From 8d2aa65402c829583e26cdf2c336b8d3057657d6 Mon Sep 17 00:00:00 2001
From: Volpeon <git@volpeon.ink>
Date: Fri, 5 May 2023 10:51:14 +0200
Subject: Update

---
 train_ti.py | 45 ++++++++++++++++++++++++++++++++-------------
 1 file changed, 32 insertions(+), 13 deletions(-)

(limited to 'train_ti.py')

diff --git a/train_ti.py b/train_ti.py
index fce4a5e..ae73639 100644
--- a/train_ti.py
+++ b/train_ti.py
@@ -237,7 +237,13 @@ def parse_args():
         "--offset_noise_strength",
         type=float,
         default=0,
-        help="Perlin offset noise strength.",
+        help="Offset noise strength.",
+    )
+    parser.add_argument(
+        "--input_pertubation",
+        type=float,
+        default=0,
+        help="The scale of input pretubation. Recommended 0.1."
     )
     parser.add_argument(
         "--num_train_epochs",
@@ -406,6 +412,16 @@ def parse_args():
             "and an Nvidia Ampere GPU."
         ),
     )
+    parser.add_argument(
+        "--compile_unet",
+        action="store_true",
+        help="Compile UNet with Torch Dynamo.",
+    )
+    parser.add_argument(
+        "--use_xformers",
+        action="store_true",
+        help="Use xformers.",
+    )
     parser.add_argument(
         "--checkpoint_frequency",
         type=int,
@@ -671,23 +687,24 @@ def main():
     tokenizer.set_dropout(args.vector_dropout)
 
     vae.enable_slicing()
-    vae.set_use_memory_efficient_attention_xformers(True)
-    unet.enable_xformers_memory_efficient_attention()
-    # unet = torch.compile(unet)
+
+    if args.use_xformers:
+        vae.set_use_memory_efficient_attention_xformers(True)
+        unet.enable_xformers_memory_efficient_attention()
 
     if args.gradient_checkpointing:
         unet.enable_gradient_checkpointing()
         text_encoder.gradient_checkpointing_enable()
 
-    convnext = create_model(
-        "convnext_tiny",
-        pretrained=False,
-        num_classes=3,
-        drop_path_rate=0.0,
-    )
-    convnext.to(accelerator.device, dtype=weight_dtype)
-    convnext.requires_grad_(False)
-    convnext.eval()
+    # convnext = create_model(
+    #     "convnext_tiny",
+    #     pretrained=False,
+    #     num_classes=3,
+    #     drop_path_rate=0.0,
+    # )
+    # convnext.to(accelerator.device, dtype=weight_dtype)
+    # convnext.requires_grad_(False)
+    # convnext.eval()
 
     if len(args.alias_tokens) != 0:
         alias_placeholder_tokens = args.alias_tokens[::2]
@@ -822,6 +839,7 @@ def main():
         noise_scheduler=noise_scheduler,
         dtype=weight_dtype,
         seed=args.seed,
+        compile_unet=args.compile_unet,
         guidance_scale=args.guidance_scale,
         prior_loss_weight=args.prior_loss_weight if args.num_class_images != 0 else 0,
         no_val=args.valid_set_size == 0,
@@ -831,6 +849,7 @@ def main():
         milestone_checkpoints=not args.no_milestone_checkpoints,
         global_step_offset=global_step_offset,
         offset_noise_strength=args.offset_noise_strength,
+        input_pertubation=args.input_pertubation,
         # --
         use_emb_decay=args.use_emb_decay,
         emb_decay_target=args.emb_decay_target,
-- 
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