Merge pull request #439 from tensorlayer/globalpool3d

release globalpool3d layers

Author: wagamamaz

docs/modules/layers.rst

@@ -279,6 +279,8 @@ Layer list
    GlobalMeanPool1d
    GlobalMaxPool2d
    GlobalMeanPool2d
+   GlobalMaxPool3d
+   GlobalMeanPool3d
 
    SubpixelConv1d
    SubpixelConv2d
@@ -603,6 +605,14 @@ Pooling layer for any dimensions and any pooling functions.
 ^^^^^^^^^^^^^^^^^^^^^^^^^^
 .. autoclass:: GlobalMeanPool2d
 
+3D Global Max pooling
+^^^^^^^^^^^^^^^^^^^^^^^^^^
+.. autoclass:: GlobalMaxPool3d
+
+3D Global Mean pooling
+^^^^^^^^^^^^^^^^^^^^^^^^^^
+.. autoclass:: GlobalMeanPool3d
+
 
 Normalization layer
 --------------------

tensorlayer/layers/padding.py

@@ -137,92 +137,3 @@ def __init__(
         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)
-
-
-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)
-
-
-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)
-
-
-class ZeroPad3d(Layer):
-    """
-    The :class:`ZeroPad3d` class is a 3D padding layer for volume [batch, height, width, depth, 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)