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[Enhance] Support --batch-size option in the validation benchmark tool.

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mzr1996 2022-10-08 11:14:35 +08:00
parent 38bea383c1
commit 23cad6a0e1
1 changed files with 7 additions and 2 deletions
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9
.dev_scripts/benchmark_regression/1-benchmark_valid.py
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@ -48,6 +48,11 @@ def parse_args():
'--inference-time',
action='store_true',
help='Test inference time by run 10 times for each model.')
parser.add_argument(
'--batch-size',
type=int,
default=1,
help='The batch size during the inference.')
parser.add_argument(
'--flops', action='store_true', help='Get Flops and Params of models')
parser.add_argument(
@ -86,7 +91,7 @@ def inference(config_file, checkpoint, work_dir, args, exp_name):
test_dataset.pipeline.insert(1, dict(type='Resize', scale=32))
data = Compose(test_dataset.pipeline)({'img_path': args.img})
data = default_collate([data])
data = default_collate([data] * args.batch_size)
resolution = tuple(data['inputs'].shape[-2:])
runner: Runner = Runner.from_cfg(cfg)
@ -103,7 +108,7 @@ def inference(config_file, checkpoint, work_dir, args, exp_name):
start = time()
model.val_step(data)
torch.cuda.synchronize()
time_record.append((time() - start) * 1000)
time_record.append((time() - start) / args.batch_size * 1000)
result['time_mean'] = np.mean(time_record[1:-1])
result['time_std'] = np.std(time_record[1:-1])
else: