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Support gptq dp #248

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merged 1 commit into from
Dec 9, 2024
Merged

Support gptq dp #248

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8 changes: 8 additions & 0 deletions llmc/compression/quantization/gptq.py
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Original file line number Diff line number Diff line change
@@ -1,10 +1,12 @@
import copy
import functools
import math
import os
from abc import ABCMeta, abstractmethod
from collections import defaultdict

import torch
import torch.distributed as dist
import torch.nn as nn
import transformers
from loguru import logger
Expand Down Expand Up @@ -249,6 +251,7 @@ def cache_input_hook(self, m, inp, out, name, feat_dict):

@torch.no_grad()
def add_batch(self, layer, name, inp, out):
world_size = int(os.environ['WORLD_SIZE'])
if len(inp.shape) == 2:
inp = inp.unsqueeze(0)
tmp = inp.shape[0]
Expand Down Expand Up @@ -279,6 +282,11 @@ def add_batch(self, layer, name, inp, out):
inp = math.sqrt(2 / self.layers_cache[name]['nsamples']) * inp.float()
self.layers_cache[name]['H'] += inp.matmul(inp.t())

dist.all_reduce(self.layers_cache[name]['H'], op=dist.ReduceOp.SUM)
dist.all_reduce(torch.tensor(self.layers_cache[name]['nsamples']).cuda(),
op=dist.ReduceOp.SUM)
self.layers_cache[name]['H'] /= world_size

@torch.no_grad()
def layer_init(self, layer, name):
W = layer.weight.data.clone()
Expand Down
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