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[legacy] clean up legacy code (#4743)
* [legacy] remove outdated codes of pipeline (#4692) * [legacy] remove cli of benchmark and update optim (#4690) * [legacy] remove cli of benchmark and update optim * [doc] fix cli doc test * [legacy] fix engine clip grad norm * [legacy] remove outdated colo tensor (#4694) * [legacy] remove outdated colo tensor * [test] fix test import * [legacy] move outdated zero to legacy (#4696) * [legacy] clean up utils (#4700) * [legacy] clean up utils * [example] update examples * [legacy] clean up amp * [legacy] fix amp module * [legacy] clean up gpc (#4742) * [legacy] clean up context * [legacy] clean core, constants and global vars * [legacy] refactor initialize * [example] fix examples ci * [example] fix examples ci * [legacy] fix tests * [example] fix gpt example * [example] fix examples ci * [devops] fix ci installation * [example] fix examples ci
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@@ -1,7 +1,8 @@
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from colossalai.context.parallel_mode import ParallelMode
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import torch
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import torch.nn as nn
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from colossalai.core import global_context as gpc
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from colossalai.legacy.context.parallel_mode import ParallelMode
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from colossalai.legacy.core import global_context as gpc
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class PreProcessor(nn.Module):
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@@ -14,8 +15,8 @@ class PreProcessor(nn.Module):
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# Create position ids
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seq_length = token_ids.size(1)
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local_rank = gpc.get_local_rank(ParallelMode.SEQUENCE)
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position_ids = torch.arange(seq_length*local_rank,
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seq_length * (local_rank+1),
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position_ids = torch.arange(seq_length * local_rank,
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seq_length * (local_rank + 1),
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dtype=torch.long,
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device=token_ids.device)
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position_ids = position_ids.unsqueeze(0).expand_as(token_ids)
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