Max pooling operation for temporal data.
Max pooling operation for temporal data.
layer_max_pooling_1d( object, pool_size = 2L, strides = NULL, padding = "valid", batch_size = NULL, name = NULL, trainable = NULL, weights = NULL )
object |
Model or layer object |
pool_size |
Integer, size of the max pooling windows. |
strides |
Integer, or NULL. Factor by which to downscale. E.g. 2 will
halve the input. If NULL, it will default to |
padding |
One of |
batch_size |
Fixed batch size for layer |
name |
An optional name string for the layer. Should be unique in a model (do not reuse the same name twice). It will be autogenerated if it isn't provided. |
trainable |
Whether the layer weights will be updated during training. |
weights |
Initial weights for layer. |
3D tensor with shape: (batch_size, steps, features).
3D tensor with shape: (batch_size, downsampled_steps, features).
Other pooling layers:
layer_average_pooling_1d(),
layer_average_pooling_2d(),
layer_average_pooling_3d(),
layer_global_average_pooling_1d(),
layer_global_average_pooling_2d(),
layer_global_average_pooling_3d(),
layer_global_max_pooling_1d(),
layer_global_max_pooling_2d(),
layer_global_max_pooling_3d(),
layer_max_pooling_2d(),
layer_max_pooling_3d()
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