[Fix] Replace generic exception classes with a more specific ones (#1989

)

* Replace generic exception classes with a more specific ones

* rerun pre-commit to pass linter tests

* Revert "rerun pre-commit to pass linter tests"

This reverts commit 67f88cc.

* reduce repetitions in errors or so

* Replace generic exception class with a more specific one

lm_eval/models/anthropic_llms.py

@@ -45,8 +45,8 @@ def anthropic_completion(
 
     try:
         import anthropic
-    except ModuleNotFoundError:
-        raise Exception(
+    except ModuleNotFoundError as exception:
+        raise type(exception)(
             "attempted to use 'anthropic' LM type, but package `anthropic` is not installed. \
 please install anthropic via `pip install 'lm-eval[anthropic]'` or `pip install -e '.[anthropic]'`",
         )
@@ -108,8 +108,8 @@ def anthropic_chat(
 
     try:
         import anthropic
-    except ModuleNotFoundError:
-        raise Exception(
+    except ModuleNotFoundError as exception:
+        raise type(exception)(
             "attempted to use 'anthropic' LM type, but package `anthropic` is not installed. \
 please install anthropic via `pip install 'lm-eval[anthropic]'` or `pip install -e '.[anthropic]'`",
         )
@@ -168,8 +168,8 @@ def __init__(
 
         try:
             import anthropic
-        except ModuleNotFoundError:
-            raise Exception(
+        except ModuleNotFoundError as exception:
+            raise type(exception)(
                 "attempted to use 'anthropic' LM type, but package `anthropic` is not installed. \
 please install anthropic via `pip install 'lm-eval[anthropic]'` or `pip install -e '.[anthropic]'`",
             )
@@ -217,8 +217,8 @@ def _loglikelihood_tokens(self, requests, disable_tqdm: bool = False):
     def generate_until(self, requests, disable_tqdm: bool = False) -> List[str]:
         try:
             import anthropic
-        except ModuleNotFoundError:
-            raise Exception(
+        except ModuleNotFoundError as exception:
+            raise type(exception)(
                 "attempted to use 'anthropic' LM type, but package `anthropic` is not installed. \
 please install anthropic via `pip install 'lm-eval[anthropic]'` or `pip install -e '.[anthropic]'`",
             )

lm_eval/models/api_models.py

@@ -144,7 +144,7 @@ def __init__(
 
                         self.tokenizer = tiktoken.encoding_for_model(self.model)
                     except ModuleNotFoundError as e:
-                        raise Exception(
+                        raise ModuleNotFoundError(
                             "Attempted to use 'openai' LM type, but the package `tiktoken` is not installed. "
                             "Please install it via `pip install lm-eval[api]` or `pip install -e .[api]`."
                         ) from e

lm_eval/models/gguf.py

@@ -68,7 +68,9 @@ def gguf_completion(
                 logger.error(f"RequestException: {e}")
                 time.sleep(delay)  # wait before retrying
         else:
-            raise Exception(f"Failed to get a valid response after {retries} retries.")
+            raise RuntimeError(
+                f"Failed to get a valid response after {retries} retries."
+            )
 
     def loglikelihood(self, requests, disable_tqdm: bool = False):
         if not requests:

lm_eval/models/huggingface.py

@@ -579,8 +579,8 @@ def _create_model(
         else:
             try:
                 from auto_gptq import AutoGPTQForCausalLM
-            except ModuleNotFoundError:
-                raise Exception(
+            except ModuleNotFoundError as exception:
+                raise type(exception)(
                     "Tried to load auto_gptq, but auto-gptq is not installed ",
                     "please install auto-gptq via pip install lm-eval[gptq] or pip install -e .[gptq]",
                 )

lm_eval/models/mamba_lm.py

@@ -69,8 +69,8 @@ def _get_config(
     ) -> None:
         try:
             from mamba_ssm.utils.hf import load_config_hf  # noqa: F811
-        except ModuleNotFoundError:
-            raise Exception(
+        except ModuleNotFoundError as exception:
+            raise type(exception)(
                 "attempted to use 'mamba_ssm' LM type, but package `mamba_ssm` is not installed. \
 please install mamba via `pip install lm-eval[mamba]` or `pip install -e .[mamba]`",
             )
@@ -88,8 +88,8 @@ def _create_model(
     ) -> None:
         try:
             from mamba_ssm.models.mixer_seq_simple import MambaLMHeadModel  # noqa: F811
-        except ModuleNotFoundError:
-            raise Exception(
+        except ModuleNotFoundError as exception:
+            raise type(exception)(
                 "attempted to use 'mamba_ssm' LM type, but package `mamba_ssm` is not installed. \
 please install mamba via `pip install lm-eval[mamba]` or `pip install -e .[mamba]`",
             )

lm_eval/models/nemo_lm.py

@@ -39,8 +39,8 @@ def _patch_pretrained_cfg(
 ):
     try:
         import omegaconf
-    except ModuleNotFoundError:
-        raise Exception(
+    except ModuleNotFoundError as exception:
+        raise type(exception)(
             "Attempted to use 'nemo_lm' model type, but package `nemo` is not installed"
             "Please install nemo following the instructions in the README: either with a NVIDIA PyTorch or NeMo container, "
             "or installing nemo following https://github.com/NVIDIA/NeMo.",
@@ -79,8 +79,8 @@ def load_model(
             MegatronGPTModel,
         )
         from nemo.collections.nlp.parts.nlp_overrides import NLPSaveRestoreConnector
-    except ModuleNotFoundError:
-        raise Exception(
+    except ModuleNotFoundError as exception:
+        raise type(exception)(
             "Attempted to use 'nemo_lm' model type, but package `nemo` is not installed"
             "Please install nemo following the instructions in the README: either with a NVIDIA PyTorch or NeMo container, "
             "or installing nemo following https://github.com/NVIDIA/NeMo.",
@@ -140,8 +140,8 @@ def _synced_build_tokenizer(self):
 def setup_distributed_environment(trainer):
     try:
         from nemo.utils.app_state import AppState
-    except ModuleNotFoundError:
-        raise Exception(
+    except ModuleNotFoundError as exception:
+        raise type(exception)(
             "Attempted to use 'nemo_lm' model type, but package `nemo` is not installed"
             "Please install nemo following the instructions in the README: either with a NVIDIA PyTorch or NeMo container, "
             "or installing nemo following https://github.com/NVIDIA/NeMo.",
@@ -194,8 +194,8 @@ def __init__(
             from pytorch_lightning.trainer.trainer import Trainer
 
             self.generate = generate
-        except ModuleNotFoundError:
-            raise Exception(
+        except ModuleNotFoundError as exception:
+            raise type(exception)(
                 "Attempted to use 'nemo_lm' model type, but package `nemo` is not installed"
                 "Please install nemo following the instructions in the README: either with a NVIDIA PyTorch or NeMo container, "
                 "or installing nemo following https://github.com/NVIDIA/NeMo.",

lm_eval/models/neuralmagic.py

@@ -38,8 +38,8 @@ def _create_model(
     ) -> None:
         try:
             from sparseml.transformers import SparseAutoModelForCausalLM
-        except ModuleNotFoundError:
-            raise Exception(
+        except ModuleNotFoundError as exception:
+            raise type(exception)(
                 "Package `sparseml` is not installed. "
                 "Please install it via `pip install sparseml[transformers]`"
             )
@@ -88,8 +88,8 @@ def _create_model(
     def _get_config(self, pretrained: str, **kwargs) -> None:
         try:
             from sparseml.transformers import SparseAutoConfig
-        except ModuleNotFoundError:
-            raise Exception(
+        except ModuleNotFoundError as exception:
+            raise type(exception)(
                 "Package `sparseml` is not installed. "
                 "Please install it via `pip install sparseml[transformers]`"
             )
@@ -112,8 +112,8 @@ def _create_tokenizer(
     ) -> None:
         try:
             from sparseml.transformers import SparseAutoTokenizer
-        except ModuleNotFoundError:
-            raise Exception(
+        except ModuleNotFoundError as exception:
+            raise type(exception)(
                 "Package `sparseml` is not installed. "
                 "Please install it via `pip install sparseml[transformers]`"
             )
@@ -171,8 +171,8 @@ def __init__(
 
         try:
             import deepsparse
-        except ModuleNotFoundError:
-            raise Exception(
+        except ModuleNotFoundError as exception:
+            raise type(exception)(
                 "Package `deepsparse` is not installed. "
                 "Please install it via `pip install deepsparse[transformers]`"
             )

lm_eval/models/neuron_optimum.py

@@ -144,7 +144,7 @@ def __init__(
         add_bos_token: Optional[bool] = False,
     ) -> None:
         if not NEURON_AVAILABLE:
-            raise Exception(
+            raise ImportError(
                 "Tried to load neuron model, but neuron is not installed ",
                 "please install neuron via pip install transformers-neuron ",
                 "also make sure you are running on an AWS inf2 instance",

lm_eval/models/optimum_lm.py

@@ -50,7 +50,7 @@ def _create_model(
         **kwargs,
     ) -> None:
         if not find_spec("optimum"):
-            raise Exception(
+            raise ModuleNotFoundError(
                 "package `optimum` is not installed. Please install it via `pip install optimum[openvino]`"
             )
         else:

lm_eval/models/vllm_causallms.py

@@ -65,7 +65,7 @@ def __init__(
         super().__init__()
 
         if not find_spec("vllm"):
-            raise Exception(
+            raise ModuleNotFoundError(
                 "attempted to use 'vllm' LM type, but package `vllm` is not installed. "
                 "Please install vllm via `pip install lm-eval[vllm]` or `pip install -e .[vllm]`"
             )

lm_eval/prompts/__init__.py

@@ -29,8 +29,8 @@ def get_prompt(prompt_id: str, dataset_name: str = None, subset_name: str = None
     if category_name == "promptsource":
         try:
             from promptsource.templates import DatasetTemplates
-        except ModuleNotFoundError:
-            raise Exception(
+        except ModuleNotFoundError as exception:
+            raise type(exception)(
                 "Tried to load a Promptsource template, but promptsource is not installed ",
                 "please install promptsource via pip install lm-eval[promptsource] or pip install -e .[promptsource]",
             )
@@ -118,7 +118,7 @@ def apply(self, doc):
 
         # TODO need a way to process doc_to_choice
         if "doc_to_choice" in self.prompt_string:
-            raise Exception("Not yet implemented to accept doc_to_choice")
+            raise NotImplementedError("Not yet implemented to accept doc_to_choice")
 
         text_string = utils.apply_template(doc_to_text, doc)
         target_string = utils.apply_template(doc_to_target, doc)

scripts/clean_training_data/generate_13_grams.py

@@ -55,7 +55,7 @@ def yield_pile(start_offsets=None, checkpoint_offset=None):
         print(
             "We expect the pile archives to be in the 'pile' directory, but this was not found."
         )
-        raise Exception("Pile directory not found.")
+        raise FileNotFoundError("Pile directory not found.")
 
     files = list(sorted(glob.glob(os.path.join(directory, "*.jsonl.zst*"))))