mirror of https://github.com/hpcaitech/ColossalAI
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50ec3a7e06
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@ -15,7 +15,7 @@ from colossalai.context import ParallelMode
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from colossalai.core import global_context as gpc
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from colossalai.nn.optimizer import ColoOptimizer
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from functools import partial
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from _utils import set_seed
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from _utils import tensor_equal, tensor_shard_equal, set_seed
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def init_1d_row_linear(weight):
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@ -144,20 +144,8 @@ def run_1d_hybrid_tp(model_name):
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with torch.no_grad():
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# check param
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for p1, p2 in zip(model.parameters(), model_torch.parameters()):
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if p1.size() == p2.size():
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assert torch.allclose(p1, p2)
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else:
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# TODO(jzy) Only check 1D spec. Need to be replaced by new DistSpec.
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if p1.size(-1) < p2.size(-1): # col
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world_size = p2.size(-1) // p1.size(-1)
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split_p2 = torch.chunk(p2, world_size, dim=-1)[0]
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elif p1.size(0) < p2.size(0): # row
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world_size = p2.size(0) // p1.size(0)
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split_p2 = torch.chunk(p2, world_size, dim=0)[0]
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assert torch.allclose(p1, split_p2)
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for p, torch_p in zip(model.parameters(), model_torch.parameters()):
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assert tensor_shard_equal(torch_p, p)
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if i > 5:
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break
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