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76 lines
2.5 KiB
76 lines
2.5 KiB
import torch
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import torch.distributed as dist
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from torch.distributed.distributed_c10d import _get_default_group
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from torch.testing import assert_close
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from colossalai import launch
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from colossalai.accelerator import get_accelerator
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from colossalai.quantization.fp8 import all_to_all_single_fp8
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from colossalai.testing import parameterize, rerun_if_address_is_in_use, spawn
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@parameterize("shape", [(4,), (1, 8, 16), (4, 8, 16)])
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@parameterize("dtype", [torch.bfloat16, torch.float16])
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@parameterize("async_op", [True, False])
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def check_all2all(shape, dtype, async_op):
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x = torch.rand(shape, dtype=dtype, device=get_accelerator().get_current_device())
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output = torch.empty_like(x)
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output_fp8 = torch.empty_like(x)
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origin_hanle = dist.all_to_all_single(output, x, group=_get_default_group(), async_op=async_op)
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fp8_handle = all_to_all_single_fp8(output_fp8, x, group=_get_default_group(), async_op=async_op)
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if async_op:
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origin_hanle.wait()
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fp8_handle.wait()
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assert_close(output, output_fp8, rtol=0.1, atol=0.1)
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@parameterize("shape", [(8, 8, 16)])
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@parameterize("dtype", [torch.bfloat16, torch.float16])
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@parameterize("async_op", [True, False])
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def check_all2all_uneven(shape, dtype, async_op):
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x = torch.rand(shape, dtype=dtype, device=get_accelerator().get_current_device())
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input_split_sizes = [3, 3, 1, 1]
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if dist.get_rank() in [0, 1]:
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output_split_sizes = [3, 3, 3, 3]
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else:
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output_split_sizes = [1, 1, 1, 1]
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output_shape = list(shape)
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output_shape[0] = sum(output_split_sizes)
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output = torch.empty(output_shape, device=x.device, dtype=x.dtype)
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output_fp8 = torch.empty(output_shape, device=x.device, dtype=x.dtype)
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origin_hanle = dist.all_to_all_single(
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output,
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x,
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output_split_sizes=output_split_sizes,
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input_split_sizes=input_split_sizes,
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group=_get_default_group(),
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async_op=async_op,
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)
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fp8_handle = all_to_all_single_fp8(
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output_fp8,
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x,
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output_split_sizes=output_split_sizes,
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input_split_sizes=input_split_sizes,
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group=_get_default_group(),
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async_op=async_op,
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)
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if async_op:
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origin_hanle.wait()
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fp8_handle.wait()
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assert_close(output, output_fp8, rtol=0.1, atol=0.1)
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def run_dist(rank, world_size, port):
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launch(rank=rank, world_size=world_size, port=port, host="localhost")
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check_all2all()
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check_all2all_uneven()
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@rerun_if_address_is_in_use()
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def test_all_to_all_single():
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spawn(run_dist, 4)
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if __name__ == "__main__":
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test_all_to_all_single()
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