Pooling layers¶
Pooling layers
MaxPooling2D 
Pooling using the max operation 

class
braid.berry.layers.
MaxPooling2D
(incoming, kernel_size, stride=1, pad='VALID', **kwargs)¶ Pooling using the
max
operationThis is used to subsample the output from convolutional layers. It works by convolving a kernel with a
max
operation across the activation of the previous layer. More specifically, it looks at a receptive field equal to[1, kernel_size, kernel_size, 1]
and outputs themax
value of the activations in this region, shifting then bystride
amount and repeating. incoming :
 Parent layer, whose output is given as input to the current layer.
 kernel_size : int
 The size of the kernel to consider for pooling.
 stride : int, optional (default = 1)
 The amount of subsample.
 pad : string, optional (default = “VALID”)
 Type of padding to apply to the input layer before doing pooling.
Expected values  “VALID”, “SAME”. No padding is applied for “VALID”,
while a padding of
(kernel_size + 1) / 2
if “SAME”. This ensures that the output layer shape is the same as that of the input layer shape.  name : string, optional (default = None)
 Name of the layer. Should be specified for better readability (
inherited from
Layer
).
Layer
ortf.Tensor
 input_layer :
 Input layer to this layer.
 input_shape : tuple
 Shape of the incoming layer.
 output :
 The Tensor obtained after performing the transformation applied by this layer.
 output_shape : tuple
 Shape of the output tensor.
 type : string
 Return the name of the class.
Layer
ortf.Tensor
tf.Tensor
See also
Inherits class
Layer
.
get_output_for
()¶ Perform the max pooling operation and return the output
tf.Tensor
.tf.Tensor
 Output tensor of this layer.

get_output_shape_for
(input_shape)¶ Shape of the output tensor after performing MaxPooling.
 input_shape : tuple or list
 Shape of the input layer.
 tuple
 Shape of the output tensor.
Note
Each dimension of the output is given as
\[l_o = \frac{( W  F +2P)}{S} + 1\]where \(W\) is the width of the input layer dim, \(F\) is the
kernel_size
, \(P\) is the amount of padding applied and \(S\) is thestride
.

validate_input_layer
(incoming)¶ Validate the input layer dimensions.
Valid input layer would be 4D.
 incoming :
 Parent layer, whose output is given as input to the current layer.
Layer
ortf.Tensor
 bool
True
if connection is valid or raises anexceptions.AssertionError
.