brainpy.dyn.layers.MinPool#

class brainpy.dyn.layers.MinPool(window_shape, strides, padding='VALID', channel_axis=None, mode=TrainingMode, name=None)[source]#

Pools the input by taking the minimum over a window.

Parameters
  • window_shape (int, sequence of int) – An integer, or a sequence of integers defining the window to reduce over.

  • strides (int, sequence of int) – An integer, or a sequence of integers, representing the inter-window strides (default: (1, …, 1)).

  • padding (str, sequence of tuple) – Either the string ‘SAME’, the string ‘VALID’, or a sequence of n (low, high) integer pairs that give the padding to apply before and after each spatial dimension.

  • channel_axis (int, optional) – Axis of the spatial channels for which pooling is skipped, used to infer window_shape or strides if they are an integer.

  • mode (Mode) – The computation mode.

  • name (optional, str) – The object name.

__init__(window_shape, strides, padding='VALID', channel_axis=None, mode=TrainingMode, name=None)[source]#

Methods

__init__(window_shape, strides[, padding, ...])

clear_input()

get_delay_data(identifier, delay_step, *indices)

Get delay data according to the provided delay steps.

load_states(filename[, verbose])

Load the model states.

nodes([method, level, include_self])

Collect all children nodes.

offline_fit(target, fit_record)

offline_init()

online_fit(target, fit_record)

online_init()

register_delay(identifier, delay_step, ...)

Register delay variable.

register_implicit_nodes(*nodes, **named_nodes)

register_implicit_vars(*variables, ...)

reset([batch_size])

Reset function which reset the whole variables in the model.

reset_local_delays([nodes])

Reset local delay variables.

reset_state([batch_size])

Reset function which reset the states in the model.

save_states(filename[, variables])

Save the model states.

train_vars([method, level, include_self])

The shortcut for retrieving all trainable variables.

unique_name([name, type_])

Get the unique name for this object.

update(sha, x)

The function to specify the updating rule.

update_local_delays([nodes])

Update local delay variables.

vars([method, level, include_self])

Collect all variables in this node and the children nodes.

Attributes

global_delay_data

mode

Mode of the model, which is useful to control the multiple behaviors of the model.

name

Name of the model.