class_docstr: Grid of parameters with a discrete number of values for each.
  
  .. deprecated:: 0.18
      This module will be removed in 0.20.
      Use :class:`sklearn.model_selection.ParameterGrid` instead.
  
  Can be used to iterate over parameter value combinations with the
  Python built-in function iter.
  
  Read more in the :ref:`User Guide <grid_search>`.
  
  Parameters
  ----------
  param_grid : dict of string to sequence, or sequence of such
      The parameter grid to explore, as a dictionary mapping estimator
      parameters to sequences of allowed values.
  
      An empty dict signifies default parameters.
  
      A sequence of dicts signifies a sequence of grids to search, and is
      useful to avoid exploring parameter combinations that make no sense
      or have no effect. See the examples below.
  
  Examples
  --------
  >>> from sklearn.grid_search import ParameterGrid
  >>> param_grid = {'a': [1, 2], 'b': [True, False]}
  >>> list(ParameterGrid(param_grid)) == (
  ...    [{'a': 1, 'b': True}, {'a': 1, 'b': False},
  ...     {'a': 2, 'b': True}, {'a': 2, 'b': False}])
  True
  
  >>> grid = [{'kernel': ['linear']}, {'kernel': ['rbf'], 'gamma': [1, 10]}]
  >>> list(ParameterGrid(grid)) == [{'kernel': 'linear'},
  ...                               {'kernel': 'rbf', 'gamma': 1},
  ...                               {'kernel': 'rbf', 'gamma': 10}]
  True
  >>> ParameterGrid(grid)[1] == {'kernel': 'rbf', 'gamma': 1}
  True
  
  See also
  --------
  :class:`GridSearchCV`:
      uses ``ParameterGrid`` to perform a full parallelized parameter search.
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docstr: Iterate over the points in the grid.
  
  Returns
  -------
  params : iterator over dict of string to any
      Yields dictionaries mapping each estimator parameter to one of its
      allowed values.
code: def __iter__(self):
      """Iterate over the points in the grid.
  
      Returns
      -------
      params : iterator over dict of string to any
          Yields dictionaries mapping each estimator parameter to one of its
          allowed values.
      """
      for p in self.param_grid:
          # Always sort the keys of a dictionary, for reproducibility
          items = sorted(p.items())
          if not items:
              yield {}
          else:
              keys, values = zip(*items)
              for v in product(*values):
                  params = dict(zip(keys, v))
                  yield params
  
imports: from __future__ import print_function
  from abc import ABCMeta, abstractmethod
  from collections import Mapping, namedtuple, Sized
  from functools import partial, reduce
  from itertools import product
  import operator
  import warnings
  import numpy
  from .base import BaseEstimator, is_classifier, clone
  from .base import MetaEstimatorMixin
  from .cross_validation import check_cv
  from .cross_validation import _fit_and_score
  from .externals.joblib import Parallel, delayed
  from .externals import six
  from .utils import check_random_state
  from .utils.random import sample_without_replacement
  from .utils.validation import _num_samples, indexable
  from .utils.metaestimators import if_delegate_has_method
  from .metrics.scorer import check_scoring
  from .exceptions import ChangedBehaviorWarning
label_desc: Use image node_id 2 for calling the ParameterGrid obj's underlying member method code with example usage: obj.__iter__() without return types