layer_max_pooling_1d
Max pooling operation for temporal data.
Description
Max pooling operation for temporal data.
Usage
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
) 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. |
| 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 pool_size. |
| padding | One of "valid" or "same" (case-insensitive). |
| 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, steps, features) while channels_first corresponds to inputs with shape (batch, features, steps). |
| 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. |
Section
Input Shape
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).
Output shape
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).
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_1d(), layer_global_max_pooling_2d(), layer_global_max_pooling_3d(), layer_max_pooling_2d(), layer_max_pooling_3d()