View source: R/layers-pooling.R
layer_max_pooling_1d | R Documentation |
Max pooling operation for temporal data.
layer_max_pooling_1d(
object,
pool_size = 2L,
strides = NULL,
padding = "valid",
data_format = "channels_last",
batch_size = NULL,
name = NULL,
trainable = NULL,
weights = NULL
)
object |
What to compose the new
|
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 |
data_format |
A string, one of "channels_last" (default) or
"channels_first". The ordering of the dimensions in the inputs.
channels_last corresponds to inputs with shape |
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. |
If data_format='channels_last': 3D tensor with shape (batch_size, steps, features)
.
If data_format='channels_first': 3D tensor with shape (batch_size, features, steps)
.
If data_format='channels_last': 3D tensor with shape (batch_size, downsampled_steps, features)
.
If data_format='channels_first': 3D tensor with shape (batch_size, features, downsampled_steps)
.
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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