class_docstr: Option Builder for Profiling API.
  
  For tutorial on the options, see
  https://github.com/tensorflow/tensorflow/tree/master/tensorflow/core/profiler/g3doc/options.md
  
  ```python
  # Users can use pre-built options:
  opts = (
      tf.profiler.ProfileOptionBuilder.trainable_variables_parameter())
  
  # Or, build your own options:
  opts = (tf.compat.v1.profiler.ProfileOptionBuilder()
      .with_max_depth(10)
      .with_min_micros(1000)
      .select(['accelerator_micros'])
      .with_stdout_output()
      .build()
  
  # Or customize the pre-built options:
  opts = (tf.compat.v1.profiler.ProfileOptionBuilder(
      tf.profiler.ProfileOptionBuilder.time_and_memory())
      .with_displaying_options(show_name_regexes=['.*rnn.*'])
      .build())
  
  # Finally, profiling with the options:
  _ = tf.compat.v1.profiler.profile(tf.compat.v1.get_default_graph(),
                          run_meta=run_meta,
                          cmd='scope',
                          options=opts)
  ```
class_docstr_tok: ["Option","Builder","for","Profiling","API",".","For","tutorial","on","the","options",",","see","https",":","\/\/github.com\/tensorflow\/tensorflow\/tree\/master\/tensorflow\/core\/profiler\/g3doc\/options.md","``","`","python","#","Users","can","use","pre-built","options",":","opts","=","(","tf.profiler.ProfileOptionBuilder.trainable_variables_parameter","(",")",")","#","Or",",","build","your","own","options",":","opts","=","(","tf.compat.v1.profiler.ProfileOptionBuilder","(",")",".with_max_depth","(","10",")",".with_min_micros","(","1000",")",".select","(","[","'accelerator_micros","'","]",")",".with_stdout_output","(",")",".build","(",")","#","Or","customize","the","pre-built","options",":","opts","=","(","tf.compat.v1.profiler.ProfileOptionBuilder","(","tf.profiler.ProfileOptionBuilder.time_and_memory","(",")",")",".with_displaying_options","(","show_name_regexes=","[","'.","*","rnn",".","*","'","]",")",".build","(",")",")","#","Finally",",","profiling","with","the","options",":","_","=","tf.compat.v1.profiler.profile","(","tf.compat.v1.get_default_graph","(",")",",","run_meta=run_meta",",","cmd='scope","'",",","options=opts",")","``","`"]
docstr: Set the maximum depth of display.
  
  The depth depends on profiling view. For 'scope' view, it's the
  depth of name scope hierarchy (tree), for 'op' view, it's the number
  of operation types (list), etc.
  
  Args:
    max_depth: Maximum depth of the data structure to display.
  Returns:
    self
docstr_tok: ["Set","the","maximum","depth","of","display",".","The","depth","depends","on","profiling","view",".","For","'scope","'","view",",","it","'s","the","depth","of","name","scope","hierarchy","(","tree",")",",","for","'op","'","view",",","it","'s","the","number","of","operation","types","(","list",")",",","etc",".","Args",":","max_depth",":","Maximum","depth","of","the","data","structure","to","display",".","Returns",":","self"]
code: def with_max_depth(self, max_depth):
      """Set the maximum depth of display.
  
      The depth depends on profiling view. For 'scope' view, it's the
      depth of name scope hierarchy (tree), for 'op' view, it's the number
      of operation types (list), etc.
  
      Args:
        max_depth: Maximum depth of the data structure to display.
      Returns:
        self
      """
      self._options["max_depth"] = max_depth
      return self
  
imports: import copy
  from tensorflow.python.profiler import tfprof_logger
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 6 for calling the ProfileOptionBuilder obj's underlying member method code with example usage: obj.with_max_depth(max_depth) and returns: self