2 Commits

Author	SHA1	Message	Date
Bagatur	a0c2281540	infra: update mypy 1.10, ruff 0.5 (#23721) ... ```python """python scripts/update_mypy_ruff.py""" import glob import tomllib from pathlib import Path import toml import subprocess import re ROOT_DIR = Path(__file__).parents[1] def main(): for path in glob.glob(str(ROOT_DIR / "libs/**/pyproject.toml"), recursive=True): print(path) with open(path, "rb") as f: pyproject = tomllib.load(f) try: pyproject["tool"]["poetry"]["group"]["typing"]["dependencies"]["mypy"] = ( "^1.10" ) pyproject["tool"]["poetry"]["group"]["lint"]["dependencies"]["ruff"] = ( "^0.5" ) except KeyError: continue with open(path, "w") as f: toml.dump(pyproject, f) cwd = "/".join(path.split("/")[:-1]) completed = subprocess.run( "poetry lock --no-update; poetry install --with typing; poetry run mypy . --no-color", cwd=cwd, shell=True, capture_output=True, text=True, ) logs = completed.stdout.split("\n") to_ignore = {} for l in logs: if re.match("^(.*)\:(\d+)\: error:.*\[(.*)\]", l): path, line_no, error_type = re.match( "^(.*)\:(\d+)\: error:.*\[(.*)\]", l ).groups() if (path, line_no) in to_ignore: to_ignore[(path, line_no)].append(error_type) else: to_ignore[(path, line_no)] = [error_type] print(len(to_ignore)) for (error_path, line_no), error_types in to_ignore.items(): all_errors = ", ".join(error_types) full_path = f"{cwd}/{error_path}" try: with open(full_path, "r") as f: file_lines = f.readlines() except FileNotFoundError: continue file_lines[int(line_no) - 1] = ( file_lines[int(line_no) - 1][:-1] + f" # type: ignore[{all_errors}]\n" ) with open(full_path, "w") as f: f.write("".join(file_lines)) subprocess.run( "poetry run ruff format .; poetry run ruff --select I --fix .", cwd=cwd, shell=True, capture_output=True, text=True, ) if __name__ == "__main__": main() ```	2024-07-03 10:33:27 -07:00
Vlad Kolesnikov	11fda490ca	community[minor]: New model parameters and dynamic batching for VertexAIEmbeddings (#13999) ... - **Description:** VertexAIEmbeddings performance improvements - **Twitter handle:** @vladkol ## Improvements - Dynamic batch size, starting from 250, lowering down to 5. Batch size varies across regions. Some regions support larger batches, and it significantly improves performance. When running large batches of texts in `us-central1`, performance gain can be up to 3.5x. The dynamic batching also makes sure every batch is below 20K token limit. - New model parameter `embeddings_type` that translates to `task_type` parameter of the API. Newer model versions support [different embeddings task types](https://cloud.google.com/vertex-ai/docs/generative-ai/embeddings/get-text-embeddings#api_changes_to_models_released_on_or_after_august_2023).	2023-12-17 22:24:22 -05:00