class_docstr: Verifies Python loops for TF-specific limits.
class_docstr_tok: ["Verifies","Python","loops","for","TF-specific","limits","."]
code: def __init__(self):
      self.iterations = 1
      self.check_inefficient_unroll = WARN_INEFFICIENT_UNROLL
  
      # Triggered when we decided to test the op counts.
      self.check_op_count_after_iteration = False
  
imports: import functools
  import sys
  import traceback
  import numpy
  from tensorflow.python.autograph.operators import py_builtins
  from tensorflow.python.autograph.operators import variables
  from tensorflow.python.autograph.utils import ag_logging
  from tensorflow.python.autograph.utils import misc
  from tensorflow.python.autograph.utils import tensors
  from tensorflow.python.autograph.utils import type_registry
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import func_graph
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_conversion
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import control_flow_assert
  from tensorflow.python.ops import control_flow_util
  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.types import distribute
  from tensorflow.python.util import nest
  from tensorflow.python.util import variable_utils
label_desc: Use image node_id 1 to create a new _PythonLoopChecker object from inherited base classes: object with example: obj = _PythonLoopChecker()