code: def _flatten_first_two_dims(x):
      """Flattens the first two dimensions of x into a single dimension."""
      old_shape = array_ops.shape(x)
      new_shape = array_ops.concat(
          [[old_shape[0] * old_shape[1]], old_shape[2:]], axis=0
      )
      return array_ops.reshape(x, new_shape)
  
imports: import functools
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.autograph.core import ag_ctx
  from tensorflow.python.autograph.impl import api
  from tensorflow.python.framework import composite_tensor
  from tensorflow.python.framework import indexed_slices
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.framework import type_spec
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import tensor_array_ops
  from tensorflow.python.ops import while_loop
  from tensorflow.python.ops.parallel_for.pfor import PFor
  from tensorflow.python.ops.parallel_for.pfor import PForConfig
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util import nest
  from tensorflow.python.util import tf_decorator
  from tensorflow.python.util import tf_inspect
  from tensorflow.python.util import variable_utils
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 2 for calling a global function with example usage: _flatten_first_two_dims(x) and returns: array_ops