Python tf.compat.v1.profiler.Profiler用法及代码示例

TensorFlow multi-step 分析器。

用法

tf.compat.v1.profiler.Profiler(
    graph=None, op_log=None
)

Typical use case:
  # Currently we are only allowed to create 1 profiler per process.
  profiler = Profiler(sess.graph)

  for i in range(total_steps):
    if i % 10000 == 0:
      run_meta = tf.compat.v1.RunMetadata()
      _ = sess.run(...,
                   options=tf.compat.v1.RunOptions(
                       trace_level=tf.RunOptions.FULL_TRACE),
                   run_metadata=run_meta)
      profiler.add_step(i, run_meta)

      # Profile the parameters of your model.
      profiler.profile_name_scope(options=(option_builder.ProfileOptionBuilder
          .trainable_variables_parameter()))

      # Or profile the timing of your model operations.
      opts = option_builder.ProfileOptionBuilder.time_and_memory()
      profiler.profile_operations(options=opts)

      # Or you can generate a timeline:
      opts = (option_builder.ProfileOptionBuilder(
              option_builder.ProfileOptionBuilder.time_and_memory())
              .with_step(i)
              .with_timeline_output(filename).build())
      profiler.profile_graph(options=opts)
    else:
      _ = sess.run(...)
  # Auto detect problems and generate advice.
  profiler.advise()