From 33d3d2084403fd34b79c835d2f2fe04f6cd8f738 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期三, 13 九月 2023 09:33:54 +0800
Subject: [PATCH] Merge branch 'main' of github.com:alibaba-damo-academy/FunASR add
---
funasr/bin/train.py | 105 ++++++++++++++++++++++++++++++++++++----------------
1 files changed, 73 insertions(+), 32 deletions(-)
diff --git a/funasr/bin/train.py b/funasr/bin/train.py
index 3e3f598..f5d10c4 100755
--- a/funasr/bin/train.py
+++ b/funasr/bin/train.py
@@ -1,4 +1,6 @@
#!/usr/bin/env python3
+# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
+# MIT License (https://opensource.org/licenses/MIT)
import argparse
import logging
@@ -16,6 +18,7 @@
from funasr.build_utils.build_scheduler import build_scheduler
from funasr.build_utils.build_trainer import build_trainer
from funasr.text.phoneme_tokenizer import g2p_choices
+from funasr.torch_utils.load_pretrained_model import load_pretrained_model
from funasr.torch_utils.model_summary import model_summary
from funasr.torch_utils.pytorch_version import pytorch_cudnn_version
from funasr.torch_utils.set_all_random_seed import set_all_random_seed
@@ -23,9 +26,9 @@
from funasr.utils.prepare_data import prepare_data
from funasr.utils.types import int_or_none
from funasr.utils.types import str2bool
-from funasr.utils.types import str2triple_str
from funasr.utils.types import str_or_none
from funasr.utils.yaml_no_alias_safe_dump import yaml_no_alias_safe_dump
+from funasr.modules.lora.utils import mark_only_lora_as_trainable
def get_parser():
@@ -161,6 +164,7 @@
)
parser.add_argument(
"--patience",
+ type=int_or_none,
default=None,
help="Number of epochs to wait without improvement "
"before stopping the training",
@@ -260,13 +264,19 @@
"training phase. If None is given, it is decided according the number "
"of training samples automatically .",
)
+ parser.add_argument(
+ "--use_tensorboard",
+ type=str2bool,
+ default=True,
+ help="Enable tensorboard logging",
+ )
# pretrained model related
parser.add_argument(
"--init_param",
type=str,
+ action="append",
default=[],
- nargs="*",
help="Specify the file path used for initialization of parameters. "
"The format is '<file_path>:<src_key>:<dst_key>:<exclude_keys>', "
"where file_path is the model file path, "
@@ -292,7 +302,7 @@
"--freeze_param",
type=str,
default=[],
- nargs="*",
+ action="append",
help="Freeze parameters",
)
@@ -310,41 +320,35 @@
help=f"The keyword arguments for dataset",
)
parser.add_argument(
- "--train_data_file",
+ "--data_dir",
type=str,
default=None,
- help="train_list for large dataset",
+ help="root path of data",
)
parser.add_argument(
- "--valid_data_file",
+ "--train_set",
type=str,
+ default="train",
+ help="train dataset",
+ )
+ parser.add_argument(
+ "--valid_set",
+ type=str,
+ default="validation",
+ help="dev dataset",
+ )
+ parser.add_argument(
+ "--data_file_names",
+ type=str,
+ default="wav.scp,text",
+ help="input data files",
+ )
+ parser.add_argument(
+ "--speed_perturb",
+ type=float,
+ nargs="+",
default=None,
- help="valid_list for large dataset",
- )
- parser.add_argument(
- "--train_data_path_and_name_and_type",
- type=str2triple_str,
- action="append",
- default=[],
- help="e.g. '--train_data_path_and_name_and_type some/path/a.scp,foo,sound'. ",
- )
- parser.add_argument(
- "--valid_data_path_and_name_and_type",
- type=str2triple_str,
- action="append",
- default=[],
- )
- parser.add_argument(
- "--train_shape_file",
- type=str,
- action="append",
- default=[],
- )
- parser.add_argument(
- "--valid_shape_file",
- type=str,
- action="append",
- default=[],
+ help="speed perturb",
)
parser.add_argument(
"--use_preprocessor",
@@ -475,6 +479,18 @@
default=None,
help="oss bucket.",
)
+ parser.add_argument(
+ "--enable_lora",
+ type=str2bool,
+ default=False,
+ help="Apply lora for finetuning.",
+ )
+ parser.add_argument(
+ "--lora_bias",
+ type=str,
+ default="none",
+ help="lora bias.",
+ )
return parser
@@ -514,6 +530,18 @@
prepare_data(args, distributed_option)
model = build_model(args)
+ model = model.to(
+ dtype=getattr(torch, args.train_dtype),
+ device="cuda" if args.ngpu > 0 else "cpu",
+ )
+ if args.enable_lora:
+ mark_only_lora_as_trainable(model, args.lora_bias)
+ for t in args.freeze_param:
+ for k, p in model.named_parameters():
+ if k.startswith(t + ".") or k == t:
+ logging.info(f"Setting {k}.requires_grad = False")
+ p.requires_grad = False
+
optimizers = build_optimizer(args, model=model)
schedulers = build_scheduler(args, optimizers)
@@ -521,6 +549,7 @@
distributed_option.dist_rank,
distributed_option.local_rank))
logging.info(pytorch_cudnn_version())
+ logging.info("Args: {}".format(args))
logging.info(model_summary(model))
logging.info("Optimizer: {}".format(optimizers))
logging.info("Scheduler: {}".format(schedulers))
@@ -537,6 +566,18 @@
else:
yaml_no_alias_safe_dump(vars(args), f, indent=4, sort_keys=False)
+ for p in args.init_param:
+ logging.info(f"Loading pretrained params from {p}")
+ load_pretrained_model(
+ model=model,
+ init_param=p,
+ ignore_init_mismatch=args.ignore_init_mismatch,
+ map_location=f"cuda:{torch.cuda.current_device()}"
+ if args.ngpu > 0
+ else "cpu",
+ oss_bucket=args.oss_bucket,
+ )
+
# dataloader for training/validation
train_dataloader, valid_dataloader = build_dataloader(args)
--
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