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49 lines
1.3 KiB
49 lines
1.3 KiB
import torch
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import torch.nn as nn
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from torch.fx import GraphModule
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from colossalai.fx.proxy import ColoProxy
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from colossalai.fx.tracer.tracer import ColoTracer
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from colossalai.testing import clear_cache_before_run
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class Conv1D(nn.Module):
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def __init__(self, nf, nx):
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super().__init__()
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self.nf = nf
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w = torch.empty(nx, nf)
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nn.init.normal_(w, std=0.02)
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self.weight = nn.Parameter(w)
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self.bias = nn.Parameter(torch.zeros(nf))
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def forward(self, x):
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size_out = x.shape[:-1] + (self.nf,)
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x = torch.addmm(self.bias, x.view(-1, x.size(-1)), self.weight)
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x = x.view(size_out)
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return x
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@clear_cache_before_run()
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def test_coloproxy():
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tracer = ColoTracer()
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model = Conv1D(3, 3)
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input_sample = {"x": torch.rand(3, 3).to("meta")}
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graph = tracer.trace(root=model, meta_args=input_sample)
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gm = GraphModule(model, graph, model.__class__.__name__)
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gm.recompile()
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node = list(gm.graph.nodes)[0]
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proxy = ColoProxy(node=node, tracer=tracer)
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proxy.meta_data = torch.empty(4, 2, device="meta")
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assert len(proxy) == 4
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assert proxy.shape[0] == 4 and proxy.shape[1] == 2
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assert proxy.dim() == 2
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assert proxy.dtype == torch.float32
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assert proxy.size(0) == 4
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if __name__ == "__main__":
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test_coloproxy()
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