benchmark / src /envs.py
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import os
from huggingface_hub import HfApi
# Info to change for your repository
# ----------------------------------
TOKEN = os.environ.get("TOKEN") # A read/write token for your org
OWNER = "ttsds" # Change to your org - don't forget to create a results and request dataset, with the correct format!
# ----------------------------------
REPO_ID = f"{OWNER}/benchmark"
QUEUE_REPO = f"{OWNER}/requests"
RESULTS_REPO = f"{OWNER}/results"
# If you setup a cache later, just change HF_HOME
CACHE_PATH = os.getenv("HF_HOME", ".")
# Local caches
EVAL_REQUESTS_PATH = os.path.join(CACHE_PATH, "eval-queue")
EVAL_RESULTS_PATH = os.path.join(CACHE_PATH, "eval-results")
EVAL_REQUESTS_PATH_BACKEND = os.path.join(CACHE_PATH, "eval-queue-bk")
EVAL_RESULTS_PATH_BACKEND = os.path.join(CACHE_PATH, "eval-results-bk")
API = HfApi(token=TOKEN)
TAGS = [
"Normalizing Flow",
"Reference-based (Speaker)",
"Prompt-based (Speaker)",
"Prosodic Correlates",
"Adversarial",
"Diffusion",
"Audio Tokens",
"Autoregressive",
"Non-autoregressive",
"Pretrained Text Encoder",
]