class_docstr: Initializer that restores tensors from a checkpoint.
class_docstr_tok: ["Initializer","that","restores","tensors","from","a","checkpoint","."]
docstr: Construct a new restoring initializer.
  Will read from the checkpoint from the SSTables file `filename` using
  the RestoreV2 Tensorflow op.
  The actual variable read from the checkpoint will be
  `scope_name` + '/' + `var_name` (or just `var_name` if `scope_name` is
  empty), where `scope_name` is given by one of
  (1) The current scope's name at the point where the initializer gets called,
      if the `scope` argument to this constructor is None,
  (2) If `scope` is callable, the result of applying it to the current scope's
      name,
  (3) Otherwise, the `scope` argument to this constructor itself.
  Args:
    filename: Name of an SSTables entry where the checkpoint is hosted.
    var_name: Name of the variable to restore.
    scope: The variable scope's name of the variable to restore, see above.
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code: def __init__(self, filename, var_name, scope=None):
      """Construct a new restoring initializer.
      Will read from the checkpoint from the SSTables file `filename` using
      the RestoreV2 Tensorflow op.
      The actual variable read from the checkpoint will be
      `scope_name` + '/' + `var_name` (or just `var_name` if `scope_name` is
      empty), where `scope_name` is given by one of
      (1) The current scope's name at the point where the initializer gets called,
          if the `scope` argument to this constructor is None,
      (2) If `scope` is callable, the result of applying it to the current scope's
          name,
      (3) Otherwise, the `scope` argument to this constructor itself.
      Args:
        filename: Name of an SSTables entry where the checkpoint is hosted.
        var_name: Name of the variable to restore.
        scope: The variable scope's name of the variable to restore, see above.
      """
      self._filename = filename
      self._var_name = var_name
      self._scope = scope
  
file_path: NiftyNet/niftynet/utilities/restore_initializer.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  from tensorflow.python.ops import init_ops
  from tensorflow.python.ops import io_ops
label_desc: Use image node_id 1 to create a new _Restore object from inherited base classes: init_ops with example: obj = _Restore(filename, var_name, scope)