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)

## Arguments

object Model or layer object 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. Fixed batch size for layer 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. Whether the layer weights will be updated during training. Initial weights for layer.

## Input shape

3D tensor with shape (batch, axis_to_crop, features)

## Output shape

3D tensor with shape (batch, cropped_axis, features)

Other convolutional layers: 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