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resnet dataloader osx (#10316)

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* mlperf dataloader on mac

* resnet dataloader [pr]

* simple should work
This commit is contained in:
George Hotz
2025-05-14 18:31:26 -07:00
committed by GitHub
parent 9b14e8c3cd
commit aef336930a
1 changed files with 3 additions and 6 deletions
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9
examples/mlperf/dataloader.py
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@@ -129,14 +129,11 @@ def batch_load_resnet(batch_size=64, val=False, shuffle=True, seed=None, pad_fir
q_in, q_out = Queue(), Queue()
sz = (batch_size*BATCH_COUNT, 224, 224, 3)
if os.path.exists("/dev/shm/resnet_X"): os.unlink("/dev/shm/resnet_X")
shm = shared_memory.SharedMemory(name="resnet_X", create=True, size=prod(sz))
shm = shared_memory.SharedMemory(name="resnet_X_val" if val else "resnet_X_train", create=True, size=prod(sz))
procs = []
try:
# disk:shm is slower
#X = Tensor.empty(*sz, dtype=dtypes.uint8, device=f"disk:shm:{shm.name}")
X = Tensor.empty(*sz, dtype=dtypes.uint8, device=f"disk:/dev/shm/resnet_X")
X = Tensor.empty(*sz, dtype=dtypes.uint8, device=f"disk:shm:{shm.name}")
Y = [None] * (batch_size*BATCH_COUNT)
for _ in range(cpu_count()):
@@ -312,7 +309,7 @@ def batch_load_unet3d(preprocessed_dataset_dir:Path, batch_size:int=6, val:bool=
proc = Process(target=load_unet3d_data, args=(preprocessed_dataset_dir, seed, queue_in, queue_out, X, Y))
proc.daemon = True
proc.start()
procs.append(proc)
for bc in range(batch_count):