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Fixed Context Parallel HtoD sync #8557

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merged 2 commits into from
Mar 6, 2024
Merged

Fixed Context Parallel HtoD sync #8557

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d73147f
Fixed cp HtoD sync
Mar 1, 2024
32a4486
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Mar 1, 2024
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4 changes: 3 additions & 1 deletion nemo/collections/nlp/models/language_modeling/megatron_gpt_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -960,7 +960,9 @@ def get_batch_on_this_context_parallel_rank(self, batch):
val.shape[seq_dim] // (2 * cp_size),
*val.shape[(seq_dim + 1) :],
)
index = torch.tensor([cp_rank, (2 * cp_size - cp_rank - 1)], device=val.device)
index = torch.tensor([cp_rank, (2 * cp_size - cp_rank - 1)], device="cpu", pin_memory=True).cuda(
non_blocking=True
)
val = val.index_select(seq_dim, index)
val = val.view(*val.shape[0:seq_dim], -1, *val.shape[(seq_dim + 2) :])
batch[key] = val
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4 changes: 3 additions & 1 deletion nemo/collections/nlp/modules/common/megatron/language_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -726,7 +726,9 @@ def set_input_tensor(self, input_tensor):
def get_position_embedding_on_this_context_parallel_rank(self, position_embedding, seq_dim):
cp_size = parallel_state.get_context_parallel_world_size()
cp_rank = parallel_state.get_context_parallel_rank()
cp_idx = torch.tensor([cp_rank, (2 * cp_size - cp_rank - 1)], device=position_embedding.device)
cp_idx = torch.tensor([cp_rank, (2 * cp_size - cp_rank - 1)], device="cpu", pin_memory=True).cuda(
non_blocking=True
)
position_embedding = position_embedding.view(
*position_embedding.shape[:seq_dim], 2 * cp_size, -1, *position_embedding.shape[(seq_dim + 1) :]
)
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