Upload train_autogrow.py with huggingface_hub

train_autogrow.py

@@ -93,7 +93,8 @@ def run_test(model, tokenizer, step):
         for i in range(10):
             t = torch.tensor([1000 - (i*100) - 1], device="cuda").long()
             pred = model(torch.cat([p_emb, r_noise], dim=1), t)
-            r_noise = 0.4 * r_noise + 0.6 * pred[:, MAX_PROMPT_LEN:, :]
+            r_0_pred = pred[:, MAX_PROMPT_LEN:, :]
+            r_noise = 0.4 * r_noise + 0.6 * r_0_pred
         norm_weights = F.normalize(model.token_embedding.weight, dim=-1)
         norm_r = F.normalize(r_noise, dim=-1)
         logits = torch.matmul(norm_r, norm_weights.T)
@@ -148,6 +149,7 @@ if __name__ == "__main__":
                 log("Syncing to HF...")
                 try: 
                     api.upload_file(path_or_fileobj=ckpt_path, path_in_repo=f"cropmark_{step}.pt", repo_id=REPO_ID, token=HF_TOKEN)
+                    api.upload_file(path_or_fileobj=CHECKPOINT_LOG, path_in_repo="checkpoint_log.txt", repo_id=REPO_ID, token=HF_TOKEN)
                     api.upload_file(path_or_fileobj="train_autogrow.py", path_in_repo="train_autogrow.py", repo_id=REPO_ID, token=HF_TOKEN)
                 except Exception as e: log(f"HF Sync Error: {e}")
             step += 1