layer_cropping_1d.RdIt 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,
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