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chore(ml): improved logging (#3918)

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* fixed `minScore` not being set correctly

* apply to init

* don't send `enabled`

* fix eslint warning

* added logger

* added logging

* refinements

* enable access log for info level

* formatting

* merged strings

---------

Co-authored-by: Alex <alex.tran1502@gmail.com>
This commit is contained in:
Mert
2023-08-30 04:22:01 -04:00
committed by GitHub
parent df26e12db6
commit 54b2779b79
5 changed files with 92 additions and 11 deletions
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36
machine-learning/app/models/base.py
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@ -1,6 +1,5 @@
from __future__ import annotations
import os
import pickle
from abc import ABC, abstractmethod
from pathlib import Path
@ -11,7 +10,7 @@ from zipfile import BadZipFile
import onnxruntime as ort
from onnxruntime.capi.onnxruntime_pybind11_state import InvalidProtobuf # type: ignore
from ..config import get_cache_dir, settings
from ..config import get_cache_dir, log, settings
from ..schemas import ModelType
@ -37,22 +36,41 @@ class InferenceModel(ABC):
self.provider_options = model_kwargs.pop(
"provider_options", [{"arena_extend_strategy": "kSameAsRequested"}] * len(self.providers)
)
log.debug(
(
f"Setting '{self.model_name}' execution providers to {self.providers}"
"in descending order of preference"
),
)
log.debug(f"Setting execution provider options to {self.provider_options}")
self.sess_options = PicklableSessionOptions()
# avoid thread contention between models
if inter_op_num_threads > 1:
self.sess_options.execution_mode = ort.ExecutionMode.ORT_PARALLEL
log.debug(f"Setting execution_mode to {self.sess_options.execution_mode.name}")
log.debug(f"Setting inter_op_num_threads to {inter_op_num_threads}")
log.debug(f"Setting intra_op_num_threads to {intra_op_num_threads}")
self.sess_options.inter_op_num_threads = inter_op_num_threads
self.sess_options.intra_op_num_threads = intra_op_num_threads
try:
loader(**model_kwargs)
except (OSError, InvalidProtobuf, BadZipFile):
log.warn(
(
f"Failed to load {self.model_type.replace('_', ' ')} model '{self.model_name}'."
"Clearing cache and retrying."
)
)
self.clear_cache()
loader(**model_kwargs)
def download(self, **model_kwargs: Any) -> None:
if not self.cached:
print(f"Downloading {self.model_type.value.replace('_', ' ')} model. This may take a while...")
log.info(
(f"Downloading {self.model_type.replace('_', ' ')} model '{self.model_name}'." "This may take a while.")
)
self._download(**model_kwargs)
def load(self, **model_kwargs: Any) -> None:
@ -62,7 +80,7 @@ class InferenceModel(ABC):
def predict(self, inputs: Any, **model_kwargs: Any) -> Any:
if not self._loaded:
print(f"Loading {self.model_type.value.replace('_', ' ')} model...")
log.info(f"Loading {self.model_type.replace('_', ' ')} model '{self.model_name}'")
self.load()
if model_kwargs:
self.configure(**model_kwargs)
@ -109,13 +127,23 @@ class InferenceModel(ABC):
def clear_cache(self) -> None:
if not self.cache_dir.exists():
log.warn(
f"Attempted to clear cache for model '{self.model_name}' but cache directory does not exist.",
)
return
if not rmtree.avoids_symlink_attacks:
raise RuntimeError("Attempted to clear cache, but rmtree is not safe on this platform.")
if self.cache_dir.is_dir():
log.info(f"Cleared cache directory for model '{self.model_name}'.")
rmtree(self.cache_dir)
else:
log.warn(
(
f"Encountered file instead of directory at cache path "
f"for '{self.model_name}'. Removing file and replacing with a directory."
),
)
self.cache_dir.unlink()
self.cache_dir.mkdir(parents=True, exist_ok=True)