parameters: (self,
                     var_store,
                     name,
                     shape=None,
                     dtype=None,
                     initializer=None,
                     regularizer=None,
                     reuse=None,
                     trainable=True,
                     collections=None,
                     caching_device=None,
                     partitioner=None,
                     validate_shape=True,
                     use_resource=None,
                     custom_getter=None,)
docstring: Gets an existing variable with this name or create a new one.
docstring_summary: Gets an existing variable with this name or create a new one.
docstring_tokens: Gets an existing variable with this name or create a new one .
function: def get_variable(self,
                     var_store,
                     name,
                     shape=None,
                     dtype=None,
                     initializer=None,
                     regularizer=None,
                     reuse=None,
                     trainable=True,
                     collections=None,
                     caching_device=None,
                     partitioner=None,
                     validate_shape=True,
                     use_resource=None,
                     custom_getter=None,):
      """Gets an existing variable with this name or create a new one."""
      if regularizer is None:
        regularizer = self._regularizer
      if caching_device is None:
        caching_device = self._caching_device
      if partitioner is None:
        partitioner = self._partitioner
      if custom_getter is None:
        custom_getter = self._custom_getter
      if reuse is None:
        reuse = self._reuse
  
      full_name = self.name + "/" + name if self.name else name
      # Variable names only depend on variable_scope (full_name here),
      # not name_scope, so we reset it below for the time of variable creation.
      with ops.name_scope(None):
        # Check that `initializer` dtype and `dtype` are consistent before
        # replacing them with defaults.
        if (dtype is not None and initializer is not None and
            not callable(initializer)):
          init_dtype = ops.convert_to_tensor(initializer).dtype.base_dtype
          if init_dtype != dtype:
            raise ValueError("Initializer type '%s' and explicit dtype '%s' "
                             "don't match." % (init_dtype, dtype))
        if initializer is None:
          initializer = self._initializer
        if dtype is None:
          dtype = self._dtype
        if use_resource is None:
          use_resource = self._use_resource
  
        return var_store.get_variable(
            full_name, shape=shape, dtype=dtype, initializer=initializer,
            regularizer=regularizer, reuse=reuse, trainable=trainable,
            collections=collections, caching_device=caching_device,
            partitioner=partitioner, validate_shape=validate_shape,
            use_resource=use_resource, custom_getter=custom_getter)
function_tokens: def get_variable ( self , var_store , name , shape = None , dtype = None , initializer = None , regularizer = None , reuse = None , trainable = True , collections = None , caching_device = None , partitioner = None , validate_shape = True , use_resource = None , custom_getter = None , ) : if regularizer is None : regularizer = self . _regularizer if caching_device is None : caching_device = self . _caching_device if partitioner is None : partitioner = self . _partitioner if custom_getter is None : custom_getter = self . _custom_getter if reuse is None : reuse = self . _reuse full_name = self . name + "/" + name if self . name else name # Variable names only depend on variable_scope (full_name here), # not name_scope, so we reset it below for the time of variable creation. with ops . name_scope ( None ) : # Check that `initializer` dtype and `dtype` are consistent before # replacing them with defaults. if ( dtype is not None and initializer is not None and not callable ( initializer ) ) : init_dtype = ops . convert_to_tensor ( initializer ) . dtype . base_dtype if init_dtype != dtype : raise ValueError ( "Initializer type '%s' and explicit dtype '%s' " "don't match." % ( init_dtype , dtype ) ) if initializer is None : initializer = self . _initializer if dtype is None : dtype = self . _dtype if use_resource is None : use_resource = self . _use_resource return var_store . get_variable ( full_name , shape = shape , dtype = dtype , initializer = initializer , regularizer = regularizer , reuse = reuse , trainable = trainable , collections = collections , caching_device = caching_device , partitioner = partitioner , validate_shape = validate_shape , use_resource = use_resource , custom_getter = custom_getter )