modules/model_class.py
@@ -10,7 +10,7 @@ from typing import Any, Callable
import keras
from src.model_modules.inception_model import InceptionModelBase
from src.model_modules.flatten import flatten_tail
-import src.model_modules.advanced_paddings as adv_pad
+from src.model_modules.advanced_paddings import PadUtils, Padding2D
class AbstractModelClass(ABC):
@@ -443,10 +443,10 @@ class MyPaperModel(AbstractModelClass):
X_input = keras.layers.Input(
shape=(self.window_history_size + 1, 1, self.channels)) # add 1 to window_size to include current time step t0
- pad_size = adv_pad.PadUtils.get_padding_for_same(first_kernel)
+ pad_size = PadUtils.get_padding_for_same(first_kernel)
# X_in = adv_pad.SymmetricPadding2D(padding=pad_size)(X_input)
# X_in = inception_model.padding_layer("SymPad2D")(padding=pad_size, name="SymPad")(X_input) # adv_pad.SymmetricPadding2D(padding=pad_size)(X_input)
- X_in = inception_model.padding_layer("SymPad2D")(padding=pad_size, name="SymPad")(X_input)
+ X_in = Padding2D("SymPad2D")(padding=pad_size, name="SymPad")(X_input)
X_in = keras.layers.Conv2D(filters=first_filters,
kernel_size=first_kernel,
kernel_regularizer=self.regularizer,
diff --git a/test/test_model_modules/test_advanced_paddings.py b/test/test_model_modules/test_advanced_paddings.py
index 5282eb6df34d4d395dbbdd1fd76fd71a95e9c8df..bbeaf1c745a63b3607062b0c4052088c9af06b92 100644
--- a/test/test_model_modules/test_advanced_paddings.py
+++ b/test/test_model_modules/test_advanced_paddings.py
@@ -417,3 +417,61 @@ class TestSymmerticPadding2D:
sym_pad = SymmetricPadding2D(padding=pad, name=layer_name)(input_x)
assert sym_pad.get_shape().as_list() == [None, 12, 10, 3]
assert sym_pad.name == 'SymPad_3x1/MirrorPad:0'
+
+
+class TestPadding2D:
+
+ @pytest.fixture
+ def input_x(self):
+ return keras.Input(shape=(32, 32, 3))
+
+ def test_init(self):
+ padding_layer = Padding2D('SymPad2D')
+ assert padding_layer.padding_type == 'SymPad2D'
+ assert padding_layer.allowed_paddings == {
+ 'RefPad2D': ReflectionPadding2D, 'ReflectionPadding2D': ReflectionPadding2D,
+ 'SymPad2D': SymmetricPadding2D, 'SymmetricPadding2D': SymmetricPadding2D,
+ 'ZeroPad2D': ZeroPadding2D, 'ZeroPadding2D': ZeroPadding2D
+ }
+
+
+ def test_check_and_get_padding_zero_padding(self):
+ assert Padding2D('ZeroPad2D')._check_and_get_padding() == ZeroPadding2D
+ assert Padding2D('ZeroPadding2D')._check_and_get_padding() == ZeroPadding2D
+ assert Padding2D(keras.layers.ZeroPadding2D)._check_and_get_padding() == ZeroPadding2D
+
+ def test_check_and_get_padding_sym_padding(self):
+ assert Padding2D('SymPad2D')._check_and_get_padding() == SymmetricPadding2D
+ assert Padding2D('SymmetricPadding2D')._check_and_get_padding() == SymmetricPadding2D
+ assert Padding2D(SymmetricPadding2D)._check_and_get_padding() == SymmetricPadding2D
+
+ def test_check_and_get_padding_ref_padding(self):
+ assert Padding2D('RefPad2D')._check_and_get_padding() == ReflectionPadding2D
+ assert Padding2D('ReflectionPadding2D')._check_and_get_padding() == ReflectionPadding2D
+ assert Padding2D(ReflectionPadding2D)._check_and_get_padding() == ReflectionPadding2D
+
+ def test_check_and_get_padding_raises(self,):
+ with pytest.raises(NotImplementedError) as einfo:
+ Padding2D('FalsePadding2D')._check_and_get_padding()
+ assert "`'FalsePadding2D'' is not implemented as padding. " \
+ "Use one of those: i) `RefPad2D', ii) `SymPad2D', iii) `ZeroPad2D'" in str(einfo.value)
+ with pytest.raises(TypeError) as einfo:
+ Padding2D(keras.layers.Conv2D)._check_and_get_padding()
+ assert "`Conv2D' is not a valid padding layer type. Use one of those: "\
+ "i) ReflectionPadding2D, ii) SymmetricPadding2D, iii) ZeroPadding2D" in str(einfo.value)
+
+ @pytest.mark.parametrize("pad_type", ["SymPad2D", "SymmetricPadding2D", SymmetricPadding2D,
+ "RefPad2D", "ReflectionPadding2D", ReflectionPadding2D,
+ "ZeroPad2D", "ZeroPadding2D", ZeroPadding2D])
+ def test_call(self, pad_type, input_x):
+ pd = Padding2D(pad_type)
+ if hasattr(pad_type, "__name__"):
+ layer_name = pad_type.__name__
+ else:
+ layer_name = pad_type
+ pd_ap = pd(padding=(1,2), name=f"{layer_name}_layer")(input_x)
+ assert pd_ap._keras_history[0].input_shape == (None, 32, 32, 3)
+ assert pd_ap._keras_history[0].output_shape == (None, 34, 36, 3)
+ assert pd_ap._keras_history[0].padding == ((1, 1), (2, 2))
+ assert pd_ap._keras_history[0].name == f"{layer_name}_layer"
+
diff --git a/test/test_model_modules/test_inception_model.py b/test/test_model_modules/test_inception_model.py
index 9dee30788c34cd8d1a7572947ea2e568ac2006b7..e5e92158425a73c5af1c6d1623d970e1037bbd80 100644
--- a/test/test_model_modules/test_inception_model.py
+++ b/test/test_model_modules/test_inception_model.py
@@ -277,48 +277,3 @@ class TestInceptionModelBase:
bn = base.batch_normalisation(input_x)._keras_history[0]
assert isinstance(bn, keras.layers.normalization.BatchNormalization)
assert bn.name == "Block_0a_BN"
-
- def test_padding_layer_zero_padding(self, base, input_x):
- padding_size = ((1, 1), (0, 0))
- zp = base.padding_layer('ZeroPad2D')
- assert zp == keras.layers.convolutional.ZeroPadding2D
- assert base.padding_layer('ZeroPadding2D') == keras.layers.convolutional.ZeroPadding2D
- assert base.padding_layer(keras.layers.ZeroPadding2D) == keras.layers.convolutional.ZeroPadding2D
- assert zp.__name__ == 'ZeroPadding2D'
- zp_ap = zp(padding=padding_size)(input_x)
- assert zp_ap._keras_history[0].padding == ((1, 1), (0, 0))
-
- def test_padding_layer_sym_padding(self, base, input_x):
- padding_size = ((1, 1), (0, 0))
- zp = base.padding_layer('SymPad2D')
- assert zp == SymmetricPadding2D
- assert base.padding_layer('SymmetricPadding2D') == SymmetricPadding2D
- assert base.padding_layer(SymmetricPadding2D) == SymmetricPadding2D
- assert zp.__name__ == 'SymmetricPadding2D'
- zp_ap = zp(padding=padding_size)(input_x)
- assert zp_ap._keras_history[0].padding == ((1, 1), (0, 0))
-
- def test_padding_layer_ref_padding(self, base, input_x):
- padding_size = ((1, 1), (0, 0))
- zp = base.padding_layer('RefPad2D')
- assert zp == ReflectionPadding2D
- assert base.padding_layer('ReflectionPadding2D') == ReflectionPadding2D
- assert base.padding_layer(ReflectionPadding2D) == ReflectionPadding2D
- assert zp.__name__ == 'ReflectionPadding2D'
- zp_ap = zp(padding=padding_size)(input_x)
- assert zp_ap._keras_history[0].padding == ((1, 1), (0, 0))
-
- def test_padding_layer_raises(self, base, input_x):
- with pytest.raises(NotImplementedError) as einfo:
- base.padding_layer('FalsePadding2D')
- assert "`'FalsePadding2D'' is not implemented as padding. " \
- "Use one of those: i) `RefPad2D', ii) `SymPad2D', iii) `ZeroPad2D'" in str(einfo.value)
- with pytest.raises(TypeError) as einfo:
- base.padding_layer(keras.layers.Conv2D)
- assert "`Conv2D' is not a valid padding layer type. Use one of those: "\
- "i) ReflectionPadding2D, ii) SymmetricPadding2D, iii) ZeroPadding2D" in str(einfo.value)
-
-
-
-
-