layer_spatial_dropout_1d {keras3} | R Documentation |
Spatial 1D version of Dropout.
Description
This layer performs the same function as Dropout, however, it drops
entire 1D feature maps instead of individual elements. If adjacent frames
within feature maps are strongly correlated (as is normally the case in
early convolution layers) then regular dropout will not regularize the
activations and will otherwise just result in an effective learning rate
decrease. In this case, SpatialDropout1D
will help promote independence
between feature maps and should be used instead.
Usage
layer_spatial_dropout_1d(object, rate, seed = NULL, name = NULL, dtype = NULL)
Arguments
object |
Object to compose the layer with. A tensor, array, or sequential model. |
rate |
Float between 0 and 1. Fraction of the input units to drop. |
seed |
Initial seed for the random number generator |
name |
String, name for the object |
dtype |
datatype (e.g., |
Value
The return value depends on the value provided for the first argument.
If object
is:
a
keras_model_sequential()
, then the layer is added to the sequential model (which is modified in place). To enable piping, the sequential model is also returned, invisibly.a
keras_input()
, then the output tensor from callinglayer(input)
is returned.-
NULL
or missing, then aLayer
instance is returned.
Call Arguments
-
inputs
: A 3D tensor. -
training
: Python boolean indicating whether the layer should behave in training mode (applying dropout) or in inference mode (pass-through).
Input Shape
3D tensor with shape: (samples, timesteps, channels)
Output Shape
Same as input.
Reference
See Also
Other spatial dropout regularization layers:
layer_spatial_dropout_2d()
layer_spatial_dropout_3d()
Other regularization layers:
layer_activity_regularization()
layer_alpha_dropout()
layer_dropout()
layer_gaussian_dropout()
layer_gaussian_noise()
layer_spatial_dropout_2d()
layer_spatial_dropout_3d()
Other layers:
Layer()
layer_activation()
layer_activation_elu()
layer_activation_leaky_relu()
layer_activation_parametric_relu()
layer_activation_relu()
layer_activation_softmax()
layer_activity_regularization()
layer_add()
layer_additive_attention()
layer_alpha_dropout()
layer_attention()
layer_average()
layer_average_pooling_1d()
layer_average_pooling_2d()
layer_average_pooling_3d()
layer_batch_normalization()
layer_bidirectional()
layer_category_encoding()
layer_center_crop()
layer_concatenate()
layer_conv_1d()
layer_conv_1d_transpose()
layer_conv_2d()
layer_conv_2d_transpose()
layer_conv_3d()
layer_conv_3d_transpose()
layer_conv_lstm_1d()
layer_conv_lstm_2d()
layer_conv_lstm_3d()
layer_cropping_1d()
layer_cropping_2d()
layer_cropping_3d()
layer_dense()
layer_depthwise_conv_1d()
layer_depthwise_conv_2d()
layer_discretization()
layer_dot()
layer_dropout()
layer_einsum_dense()
layer_embedding()
layer_feature_space()
layer_flatten()
layer_flax_module_wrapper()
layer_gaussian_dropout()
layer_gaussian_noise()
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_group_normalization()
layer_group_query_attention()
layer_gru()
layer_hashed_crossing()
layer_hashing()
layer_identity()
layer_integer_lookup()
layer_jax_model_wrapper()
layer_lambda()
layer_layer_normalization()
layer_lstm()
layer_masking()
layer_max_pooling_1d()
layer_max_pooling_2d()
layer_max_pooling_3d()
layer_maximum()
layer_mel_spectrogram()
layer_minimum()
layer_multi_head_attention()
layer_multiply()
layer_normalization()
layer_permute()
layer_random_brightness()
layer_random_contrast()
layer_random_crop()
layer_random_flip()
layer_random_rotation()
layer_random_translation()
layer_random_zoom()
layer_repeat_vector()
layer_rescaling()
layer_reshape()
layer_resizing()
layer_rnn()
layer_separable_conv_1d()
layer_separable_conv_2d()
layer_simple_rnn()
layer_spatial_dropout_2d()
layer_spatial_dropout_3d()
layer_spectral_normalization()
layer_string_lookup()
layer_subtract()
layer_text_vectorization()
layer_tfsm()
layer_time_distributed()
layer_torch_module_wrapper()
layer_unit_normalization()
layer_upsampling_1d()
layer_upsampling_2d()
layer_upsampling_3d()
layer_zero_padding_1d()
layer_zero_padding_2d()
layer_zero_padding_3d()
rnn_cell_gru()
rnn_cell_lstm()
rnn_cell_simple()
rnn_cells_stack()