HongChuang/ultralytics-ascend
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Start export implementation (#110)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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Glenn Jocher 2022-12-29 14:17:14 +01:00 • committed by GitHub
parent c1b38428bc
commit 92dad1c1b5
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32 changed files with 827 additions and 222 deletions
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8
ultralytics/yolo/engine/validator.py
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@ -66,7 +66,7 @@ class BaseValidator:
self.args.batch_size = model.batch_size
else:
self.device = model.device
if not (pt or jit):
if not pt and not jit:
self.args.batch_size = 1 # export.py models default to batch-size 1
self.logger.info(
f'Forcing --batch-size 1 square inference (1,3,{imgsz},{imgsz}) for non-PyTorch models')
@ -75,8 +75,8 @@ class BaseValidator:
data = check_dataset_yaml(self.args.data)
else:
data = check_dataset(self.args.data)
self.dataloader = self.get_dataloader(data.get("val") or data.set("test"),
self.args.batch_size) if not self.dataloader else self.dataloader
self.dataloader = self.dataloader or \
self.get_dataloader(data.get("val") or data.set("test"), self.args.batch_size)
model.eval()
@ -139,7 +139,7 @@ class BaseValidator:
def postprocess(self, preds):
return preds
def init_metrics(self):
def init_metrics(self, model):
pass
def update_metrics(self, preds, batch):