remove redudant code

Author: horheynm

src/llmcompressor/transformers/utils/helpers.py

@@ -5,7 +5,7 @@
 
 import os
 from pathlib import Path
-from typing import TYPE_CHECKING, Optional, Tuple, Union
+from typing import TYPE_CHECKING, Optional, Union
 
 import requests
 from huggingface_hub import HUGGINGFACE_CO_URL_HOME, hf_hub_download
@@ -77,211 +77,83 @@ def is_model_quantized_from_path(path: str) -> bool:
     return False
 
 
-def resolve_recipe(
-    model_path: Union[str, Path],
-    recipe: Union[str, Path, None] = None,
-) -> Union[str, None]:
-    """
-    Resolve the recipe to apply to the model.
-    :param recipe: the recipe to apply to the model.
-
-        It can be one of the following:
-        - None
-            This means that we are not either not applying
-            any recipe and allowing the model to potentially
-            infer the appropriate pre-existing recipe
-            from the model_path
-        - a path to the recipe file
-            This can be a string or Path object pointing
-            to a recipe file. If the specified recipe file
-            is different from the potential pre-existing
-            recipe for that model (stored in the model_path),
-            the function will raise an warning
-        - name of the recipe file (e.g. "recipe.yaml")
-            Recipe file name specific is assumed to be stored
-            in the model_path
-        - a string containing the recipe
-            Needs to adhere to the SparseML recipe format
-
-    :param model_path: the path to the model to load.
-        It can be one of the following:
-        - a path to the model directory
-        - a path to the model file
-        - Hugging face model id
-
-    :return: the resolved recipe
-    """
-
-    if recipe is None:
-        return infer_recipe_from_model_path(model_path)
-
-    elif os.path.isfile(recipe):
-        # recipe is a path to a recipe file
-        return resolve_recipe_file(recipe, model_path)
-
-    elif os.path.isfile(os.path.join(model_path, recipe)):
-        # recipe is a name of a recipe file
-        recipe = os.path.join(model_path, recipe)
-        return resolve_recipe_file(recipe, model_path)
-
-    elif isinstance(recipe, str):
-        # recipe is a string containing the recipe
-        logger.debug(
-            "Applying the recipe string directly to the model, without "
-            "checking for a potential existing recipe in the model_path."
-        )
-        return recipe
-
-    logger.info(
-        "No recipe requested and no default recipe "
-        f"found in {model_path}. Skipping recipe resolution."
-    )
-    return None
-
-
 def infer_recipe_from_model_path(model_path: Union[str, Path]) -> Optional[str]:
     """
     Infer the recipe from the model_path.
-    :param model_path: the path to the model to load.
-        It can be one of the following:
+
+    :param model_path: The path to the model to load. It can be one of the following:
         - a path to the model directory
         - a path to the model file
-        - Hugging face model id
-    :return the path to the recipe file if found, None otherwise
+        - Hugging face model ID
+    :return: The path to the recipe file if found, None otherwise.
     """
     model_path = model_path.as_posix() if isinstance(model_path, Path) else model_path
 
     if os.path.isdir(model_path) or os.path.isfile(model_path):
-        # model_path is a local path to the model directory or model file
-        # attempting to find the recipe in the model_directory
+        # Model path is a local path to the model directory or file
         model_path = (
             os.path.dirname(model_path) if os.path.isfile(model_path) else model_path
         )
         recipe = os.path.join(model_path, RECIPE_FILE_NAME)
+
         if os.path.isfile(recipe):
             logger.info(f"Found recipe in the model_path: {recipe}")
             return recipe
         logger.debug(f"No recipe found in the model_path: {model_path}")
         return None
 
-    recipe = recipe_from_huggingface_model_id(model_path)[0]
+    # If the model path is a Hugging Face model ID
+    recipe = recipe_from_huggingface_model_id(model_path)
 
     if recipe is None:
         logger.info("Failed to infer the recipe from the model_path")
+
     return recipe
 
 
 def recipe_from_huggingface_model_id(
     model_path: str, recipe_file_name: str = RECIPE_FILE_NAME
-) -> Tuple[Optional[str], bool]:
+) -> Optional[str]:
     """
-    Attempts to download the recipe from the huggingface model id.
+    Attempts to download the recipe from the Hugging Face model ID.
 
-    :param model_path: Assumed to be the huggingface model id.
-        If it is not, this function will return None.
+    :param model_path: Assumed to be the Hugging Face model ID.
     :param recipe_file_name: The name of the recipe file to download.
-        Defaults to recipe_file_name.
-    :return: tuple:
-        - the path to the recipe file if found, None otherwise
-        - True if model_path is a valid huggingface model id, False otherwise
+     Defaults to RECIPE_FILE_NAME.
+    :return: A tuple:
+        - The path to the recipe file if found, None otherwise.
+        - True if model_path is a valid Hugging Face model ID, False otherwise.
     """
-    model_id = os.path.join(HUGGINGFACE_CO_URL_HOME, model_path)
-    request = requests.get(model_id)
-    if not request.status_code == 200:
+    model_id_url = os.path.join(HUGGINGFACE_CO_URL_HOME, model_path)
+    request = requests.get(model_id_url)
+
+    if request.status_code != 200:
         logger.debug(
-            "model_path is not a valid huggingface model id. "
-            "Skipping recipe resolution."
+            (
+                "model_path is not a valid Hugging Face model ID. ",
+                "Skipping recipe resolution.",
+            )
         )
-        return None, False
+        return None
 
     logger.info(
-        "model_path is a huggingface model id. "
-        "Attempting to download recipe from "
-        f"{HUGGINGFACE_CO_URL_HOME}"
+        (
+            "model_path is a Hugging Face model ID. ",
+            f"Attempting to download recipe from {HUGGINGFACE_CO_URL_HOME}",
+        )
     )
+
     try:
         recipe = hf_hub_download(repo_id=model_path, filename=recipe_file_name)
-        logger.info(f"Found recipe: {recipe_file_name} for model id: {model_path}.")
+        logger.info(f"Found recipe: {recipe_file_name} for model ID: {model_path}.")
     except Exception as e:
-        logger.info(
-            f"Unable to to find recipe {recipe_file_name} "
-            f"for model id: {model_path}: {e}. "
-            "Skipping recipe resolution."
-        )
-        recipe = None
-    return recipe, True
-
-
-def resolve_recipe_file(
-    requested_recipe: Union[str, Path], model_path: Union[str, Path]
-) -> Union[str, Path, None]:
-    """
-    Given the requested recipe and the model_path, return the path to the recipe file.
-
-    :param requested_recipe. Is a full path to the recipe file
-    :param model_path: the path to the model to load.
-        It can be one of the following:
-        - a path to the model directory
-        - a path to the model file
-        - Hugging face model id
-    :return the path to the recipe file if found, None otherwise
-    """
-    # preprocess arguments so that they are all strings
-    requested_recipe = (
-        requested_recipe.as_posix()
-        if isinstance(requested_recipe, Path)
-        else requested_recipe
-    )
-    model_path = model_path.as_posix() if isinstance(model_path, Path) else model_path
-    model_path = (
-        os.path.dirname(model_path) if os.path.isfile(model_path) else model_path
-    )
-
-    if not os.path.isdir(model_path):
-        default_recipe, model_exists = recipe_from_huggingface_model_id(model_path)
-        if not model_exists:
-            raise ValueError(f"Unrecognized model_path: {model_path}")
-
-        if not default_recipe == requested_recipe and default_recipe is not None:
-            logger.warning(
-                f"Attempting to apply recipe: {requested_recipe} "
-                f"to the model at: {model_path}, "
-                f"but the model already has a recipe: {default_recipe}. "
-                f"Using {requested_recipe} instead."
+        logger.error(
+            (
+                f"Unable to find recipe {recipe_file_name} "
+                f"for model ID: {model_path}: {e}."
+                "Skipping recipe resolution."
             )
-        return requested_recipe
-
-    # pathway for model_path that is a directory
-    default_recipe = os.path.join(model_path, RECIPE_FILE_NAME)
-    default_recipe_exists = os.path.isfile(default_recipe)
-    default_and_request_recipes_identical = os.path.samefile(
-        default_recipe, requested_recipe
-    )
-
-    if (
-        default_recipe_exists
-        and requested_recipe
-        and not default_and_request_recipes_identical
-    ):
-        logger.warning(
-            f"Attempting to apply recipe: {requested_recipe} "
-            f"to the model located in {model_path}, "
-            f"but the model already has a recipe stored as {default_recipe}. "
-            f"Using {requested_recipe} instead."
-        )
-
-    elif not default_recipe_exists and requested_recipe:
-        logger.warning(
-            f"Attempting to apply {requested_recipe} "
-            f"to the model located in {model_path}."
-            "However, it is expected that the model "
-            f"has its target recipe stored as {default_recipe}."
-            "Applying any recipe before the target recipe may "
-            "result in unexpected behavior."
-            f"Applying {requested_recipe} nevertheless."
         )
+        recipe = None
 
-    elif default_recipe_exists:
-        logger.info(f"Using the default recipe: {requested_recipe}")
-
-    return requested_recipe
+    return recipe

tests/llmcompressor/transformers/obcq/test_consecutive_runs.py

@@ -8,7 +8,7 @@
 from transformers import AutoModelForCausalLM
 from transformers.utils.quantization_config import CompressedTensorsConfig
 
-from llmcompressor.transformers.utils.helpers import resolve_recipe
+from llmcompressor.transformers.utils.helpers import infer_recipe_from_model_path
 from tests.testing_utils import parse_params, requires_gpu
 
 CONFIGS_DIRECTORY = "tests/llmcompressor/transformers/obcq/obcq_configs/consec_runs"
@@ -60,7 +60,7 @@ def _test_consecutive_runs(
         self.assertEqual(len(stages), 1)
         session.reset()
 
-        recipe = resolve_recipe(recipe=self.first_recipe, model_path=self.output_first)
+        recipe = infer_recipe_from_model_path(model_path=self.output_first)
         if recipe:
             initialize_recipe(model=first_model, recipe_path=recipe)