khoj/tests/conftest.py
Debanjum Singh Solanky eda4b65ddb Improve Query Speed. Normalize Embeddings, Moving them to Cuda GPU
- Move embeddings to CUDA GPU for compute, when available
- Normalize embeddings and Use Dot Product instead of Cosine
2022-06-30 00:59:57 +04:00

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Python

# Standard Packages
import pytest
import torch
# Internal Packages
from src.search_type import asymmetric, image_search
from src.utils.rawconfig import ContentConfig, TextContentConfig, ImageContentConfig, SearchConfig, SymmetricSearchConfig, AsymmetricSearchConfig, ImageSearchConfig
@pytest.fixture(scope='session')
def search_config(tmp_path_factory):
model_dir = tmp_path_factory.mktemp('data')
search_config = SearchConfig()
search_config.asymmetric = SymmetricSearchConfig(
encoder = "sentence-transformers/paraphrase-MiniLM-L6-v2",
cross_encoder = "cross-encoder/ms-marco-MiniLM-L-6-v2",
model_directory = model_dir
)
search_config.asymmetric = AsymmetricSearchConfig(
encoder = "sentence-transformers/msmarco-MiniLM-L-6-v3",
cross_encoder = "cross-encoder/ms-marco-MiniLM-L-6-v2",
model_directory = model_dir
)
search_config.image = ImageSearchConfig(
encoder = "clip-ViT-B-32",
model_directory = model_dir
)
return search_config
@pytest.fixture(scope='session')
def model_dir(search_config):
model_dir = search_config.asymmetric.model_directory
device = torch.device("cuda:0") if torch.cuda.is_available() else torch.device("cpu")
# Generate Image Embeddings from Test Images
content_config = ContentConfig()
content_config.image = ImageContentConfig(
input_directory = 'tests/data/images',
embeddings_file = model_dir.joinpath('image_embeddings.pt'),
batch_size = 10,
use_xmp_metadata = False)
image_search.setup(content_config.image, search_config.image, regenerate=False, verbose=True)
# Generate Notes Embeddings from Test Notes
content_config.org = TextContentConfig(
input_files = None,
input_filter = 'tests/data/notes/*.org',
compressed_jsonl = model_dir.joinpath('notes.jsonl.gz'),
embeddings_file = model_dir.joinpath('note_embeddings.pt'))
asymmetric.setup(content_config.org, search_config.asymmetric, regenerate=False, device=device, verbose=True)
return model_dir
@pytest.fixture(scope='session')
def content_config(model_dir):
content_config = ContentConfig()
content_config.org = TextContentConfig(
input_files = None,
input_filter = 'tests/data/notes/*.org',
compressed_jsonl = model_dir.joinpath('notes.jsonl.gz'),
embeddings_file = model_dir.joinpath('note_embeddings.pt'))
content_config.image = ImageContentConfig(
input_directory = 'tests/data/images',
embeddings_file = model_dir.joinpath('image_embeddings.pt'),
batch_size = 10,
use_xmp_metadata = False)
return content_config