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Zero2: avoid graph breaks in torch.compile by using param_idx #6803
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nelyahu
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inside reduce_independent_p_g_buckets_and_remove_grads and in reduce_ipg_grads which are being executed during the BWD hook in zero2, the model param is being stored inside params_in_ipg_bucket. torch.compile has hard time tracing parameters. By using the param's static index inside the group the same logic can be maintain with less complexity.
tjruwase
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Dec 2, 2024
assign param according to the param idx Co-authored-by: Olatunji Ruwase <[email protected]>
tjruwase
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Dec 12, 2024
loadams
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Dec 16, 2024
@@ -1067,7 +1068,8 @@ def average_tensor(self, tensor): | |||
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process_group = self.dp_process_group | |||
# count = 0 | |||
for i, param, param_id in self.params_in_ipg_bucket: | |||
for i, param_idx_in_group, param_id in self.params_in_ipg_bucket: | |||
param = self.bit16_groups[group_idx][param_idx_in_group] |
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@nelyahu - this is failing on group_idx just fyi
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fixed
fix index value to 'i' instead of 'group_idx'
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inside reduce_independent_p_g_buckets_and_remove_grads and in reduce_ipg_grads which are being executed during the BWD hook in zero2, the model param is being stored inside params_in_ipg_bucket. torch.compile has hard time tracing parameters.
By using the param's static index inside the group the same logic can be maintain with less complexity.