layer_global_max_pooling_1d
Global max pooling operation for temporal data.
Description
Global max pooling operation for temporal data.
Usage
layer_global_max_pooling_1d(
object, data_format = "channels_last",
keepdims = FALSE,
... )
Arguments
Arguments | Description |
---|---|
object | What to compose the new Layer instance with. Typically a Sequential model or a Tensor (e.g., as returned by layer_input() ). The return value depends on object . If object is: - missing or NULL , the Layer instance is returned. - a Sequential model, the model with an additional layer is returned. - a Tensor, the output tensor from layer_instance(object) is returned. |
data_format | One of channels_last (default) or channels_first . The ordering of the dimensions in the inputs. |
keepdims | A boolean, whether to keep the spatial dimensions or not. If keepdims is FALSE (default), the rank of the tensor is reduced for spatial dimensions. If keepdims is TRUE , the spatial dimensions are retained with length 1. The behavior is the same as for tf.reduce_mean or np.mean . |
… | standard layer arguments. |
Section
Input shape
3D tensor with shape: (batch_size, steps, features)
.
Output shape
2D tensor with shape: (batch_size, channels)
See Also
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_2d()
, layer_global_max_pooling_3d()
, layer_max_pooling_1d()
, layer_max_pooling_2d()
, layer_max_pooling_3d()