# -*- coding: utf-8 -*-
from .core import *
[docs]class ExpandDimsLayer(Layer):
"""
The :class:`ExpandDimsLayer` class inserts a dimension of 1 into a tensor's shape,
see `tf.expand_dims() <https://www.tensorflow.org/api_docs/python/array_ops/shapes_and_shaping#expand_dims>`__ .
Parameters
----------
layer : :class:`Layer`
The previous layer.
axis : int
The dimension index at which to expand the shape of input.
name : str
A unique layer name.
Examples
--------
>>> x = tf.placeholder(tf.float32, (None, 100))
>>> n = tl.layers.InputLayer(x, name='in')
>>> n = tl.layers.ExpandDimsLayer(n, 2)
... [None, 100, 1]
"""
def __init__(
self,
prev_layer,
axis,
name='expand_dims',
):
Layer.__init__(self, prev_layer=prev_layer, name=name)
self.inputs = prev_layer.outputs
logging.info("ExpandDimsLayer %s: axis:%d" % (self.name, axis))
with tf.variable_scope(name):
try: # TF12 TF1.0
self.outputs = tf.expand_dims(self.inputs, axis=axis)
except Exception: # TF11
self.outputs = tf.expand_dims(self.inputs, dim=axis)
# self.all_layers = list(layer.all_layers)
self.all_params = list(prev_layer.all_params)
self.all_drop = dict(prev_layer.all_drop)
self.all_layers.append(self.outputs)
# self.all_params.extend( variables )
[docs]class TileLayer(Layer):
"""
The :class:`TileLayer` class constructs a tensor by tiling a given tensor,
see `tf.tile() <https://www.tensorflow.org/api_docs/python/array_ops/slicing_and_joining#tile>`__ .
Parameters
----------
layer : :class:`Layer`
The previous layer.
multiples: tensor
Must be one of the following types: int32, int64.
1-D Length must be the same as the number of dimensions in input.
name : str
A unique layer name.
Examples
--------
>>> x = tf.placeholder(tf.float32, (None, 100))
>>> n = tl.layers.InputLayer(x, name='in')
>>> n = tl.layers.ExpandDimsLayer(n, 2)
>>> n = tl.layers.TileLayer(n, [-1, 1, 3])
... [None, 100, 3]
"""
def __init__(
self,
prev_layer=None,
multiples=None,
name='tile',
):
Layer.__init__(self, prev_layer=prev_layer, name=name)
self.inputs = prev_layer.outputs
logging.info("TileLayer %s: multiples:%s" % (self.name, multiples))
with tf.variable_scope(name):
self.outputs = tf.tile(self.inputs, multiples=multiples)
# self.all_layers = list(layer.all_layers)
# self.all_params = list(layer.all_params)
# self.all_drop = dict(layer.all_drop)
self.all_layers.append(self.outputs)
# self.all_params.extend( variables )