class_docstr: A protocol allowing custom classes to control tf.function retracing.
docstr: Returns the tracing type of this object.
  
  The tracing type is used to build the signature of a tf.function
  when traced, and to match arguments with existing signatures.
  When a Function object is called, tf.function looks at the tracing type
  of the call arguments. If an existing signature of matching type exists,
  it will be used. Otherwise, a new function is traced, and its signature
  will use the tracing type of the call arguments.
  
  Args:
    context: a context reserved for internal/future usage.
  
  Returns:
    The tracing type of this object.
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code: def __tf_tracing_type__(self, context: TracingContext) -> TraceType:
      """Returns the tracing type of this object.
  
      The tracing type is used to build the signature of a tf.function
      when traced, and to match arguments with existing signatures.
      When a Function object is called, tf.function looks at the tracing type
      of the call arguments. If an existing signature of matching type exists,
      it will be used. Otherwise, a new function is traced, and its signature
      will use the tracing type of the call arguments.
  
      Args:
        context: a context reserved for internal/future usage.
  
      Returns:
        The tracing type of this object.
      """
  
imports: import abc
  from typing import Any, Iterator, List, Optional, Sequence
  from typing_extensions import Protocol
  from typing_extensions import runtime_checkable
  from tensorflow.python.types import core
  from tensorflow.python.util.tf_export import tf_export
  from tensorflow.tools.docs import doc_controls
label_desc: Use image node_id 1 for calling the SupportsTracingProtocol obj's underlying member method code with example usage: obj.__tf_tracing_type__(context) without return types