Revert to Gradio 5.49.1 and ASCII logs

README.md

@@ -4,8 +4,7 @@ emoji: "⚡"
 colorFrom: blue
 colorTo: purple
 sdk: gradio
-sdk_version: 4.44.1
-python_version: "3.10"
+sdk_version: 5.49.1
 app_file: app.py
 pinned: false
 license: mit

app.py

@@ -18,10 +18,10 @@ startup_log = []
 def check_import(name, import_fn):
     try:
         result = import_fn()
-        startup_log.append(f"✓ {name}: {result}")
+        startup_log.append(f"[OK] {name}: {result}")
         return True
     except Exception as e:
-        startup_log.append(f"✗ {name}: {str(e)[:80]}")
+        startup_log.append(f"[ERR] {name}: {str(e)[:80]}")
         return False
 
 check_import("torch", lambda: __import__("torch").__version__)
@@ -33,18 +33,18 @@ check_import("huggingface_hub", lambda: __import__("huggingface_hub").__version_
 
 try:
     from trl import GRPOConfig, GRPOTrainer
-    startup_log.append("✓ GRPOTrainer: OK")
+    startup_log.append("[OK] GRPOTrainer: OK")
 except Exception as e:
-    startup_log.append(f"✗ GRPOTrainer: {e}")
+    startup_log.append(f"[ERR] GRPOTrainer: {e}")
 
 try:
     import torch
     if torch.cuda.is_available():
-        startup_log.append(f"✓ CUDA: {torch.cuda.get_device_name(0)}")
+        startup_log.append(f"[OK] CUDA: {torch.cuda.get_device_name(0)}")
     else:
-        startup_log.append("✗ CUDA: Not available")
+        startup_log.append("[ERR] CUDA: Not available")
 except Exception as e:
-    startup_log.append(f"✗ CUDA check: {e}")
+    startup_log.append(f"[ERR] CUDA check: {e}")
 
 # Prefer simulator + KernelBuilder from bundled original_performance_takehome.
 # In Spaces, this keeps evaluation consistent and enables correctness checks.
@@ -61,19 +61,19 @@ try:
         SLOT_LIMITS, VLEN, N_CORES, SCRATCH_SIZE, CoreState
     )
     from perf_takehome import KernelBuilder, HASH_STAGES
-    startup_log.append("✓ VLIW Simulator: OK")
+    startup_log.append("[OK] VLIW Simulator: OK")
     SIMULATOR_AVAILABLE = True
 except Exception as e:
-    startup_log.append(f"✗ VLIW Simulator: {e}")
+    startup_log.append(f"[ERR] VLIW Simulator: {e}")
     SIMULATOR_AVAILABLE = False
 
 # Hugging Face Hub adapter persistence via dataset repo
 try:
     from huggingface_hub import HfApi, snapshot_download
-    startup_log.append("✓ huggingface_hub: OK")
+    startup_log.append("[OK] huggingface_hub: OK")
     HF_HUB_AVAILABLE = True
 except Exception as e:
-    startup_log.append(f"✗ huggingface_hub: {str(e)[:80]}")
+    startup_log.append(f"[ERR] huggingface_hub: {str(e)[:80]}")
     HF_HUB_AVAILABLE = False
 
 # Constants
@@ -142,7 +142,7 @@ def _adapter_exists(path: str) -> bool:
 
 def _try_download_adapter(add_log) -> None:
     if not HF_HUB_AVAILABLE:
-        add_log("✗ Hub sync disabled: huggingface_hub not available")
+        add_log("[ERR] Hub sync disabled: huggingface_hub not available")
         return
     _ensure_dir(os.path.dirname(ADAPTER_DIR))
     allow = [f"{ADAPTER_DATASET_SUBDIR}/**"]
@@ -170,7 +170,7 @@ def _try_download_adapter(add_log) -> None:
                         dst = os.path.join(dst_root, name)
                         with open(src, "rb") as fsrc, open(dst, "wb") as fdst:
                             fdst.write(fsrc.read())
-            add_log(f"✓ Downloaded adapter from dataset: {ADAPTER_DATASET_REPO}/{ADAPTER_DATASET_SUBDIR}")
+            add_log(f"[OK] Downloaded adapter from dataset: {ADAPTER_DATASET_REPO}/{ADAPTER_DATASET_SUBDIR}")
         else:
             add_log("ℹ No adapter found in dataset yet")
     except Exception as e:
@@ -179,7 +179,7 @@ def _try_download_adapter(add_log) -> None:
 
 def _try_upload_adapter(add_log) -> None:
     if not HF_HUB_AVAILABLE:
-        add_log("✗ Hub sync disabled: huggingface_hub not available")
+        add_log("[ERR] Hub sync disabled: huggingface_hub not available")
         return
     if not _adapter_exists(ADAPTER_DIR):
         add_log("ℹ No adapter to upload yet")
@@ -198,7 +198,7 @@ def _try_upload_adapter(add_log) -> None:
             path_in_repo=ADAPTER_DATASET_SUBDIR,
             commit_message="Update perf_takehome adapter",
         )
-        add_log(f"✓ Uploaded adapter to dataset: {ADAPTER_DATASET_REPO}/{ADAPTER_DATASET_SUBDIR}")
+        add_log(f"[OK] Uploaded adapter to dataset: {ADAPTER_DATASET_REPO}/{ADAPTER_DATASET_SUBDIR}")
     except Exception as e:
         add_log(f"ℹ Adapter upload skipped: {str(e)[:160]}")
 
@@ -496,7 +496,7 @@ def run_training(model_name, chunk_steps, max_total_steps, max_minutes, auto_con
         tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
         if tokenizer.pad_token is None:
             tokenizer.pad_token = tokenizer.eos_token
-        add_log("✓ Tokenizer ready")
+        add_log("[OK] Tokenizer ready")
 
         # Load model with 4-bit quantization
         add_log("Loading model (4-bit quantization)...")
@@ -511,7 +511,7 @@ def run_training(model_name, chunk_steps, max_total_steps, max_minutes, auto_con
             device_map="auto",
             trust_remote_code=True,
         )
-        add_log(f"✓ Base model loaded on {next(base_model.parameters()).device}")
+        add_log(f"[OK] Base model loaded on {next(base_model.parameters()).device}")
 
         # Try to restore adapter from dataset before loading it
         _try_download_adapter(add_log)
@@ -521,7 +521,7 @@ def run_training(model_name, chunk_steps, max_total_steps, max_minutes, auto_con
         if os.path.isdir(ADAPTER_DIR) and os.path.exists(os.path.join(ADAPTER_DIR, "adapter_config.json")):
             add_log("Loading existing LoRA adapter (resume)...")
             model = PeftModel.from_pretrained(base_model, ADAPTER_DIR, is_trainable=True)
-            add_log("✓ Adapter loaded")
+            add_log("[OK] Adapter loaded")
             resume_adapter = True
         else:
             model = base_model
@@ -530,7 +530,7 @@ def run_training(model_name, chunk_steps, max_total_steps, max_minutes, auto_con
         add_log("Creating VLIW optimization dataset...")
         prompts = [PERF_TAKEHOME_PROMPT] * 16
         dataset = Dataset.from_dict({"prompt": prompts})
-        add_log(f"✓ Dataset ready: {len(prompts)} prompts")
+        add_log(f"[OK] Dataset ready: {len(prompts)} prompts")
 
         # LoRA config
         add_log("Setting up LoRA...")
@@ -571,7 +571,7 @@ def run_training(model_name, chunk_steps, max_total_steps, max_minutes, auto_con
         output_dir = os.path.join(PERSIST_DIR, "grpo_perf_takehome_output")
         os.makedirs(output_dir, exist_ok=True)
 
-        add_log("✓ Trainer config ready")
+        add_log("[OK] Trainer config ready")
         add_log("Starting training loop...")
         add_log("(Stops early if target reached; can auto-continue in chunks)")
 
@@ -632,10 +632,10 @@ def run_training(model_name, chunk_steps, max_total_steps, max_minutes, auto_con
             try:
                 os.makedirs(os.path.dirname(ADAPTER_DIR), exist_ok=True)
                 trainer.save_model(ADAPTER_DIR)
-                add_log(f"✓ Saved adapter to {ADAPTER_DIR}")
+                add_log(f"[OK] Saved adapter to {ADAPTER_DIR}")
                 _try_upload_adapter(add_log)
             except Exception as e:
-                add_log(f"✗ Failed to save adapter: {str(e)[:120]}")
+                add_log(f"[ERR] Failed to save adapter: {str(e)[:120]}")
 
             if not auto_continue:
                 break
@@ -663,11 +663,11 @@ def run_training(model_name, chunk_steps, max_total_steps, max_minutes, auto_con
         else:
             add_log(f"Generated kernel invalid: {verify_out.get('msg', '')[:160]}")
 
-        add_log("\n✓ All done!")
+        add_log("\n[OK] All done!")
 
     except Exception as e:
         import traceback
-        add_log(f"✗ Error: {e}")
+        add_log(f"[ERR] Error: {e}")
         add_log(traceback.format_exc()[:800])
     finally:
         with state_lock:

requirements.txt

@@ -1,10 +1,9 @@
 torch>=2.1.0
 transformers>=4.45.0
-huggingface_hub>=0.22.0,<0.23.0
-datasets==2.18.0
+huggingface_hub>=0.30.0
+datasets>=2.18.0
 peft>=0.13.0
 trl>=0.12.0
 accelerate>=0.34.0
 bitsandbytes>=0.44.0
-gradio>=4.0.0,<5.0.0
-audioop-lts>=0.2.2
+gradio>=5.49.1,<6.0.0