Pooling layers

class dynn.layers.pooling_layers.MaxPool1D(kernel_size=None, stride=1)

Bases: dynn.layers.base_layers.BaseLayer

1D max pooling

Parameters:
  • kernel_size (int, optional) – Default kernel size. If this is not specified, the default is to pool over the full sequence (default: None)
  • stride (int, optional) – Default temporal stride (default: 1)
__call__(x, kernel_size=None, stride=None)

Max pooling over the first dimension.

This takes either a list of N d-dimensional vectors or a N x d matrix.

The output will be a matrix of dimension (N - kernel_size + 1) // stride x d

Parameters:
  • x (dynet.Expression) – Input matrix or list of vectors
  • dim (int, optional) – The reduction dimension (default: 0)
  • kernel_size (int, optional) – Kernel size. If this is not specified, the default size specified in the constructor is used.
  • stride (int, optional) – Temporal stride. If this is not specified, the default stride specified in the constructor is used.
Returns:

Pooled sequence.
Return type:

dynet.Expression
__init__(kernel_size=None, stride=1)

Initialize self. See help(type(self)) for accurate signature.

class dynn.layers.pooling_layers.MaxPool2D(kernel_size=None, strides=None)

Bases: dynn.layers.base_layers.BaseLayer

2D max pooling.

Parameters:
  • kernel_size (list, optional) – Default kernel size. This is a list of two elements, one per dimension. If either is not specified, the default is to pool over the entire dimension (default: [None, None])
  • strides (list, optional) – Stride along each dimension (list of size 2, defaults to [1, 1]).
__call__(x, kernel_size=None, strides=None)

Max pooling over the first dimension.

If either of the kernel_size elements is not specified, the pooling will be done over the full dimension (and the stride is ignored)

Parameters:
  • x (dynet.Expression) – Input image (3-d tensor) or matrix.
  • kernel_size (list, optional) – Size of the pooling kernel. If this is not specified, the default specified in the constructor is used.
  • strides (list, optional) – Stride along width/height. If this is not specified, the default specified in the constructor is used.
Returns:

Pooled sequence.
Return type:

dynet.Expression
__init__(kernel_size=None, strides=None)

Initialize self. See help(type(self)) for accurate signature.

class dynn.layers.pooling_layers.MeanPool1D(kernel_size=None, stride=1)

Bases: dynn.layers.base_layers.BaseLayer

1D mean pooling.

The stride and kernel size arguments are here for consistency with MaxPooling1D but they are unsupported for now.

Parameters:
  • kernel_size (int, optional) – Default kernel size. If this is not specified, the default is to pool over the full sequence (default: None)
  • stride (int, optional) – Default temporal stride (default: 1)
__call__(x, kernel_size=None, stride=None, lengths=None)

Mean pooling over the first dimension.

This takes either a list of N d-dimensional vectors or a N x d matrix.

The output will be a matrix of dimension (N - kernel_size + 1) // stride x d

Parameters:
  • x (dynet.Expression) – Input matrix or list of vectors
  • dim (int, optional) – The reduction dimension (default: 0)
  • kernel_size (int, optional) – Kernel size. If this is not specified, the default size specified in the constructor is used.
  • stride (int, optional) – Temporal stride. If this is not specified, the default stride specified in the constructor is used.
Returns:

Pooled sequence.
Return type:

dynet.Expression
__init__(kernel_size=None, stride=1)

Initialize self. See help(type(self)) for accurate signature.

dynn.layers.pooling_layers.max_pool_dim(x, d=0, kernel_width=None, stride=1)

Efficent max pooling on GPU, assuming x is a matrix or a list of vectors