code: def fixed_size_partitioner(num_shards, axis=0):
      """Partitioner to specify a fixed number of shards along given axis.
  
      @compatibility(TF2)
      This API is deprecated in TF2. In TF2, partitioner is no longer part of
      the variable declaration via `tf.Variable`.
      [ParameterServer Training]
      (https://www.tensorflow.org/tutorials/distribute/parameter_server_training)
      handles partitioning of variables. The corresponding TF2 partitioner class of
      `fixed_size_partitioner` is
      `tf.distribute.experimental.partitioners.FixedShardsPartitioner`.
  
      Check the [migration guide]
      (https://www.tensorflow.org/guide/migrate#2_use_python_objects_to_track_variables_and_losses)
      on the differences in treatment of variables and losses between TF1 and TF2.
  
      Before:
  
        ```
        x = tf.compat.v1.get_variable(
          "x", shape=(2,), partitioner=tf.compat.v1.fixed_size_partitioner(2)
        )
        ```
      After:
  
        ```
        partitioner = (
            tf.distribute.experimental.partitioners.FixedShardsPartitioner(
                num_shards=2)
        )
        strategy = tf.distribute.experimental.ParameterServerStrategy(
                       cluster_resolver=cluster_resolver,
                       variable_partitioner=partitioner)
  
        with strategy.scope():
          x = tf.Variable([1.0, 2.0])
        ```
      @end_compatibility
  
      Args:
        num_shards: `int`, number of shards to partition variable.
        axis: `int`, axis to partition on.
  
      Returns:
        A partition function usable as the `partitioner` argument to
        `variable_scope` and `get_variable`.
      """
  
      def _partitioner(shape, **unused_args):
          partitions_list = [1] * len(shape)
          partitions_list[axis] = min(
              num_shards, shape.dims[axis].value
          )
          return partitions_list
  
      return _partitioner
  
file_path: tensorflow/tensorflow/python/ops/partitioned_variables.py
imports: import math
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 3 for calling a global function with example usage: fixed_size_partitioner(num_shards, axis) and returns: _partitioner, partitions_list