From 4ace5a95b052d338947fc88809a440ccd55cf6b4 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期四, 16 十一月 2023 16:39:52 +0800
Subject: [PATCH] funasr pages

---
 funasr/train/trainer.py |   26 ++++++++++++++++++++------
 1 files changed, 20 insertions(+), 6 deletions(-)

diff --git a/funasr/train/trainer.py b/funasr/train/trainer.py
index 4f83ace..27d6f9c 100644
--- a/funasr/train/trainer.py
+++ b/funasr/train/trainer.py
@@ -26,7 +26,6 @@
 import torch
 import torch.nn
 import torch.optim
-from typeguard import check_argument_types
 
 from funasr.iterators.abs_iter_factory import AbsIterFactory
 from funasr.main_funcs.average_nbest_models import average_nbest_models
@@ -44,6 +43,7 @@
 from funasr.train.reporter import Reporter
 from funasr.train.reporter import SubReporter
 from funasr.utils.build_dataclass import build_dataclass
+from funasr.utils.kwargs2args import kwargs2args
 
 if torch.distributed.is_available():
     from torch.distributed import ReduceOp
@@ -126,7 +126,6 @@
     @classmethod
     def build_options(cls, args: argparse.Namespace) -> TrainerOptions:
         """Build options consumed by train(), eval()"""
-        assert check_argument_types()
         return build_dataclass(TrainerOptions, args)
 
     @classmethod
@@ -187,7 +186,6 @@
         distributed_option: DistributedOption,
     ) -> None:
         """Perform training. This method performs the main process of training."""
-        assert check_argument_types()
         # NOTE(kamo): Don't check the type more strictly as far trainer_options
         assert is_dataclass(trainer_options), type(trainer_options)
         assert len(optimizers) == len(schedulers), (len(optimizers), len(schedulers))
@@ -371,7 +369,7 @@
                             ],
                             "scaler": scaler.state_dict() if scaler is not None else None,
                             "ema_model": model.encoder.ema.model.state_dict()
-                            if hasattr(model.encoder, "ema") and model.encoder.ema is not None else None,
+                            if hasattr(model, "encoder") and hasattr(model.encoder, "ema") and model.encoder.ema is not None else None,
                         },
                         buffer,
                     )
@@ -550,7 +548,6 @@
         options: TrainerOptions,
         distributed_option: DistributedOption,
     ) -> Tuple[bool, bool]:
-        assert check_argument_types()
 
         grad_noise = options.grad_noise
         accum_grad = options.accum_grad
@@ -619,6 +616,24 @@
             if no_forward_run:
                 all_steps_are_invalid = False
                 continue
+
+            if iiter == 1 and summary_writer is not None:
+                try:
+                    args = kwargs2args(model.forward, batch)
+                except (ValueError, TypeError):
+                    logging.warning(
+                        "inpect.signature() is failed for the model. "
+                        "The graph can't be added for tensorboard."
+                    )
+                else:
+                    try:
+                        summary_writer.add_graph(model, args, use_strict_trace=False)
+                    except Exception:
+                        logging.warning(
+                            "summary_writer.add_graph() is failed for the model. "
+                            "The graph can't be added for tensorboard."
+                        )
+                    del args
 
             with autocast(scaler is not None):
                 with reporter.measure_time("forward_time"):
@@ -826,7 +841,6 @@
         options: TrainerOptions,
         distributed_option: DistributedOption,
     ) -> None:
-        assert check_argument_types()
         ngpu = options.ngpu
         no_forward_run = options.no_forward_run
         distributed = distributed_option.distributed

--
Gitblit v1.9.1