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update seeding on dataloader and the start of training script

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Francis Lata
2025-02-28 14:58:28 +00:00
parent 87bfa77f4a
commit bdf442717c
2 changed files with 6 additions and 7 deletions
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9
examples/mlperf/dataloader.py
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@@ -361,13 +361,14 @@ def load_retinanet_data(base_dir:Path, val:bool, queue_in:Queue, queue_out:Queue
idx, img, tgt = data
img = image_load(base_dir, img["subset"], img["file_name"])
if seed is not None:
np.random.seed(seed)
torch.manual_seed(seed)
if val:
img = resize(img)[0]
else:
if seed is not None:
np.random.seed(seed * 2 ** 10 + idx)
random.seed(seed * 2 ** 10 + idx)
torch.manual_seed(seed * 2 ** 10 + idx)
img, tgt = random_horizontal_flip(img, tgt)
img, tgt, _ = resize(img, tgt=tgt)
match_quality_matrix = box_iou(tgt["boxes"], (anchor := np.concatenate(generate_anchors((800, 800)))))

4
examples/mlperf/model_train.py
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@@ -414,9 +414,7 @@ def train_retinanet():
config["lr_warmup_epochs"] = lr_warmup_epochs = getenv("LR_WARMUP_EPOCHS", 1)
config["lr_warmup_factor"] = lr_warmup_factor = getenv("LR_WARMUP_FACTOR", 1e-3)
if SEED:
Tensor.manual_seed(SEED)
np.random.seed(seed=SEED)
if SEED: Tensor.manual_seed(SEED)
# ** model initializers **
resnet.BatchNorm = FrozenBatchNorm2d