def main()

in evaluations/evaluator.py [0:0]

• 29 lines of code
• 1 McCabe index (conditional complexity)

def main():
    parser = argparse.ArgumentParser()
    parser.add_argument("ref_batch", help="path to reference batch npz file")
    parser.add_argument("sample_batch", help="path to sample batch npz file")
    args = parser.parse_args()

    config = tf.ConfigProto(
        allow_soft_placement=True  # allows DecodeJpeg to run on CPU in Inception graph
    )
    config.gpu_options.allow_growth = True
    evaluator = Evaluator(tf.Session(config=config))

    print("warming up TensorFlow...")
    # This will cause TF to print a bunch of verbose stuff now rather
    # than after the next print(), to help prevent confusion.
    evaluator.warmup()

    print("computing reference batch activations...")
    ref_acts = evaluator.read_activations(args.ref_batch)
    print("computing/reading reference batch statistics...")
    ref_stats, ref_stats_spatial = evaluator.read_statistics(args.ref_batch, ref_acts)

    print("computing sample batch activations...")
    sample_acts = evaluator.read_activations(args.sample_batch)
    print("computing/reading sample batch statistics...")
    sample_stats, sample_stats_spatial = evaluator.read_statistics(
        args.sample_batch, sample_acts
    )

    print("Computing evaluations...")
    print("Inception Score:", evaluator.compute_inception_score(sample_acts[0]))
    print("FID:", sample_stats.frechet_distance(ref_stats))
    print("sFID:", sample_stats_spatial.frechet_distance(ref_stats_spatial))
    prec, recall = evaluator.compute_prec_recall(ref_acts[0], sample_acts[0])
    print("Precision:", prec)
    print("Recall:", recall)