Cropping layer for 1D input (e.g. temporal sequence).
It crops along the time dimension (axis 1).
layer_cropping_1d( object, cropping = c(1L, 1L), batch_size = NULL, name = NULL, trainable = NULL, weights = NULL )
object |
Model or layer object |
cropping |
int or list of int (length 2) How many units should be trimmed off at the beginning and end of the cropping dimension (axis 1). If a single int is provided, the same value will be used for both. |
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, axis_to_crop, features)
3D tensor with shape (batch, cropped_axis, features)
Other convolutional layers:
layer_conv_1d_transpose(),
layer_conv_1d(),
layer_conv_2d_transpose(),
layer_conv_2d(),
layer_conv_3d_transpose(),
layer_conv_3d(),
layer_conv_lstm_2d(),
layer_cropping_2d(),
layer_cropping_3d(),
layer_depthwise_conv_2d(),
layer_separable_conv_1d(),
layer_separable_conv_2d(),
layer_upsampling_1d(),
layer_upsampling_2d(),
layer_upsampling_3d(),
layer_zero_padding_1d(),
layer_zero_padding_2d(),
layer_zero_padding_3d()
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