From 5821523a524190490a287c5e2aacb6e72cc3a4cf Mon Sep 17 00:00:00 2001
From: Volpeon <git@volpeon.ink>
Date: Tue, 17 Jan 2023 07:20:45 +0100
Subject: Update

---
 training/functional.py | 19 ++++++++++++++-----
 1 file changed, 14 insertions(+), 5 deletions(-)

(limited to 'training/functional.py')

diff --git a/training/functional.py b/training/functional.py
index 3d27380..7a3e821 100644
--- a/training/functional.py
+++ b/training/functional.py
@@ -39,11 +39,18 @@ class TrainingCallbacks():
     on_train: Callable[[int], _GeneratorContextManager] = const(nullcontext())
     on_before_optimize: Callable[[int], None] = const()
     on_after_optimize: Callable[[float], None] = const()
+    on_after_epoch: Callable[[float], None] = const()
     on_eval: Callable[[], _GeneratorContextManager] = const(nullcontext())
     on_sample: Callable[[int], None] = const()
     on_checkpoint: Callable[[int, str], None] = const()
 
 
+@dataclass
+class TrainingStrategy():
+    callbacks: Callable[..., TrainingCallbacks]
+    prepare_unet: bool = False
+
+
 def make_grid(images, rows, cols):
     w, h = images[0].size
     grid = Image.new('RGB', size=(cols*w, rows*h))
@@ -373,6 +380,7 @@ def train_loop(
     on_train = callbacks.on_train
     on_before_optimize = callbacks.on_before_optimize
     on_after_optimize = callbacks.on_after_optimize
+    on_after_epoch = callbacks.on_after_epoch
     on_eval = callbacks.on_eval
     on_sample = callbacks.on_sample
     on_checkpoint = callbacks.on_checkpoint
@@ -434,6 +442,8 @@ def train_loop(
 
             accelerator.wait_for_everyone()
 
+            on_after_epoch(lr_scheduler.get_last_lr()[0])
+
             if val_dataloader is not None:
                 model.eval()
 
@@ -512,8 +522,7 @@ def train(
     val_dataloader: Optional[DataLoader],
     optimizer: torch.optim.Optimizer,
     lr_scheduler: torch.optim.lr_scheduler._LRScheduler,
-    callbacks_fn: Callable[..., TrainingCallbacks],
-    prepare_unet: bool = False,
+    strategy: TrainingStrategy,
     num_train_epochs: int = 100,
     sample_frequency: int = 20,
     checkpoint_frequency: int = 50,
@@ -524,12 +533,12 @@ def train(
 ):
     prep = [text_encoder, optimizer, train_dataloader, val_dataloader, lr_scheduler]
 
-    if prepare_unet:
+    if strategy.prepare_unet:
         prep.append(unet)
 
     prep = accelerator.prepare(*prep)
 
-    if prepare_unet:
+    if strategy.prepare_unet:
         text_encoder, optimizer, train_dataloader, val_dataloader, lr_scheduler, unet = prep
     else:
         text_encoder, optimizer, train_dataloader, val_dataloader, lr_scheduler = prep
@@ -542,7 +551,7 @@ def train(
         model.requires_grad_(False)
         model.eval()
 
-    callbacks = callbacks_fn(
+    callbacks = strategy.callbacks(
         accelerator=accelerator,
         unet=unet,
         text_encoder=text_encoder,
-- 
cgit v1.2.3-54-g00ecf