code: def _argmin_min_reduce(dist, start):
      # `start` is specified in the signature but not used. This is because the higher
      # order `pairwise_distances_chunked` function needs reduction functions that are
      # passed as argument to have a two arguments signature.
      indices = dist.argmin(axis=1)
      values = dist[np.arange(dist.shape[0]), indices]
      return indices, values
  
imports: import itertools
  import warnings
  from functools import partial
  from numbers import Integral, Real
  import numpy
  from joblib import effective_n_jobs
  from scipy.sparse import csr_matrix, issparse
  from scipy.spatial import distance
  from ..None import config_context
  from ..exceptions import DataConversionWarning
  from ..preprocessing import normalize
  from ..utils import check_array, gen_batches, gen_even_slices, get_chunk_n_rows, is_scalar_nan
  from ..utils._mask import _get_mask
  from ..utils._param_validation import Hidden, Interval, MissingValues, Options, StrOptions, validate_params
  from ..utils.extmath import row_norms, safe_sparse_dot
  from ..utils.fixes import parse_version, sp_base_version
  from ..utils.parallel import Parallel, delayed
  from ..utils.validation import _num_samples, check_non_negative
  from ._pairwise_distances_reduction import ArgKmin
  from ._pairwise_fast import _chi2_kernel_fast, _sparse_manhattan
label_desc: Use image node_id 8 for calling a global function with example usage: _argmin_min_reduce(dist, start) and returns: indices,  values