P2A-test-NV / laser /laser_encoders /validate_models.py
KuangDW
Add laser2.spm using Git LFS
05d3571
import os
import tempfile
import pytest
from laser_encoders.download_models import LaserModelDownloader
from laser_encoders.language_list import LASER2_LANGUAGE, LASER3_LANGUAGE
from laser_encoders.laser_tokenizer import initialize_tokenizer
from laser_encoders.models import initialize_encoder
@pytest.mark.slow
@pytest.mark.parametrize("lang", LASER3_LANGUAGE)
def test_validate_language_models_and_tokenize_laser3(lang):
with tempfile.TemporaryDirectory() as tmp_dir:
print(f"Created temporary directory for {lang}", tmp_dir)
downloader = LaserModelDownloader(model_dir=tmp_dir)
if lang in ["kashmiri", "kas", "central kanuri", "knc"]:
with pytest.raises(ValueError) as excinfo:
downloader.download_laser3(lang)
assert "ValueError" in str(excinfo.value)
print(f"{lang} language model raised a ValueError as expected.")
else:
downloader.download_laser3(lang)
encoder = initialize_encoder(lang, model_dir=tmp_dir)
tokenizer = initialize_tokenizer(lang, model_dir=tmp_dir)
# Test tokenization with a sample sentence
tokenized = tokenizer.tokenize("This is a sample sentence.")
print(f"{lang} model validated successfully")
@pytest.mark.slow
@pytest.mark.parametrize("lang", LASER2_LANGUAGE)
def test_validate_language_models_and_tokenize_laser2(lang):
with tempfile.TemporaryDirectory() as tmp_dir:
print(f"Created temporary directory for {lang}", tmp_dir)
downloader = LaserModelDownloader(model_dir=tmp_dir)
downloader.download_laser2()
encoder = initialize_encoder(lang, model_dir=tmp_dir)
tokenizer = initialize_tokenizer(lang, model_dir=tmp_dir)
# Test tokenization with a sample sentence
tokenized = tokenizer.tokenize("This is a sample sentence.")
print(f"{lang} model validated successfully")
class MockLaserModelDownloader(LaserModelDownloader):
def __init__(self, model_dir):
self.model_dir = model_dir
def download_laser3(self, lang):
lang = self.get_language_code(LASER3_LANGUAGE, lang)
file_path = os.path.join(self.model_dir, f"laser3-{lang}.v1.pt")
if not os.path.exists(file_path):
raise FileNotFoundError(f"Could not find {file_path}.")
def download_laser2(self):
files = ["laser2.pt", "laser2.spm", "laser2.cvocab"]
for file_name in files:
file_path = os.path.join(self.model_dir, file_name)
if not os.path.exists(file_path):
raise FileNotFoundError(f"Could not find {file_path}.")
CACHE_DIR = "/home/user/.cache/models" # Change this to the desired cache directory
# This uses the mock downloader
@pytest.mark.slow
@pytest.mark.parametrize("lang", LASER3_LANGUAGE)
def test_validate_language_models_and_tokenize_mock_laser3(lang):
downloader = MockLaserModelDownloader(model_dir=CACHE_DIR)
try:
downloader.download_laser3(lang)
except FileNotFoundError as e:
raise pytest.error(str(e))
encoder = initialize_encoder(lang, model_dir=CACHE_DIR)
tokenizer = initialize_tokenizer(lang, model_dir=CACHE_DIR)
tokenized = tokenizer.tokenize("This is a sample sentence.")
print(f"{lang} model validated successfully")
# This uses the mock downloader
@pytest.mark.slow
@pytest.mark.parametrize("lang", LASER2_LANGUAGE)
def test_validate_language_models_and_tokenize_mock_laser2(lang):
downloader = MockLaserModelDownloader(model_dir=CACHE_DIR)
try:
downloader.download_laser2()
except FileNotFoundError as e:
raise pytest.error(str(e))
encoder = initialize_encoder(lang, model_dir=CACHE_DIR)
tokenizer = initialize_tokenizer(lang, model_dir=CACHE_DIR)
tokenized = tokenizer.tokenize("This is a sample sentence.")
print(f"{lang} model validated successfully")