code: def _eager_reshape(tensor, shape, ctx):
      """Eager-only version of Reshape op; requires tensor is an eager Tensor."""
      attr_t = (
          tensor._datatype_enum()
      )  # pylint: disable=protected-access
      attr_tshape, (shape,) = execute.args_to_matching_eager(
          [shape], ctx, [dtypes.int32, dtypes.int64], dtypes.int32
      )
      inputs_flat = [tensor, shape]
      attrs = ("T", attr_t, "Tshape", attr_tshape)
      [result] = execute.execute(
          b"Reshape", 1, inputs=inputs_flat, attrs=attrs, ctx=ctx
      )
      return result
  
imports: from typing import Union
  import numpy
  from tensorflow.core.framework import types_pb2
  from tensorflow.core.protobuf import struct_pb2
  from tensorflow.python.eager import context
  from tensorflow.python.eager import execute
  from tensorflow.python.framework import constant_tensor_conversion
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_conversion_registry
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.profiler import trace
  from tensorflow.python.saved_model import nested_structure_coder
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 1 for calling a global function with example usage: _eager_reshape(tensor, shape, ctx) and returns: result