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from .dist_flash_attn.prepare_input import prepare_dist_flash_attn_inputs
from .dist_flash_attn.monkey_patch import apply_dist_flash_attn_monkey_patch_llama
from .zigzag_ring_attn.prepare_inputs import prepare_zigzag_ring_attn_inputs
from .zigzag_ring_attn.monkey_patch import apply_zigzag_ring_attn_monkey_patch_llama
from .zigzag_ring_attn.monkey_patch import apply_zigzag_ring_attn_monkey_patch_mistral
from .unsloth_offloaded_gradient_checkpoint.monkey_patch import apply_unsloth_offloaded_gradient_checkpoint_monkey_patch
from .ulysses_attn.prepare_inputs import prepare_ulysses_attn_inputs
from .ulysses_attn.monkey_patch import apply_ulysses_attn_monkey_patch_llama
from .modeling_qwen2 import Qwen2ForCausalLM_RingAttn
def prepare_seq_parallel_inputs(
seq_algo, input_ids, position_ids, target_ids, rank, world_size, device
):
if seq_algo == "zigzag_ring_attn":
return prepare_zigzag_ring_attn_inputs(
input_ids, position_ids, target_ids, rank, world_size, device
)
elif seq_algo == "dist_flash_attn":
return prepare_dist_flash_attn_inputs(
input_ids, position_ids, target_ids, rank, world_size, device
)
elif seq_algo == "ulysses_attn":
return prepare_ulysses_attn_inputs(
input_ids, position_ids, target_ids, rank, world_size, device
)
elif seq_algo == "data_parallel":
return {
"local_input_ids": input_ids.to(device),
"local_position_ids": position_ids.to(device),
"local_target_ids": target_ids.to(device),
}
else:
raise ValueError(f"Invalid seq_algo: {seq_algo}")
def apply_seq_parallel_monkey_patch(
seq_algo, model
):
assert seq_algo in ["zigzag_ring_attn", "dist_flash_attn", "ulysses_attn", "data_parallel"], f"Invalid seq_algo: {seq_algo}"
assert model in ["llama", "mistral"], f"Invalid model: {model}"
if seq_algo == "data_parallel":
return
elif seq_algo == "zigzag_ring_attn" and model == "llama":
apply_zigzag_ring_attn_monkey_patch_llama()
elif seq_algo == "zigzag_ring_attn" and model == "mistral":
apply_zigzag_ring_attn_monkey_patch_mistral()
elif seq_algo == "dist_flash_attn" and model == "llama":
apply_dist_flash_attn_monkey_patch_llama()
elif seq_algo == "ulysses_attn" and model == "llama":
apply_ulysses_attn_monkey_patch_llama()
else:
raise ValueError(f"Invalid seq_algo: {seq_algo} or model: {model}")
def prepare_dataloader(seq_algo, dataloader, acclerator):
if seq_algo == "data_parallel":
return acclerator.prepare(dataloader)
else:
return dataloader |