Merge pull request #614 from milosgajdos/smol-cleanup

Small clean up of empty chars and unusued vars.

docker-compose.runner.yaml

@@ -4,9 +4,9 @@ services:
     restart: always
     build:
       context: .
-      dockerfile: Dockerfile.runner    
+      dockerfile: Dockerfile.runner
     network_mode: "host" # So the runner can access the control plane that is running on the host
-    volumes:      
+    volumes:
       - ~/.cache/huggingface:/root/.cache/huggingface
     environment:
       - RUNNER_ID=local-dev-runner

install.sh

@@ -292,7 +292,7 @@ fi
 # Function to gather planned modifications
 gather_modifications() {
     local modifications=""
-    
+
     if [ "$CLI" = true ]; then
         modifications+="  - Install Helix CLI version ${LATEST_RELEASE}\n"
     fi
@@ -309,7 +309,7 @@ gather_modifications() {
         modifications+="  - Ensure NVIDIA Docker runtime is installed\n"
         modifications+="  - Install Helix Runner version ${LATEST_RELEASE}\n"
     fi
-    
+
     echo -e "$modifications"
 }
 
@@ -318,7 +318,7 @@ ask_for_approval() {
     if [ "$AUTO_APPROVE" = true ]; then
         return 0
     fi
-    
+
     echo "┌───────────────────────────────────────────────────────────────────────────┐"
     echo "│ The following modifications will be made to your system:                  │"
     echo "└───────────────────────────────────────────────────────────────────────────┘"
@@ -331,7 +331,7 @@ ask_for_approval() {
     echo
     read -p "Do you want to proceed? (y/N) " response
     case "$response" in
-        [yY][eE][sS]|[yY]) 
+        [yY][eE][sS]|[yY])
             return 0
             ;;
         *)
@@ -490,7 +490,7 @@ EOF
     ENV_FILE="$INSTALL_DIR/.env"
     echo -e "\nCreating/updating .env file..."
     echo
-    
+
     # Default to localhost if it wasn't passed
     if [ -z "$API_HOST" ]; then
         API_HOST="http://localhost:8080"

runner/helix-llama3.2-instruct-1b-v1.yml

@@ -1,6 +1,6 @@
 # Compare this file with
 # https://github.com/axolotl-ai-cloud/axolotl/blob/main/examples/llama-3/instruct-lora-8b.yml and
-# https://github.com/axolotl-ai-cloud/axolotl/blob/main/examples/llama-3/qlora.yml 
+# https://github.com/axolotl-ai-cloud/axolotl/blob/main/examples/llama-3/qlora.yml
 
 base_model: unsloth/Llama-3.2-1B-Instruct
 model_type: LlamaForCausalLM
@@ -84,4 +84,4 @@ special_tokens:
 datasets:
   - path: teknium/GPT4-LLM-Cleaned
     type: alpaca
-output_dir: ./outputs/qlora-out
+output_dir: ./outputs/qlora-out

runner/sdxl_finetune.py

@@ -4,6 +4,7 @@
 import time
 import json
 
+
 def do_inference():
     getJobURL = os.environ.get("HELIX_NEXT_TASK_URL", None)
     readSessionURL = os.environ.get("HELIX_INITIAL_SESSION_URL", "")
@@ -15,22 +16,19 @@ def do_inference():
 
     if readSessionURL == "":
         sys.exit("HELIX_INITIAL_SESSION_URL is not set")
-
-    lora_dir = ""
+
     waiting_for_initial_session = True
 
     while waiting_for_initial_session:
         response = requests.get(readSessionURL)
         if response.status_code != 200:
             time.sleep(0.1)
             continue
-
-        session = json.loads(response.content)
+
         waiting_for_initial_session = False
-        lora_dir = session["lora_dir"]
 
     session_id = ""
-    
+
     while True:
         currentJobData = ""
 
@@ -56,16 +54,18 @@ def do_inference():
             time.sleep(int(mockDelay))
 
         task = json.loads(currentJobData)
-        instruction: str = task["prompt"]
         session_id = task["session_id"]
         dir_path = os.getcwd() + "/runner/fixtures"
         print(f" [SESSION_START]session_id={session_id} ", file=sys.stdout, flush=True)
         print("steps:\n")
         for i in range(1, 101):
-          print(f"{i}%|\n")
-          time.sleep(0.1)
-
-        print(f" [SESSION_END_LORA_DIR]lora_dir={dir_path} ", file=sys.stdout, flush=True)
+            print(f"{i}%|\n")
+            time.sleep(0.1)
+
+        print(
+            f" [SESSION_END_LORA_DIR]lora_dir={dir_path} ", file=sys.stdout, flush=True
+        )
+
 
 if __name__ == "__main__":
-    do_inference()
+    do_inference()

runner/sdxl_inference.py

@@ -5,10 +5,12 @@
 import json
 import builtins
 
+
 def print(*args, **kwargs):
-    kwargs['flush'] = True
+    kwargs["flush"] = True
     return builtins.print(*args, **kwargs)
 
+
 def do_inference():
     getJobURL = os.environ.get("HELIX_NEXT_TASK_URL", None)
     readSessionURL = os.environ.get("HELIX_INITIAL_SESSION_URL", "")
@@ -20,7 +22,7 @@ def do_inference():
 
     if readSessionURL == "":
         sys.exit("HELIX_INITIAL_SESSION_URL is not set")
-    
+
     lora_dir = ""
     waiting_for_initial_session = True
 
@@ -29,17 +31,19 @@ def do_inference():
         if response.status_code != 200:
             time.sleep(0.1)
             continue
-        
+
         session = json.loads(response.content)
         waiting_for_initial_session = False
         lora_dir = session["lora_dir"]
 
     if lora_dir != "":
-        print("🟡🟡🟡 SDXL Lora dir --------------------------------------------------\n")
+        print(
+            "🟡🟡🟡 SDXL Lora dir --------------------------------------------------\n"
+        )
         print(lora_dir)
 
     session_id = ""
-    
+
     while True:
         currentJobData = ""
 
@@ -62,16 +66,20 @@ def do_inference():
             time.sleep(int(mockDelay))
 
         task = json.loads(currentJobData)
-        instruction: str = task["prompt"]
         session_id = task["session_id"]
         image_path = os.getcwd() + "/runner/fixtures/image.png"
         print(f" [SESSION_START]session_id={session_id} ", file=sys.stdout, flush=True)
 
         for i in range(1, 101):
-          print(f"{i}%|\n")
-          time.sleep(0.1)
-
-        print(f" [SESSION_END_IMAGES]images=[\"{image_path}\"] ", file=sys.stdout, flush=True)
+            print(f"{i}%|\n")
+            time.sleep(0.1)
+
+        print(
+            f' [SESSION_END_IMAGES]images=["{image_path}"] ',
+            file=sys.stdout,
+            flush=True,
+        )
+
 
 if __name__ == "__main__":
-    do_inference()
+    do_inference()