code: def _fit(
      X, num_features=10_000, max_dilations_per_kernel=32, seed=None
  ):
      _, n_timepoints = X.shape
  
      num_kernels = 84
  
      dilations, num_features_per_dilation = _fit_dilations(
          n_timepoints, num_features, max_dilations_per_kernel
      )
  
      num_features_per_kernel = np.sum(num_features_per_dilation)
  
      quantiles = _quantiles(num_kernels * num_features_per_kernel)
  
      biases = _fit_biases(
          X, dilations, num_features_per_dilation, quantiles, seed
      )
  
      return dilations, num_features_per_dilation, biases
  
imports: import numpy
  from sktime.utils.numba.njit import njit
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 4 for calling a global function with example usage: _fit(X, num_features, max_dilations_per_kernel, seed) and returns: dilations,  num_features_per_dilation,  biases