code: def main(_):
      benchmark_name = FLAGS.benchmark_name
      num_samples = FLAGS.num_samples
      batch_size = FLAGS.batch_size
      jit_compile = FLAGS.jit_compile
  
      if benchmark_name is None:
          for name, benchmark_fn in BENCHMARK_NAMES.items():
              benchmark_fn(num_samples, batch_size, jit_compile)
          return
  
      if benchmark_name not in BENCHMARK_NAMES:
          raise ValueError(
              f"Invalid benchmark name: {benchmark_name}, `benchmark_name` must "
              f"be one of {BENCHMARK_NAMES.keys()}"
          )
      benchmark_fn = BENCHMARK_NAMES[benchmark_name]
      benchmark_fn(num_samples, batch_size, jit_compile)
  
file_path: keras/benchmarks/layer_benchmark/core_benchmark.py
imports: import numpy
  from absl import app
  from absl import flags
  from benchmarks.layer_benchmark.base_benchmark import LayerBenchmark
label_desc: Use image node_id 4 for calling a global function with example usage: main(_) without return types