huggingface/text-generation-inference
5
0
Fork 0
mirror of https://github.com/huggingface/text-generation-inference.git synced 2025-04-22 15:32:08 +00:00
Code Issues Packages Projects Releases Wiki Activity

format codfe'

Browse Source
This commit is contained in:
Mohit Sharma 2025-01-29 10:39:09 +00:00
parent 57de05b0dd
commit 05d0aa678e
3 changed files with 7 additions and 20 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

10
server/text_generation_server/layers/fp8.py
View File

@ -1,11 +1,11 @@
from dataclasses import dataclass
import os
from typing import Optional, Tuple, Type, Union, List
from moe_kernels.fp8_utils import w8a8_block_fp8_matmul, per_token_group_quant_fp8
import torch
from loguru import logger
from moe_kernels import w8a8_block_fp8_matmul, per_token_group_quant_fp8
from text_generation_server.utils.import_utils import SYSTEM
from text_generation_server.utils.weights import (
Weight,
@ -187,8 +187,6 @@ class HybridFP8UnquantLoader(WeightsLoader):
if w.dtype == torch.float8_e4m3fn:
if self.weight_block_size is not None:
scale = weights.get_tensor(f"{prefix}.weight_scale_inv")
if scale.device == torch.device("cpu"):
scale = scale.to(weights.device)
return Fp8Weight(
weight=w,
weight_scale=scale,
@ -289,9 +287,7 @@ class HybridFP8UnquantLoader(WeightsLoader):
weights.get_sharded(f"{p}.weight_scale_inv", dim=0, to_device=False)
for p in prefixes
]
scale = torch.cat(scale, dim=dim)
if scale.device == torch.device("cpu"):
scale = scale.to(weights.device)
scale = torch.cat(scale, dim=dim).to(weights.device)
return Fp8Weight(
weight=w,
weight_scale=scale,
@ -347,8 +343,6 @@ class HybridFP8UnquantLoader(WeightsLoader):
if w.dtype == torch.float8_e4m3fn:
if self.weight_block_size is not None:
scale = weights.get_sharded(f"{prefix}.weight_scale_inv", dim=1)
if scale.device == torch.device("cpu"):
scale = scale.to(weights.device)
return Fp8Weight(
weight=w,

7
server/text_generation_server/utils/quantization.py
View File

@ -60,6 +60,7 @@ def _get_quantizer_config(model_id, revision):
return _FP8QuantizerConfig(
activation_scale_ub=data["quantization_config"]["activation_scale_ub"]
)
weight_block_size = data["quantization_config"].get("weight_block_size", None)
if "zero_point" in data["quantization_config"]:
sym = not data["quantization_config"]["zero_point"]
@ -67,16 +68,12 @@ def _get_quantizer_config(model_id, revision):
elif "sym" in data["quantization_config"]:
sym = data["quantization_config"]["sym"]
if "bits" in data["quantization_config"]:
bits = data["quantization_config"]["bits"]
if "group_size" in data["quantization_config"]:
groupsize = data["quantization_config"]["group_size"]
# Order is important here, desc_act is missing on some real models
quant_method = data["quantization_config"]["quant_method"]
checkpoint_format = data["quantization_config"].get("checkpoint_format", None)
if desc_act in data["quantization_config"]:
checkpoint_format = data["quantization_config"].get("checkpoint_format")
desc_act = data["quantization_config"]["desc_act"]
weight_block_size = data["quantization_config"].get("weight_block_size", None)
except Exception:
filename = "quantize_config.json"
try:

4
server/text_generation_server/utils/weights.py
View File

@ -149,10 +149,6 @@ class Weights:
):
routing = {}
for filename in filenames:
# if filename.as_posix().endswith("l.safetensors"):
# from loguru import logger
# logger.info(f"Skipping {filename}")
# continue
with safe_open(filename, framework="pytorch") as f:
for k in f.keys():
if k in routing: