# -*- coding: utf-8 -*-
import tensorflow as tf
from .. import _logging as logging
from .core import *
__all__ = [
'PadLayer',
'ZeroPad1d',
'ZeroPad2d',
'ZeroPad3d',
]
[docs]class PadLayer(Layer):
"""The :class:`PadLayer` class is a padding layer for any mode and dimension.
Please see `tf.pad <https://www.tensorflow.org/api_docs/python/tf/pad>`__ for usage.
Parameters
----------
layer : :class:`Layer`
The previous layer.
padding : list of lists of 2 ints, or a Tensor of type int32.
The int32 values to pad.
mode : str
"CONSTANT", "REFLECT", or "SYMMETRIC" (case-insensitive).
name : str
A unique layer name.
Examples
--------
>>> net = InputLayer(image, name='in')
>>> net = PadLayer(net, [[0, 0], [3, 3], [3, 3], [0, 0]], "REFLECT", name='inpad')
"""
def __init__(
self,
prev_layer,
padding=None,
mode='CONSTANT',
name='pad_layer',
):
Layer.__init__(self, prev_layer=prev_layer, name=name)
if padding is None:
raise Exception("padding should be a Tensor of type int32. see https://www.tensorflow.org/api_docs/python/tf/pad")
self.inputs = prev_layer.outputs
logging.info("PadLayer %s: padding:%s mode:%s" % (self.name, list(padding), mode))
self.outputs = tf.pad(self.inputs, paddings=padding, mode=mode, name=name)
self.all_layers.append(self.outputs)
[docs]class ZeroPad1d(Layer):
"""
The :class:`ZeroPad1d` class is a 1D padding layer for signal [batch, length, channel].
Parameters
----------
layer : :class:`Layer`
The previous layer.
padding : int, or tuple of 2 ints
- If int, zeros to add at the beginning and end of the padding dimension (axis 1).
- If tuple of 2 ints, zeros to add at the beginning and at the end of the padding dimension.
name : str
A unique layer name.
"""
def __init__(
self,
prev_layer,
padding,
name='zeropad1d',
):
Layer.__init__(self, prev_layer=prev_layer, name=name)
self.inputs = prev_layer.outputs
logging.info("ZeroPad1d %s: padding:%s" % (self.name, str(padding)))
self.outputs = tf.keras.layers.ZeroPadding1D(padding=padding, name=name)(self.inputs)
self.all_layers.append(self.outputs)
[docs]class ZeroPad2d(Layer):
"""
The :class:`ZeroPad2d` class is a 2D padding layer for image [batch, height, width, channel].
Parameters
----------
layer : :class:`Layer`
The previous layer.
padding : int, or tuple of 2 ints, or tuple of 2 tuples of 2 ints.
- If int, the same symmetric padding is applied to width and height.
- If tuple of 2 ints, interpreted as two different symmetric padding values for height and width as ``(symmetric_height_pad, symmetric_width_pad)``.
- If tuple of 2 tuples of 2 ints, interpreted as ``((top_pad, bottom_pad), (left_pad, right_pad))``.
name : str
A unique layer name.
"""
def __init__(
self,
prev_layer,
padding,
name='zeropad2d',
):
Layer.__init__(self, prev_layer=prev_layer, name=name)
self.inputs = prev_layer.outputs
logging.info("ZeroPad2d %s: padding:%s" % (self.name, str(padding)))
self.outputs = tf.keras.layers.ZeroPadding2D(padding=padding, name=name)(self.inputs)
self.all_layers.append(self.outputs)
[docs]class ZeroPad3d(Layer):
"""
The :class:`ZeroPad3d` class is a 3D padding layer for volume [batch, depth, height, width, channel].
Parameters
----------
layer : :class:`Layer`
The previous layer.
padding : int, or tuple of 2 ints, or tuple of 2 tuples of 2 ints.
- If int, the same symmetric padding is applied to width and height.
- If tuple of 2 ints, interpreted as two different symmetric padding values for height and width as ``(symmetric_dim1_pad, symmetric_dim2_pad, symmetric_dim3_pad)``.
- If tuple of 2 tuples of 2 ints, interpreted as ``((left_dim1_pad, right_dim1_pad), (left_dim2_pad, right_dim2_pad), (left_dim3_pad, right_dim3_pad))``.
name : str
A unique layer name.
"""
def __init__(
self,
prev_layer,
padding,
name='zeropad3d',
):
Layer.__init__(self, prev_layer=prev_layer, name=name)
self.inputs = prev_layer.outputs
logging.info("ZeroPad3d %s: padding:%s" % (self.name, str(padding)))
self.outputs = tf.keras.layers.ZeroPadding3D(padding=padding, name=name)(self.inputs)
self.all_layers.append(self.outputs)