update all pooling from function to class (#507)

* update all pooling from function to class

* fix codacy

Author: zsdonghao

docs/modules/layers.rst

@@ -571,19 +571,19 @@ Pooling layer for any dimensions and any pooling functions.
 
 1D Max pooling
 ^^^^^^^^^^^^^^^^^^^
-.. autofunction:: MaxPool1d
+.. autoclass:: MaxPool1d
 
 1D Mean pooling
 ^^^^^^^^^^^^^^^^^^^
-.. autofunction:: MeanPool1d
+.. autoclass:: MeanPool1d
 
 2D Max pooling
 ^^^^^^^^^^^^^^^^^^^
-.. autofunction:: MaxPool2d
+.. autoclass:: MaxPool2d
 
 2D Mean pooling
 ^^^^^^^^^^^^^^^^^^^
-.. autofunction:: MeanPool2d
+.. autoclass:: MeanPool2d
 
 3D Max pooling
 ^^^^^^^^^^^^^^^^^^^

tensorlayer/layers/pooling.py

@@ -70,13 +70,13 @@ def __init__(
         logging.info("PoolLayer   %s: ksize:%s strides:%s padding:%s pool:%s" % (name, str(ksize), str(strides), padding, pool.__name__))
 
         self.inputs = prev_layer.outputs
-
+        # operation (customized)
         self.outputs = pool(self.inputs, ksize=ksize, strides=strides, padding=padding, name=name)
+        # update layer (customized)
         self.all_layers.append(self.outputs)
 
 
-@deprecated_alias(net='prev_layer', end_support_version=1.9)  # TODO remove this line for the 1.9 release
-def maxpool1d(prev_layer, filter_size=3, strides=2, padding='valid', data_format='channels_last', name=None):
+class MaxPool1d(Layer):
     """Max pooling for 1D signal [batch, length, channel]. Wrapper for `tf.layers.max_pooling1d <https://www.tensorflow.org/api_docs/python/tf/layers/max_pooling1d>`__ .
 
     Parameters
@@ -97,23 +97,20 @@ def maxpool1d(prev_layer, filter_size=3, strides=2, padding='valid', data_format
     name : str
         A unique layer name.
 
-    Returns
-    -------
-    :class:`Layer`
-        A max pooling 1-D layer with a output rank as 3.
-
     """
-    logging.info("MaxPool1d %s: filter_size:%s strides:%s padding:%s" % (name, str(filter_size), str(strides), str(padding)))
-    outputs = tf.layers.max_pooling1d(prev_layer.outputs, filter_size, strides, padding=padding, data_format=data_format, name=name)
 
-    net_new = copy.copy(prev_layer)
-    net_new.outputs = outputs
-    net_new.all_layers.extend([outputs])
-    return net_new
+    @deprecated_alias(net='prev_layer', end_support_version=1.9)  # TODO remove this line for the 1.9 release
+    def __init__(self, prev_layer, filter_size=3, strides=2, padding='valid', data_format='channels_last', name='maxpool1d'):
+        super(MaxPool1d, self).__init__(prev_layer=prev_layer, name=name)
+        logging.info("MaxPool1d %s: filter_size:%s strides:%s padding:%s" % (name, str(filter_size), str(strides), str(padding)))
+        self.inputs = prev_layer.outputs
+        # operation (customized)
+        self.outputs = tf.layers.max_pooling1d(self.inputs, filter_size, strides, padding=padding, data_format=data_format, name=name)
+        # update layer (customized)
+        self.all_layers.append(self.outputs)
 
 
-@deprecated_alias(net='prev_layer', end_support_version=1.9)  # TODO remove this line for the 1.9 release
-def meanpool1d(prev_layer, filter_size=3, strides=2, padding='valid', data_format='channels_last', name=None):
+class MeanPool1d(Layer):
     """Mean pooling for 1D signal [batch, length, channel]. Wrapper for `tf.layers.average_pooling1d <https://www.tensorflow.org/api_docs/python/tf/layers/average_pooling1d>`__ .
 
     Parameters
@@ -134,24 +131,28 @@ def meanpool1d(prev_layer, filter_size=3, strides=2, padding='valid', data_forma
     name : str
         A unique layer name.
 
-    Returns
-    -------
-    :class:`Layer`
-        A mean pooling 1-D layer with a output rank as 3.
-
     """
-    logging.info("MeanPool1d %s: filter_size:%s strides:%s padding:%s" % (name, str(filter_size), str(strides), str(padding)))
-    outputs = tf.layers.average_pooling1d(prev_layer.outputs, filter_size, strides, padding=padding, data_format=data_format, name=name)
+    # logging.info("MeanPool1d %s: filter_size:%s strides:%s padding:%s" % (name, str(filter_size), str(strides), str(padding)))
+    # outputs = tf.layers.average_pooling1d(prev_layer.outputs, filter_size, strides, padding=padding, data_format=data_format, name=name)
+    #
+    # net_new = copy.copy(prev_layer)
+    # net_new.outputs = outputs
+    # net_new.all_layers.extend([outputs])
+    # return net_new
+    @deprecated_alias(net='prev_layer', end_support_version=1.9)  # TODO remove this line for the 1.9 release
+    def __init__(self, prev_layer, filter_size=3, strides=2, padding='valid', data_format='channels_last', name='meanpool1d'):
+        super(MeanPool1d, self).__init__(prev_layer=prev_layer, name=name)
+        logging.info("MeanPool1d %s: filter_size:%s strides:%s padding:%s" % (name, str(filter_size), str(strides), str(padding)))
 
-    net_new = copy.copy(prev_layer)
-    net_new.outputs = outputs
-    net_new.all_layers.extend([outputs])
-    return net_new
+        # operation (customized)
+        self.outputs = tf.layers.average_pooling1d(prev_layer.outputs, filter_size, strides, padding=padding, data_format=data_format, name=name)
+
+        # update layer (customized)
+        self.all_layers.append(self.outputs)
 
 
-@deprecated_alias(net='prev_layer', end_support_version=1.9)  # TODO remove this line for the 1.9 release
-def maxpool2d(prev_layer, filter_size=(3, 3), strides=(2, 2), padding='SAME', name='maxpool'):
-    """Max pooling for 2D image [batch, height, width, channel]. Wrapper for :class:`PoolLayer`.
+class MaxPool2d(Layer):
+    """Max pooling for 2D image [batch, height, width, channel].
 
     Parameters
     -----------
@@ -166,33 +167,31 @@ def maxpool2d(prev_layer, filter_size=(3, 3), strides=(2, 2), padding='SAME', na
     name : str
         A unique layer name.
 
-    Returns
-    -------
-    :class:`Layer`
-        A max pooling 2-D layer with a output rank as 4.
-
     """
-    if strides is None:
-        strides = filter_size
-    if tf.__version__ > '1.5':
-        outputs = tf.layers.max_pooling2d(prev_layer.outputs, filter_size, strides, padding=padding, data_format='channels_last', name=name)
-        net_new = copy.copy(prev_layer)
-        net_new.outputs = outputs
-        net_new.all_layers.extend([outputs])
-        return net_new
-    else:
 
-        assert len(strides) == 2, "len(strides) should be 2, MaxPool2d and PoolLayer are different."
+    @deprecated_alias(net='prev_layer', end_support_version=1.9)  # TODO remove this line for the 1.9 release
+    def __init__(self, prev_layer, filter_size=(3, 3), strides=(2, 2), padding='SAME', name='maxpool2d'):
+        if strides is None:
+            strides = filter_size
 
-        prev_layer = PoolLayer(
-            prev_layer, ksize=[1, filter_size[0], filter_size[1], 1], strides=[1, strides[0], strides[1], 1], padding=padding, pool=tf.nn.max_pool, name=name)
-
-        return prev_layer
+        super(MaxPool2d, self).__init__(prev_layer=prev_layer, name=name)
+        logging.info("MaxPool2d %s: filter_size:%s strides:%s padding:%s" % (name, str(filter_size), str(strides), str(padding)))
+        self.inputs = prev_layer.outputs
+        # operation (customized)
+        if tf.__version__ > '1.5':
+            self.outputs = tf.layers.max_pooling2d(self.inputs, filter_size, strides, padding=padding, data_format='channels_last', name=name)
+        else:
+            if len(strides) == 2:
+                raise Exception("len(strides) should be 2.")
+            ksize = [1, filter_size[0], filter_size[1], 1]
+            strides = [1, strides[0], strides[1], 1]
+            self.outputs = tf.nn.max_pool(self.inputs, ksize=ksize, strides=strides, padding=padding, name=name)
+        # update layer (customized)
+        self.all_layers.append(self.outputs)
 
 
-@deprecated_alias(net='prev_layer', end_support_version=1.9)  # TODO remove this line for the 1.9 release
-def meanpool2d(prev_layer, filter_size=(3, 3), strides=(2, 2), padding='SAME', name='meanpool'):
-    """Mean pooling for 2D image [batch, height, width, channel]. Wrapper for :class:`PoolLayer`.
+class MeanPool2d(Layer):
+    """Mean pooling for 2D image [batch, height, width, channel].
 
     Parameters
     -----------
@@ -207,27 +206,27 @@ def meanpool2d(prev_layer, filter_size=(3, 3), strides=(2, 2), padding='SAME', n
     name : str
         A unique layer name.
 
-    Returns
-    -------
-    :class:`Layer`
-        A mean pooling 2-D layer with a output rank as 4.
-
     """
-    if strides is None:
-        strides = filter_size
-    if tf.__version__ > '1.5':
-        outputs = tf.layers.average_pooling2d(prev_layer.outputs, filter_size, strides, padding=padding, data_format='channels_last', name=name)
-        net_new = copy.copy(prev_layer)
-        net_new.outputs = outputs
-        net_new.all_layers.extend([outputs])
-        return net_new
-    else:
 
-        assert len(strides) == 2, "len(strides) should be 2, MeanPool2d and PoolLayer are different."
+    @deprecated_alias(net='prev_layer', end_support_version=1.9)  # TODO remove this line for the 1.9 release
+    def __init__(self, prev_layer, filter_size=(3, 3), strides=(2, 2), padding='SAME', name='meanpool2d'):
+        if strides is None:
+            strides = filter_size
 
-        prev_layer = PoolLayer(
-            prev_layer, ksize=[1, filter_size[0], filter_size[1], 1], strides=[1, strides[0], strides[1], 1], padding=padding, pool=tf.nn.avg_pool, name=name)
-        return prev_layer
+        super(MeanPool2d, self).__init__(prev_layer=prev_layer, name=name)
+        logging.info("MeanPool2d %s: filter_size:%s strides:%s padding:%s" % (name, str(filter_size), str(strides), str(padding)))
+        self.inputs = prev_layer.outputs
+        # operation (customized)
+        if tf.__version__ > '1.5':
+            self.outputs = tf.layers.average_pooling2d(self.inputs, filter_size, strides, padding=padding, data_format='channels_last', name=name)
+        else:
+            if len(strides) == 2:
+                raise Exception("len(strides) should be 2.")
+            ksize = [1, filter_size[0], filter_size[1], 1]
+            strides = [1, strides[0], strides[1], 1]
+            self.outputs = tf.nn.avg_pool(self.inputs, ksize=ksize, strides=strides, padding=padding, name=name)
+        # update layer (customized)
+        self.all_layers.append(self.outputs)
 
 
 # def maxpool3d(net, filter_size=(3, 3, 3), strides=(2, 2, 2), padding='valid', data_format='channels_last', name='maxpool3d'):
@@ -261,13 +260,11 @@ class MaxPool3d(Layer):
 
     @deprecated_alias(layer='prev_layer', end_support_version=1.9)  # TODO remove this line for the 1.9 release
     def __init__(self, prev_layer, filter_size=(3, 3, 3), strides=(2, 2, 2), padding='valid', data_format='channels_last', name='maxpool3d'):
-
         super(MaxPool3d, self).__init__(prev_layer=prev_layer, name=name)
         logging.info("MaxPool3d %s: filter_size:%s strides:%s padding:%s" % (name, str(filter_size), str(strides), str(padding)))
-
+        # operation (customized)
         self.inputs = prev_layer.outputs
-
-        self.outputs = tf.layers.max_pooling3d(prev_layer.outputs, filter_size, strides, padding=padding, data_format=data_format, name=name)
+        self.outputs = tf.layers.max_pooling3d(self.inputs, filter_size, strides, padding=padding, data_format=data_format, name=name)
         # update layer (customized)
         self.all_layers.append(self.outputs)
 
@@ -338,12 +335,9 @@ class GlobalMaxPool1d(Layer):
     def __init__(self, prev_layer, name='globalmaxpool1d'):
         super(GlobalMaxPool1d, self).__init__(prev_layer=prev_layer, name=name)
         logging.info("GlobalMaxPool1d %s" % name)
-
         self.inputs = prev_layer.outputs
-
         # operation (customized)
-        self.outputs = tf.reduce_max(prev_layer.outputs, axis=1, name=name)
-
+        self.outputs = tf.reduce_max(self.inputs, axis=1, name=name)
         # update layer (customized)
         self.all_layers.append(self.outputs)
 
@@ -370,12 +364,9 @@ class GlobalMeanPool1d(Layer):
     def __init__(self, prev_layer, name='globalmeanpool1d'):
         super(GlobalMeanPool1d, self).__init__(prev_layer=prev_layer, name=name)
         logging.info("GlobalMeanPool1d %s" % name)
-
         self.inputs = prev_layer.outputs
-
         # operation (customized)
-        self.outputs = tf.reduce_mean(prev_layer.outputs, axis=1, name=name)
-
+        self.outputs = tf.reduce_mean(self.inputs, axis=1, name=name)
         # update layer (customized)
         self.all_layers.append(self.outputs)
 
@@ -402,12 +393,9 @@ class GlobalMaxPool2d(Layer):
     def __init__(self, prev_layer, name='globalmaxpool2d'):
         super(GlobalMaxPool2d, self).__init__(prev_layer=prev_layer, name=name)
         logging.info("GlobalMaxPool2d %s" % name)
-
         self.inputs = prev_layer.outputs
-
         # operation (customized)
-        self.outputs = tf.reduce_max(prev_layer.outputs, axis=[1, 2], name=name)
-
+        self.outputs = tf.reduce_max(self.inputs, axis=[1, 2], name=name)
         # update layer (customized)
         self.all_layers.append(self.outputs)
 
@@ -434,12 +422,9 @@ class GlobalMeanPool2d(Layer):
     def __init__(self, prev_layer, name='globalmeanpool2d'):
         super(GlobalMeanPool2d, self).__init__(prev_layer=prev_layer, name=name)
         logging.info("GlobalMeanPool2d %s" % name)
-
         self.inputs = prev_layer.outputs
-
         # operation (customized)
-        self.outputs = tf.reduce_mean(prev_layer.outputs, axis=[1, 2], name=name)
-
+        self.outputs = tf.reduce_mean(self.inputs, axis=[1, 2], name=name)
         # update layer (customized)
         self.all_layers.append(self.outputs)
 
@@ -465,15 +450,11 @@ class GlobalMaxPool3d(Layer):
     @deprecated_alias(layer='prev_layer', end_support_version=1.9)  # TODO remove this line for the 1.9 release
     def __init__(self, prev_layer, name='globalmaxpool3d'):
         super(GlobalMaxPool3d, self).__init__(prev_layer=prev_layer, name=name)
-
         self.inputs = prev_layer.outputs
-
         # print out info (customized)
         logging.info("GlobalMaxPool3d %s" % name)
-
         # operation (customized)
-        self.outputs = tf.reduce_max(prev_layer.outputs, axis=[1, 2, 3], name=name)
-
+        self.outputs = tf.reduce_max(self.inputs, axis=[1, 2, 3], name=name)
         # update layer (customized)
         self.all_layers.append(self.outputs)
 
@@ -500,18 +481,15 @@ class GlobalMeanPool3d(Layer):
     def __init__(self, prev_layer, name='globalmeanpool3d'):
         super(GlobalMeanPool3d, self).__init__(prev_layer=prev_layer, name=name)
         logging.info("GlobalMeanPool3d %s" % name)
-
         self.inputs = prev_layer.outputs
-
         # operation (customized)
-        self.outputs = tf.reduce_mean(prev_layer.outputs, axis=[1, 2, 3], name=name)
-
+        self.outputs = tf.reduce_mean(self.inputs, axis=[1, 2, 3], name=name)
         # update layer (customized)
         self.all_layers.append(self.outputs)
 
 
 # Alias
-MaxPool1d = maxpool1d
-MaxPool2d = maxpool2d
-MeanPool1d = meanpool1d
-MeanPool2d = meanpool2d
+# MaxPool1d = maxpool1d
+# MaxPool2d = maxpool2d
+# MeanPool1d = meanpool1d
+# MeanPool2d = meanpool2d