From 2404827cb49812c13c9b340a5e5640ddd2e80366 Mon Sep 17 00:00:00 2001
From: Felix Kleinert <f.kleinert@fz-juelich.de>
Date: Tue, 3 Mar 2020 10:46:36 +0100
Subject: [PATCH] update raise conditions for invalid data formats
---
src/model_modules/advanced_paddings.py | 23 ++++++++++++++++++++---
1 file changed, 20 insertions(+), 3 deletions(-)
diff --git a/src/model_modules/advanced_paddings.py b/src/model_modules/advanced_paddings.py
index f5a386fb..6450752a 100644
--- a/src/model_modules/advanced_paddings.py
+++ b/src/model_modules/advanced_paddings.py
@@ -27,7 +27,11 @@ class PadUtils:
"""
if strides != 1:
raise NotImplementedError("Strides other than 1 not implemented!")
+ if not all(isinstance(k, int) for k in kernel_size):
+ raise ValueError(f"The `kernel_size` argument must have a tuple of integers. Got: {kernel_size}")
+
ks = np.array(kernel_size, dtype=np.int64)
+
if any(k <= 0 for k in ks):
raise ValueError(f"All values of kernel_size must be > 0. Got: {kernel_size} ")
@@ -36,8 +40,9 @@ class PadUtils:
# convert numpy int to base int
pad = [np.asscalar(v) for v in pad]
return tuple(pad)
+ # return tuple(PadUtils.check_padding_format(pad))
else:
- raise NotImplementedError("even kernel size not implemented")
+ raise NotImplementedError(f"even kernel size not implemented. Got {kernel_size}")
@staticmethod
def spatial_2d_padding(padding=((1, 1), (1, 1)), data_format=None):
@@ -74,6 +79,16 @@ class PadUtils:
if len(padding) != 2:
raise ValueError('`padding` should have two elements. '
'Found: ' + str(padding))
+ for idx_pad, sub_pad in enumerate(padding):
+ if isinstance(sub_pad, str):
+ raise ValueError(f'`padding[{idx_pad}]` is str but must be int')
+ if hasattr(sub_pad, '__len__'):
+ if len(sub_pad) != 2:
+ raise ValueError(f'`padding[{idx_pad}]` should have one or two elements. '
+ f'Found: {padding[idx_pad]}')
+ if not all(isinstance(sub_k, int) for sub_k in padding[idx_pad]):
+ raise ValueError(f'`padding[{idx_pad}]` should have one or two elements of type int. '
+ f"Found:{padding[idx_pad]} of type {[type(sub_k) for sub_k in padding[idx_pad]]}")
height_padding = conv_utils.normalize_tuple(padding[0], 2,
'1st entry of padding')
if not all(k >= 0 for k in height_padding):
@@ -239,17 +254,18 @@ class SymmetricPadding2D(_ZeroPadding):
if __name__ == '__main__':
from keras.models import Model
from keras.layers import Conv2D, Flatten, Dense, Input
+
kernel_1 = (3, 3)
kernel_2 = (5, 5)
x = np.array(range(2000)).reshape(-1, 10, 10, 1)
y = x.mean(axis=(1, 2))
x_input = Input(shape=x.shape[1:])
- pad1 = PadUtils.get_padding_for_same(kernel_1)
+ pad1 = PadUtils.get_padding_for_same(kernel_size=kernel_1)
x_out = ReflectionPadding2D(padding=pad1, name="RefPAD")(x_input)
x_out = Conv2D(5, kernel_size=kernel_1, activation='relu')(x_out)
- pad2 = PadUtils.get_padding_for_same(kernel_2)
+ 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)
x_out = Flatten()(x_out)
@@ -258,5 +274,6 @@ if __name__ == '__main__':
model = Model(inputs=x_input, outputs=x_out)
model.compile('adam', loss='mse')
model.summary()
+ model.fit(x, y, epochs=10)
--
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