init ascend tts

ascend_910-gpt-sovits/GPT-SoVITS/GPT_SoVITS/text/g2pw/utils.py

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+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+Credits
+    This code is modified from https://github.com/GitYCC/g2pW
+"""
+
+import os
+import re
+
+
+def wordize_and_map(text: str):
+    words = []
+    index_map_from_text_to_word = []
+    index_map_from_word_to_text = []
+    while len(text) > 0:
+        match_space = re.match(r"^ +", text)
+        if match_space:
+            space_str = match_space.group(0)
+            index_map_from_text_to_word += [None] * len(space_str)
+            text = text[len(space_str) :]
+            continue
+
+        match_en = re.match(r"^[a-zA-Z0-9]+", text)
+        if match_en:
+            en_word = match_en.group(0)
+
+            word_start_pos = len(index_map_from_text_to_word)
+            word_end_pos = word_start_pos + len(en_word)
+            index_map_from_word_to_text.append((word_start_pos, word_end_pos))
+
+            index_map_from_text_to_word += [len(words)] * len(en_word)
+
+            words.append(en_word)
+            text = text[len(en_word) :]
+        else:
+            word_start_pos = len(index_map_from_text_to_word)
+            word_end_pos = word_start_pos + 1
+            index_map_from_word_to_text.append((word_start_pos, word_end_pos))
+
+            index_map_from_text_to_word += [len(words)]
+
+            words.append(text[0])
+            text = text[1:]
+    return words, index_map_from_text_to_word, index_map_from_word_to_text
+
+
+def tokenize_and_map(tokenizer, text: str):
+    words, text2word, word2text = wordize_and_map(text=text)
+
+    tokens = []
+    index_map_from_token_to_text = []
+    for word, (word_start, word_end) in zip(words, word2text):
+        word_tokens = tokenizer.tokenize(word)
+
+        if len(word_tokens) == 0 or word_tokens == ["[UNK]"]:
+            index_map_from_token_to_text.append((word_start, word_end))
+            tokens.append("[UNK]")
+        else:
+            current_word_start = word_start
+            for word_token in word_tokens:
+                word_token_len = len(re.sub(r"^##", "", word_token))
+                index_map_from_token_to_text.append((current_word_start, current_word_start + word_token_len))
+                current_word_start = current_word_start + word_token_len
+                tokens.append(word_token)
+
+    index_map_from_text_to_token = text2word
+    for i, (token_start, token_end) in enumerate(index_map_from_token_to_text):
+        for token_pos in range(token_start, token_end):
+            index_map_from_text_to_token[token_pos] = i
+
+    return tokens, index_map_from_text_to_token, index_map_from_token_to_text
+
+
+def _load_config(config_path: os.PathLike):
+    import importlib.util
+
+    spec = importlib.util.spec_from_file_location("__init__", config_path)
+    config = importlib.util.module_from_spec(spec)
+    spec.loader.exec_module(config)
+    return config
+
+
+default_config_dict = {
+    "manual_seed": 1313,
+    "model_source": "bert-base-chinese",
+    "window_size": 32,
+    "num_workers": 2,
+    "use_mask": True,
+    "use_char_phoneme": False,
+    "use_conditional": True,
+    "param_conditional": {
+        "affect_location": "softmax",
+        "bias": True,
+        "char-linear": True,
+        "pos-linear": False,
+        "char+pos-second": True,
+        "char+pos-second_lowrank": False,
+        "lowrank_size": 0,
+        "char+pos-second_fm": False,
+        "fm_size": 0,
+        "fix_mode": None,
+        "count_json": "train.count.json",
+    },
+    "lr": 5e-5,
+    "val_interval": 200,
+    "num_iter": 10000,
+    "use_focal": False,
+    "param_focal": {"alpha": 0.0, "gamma": 0.7},
+    "use_pos": True,
+    "param_pos ": {
+        "weight": 0.1,
+        "pos_joint_training": True,
+        "train_pos_path": "train.pos",
+        "valid_pos_path": "dev.pos",
+        "test_pos_path": "test.pos",
+    },
+}
+
+
+def load_config(config_path: os.PathLike, use_default: bool = False):
+    config = _load_config(config_path)
+    if use_default:
+        for attr, val in default_config_dict.items():
+            if not hasattr(config, attr):
+                setattr(config, attr, val)
+            elif isinstance(val, dict):
+                d = getattr(config, attr)
+                for dict_k, dict_v in val.items():
+                    if dict_k not in d:
+                        d[dict_k] = dict_v
+    return config