step model bin save

change workflow

.github/workflows/python-app.yml

@@ -27,14 +27,11 @@ jobs:
       run: |
         python -m pip install --upgrade pip
         pip install flake8 pytest
+        pip install -e .
         if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
     - name: Lint with flake8
       run: |
         flake8 . --count --show-source --statistics --max-line-length=127 --max-complexity 15
     - name: Test with pytest
       run: |
         pytest
-    - name: Upload coverage reports to Codecov
-      uses: codecov/codecov-action@v3
-      env:
-        CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}

aspen/modelloader.py

@@ -122,10 +122,10 @@ def load_random_lora_7b_weight(model: LlamaModel,
                     adapter_name, "lora_B", lora_b_weight)
 
 
-def save_lora_model(model: LlamaModel, config: Dict[str, str]):
+def save_lora_model(model: LlamaModel, config: Dict[str, str], dir_suffix=""):
     for lora_config in config["lora"]:
         lora_name = lora_config["name"]
-        lora_output_dir = lora_config["output"]
+        lora_output_dir = lora_config["output"] + "_" + dir_suffix
 
         if not os.path.exists(lora_output_dir):
             os.makedirs(lora_output_dir)

legacy.py

@@ -80,6 +80,6 @@ def init_lora_model(llama_model: aspen.LlamaModel):
         optimizer.step()
 
         if step_cnt % config["save_step"] == 0:
-            aspen.save_lora_model(llama_model, config)
+            aspen.save_lora_model(llama_model, config, f"{step_cnt}")
 
     aspen.save_lora_model(llama_model, config)

requirements.txt

@@ -4,3 +4,4 @@ xformers
 transformers
 bitsandbytes
 sentencepiece
+scipy