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[webui] upgrade webui and fix api (#8460)

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This commit is contained in:
Yaowei Zheng
2025-06-25 21:59:58 +08:00
committed by GitHub
parent f276b9a963
commit 4407231a3b
9 changed files with 109 additions and 27 deletions
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42
src/llamafactory/webui/runner.py
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@@ -16,14 +16,13 @@ import json
import os
from collections.abc import Generator
from copy import deepcopy
from subprocess import Popen, TimeoutExpired
from subprocess import PIPE, Popen, TimeoutExpired
from typing import TYPE_CHECKING, Any, Optional
from transformers.trainer import TRAINING_ARGS_NAME
from transformers.utils import is_torch_npu_available
from ..extras.constants import LLAMABOARD_CONFIG, MULTIMODAL_SUPPORTED_MODELS, PEFT_METHODS, TRAINING_STAGES
from ..extras.misc import is_accelerator_available, torch_gc, use_ray
from ..extras.misc import is_accelerator_available, torch_gc
from ..extras.packages import is_gradio_available
from .common import (
DEFAULT_CACHE_DIR,
@@ -114,7 +113,7 @@ class Runner:
return ""
def _finalize(self, lang: str, finish_info: str) -> str:
def _finalize(self, lang: str, finish_info: str) -> None:
r"""Clean the cached memory and resets the runner."""
finish_info = ALERTS["info_aborted"][lang] if self.aborted else finish_info
gr.Info(finish_info)
@@ -123,7 +122,6 @@ class Runner:
self.running = False
self.running_data = None
torch_gc()
return finish_info
def _parse_train_args(self, data: dict["Component", Any]) -> dict[str, Any]:
r"""Build and validate the training arguments."""
@@ -314,11 +312,13 @@ class Runner:
max_samples=int(get("eval.max_samples")),
per_device_eval_batch_size=get("eval.batch_size"),
predict_with_generate=True,
report_to="none",
max_new_tokens=get("eval.max_new_tokens"),
top_p=get("eval.top_p"),
temperature=get("eval.temperature"),
output_dir=get_save_dir(model_name, finetuning_type, get("eval.output_dir")),
trust_remote_code=True,
ddp_timeout=180000000,
)
if get("eval.predict"):
@@ -375,7 +375,7 @@ class Runner:
env["FORCE_TORCHRUN"] = "1"
# NOTE: DO NOT USE shell=True to avoid security risk
self.trainer = Popen(["llamafactory-cli", "train", save_cmd(args)], env=env)
self.trainer = Popen(["llamafactory-cli", "train", save_cmd(args)], env=env, stderr=PIPE, text=True)
yield from self.monitor()
def _build_config_dict(self, data: dict["Component", Any]) -> dict[str, Any]:
@@ -417,7 +417,8 @@ class Runner:
swanlab_link = self.manager.get_elem_by_id("train.swanlab_link") if self.do_train else None
running_log = ""
while self.trainer is not None:
return_code = -1
while return_code == -1:
if self.aborted:
yield {
output_box: ALERTS["info_aborting"][lang],
@@ -436,27 +437,26 @@ class Runner:
return_dict[swanlab_link] = running_info["swanlab_link"]
yield return_dict
try:
self.trainer.wait(2)
self.trainer = None
stderr = self.trainer.communicate(timeout=2)[1]
return_code = self.trainer.returncode
except TimeoutExpired:
continue
if self.do_train:
if os.path.exists(os.path.join(output_path, TRAINING_ARGS_NAME)) or use_ray():
finish_info = ALERTS["info_finished"][lang]
if return_code == 0:
finish_info = ALERTS["info_finished"][lang]
if self.do_train:
finish_log = ALERTS["info_finished"][lang] + "\n\n" + running_log
else:
finish_info = ALERTS["err_failed"][lang]
finish_log = load_eval_results(os.path.join(output_path, "all_results.json")) + "\n\n" + running_log
else:
if os.path.exists(os.path.join(output_path, "all_results.json")) or use_ray():
finish_info = load_eval_results(os.path.join(output_path, "all_results.json"))
else:
finish_info = ALERTS["err_failed"][lang]
print(stderr)
finish_info = ALERTS["err_failed"][lang]
finish_log = ALERTS["err_failed"][lang] + f" Exit code: {return_code}\n\n```\n{stderr}\n```\n"
return_dict = {
output_box: self._finalize(lang, finish_info) + "\n\n" + running_log,
progress_bar: gr.Slider(visible=False),
}
self._finalize(lang, finish_info)
return_dict = {output_box: finish_log, progress_bar: gr.Slider(visible=False)}
yield return_dict
def save_args(self, data):