mirror of https://github.com/hpcaitech/ColossalAI
37 lines
733 B
Python
37 lines
733 B
Python
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from colossalai.amp import AMP_TYPE
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# hyperparameters
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# BATCH_SIZE is as per GPU
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# global batch size = BATCH_SIZE x data parallel size
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BATCH_SIZE = 256
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LEARNING_RATE = 3e-3
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WEIGHT_DECAY = 0.3
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NUM_EPOCHS = 10
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WARMUP_EPOCHS = 3
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# model config
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IMG_SIZE = 224
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PATCH_SIZE = 16
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HIDDEN_SIZE = 512
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DEPTH = 4
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NUM_HEADS = 4
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MLP_RATIO = 2
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NUM_CLASSES = 1000
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CHECKPOINT = False
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SEQ_LENGTH = (IMG_SIZE // PATCH_SIZE)**2 + 1 # add 1 for cls token
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# parallel setting
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TENSOR_PARALLEL_SIZE = 2
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TENSOR_PARALLEL_MODE = '1d'
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parallel = dict(
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pipeline=2,
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tensor=dict(mode=TENSOR_PARALLEL_MODE, size=TENSOR_PARALLEL_SIZE),
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)
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fp16 = dict(mode=AMP_TYPE.NAIVE)
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clip_grad_norm = 1.0
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# pipeline config
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NUM_MICRO_BATCHES = parallel['pipeline']
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