nvidia.dali.fn.preemphasis_filter(__input, /, *, border='clamp', bytes_per_sample_hint=[0], dtype=DALIDataType.FLOAT, preemph_coeff=0.97, preserve=False, seed=-1, device=None, name=None)

Applies preemphasis filter to the input data.

This filter, in simple form, can be expressed by the formula:

Y[t] = X[t] - coeff * X[t-1]    if t > 1
Y[t] = X[t] - coeff * X_border  if t == 0

with X and Y being the input and output signal, respectively.

The value of X_border depends on the border argument:

X_border = 0                    if border_type == 'zero'
X_border = X[0]                 if border_type == 'clamp'
X_border = X[1]                 if border_type == 'reflect'
Supported backends
  • ‘cpu’

  • ‘gpu’


__input (TensorList) – Input to the operator.

Keyword Arguments:
  • border (str, optional, default = ‘clamp’) – Border value policy. Possible values are "zero", "clamp", "reflect".

  • bytes_per_sample_hint (int or list of int, optional, default = [0]) –

    Output size hint, in bytes per sample.

    If specified, the operator’s outputs residing in GPU or page-locked host memory will be preallocated to accommodate a batch of samples of this size.

  • dtype (nvidia.dali.types.DALIDataType, optional, default = DALIDataType.FLOAT) – Data type for the output.

  • preemph_coeff (float or TensorList of float, optional, default = 0.97) – Preemphasis coefficient coeff.

  • preserve (bool, optional, default = False) – Prevents the operator from being removed from the graph even if its outputs are not used.

  • seed (int, optional, default = -1) –

    Random seed.

    If not provided, it will be populated based on the global seed of the pipeline.