ai-content-maker/.venv/Lib/site-packages/TTS/config/__init__.py

136 lines
4.3 KiB
Python

import json
import os
import re
from typing import Dict
import fsspec
import yaml
from coqpit import Coqpit
from TTS.config.shared_configs import *
from TTS.utils.generic_utils import find_module
def read_json_with_comments(json_path):
"""for backward compat."""
# fallback to json
with fsspec.open(json_path, "r", encoding="utf-8") as f:
input_str = f.read()
# handle comments but not urls with //
input_str = re.sub(r"(\"(?:[^\"\\]|\\.)*\")|(/\*(?:.|[\\n\\r])*?\*/)|(//.*)", lambda m: m.group(1) or m.group(2) or "", input_str)
return json.loads(input_str)
def register_config(model_name: str) -> Coqpit:
"""Find the right config for the given model name.
Args:
model_name (str): Model name.
Raises:
ModuleNotFoundError: No matching config for the model name.
Returns:
Coqpit: config class.
"""
config_class = None
config_name = model_name + "_config"
# TODO: fix this
if model_name == "xtts":
from TTS.tts.configs.xtts_config import XttsConfig
config_class = XttsConfig
paths = ["TTS.tts.configs", "TTS.vocoder.configs", "TTS.encoder.configs", "TTS.vc.configs"]
for path in paths:
try:
config_class = find_module(path, config_name)
except ModuleNotFoundError:
pass
if config_class is None:
raise ModuleNotFoundError(f" [!] Config for {model_name} cannot be found.")
return config_class
def _process_model_name(config_dict: Dict) -> str:
"""Format the model name as expected. It is a band-aid for the old `vocoder` model names.
Args:
config_dict (Dict): A dictionary including the config fields.
Returns:
str: Formatted modelname.
"""
model_name = config_dict["model"] if "model" in config_dict else config_dict["generator_model"]
model_name = model_name.replace("_generator", "").replace("_discriminator", "")
return model_name
def load_config(config_path: str) -> Coqpit:
"""Import `json` or `yaml` files as TTS configs. First, load the input file as a `dict` and check the model name
to find the corresponding Config class. Then initialize the Config.
Args:
config_path (str): path to the config file.
Raises:
TypeError: given config file has an unknown type.
Returns:
Coqpit: TTS config object.
"""
config_dict = {}
ext = os.path.splitext(config_path)[1]
if ext in (".yml", ".yaml"):
with fsspec.open(config_path, "r", encoding="utf-8") as f:
data = yaml.safe_load(f)
elif ext == ".json":
try:
with fsspec.open(config_path, "r", encoding="utf-8") as f:
data = json.load(f)
except json.decoder.JSONDecodeError:
# backwards compat.
data = read_json_with_comments(config_path)
else:
raise TypeError(f" [!] Unknown config file type {ext}")
config_dict.update(data)
model_name = _process_model_name(config_dict)
config_class = register_config(model_name.lower())
config = config_class()
config.from_dict(config_dict)
return config
def check_config_and_model_args(config, arg_name, value):
"""Check the give argument in `config.model_args` if exist or in `config` for
the given value.
Return False if the argument does not exist in `config.model_args` or `config`.
This is to patch up the compatibility between models with and without `model_args`.
TODO: Remove this in the future with a unified approach.
"""
if hasattr(config, "model_args"):
if arg_name in config.model_args:
return config.model_args[arg_name] == value
if hasattr(config, arg_name):
return config[arg_name] == value
return False
def get_from_config_or_model_args(config, arg_name):
"""Get the given argument from `config.model_args` if exist or in `config`."""
if hasattr(config, "model_args"):
if arg_name in config.model_args:
return config.model_args[arg_name]
return config[arg_name]
def get_from_config_or_model_args_with_default(config, arg_name, def_val):
"""Get the given argument from `config.model_args` if exist or in `config`."""
if hasattr(config, "model_args"):
if arg_name in config.model_args:
return config.model_args[arg_name]
if hasattr(config, arg_name):
return config[arg_name]
return def_val