forked from TensorLayer/tensorlayer3
239 lines
7.0 KiB
Python
239 lines
7.0 KiB
Python
#! /usr/bin/python
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# -*- coding: utf-8 -*-
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import tensorlayer as tl
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from tensorlayer import logging
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from tensorlayer.layers.core import Module
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__all__ = [
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'PadLayer',
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'ZeroPad1d',
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'ZeroPad2d',
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'ZeroPad3d',
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]
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class PadLayer(Module):
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"""The :class:`PadLayer` class is a padding layer for any mode and dimension.
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Please see `tf.pad <https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/pad>`__ for usage.
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Parameters
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----------
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padding : list of lists of 2 ints, or a Tensor of type int32.
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The int32 values to pad.
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mode : str
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"CONSTANT", "REFLECT", or "SYMMETRIC" (case-insensitive).
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name : None or str
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A unique layer name.
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Examples
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--------
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With TensorLayer
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>>> net = tl.layers.Input([10, 224, 224, 3], name='input')
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>>> padlayer = tl.layers.PadLayer([[0, 0], [3, 3], [3, 3], [0, 0]], "REFLECT", name='inpad')(net)
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>>> print(padlayer)
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>>> output shape : (10, 230, 230, 3)
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"""
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def __init__(
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self,
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padding=None,
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mode='CONSTANT',
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constant_values=0,
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name=None, # 'pad_layer',
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):
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super().__init__(name)
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self.padding = padding
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self.mode = mode
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self.constant_values = constant_values
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logging.info("PadLayer %s: padding: %s mode: %s" % (self.name, self.padding, self.mode))
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if self.padding is None:
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raise Exception(
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"padding should be a Tensor of type int32. see https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/pad"
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)
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self.build()
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self._built = True
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def __repr__(self):
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s = '{classname}(padding={padding}, mode={mode}'
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if self.name is not None:
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s += ', name=\'{name}\''
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s += ')'
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return s.format(classname=self.__class__.__name__, **self.__dict__)
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def build(self, inputs_shape=None):
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self.pad = tl.ops.Pad(paddings=self.padding, mode=self.mode, constant_values=self.constant_values)
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def forward(self, inputs):
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outputs = self.pad(inputs)
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return outputs
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class ZeroPad1d(Module):
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"""
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The :class:`ZeroPad1d` class is a 1D padding layer for signal [batch, length, channel].
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Parameters
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----------
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padding : int, or tuple of 2 ints
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- If int, zeros to add at the beginning and end of the padding dimension (axis 1).
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- If tuple of 2 ints, zeros to add at the beginning and at the end of the padding dimension.
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name : None or str
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A unique layer name.
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Examples
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--------
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With TensorLayer
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>>> net = tl.layers.Input([10, 100, 1], name='input')
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>>> pad1d = tl.layers.ZeroPad1d(padding=(3, 3))(net)
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>>> print(pad1d)
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>>> output shape : (10, 106, 1)
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"""
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def __init__(
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self,
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padding,
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name=None, # 'zeropad1d',
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):
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super().__init__(name)
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self.padding = padding
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logging.info("ZeroPad1d %s: padding: %s" % (self.name, str(padding)))
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if not isinstance(self.padding, (int, tuple, dict)):
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raise AssertionError()
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self.build()
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self._built = True
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def __repr__(self):
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s = '{classname}(padding={padding}'
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if self.name is not None:
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s += ', name=\'{name}\''
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s += ')'
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return s.format(classname=self.__class__.__name__, **self.__dict__)
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def build(self, inputs_shape=None):
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self.layer = tl.ops.ZeroPadding1D(padding=self.padding)
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def forward(self, inputs):
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outputs = self.layer(inputs)
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return outputs
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class ZeroPad2d(Module):
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"""
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The :class:`ZeroPad2d` class is a 2D padding layer for image [batch, height, width, channel].
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Parameters
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----------
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padding : tuple of 2 ints or int, or tuple of 2 tuples of 2 ints.
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- If int, the same symmetric padding is applied to width and height.
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- If tuple of 2 ints, interpreted as two different symmetric padding values for height and width as ``(symmetric_height_pad, symmetric_width_pad)``.
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- If tuple of 2 tuples of 2 ints, interpreted as ``((top_pad, bottom_pad), (left_pad, right_pad))``.
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name : None or str
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A unique layer name.
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Examples
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--------
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With TensorLayer
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>>> net = tl.layers.Input([10, 100, 100, 3], name='input')
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>>> pad2d = tl.layers.ZeroPad2d(padding=((3, 3), (4, 4)))(net)
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>>> print(pad2d)
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>>> output shape : (10, 106, 108, 3)
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"""
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def __init__(
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self,
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padding,
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name=None, # 'zeropad2d',
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):
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super().__init__(name)
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self.padding = padding
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logging.info("ZeroPad2d %s: padding: %s" % (self.name, str(self.padding)))
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if not isinstance(self.padding, (int, tuple)):
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raise AssertionError("Padding should be of type `int` or `tuple`")
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self.build()
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self._built = True
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def __repr__(self):
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s = '{classname}(padding={padding}'
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if self.name is not None:
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s += ', name=\'{name}\''
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s += ')'
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return s.format(classname=self.__class__.__name__, **self.__dict__)
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def build(self, inputs_shape=None):
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self.layer = tl.ops.ZeroPadding2D(padding=self.padding)
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def forward(self, inputs):
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outputs = self.layer(inputs)
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return outputs
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class ZeroPad3d(Module):
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"""
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The :class:`ZeroPad3d` class is a 3D padding layer for volume [batch, depth, height, width, channel].
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Parameters
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----------
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padding : int, or tuple of 2 ints, or tuple of 2 tuples of 2 ints.
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- If int, the same symmetric padding is applied to width and height.
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- 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)``.
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- If tuple of 2 tuples of 2 ints, interpreted as
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``((left_dim1_pad, right_dim1_pad), (left_dim2_pad, right_dim2_pad), (left_dim3_pad, right_dim3_pad))``.
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name : None or str
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A unique layer name.
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Examples
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--------
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With TensorLayer
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>>> net = tl.layers.Input([10, 100, 100, 100, 3], name='input')
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>>> pad3d = tl.layers.ZeroPad3d(padding=((3, 3), (4, 4), (5, 5)))(net)
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>>> print(pad3d)
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>>> output shape : (10, 106, 108, 110, 3)
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"""
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def __init__(
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self,
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padding,
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name=None, # 'zeropad3d',
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):
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super().__init__(name)
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self.padding = padding
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logging.info("ZeroPad3d %s: padding: %s" % (self.name, str(self.padding)))
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if not isinstance(self.padding, (int, tuple)):
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raise AssertionError()
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self.build()
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self._built = True
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def __repr__(self):
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s = '{classname}(padding={padding}'
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if self.name is not None:
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s += ', name=\'{name}\''
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s += ')'
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return s.format(classname=self.__class__.__name__, **self.__dict__)
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def build(self, inputs_shape=None):
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self.layer = tl.ops.ZeroPadding3D(padding=self.padding)
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def forward(self, inputs):
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outputs = self.layer(inputs)
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return outputs
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