1 min voice data can also be used to train a good TTS model! (few shot voice cloning)
This report presents the forensic synthetic code analysis of RVC-Boss/GPT-SoVITS, a Python project with 61,307 GitHub stars. SynthScan v2.0 examined 54,244 lines of code across 205 source files, recording 292 pattern matches distributed across 13 syntactic categories. The overall adjusted score of 6.1 places this repository in the Low AI signal band.
The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).
This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.
Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.
This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.
The scanner identified 292 distinct pattern matches across 13 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.
Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | webui.py | 167 | def check_pretrained_is_exist(version): | CODE |
| LOW | api.py | 493 | def change_gpt_sovits_weights(gpt_path, sovits_path): | CODE |
| LOW⚡ | tools/asr/funasr_asr.py | 29 | def is_unregistered_model_error(exc): | CODE |
| LOW⚡ | tools/asr/funasr_asr.py | 34 | def create_fun_asr_nano_model(device): | CODE |
| LOW | GPT_SoVITS/process_ckpt.py | 100 | def get_sovits_version_from_path_fast(sovits_path): | CODE |
| LOW | GPT_SoVITS/inference_webui.py | 750 | def merge_short_text_in_array(texts, threshold): | CODE |
| LOW | GPT_SoVITS/export_torch_script.py | 107 | def multinomial_sample_one_no_sync(probs_sort): | CODE |
| LOW | GPT_SoVITS/export_torch_script.py | 554 | def build_phone_level_feature(res: Tensor, word2ph: IntTensor): | CODE |
| LOW | GPT_SoVITS/utils.py | 120 | def plot_spectrogram_to_numpy(spectrogram): | CODE |
| LOW | GPT_SoVITS/stream_v2pro.py | 188 | def find_best_audio_offset_fast(reference_audio: Tensor, search_audio: Tensor): | CODE |
| LOW | GPT_SoVITS/eres2net/kaldi.py | 121 | def _get_waveform_and_window_properties( | CODE |
| LOW | GPT_SoVITS/module/mel_processing.py | 8 | def dynamic_range_compression_torch(x, C=1, clip_val=1e-5): | CODE |
| LOW | GPT_SoVITS/module/mel_processing.py | 17 | def dynamic_range_decompression_torch(x, C=1): | CODE |
| LOW | GPT_SoVITS/module/mel_processing.py | 31 | def spectral_de_normalize_torch(magnitudes): | CODE |
| LOW | GPT_SoVITS/module/transforms.py | 12 | def piecewise_rational_quadratic_transform( | CODE |
| LOW | GPT_SoVITS/module/transforms.py | 50 | def unconstrained_rational_quadratic_spline( | CODE |
| LOW | GPT_SoVITS/module/transforms.py | 100 | def rational_quadratic_spline( | CODE |
| LOW | GPT_SoVITS/module/mrte_model.py | 158 | def fused_add_tanh_sigmoid_multiply(input, n_channels): | CODE |
| LOW | GPT_SoVITS/module/attentions.py | 260 | def _matmul_with_relative_values(self, x, y): | CODE |
| LOW | GPT_SoVITS/module/attentions.py | 269 | def _matmul_with_relative_keys(self, x, y): | CODE |
| LOW | GPT_SoVITS/module/attentions.py | 294 | def _relative_position_to_absolute_position(self, x): | CODE |
| LOW | GPT_SoVITS/module/attentions.py | 311 | def _absolute_position_to_relative_position(self, x): | CODE |
| LOW | GPT_SoVITS/module/attentions.py | 507 | def remove_weight_norm_modules(module, name="weight"): | CODE |
| LOW | GPT_SoVITS/module/data_utils.py | 109 | def get_audio_text_speaker_pair(self, audiopath_sid_text): | CODE |
| LOW | GPT_SoVITS/module/data_utils.py | 375 | def get_audio_text_speaker_pair(self, audiopath_sid_text): | CODE |
| LOW | GPT_SoVITS/module/data_utils.py | 613 | def get_audio_text_speaker_pair(self, audiopath_sid_text): | CODE |
| LOW | GPT_SoVITS/module/data_utils.py | 824 | def get_audio_text_speaker_pair(self, audiopath_sid_text): | CODE |
| LOW | GPT_SoVITS/module/commons.py | 97 | def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels): | CODE |
| LOW | GPT_SoVITS/module/attentions_onnx.py | 27 | def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels): | CODE |
| LOW | GPT_SoVITS/module/attentions_onnx.py | 223 | def _matmul_with_relative_values(self, x, y): | CODE |
| LOW | GPT_SoVITS/module/attentions_onnx.py | 232 | def _matmul_with_relative_keys(self, x, y): | CODE |
| LOW | GPT_SoVITS/module/attentions_onnx.py | 257 | def _relative_position_to_absolute_position(self, x): | CODE |
| LOW | GPT_SoVITS/module/attentions_onnx.py | 274 | def _absolute_position_to_relative_position(self, x): | CODE |
| LOW | GPT_SoVITS/TTS_infer_pack/TTS.py | 1664 | def using_vocoder_synthesis_batched_infer( | CODE |
| LOW | GPT_SoVITS/TTS_infer_pack/TextPreprocessor.py | 34 | def merge_short_text_in_array(texts: str, threshold: int) -> list: | CODE |
| LOW | GPT_SoVITS/TTS_infer_pack/TextPreprocessor.py | 117 | def segment_and_extract_feature_for_text( | CODE |
| LOW | GPT_SoVITS/TTS_infer_pack/TextPreprocessor.py | 235 | def replace_consecutive_punctuation(self, text): | CODE |
| LOW | GPT_SoVITS/AR/models/t2s_model_onnx.py | 74 | def multinomial_sample_one_no_sync( | CODE |
| LOW | GPT_SoVITS/AR/models/utils.py | 140 | def multinomial_sample_one_no_sync( | CODE |
| LOW | GPT_SoVITS/AR/models/t2s_model.py | 39 | def scaled_dot_product_attention( | CODE |
| LOW | GPT_SoVITS/AR/models/t2s_model.py | 783 | def infer_panel_naive_batched( | CODE |
| LOW | GPT_SoVITS/AR/modules/patched_mha_with_cache_onnx.py | 7 | def multi_head_attention_forward_patched( | CODE |
| LOW | GPT_SoVITS/AR/modules/patched_mha_with_cache.py | 13 | def multi_head_attention_forward_patched( | CODE |
| LOW | GPT_SoVITS/AR/modules/optim.py | 363 | def _show_gradient_dominating_parameter(self, tuples: List[Tuple[Tensor, dict, List[str]]], tot_sumsq: Tensor): | CODE |
| LOW | GPT_SoVITS/text/chinese2.py | 305 | def replace_punctuation_with_en(text): | CODE |
| LOW | GPT_SoVITS/text/chinese2.py | 316 | def replace_consecutive_punctuation(text): | CODE |
| LOW | GPT_SoVITS/text/cantonese.py | 118 | def jyuping_to_initials_finals_tones(jyuping_syllables): | CODE |
| LOW | GPT_SoVITS/text/japanese.py | 138 | def replace_consecutive_punctuation(text): | CODE |
| LOW | GPT_SoVITS/text/japanese.py | 260 | def _numeric_feature_by_regex(regex, s): | CODE |
| LOW | GPT_SoVITS/text/english.py | 124 | def replace_consecutive_punctuation(text): | CODE |
| LOW | GPT_SoVITS/text/tone_sandhi.py | 679 | def _merge_continuous_three_tones(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: | CODE |
| LOW | GPT_SoVITS/text/chinese.py | 58 | def replace_punctuation_with_en(text): | CODE |
| LOW | GPT_SoVITS/text/chinese.py | 69 | def replace_consecutive_punctuation(text): | CODE |
| LOW | GPT_SoVITS/text/g2pw/onnx_api.py | 56 | def _load_json_from_candidates(filename: str, candidate_dirs: List[str]) -> Dict[str, Any]: | CODE |
| LOW | GPT_SoVITS/text/g2pw/onnx_api.py | 67 | def _find_first_existing_file(*paths: str) -> str: | CODE |
| LOW | GPT_SoVITS/text/g2pw/onnx_api.py | 193 | def _convert_bopomofo_to_pinyin(self, bopomofo: str) -> str: | CODE |
| LOW | GPT_SoVITS/text/g2pw/onnx_api.py | 289 | def _predict_with_sentence_dedup( | CODE |
| LOW | GPT_SoVITS/text/zh_normalization/num.py | 175 | def replace_positive_quantifier(match) -> str: | CODE |
| LOW | GPT_SoVITS/text/zh_normalization/char_convert.py | 30 | def tranditional_to_simplified(text: str) -> str: | CODE |
| LOW | GPT_SoVITS/text/zh_normalization/char_convert.py | 34 | def simplified_to_traditional(text: str) -> str: | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | api_v2.py | 456 | CODE | |
| LOW | api.py | 829 | CODE | |
| LOW | api.py | 1361 | CODE | |
| LOW | tools/uvr5/bs_roformer/attend.py | 67 | CODE | |
| LOW | tools/uvr5/bs_roformer/bs_roformer.py | 147 | CODE | |
| LOW | tools/uvr5/bs_roformer/bs_roformer.py | 332 | CODE | |
| LOW | tools/uvr5/bs_roformer/mel_band_roformer.py | 156 | CODE | |
| LOW | tools/uvr5/bs_roformer/mel_band_roformer.py | 276 | CODE | |
| LOW | GPT_SoVITS/inference_webui.py | 789 | CODE | |
| LOW | GPT_SoVITS/export_torch_script_v3v4.py | 99 | CODE | |
| LOW | GPT_SoVITS/export_torch_script_v3v4.py | 155 | CODE | |
| LOW | GPT_SoVITS/eres2net/ERes2NetV2.py | 84 | CODE | |
| LOW | GPT_SoVITS/eres2net/ERes2NetV2.py | 149 | CODE | |
| LOW | GPT_SoVITS/eres2net/ERes2NetV2.py | 153 | CODE | |
| LOW | GPT_SoVITS/eres2net/kaldi.py | 422 | CODE | |
| LOW | GPT_SoVITS/module/mel_processing.py | 28 | CODE | |
| LOW | GPT_SoVITS/module/mel_processing.py | 33 | CODE | |
| LOW | GPT_SoVITS/module/transforms.py | 100 | CODE | |
| LOW | GPT_SoVITS/module/models.py | 437 | CODE | |
| LOW | GPT_SoVITS/module/models_onnx.py | 380 | CODE | |
| LOW | GPT_SoVITS/module/attentions.py | 267 | CODE | |
| LOW | GPT_SoVITS/module/attentions.py | 276 | CODE | |
| LOW | GPT_SoVITS/module/attentions.py | 449 | CODE | |
| LOW | GPT_SoVITS/module/modules.py | 528 | CODE | |
| LOW | GPT_SoVITS/module/modules.py | 593 | CODE | |
| LOW | GPT_SoVITS/module/attentions_onnx.py | 230 | CODE | |
| LOW | GPT_SoVITS/module/attentions_onnx.py | 239 | CODE | |
| LOW | GPT_SoVITS/TTS_infer_pack/TextPreprocessor.py | 239 | CODE | |
| LOW | …T_SoVITS/BigVGAN/alias_free_activation/torch/filter.py | 99 | CODE | |
| LOW | GPT_SoVITS/f5_tts/model/backbones/dit.py | 89 | CODE | |
| LOW | GPT_SoVITS/AR/models/t2s_model_cudagraph.py | 233 | CODE | |
| LOW | GPT_SoVITS/AR/models/t2s_model_cudagraph.py | 240 | CODE | |
| LOW | GPT_SoVITS/AR/modules/transformer_onnx.py | 150 | CODE | |
| LOW | GPT_SoVITS/AR/modules/patched_mha_with_cache_onnx.py | 7 | CODE | |
| LOW | GPT_SoVITS/AR/modules/scaling.py | 231 | CODE | |
| LOW | GPT_SoVITS/AR/modules/patched_mha_with_cache.py | 13 | CODE | |
| LOW | GPT_SoVITS/AR/modules/activation_onnx.py | 19 | CODE | |
| LOW | GPT_SoVITS/AR/modules/activation.py | 78 | CODE | |
| LOW | GPT_SoVITS/AR/modules/transformer.py | 178 | CODE | |
| LOW | GPT_SoVITS/AR/modules/optim.py | 156 | CODE | |
| LOW | GPT_SoVITS/text/chinese2.py | 320 | CODE | |
| LOW | GPT_SoVITS/text/japanese.py | 142 | CODE | |
| LOW | GPT_SoVITS/text/english.py | 128 | CODE | |
| LOW | GPT_SoVITS/text/chinese.py | 73 | CODE | |
| LOW | GPT_SoVITS/text/en_normalization/expend.py | 260 | CODE | |
| LOW | GPT_SoVITS/text/en_normalization/expend.py | 277 | CODE | |
| LOW | GPT_SoVITS/text/zh_normalization/num.py | 54 | CODE | |
| LOW | GPT_SoVITS/text/zh_normalization/num.py | 73 | CODE | |
| LOW | GPT_SoVITS/text/zh_normalization/num.py | 93 | CODE | |
| LOW | GPT_SoVITS/text/zh_normalization/num.py | 130 | CODE | |
| LOW | GPT_SoVITS/text/zh_normalization/num.py | 164 | CODE | |
| LOW | GPT_SoVITS/text/zh_normalization/num.py | 191 | CODE | |
| LOW | GPT_SoVITS/text/zh_normalization/num.py | 239 | CODE | |
| LOW | GPT_SoVITS/text/zh_normalization/num.py | 256 | CODE | |
| LOW | GPT_SoVITS/text/zh_normalization/quantifier.py | 56 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | api_v2.py | 345 | CODE | |
| LOW | webui.py | 244 | CODE | |
| LOW | webui.py | 1046 | CODE | |
| LOW | api.py | 544 | CODE | |
| LOW | api.py | 829 | CODE | |
| LOW | tools/slicer2.py | 67 | CODE | |
| LOW | tools/slice_audio.py | 13 | CODE | |
| LOW | tools/my_utils.py | 49 | CODE | |
| LOW | tools/my_utils.py | 140 | CODE | |
| LOW | tools/my_utils.py | 187 | CODE | |
| LOW | tools/uvr5/webui.py | 45 | CODE | |
| LOW | tools/uvr5/vr.py | 45 | CODE | |
| LOW | tools/uvr5/vr.py | 217 | CODE | |
| LOW | tools/uvr5/mdxnet.py | 172 | CODE | |
| LOW | tools/uvr5/bsroformer.py | 111 | CODE | |
| LOW | tools/asr/fasterwhisper_asr.py | 104 | CODE | |
| LOW | tools/i18n/scan_i18n.py | 29 | CODE | |
| LOW | GPT_SoVITS/s1_train.py | 46 | CODE | |
| LOW | GPT_SoVITS/inference_webui.py | 639 | CODE | |
| LOW | GPT_SoVITS/inference_webui.py | 789 | CODE | |
| LOW | GPT_SoVITS/s2_train_v3_lora.py | 263 | CODE | |
| LOW | GPT_SoVITS/s2_train.py | 318 | CODE | |
| LOW | GPT_SoVITS/stream_v2pro.py | 240 | CODE | |
| LOW | GPT_SoVITS/eres2net/kaldi.py | 82 | CODE | |
| LOW | GPT_SoVITS/module/mrte_model.py | 25 | CODE | |
| LOW | GPT_SoVITS/module/ddp_utils.py | 58 | CODE | |
| LOW | GPT_SoVITS/TTS_infer_pack/TTS.py | 855 | CODE | |
| LOW | GPT_SoVITS/TTS_infer_pack/TTS.py | 997 | CODE | |
| LOW | GPT_SoVITS/TTS_infer_pack/TextPreprocessor.py | 122 | CODE | |
| LOW | GPT_SoVITS/AR/utils/initialize.py | 8 | CODE | |
| LOW | GPT_SoVITS/AR/models/t2s_model_cudagraph.py | 458 | CODE | |
| LOW | GPT_SoVITS/AR/models/t2s_model.py | 583 | CODE | |
| LOW | GPT_SoVITS/AR/modules/patched_mha_with_cache.py | 13 | CODE | |
| LOW | GPT_SoVITS/AR/modules/activation.py | 204 | CODE | |
| LOW | GPT_SoVITS/AR/modules/optim.py | 197 | CODE | |
| LOW | GPT_SoVITS/text/chinese2.py | 180 | CODE | |
| LOW | GPT_SoVITS/text/cantonese.py | 118 | CODE | |
| LOW | GPT_SoVITS/text/cantonese.py | 176 | CODE | |
| LOW | GPT_SoVITS/text/japanese.py | 183 | CODE | |
| LOW | GPT_SoVITS/text/english.py | 131 | CODE | |
| LOW | GPT_SoVITS/text/english.py | 155 | CODE | |
| LOW | GPT_SoVITS/text/english.py | 270 | CODE | |
| LOW | GPT_SoVITS/text/english.py | 309 | CODE | |
| LOW | GPT_SoVITS/text/tone_sandhi.py | 495 | CODE | |
| LOW | GPT_SoVITS/text/tone_sandhi.py | 550 | CODE | |
| LOW | GPT_SoVITS/text/tone_sandhi.py | 586 | CODE | |
| LOW | GPT_SoVITS/text/chinese.py | 94 | CODE | |
| LOW | GPT_SoVITS/text/korean.py | 183 | CODE | |
| LOW | GPT_SoVITS/text/korean.py | 15 | CODE | |
| LOW | GPT_SoVITS/text/en_normalization/expend.py | 226 | CODE | |
| LOW | GPT_SoVITS/text/g2pw/onnx_api.py | 74 | CODE | |
| LOW | GPT_SoVITS/text/g2pw/onnx_api.py | 248 | CODE | |
| LOW | GPT_SoVITS/text/g2pw/utils.py | 132 | CODE | |
| LOW | GPT_SoVITS/text/LangSegmenter/langsegmenter.py | 90 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | api_v2.py | 444 | except Exception as e: | CODE |
| LOW | api_v2.py | 521 | except Exception as e: | CODE |
| LOW | api_v2.py | 551 | except Exception as e: | CODE |
| LOW | api_v2.py | 563 | except Exception as e: | CODE |
| LOW | api_v2.py | 573 | except Exception: | CODE |
| LOW | webui.py | 32 | except Exception as e: | CODE |
| LOW | api.py | 497 | except Exception as e: | CODE |
| LOW | api.py | 900 | except Exception as e: | CODE |
| MEDIUM | api.py | 493 | def change_gpt_sovits_weights(gpt_path, sovits_path): | CODE |
| LOW | tools/my_utils.py | 29 | except Exception: | CODE |
| MEDIUM | tools/my_utils.py | 16 | def load_audio(file, sr): | CODE |
| MEDIUM | tools/uvr5/bsroformer.py | 107 | print("Error: Unknown model: {}".format(self.model_type)) | CODE |
| LOW | tools/uvr5/bsroformer.py | 212 | except Exception as e: | CODE |
| MEDIUM | tools/uvr5/bsroformer.py | 214 | print("Error message: {}".format(str(e))) | CODE |
| LOW⚡ | tools/asr/funasr_asr.py | 23 | except Exception: | CODE |
| LOW | tools/asr/funasr_asr.py | 140 | except Exception: | CODE |
| MEDIUM | tools/asr/funasr_asr.py | 19 | def only_asr(input_file, language, backend="fun-asr-nano"): | CODE |
| LOW | tools/asr/fasterwhisper_asr.py | 47 | except Exception: | CODE |
| LOW | tools/asr/fasterwhisper_asr.py | 137 | except Exception as e: | CODE |
| LOW | tools/i18n/scan_i18n.py | 48 | except Exception as e: | CODE |
| LOW | GPT_SoVITS/s1_train.py | 144 | except Exception: | CODE |
| LOW | GPT_SoVITS/inference_webui.py | 165 | except Exception as e: | CODE |
| LOW | GPT_SoVITS/module/data_utils.py | 83 | except Exception: | CODE |
| LOW | GPT_SoVITS/module/data_utils.py | 337 | except Exception: | CODE |
| LOW | GPT_SoVITS/module/data_utils.py | 575 | except Exception: | CODE |
| LOW | GPT_SoVITS/module/data_utils.py | 786 | except Exception: | CODE |
| LOW | GPT_SoVITS/TTS_infer_pack/TTS.py | 1515 | except Exception as e: | CODE |
| MEDIUM | GPT_SoVITS/TTS_infer_pack/TTS.py | 126 | def __getattr__(self, item): | CODE |
| LOW | GPT_SoVITS/AR/utils/__init__.py | 34 | except Exception: | CODE |
| MEDIUM | GPT_SoVITS/AR/utils/__init__.py | 28 | def check_txt_file(file_path): | CODE |
| LOW | GPT_SoVITS/AR/models/t2s_model_cudagraph.py | 584 | except Exception as e: | CODE |
| LOW | GPT_SoVITS/AR/data/dataset.py | 134 | except Exception: | CODE |
| LOW | GPT_SoVITS/text/japanese.py | 72 | except Exception: | CODE |
| LOW | GPT_SoVITS/text/g2pw/onnx_api.py | 24 | except Exception: | CODE |
| LOW | GPT_SoVITS/text/g2pw/dataset.py | 75 | except Exception: | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | api_v2.py | 181 | def pack_ogg(io_buffer: BytesIO, data: np.ndarray, rate: int): | COMMENT |
| LOW | api_v2.py | 521 | except Exception as e: | COMMENT |
| LOW | api.py | 681 | def pack_ogg(audio_bytes, data, rate): | COMMENT |
| LOW | GPT_SoVITS/inference_webui.py | 1401 | inp_refs, | COMMENT |
| LOW | GPT_SoVITS/export_torch_script_v3v4.py | 681 | cfm.estimator, | COMMENT |
| LOW | GPT_SoVITS/export_torch_script_v3v4.py | 881 | # torch.onnx.export( | COMMENT |
| LOW | GPT_SoVITS/export_torch_script_v3v4.py | 1221 | gpt_sovits_v3v4, | COMMENT |
| LOW | GPT_SoVITS/export_torch_script.py | 941 | # bert_model = AutoModelForMaskedLM.from_pretrained(bert_path,output_hidden_states=True,torchscript=True) | COMMENT |
| LOW | GPT_SoVITS/s2_train_v3.py | 161 | ) | COMMENT |
| LOW | GPT_SoVITS/s2_train_v3.py | 221 | # torch.load(hps.train.pretrained_s2D, map_location="cpu")["weight"] | COMMENT |
| LOW | GPT_SoVITS/s2_train_v3.py | 381 | # "slice/mel_gen": utils.plot_spectrogram_to_numpy(y_hat_mel[0].data.cpu().numpy()), | COMMENT |
| LOW | GPT_SoVITS/module/attentions_onnx.py | 101 | # x = x * x_mask | COMMENT |
| LOW | GPT_SoVITS/module/core_vq.py | 1 | # Copyright (c) Meta Platforms, Inc. and affiliates. | COMMENT |
| LOW | GPT_SoVITS/TTS_infer_pack/TTS.py | 281 | "v2Pro": 486, | COMMENT |
| LOW | GPT_SoVITS/TTS_infer_pack/TTS.py | 941 | #### 直接对phones和bert_features进行pad。(padding策略会影响T2S模型生成的结果,但不直接影响复读概率。影响复读概率的主要因素是mask的策略) | COMMENT |
| LOW | GPT_SoVITS/TTS_infer_pack/TTS.py | 1281 | t_34 += t4 - t3 | COMMENT |
| LOW | GPT_SoVITS/AR/models/t2s_lightning_module.py | 81 | ) | COMMENT |
| LOW | GPT_SoVITS/AR/models/t2s_lightning_module.py | 101 | # f"val_top_{self.top_k}_acc", | COMMENT |
| LOW | GPT_SoVITS/AR/models/t2s_model.py | 661 | value=False, | COMMENT |
| LOW | GPT_SoVITS/AR/models/t2s_model.py | 681 | COMMENT | |
| LOW | GPT_SoVITS/AR/modules/scaling.py | 1 | # Copyright 2022 Xiaomi Corp. (authors: Daniel Povey) | COMMENT |
| LOW | GPT_SoVITS/AR/modules/optim.py | 1 | # Copyright 2022 Xiaomi Corp. (authors: Daniel Povey) | COMMENT |
| LOW | GPT_SoVITS/AR/data/dataset.py | 321 | # print('batch["phoneme_ids_len"]:', batch["phoneme_ids_len"], | COMMENT |
| LOW | GPT_SoVITS/text/tone_sandhi.py | 1 | # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. | COMMENT |
| LOW | GPT_SoVITS/text/korean.py | 61 | # This is a list of Korean classifiers preceded by pure Korean numerals. | COMMENT |
| LOW | GPT_SoVITS/text/g2pw/dataset.py | 1 | # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. | COMMENT |
| LOW | GPT_SoVITS/text/g2pw/utils.py | 1 | # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. | COMMENT |
| LOW | GPT_SoVITS/text/zh_normalization/num.py | 1 | # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. | COMMENT |
| LOW | GPT_SoVITS/text/zh_normalization/constants.py | 1 | # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. | COMMENT |
| LOW | GPT_SoVITS/text/zh_normalization/__init__.py | 1 | # Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. | COMMENT |
| LOW | GPT_SoVITS/text/zh_normalization/char_convert.py | 1 | # coding=utf-8 | COMMENT |
| LOW | GPT_SoVITS/text/zh_normalization/chronology.py | 1 | # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. | COMMENT |
| LOW | GPT_SoVITS/text/zh_normalization/phonecode.py | 1 | # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. | COMMENT |
| LOW | GPT_SoVITS/text/zh_normalization/text_normlization.py | 1 | # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. | COMMENT |
| LOW | GPT_SoVITS/text/zh_normalization/quantifier.py | 1 | # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. | COMMENT |
| LOW | GPT_SoVITS/feature_extractor/cnhubert.py | 41 | # def __init__(self): | COMMENT |
| LOW | GPT_SoVITS/feature_extractor/cnhubert.py | 61 | # def __init__(self): | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | api.py | 1154 | # -------------------------------- | COMMENT |
| MEDIUM | api.py | 1156 | # -------------------------------- | COMMENT |
| MEDIUM | api.py | 1294 | # -------------------------------- | COMMENT |
| MEDIUM | api.py | 1296 | # -------------------------------- | COMMENT |
| MEDIUM | GPT_SoVITS/AR/models/t2s_model_cudagraph.py | 74 | # ─── KV Cache ────────────────────���─────────────────────────────────────────── | COMMENT |
| MEDIUM | GPT_SoVITS/AR/models/t2s_model_cudagraph.py | 117 | # ─── Attention (PyTorch native SDPA, no flash_attn) ───────────────────────── | COMMENT |
| MEDIUM | GPT_SoVITS/AR/models/t2s_model_cudagraph.py | 185 | # ─── Feed Forward ──────────────────────────────────────────────────────────── | COMMENT |
| MEDIUM | GPT_SoVITS/AR/models/t2s_model_cudagraph.py | 201 | # ─── Transformer Block ────────────────────────────────────────────────────── | COMMENT |
| MEDIUM | GPT_SoVITS/AR/models/t2s_model_cudagraph.py | 243 | # ─── Transformer Decoder ──────────────────────────────────────────────────── | COMMENT |
| MEDIUM | GPT_SoVITS/AR/models/t2s_model_cudagraph.py | 291 | # ─── T2S Decoder ───────────────────────────────────────────────────────────── | COMMENT |
| MEDIUM | GPT_SoVITS/AR/models/t2s_model_cudagraph.py | 433 | # ─── CUDA Graph Runner ─────────────────────────────────────────────────────── | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | api.py | 541 | CODE | |
| LOW | tools/audio_sr.py | 1 | CODE | |
| LOW | tools/audio_sr.py | 1 | CODE | |
| LOW | tools/audio_sr.py | 1 | CODE | |
| LOW | tools/audio_sr.py | 1 | CODE | |
| LOW | GPT_SoVITS/inference_webui.py | 636 | CODE | |
| LOW | GPT_SoVITS/module/core_vq.py | 36 | CODE | |
| LOW | GPT_SoVITS/TTS_infer_pack/__init__.py | 1 | CODE | |
| LOW | GPT_SoVITS/TTS_infer_pack/__init__.py | 1 | CODE | |
| LOW | GPT_SoVITS/TTS_infer_pack/TextPreprocessor.py | 13 | CODE | |
| LOW | …SoVITS/BigVGAN/alias_free_activation/torch/__init__.py | 4 | CODE | |
| LOW | …SoVITS/BigVGAN/alias_free_activation/torch/__init__.py | 5 | CODE | |
| LOW | …SoVITS/BigVGAN/alias_free_activation/torch/__init__.py | 6 | CODE | |
| LOW | GPT_SoVITS/f5_tts/model/__init__.py | 1 | CODE | |
| LOW | GPT_SoVITS/f5_tts/model/modules.py | 10 | CODE | |
| LOW | GPT_SoVITS/f5_tts/model/backbones/dit.py | 10 | CODE | |
| LOW | GPT_SoVITS/AR/models/structs_cudagraph.py | 1 | CODE | |
| LOW | GPT_SoVITS/AR/models/t2s_model_cudagraph.py | 7 | CODE | |
| LOW | GPT_SoVITS/AR/models/t2s_model_cudagraph.py | 9 | CODE | |
| LOW | GPT_SoVITS/AR/models/t2s_model_cudagraph.py | 12 | CODE | |
| LOW | GPT_SoVITS/AR/models/t2s_model_cudagraph.py | 12 | CODE | |
| LOW | GPT_SoVITS/AR/modules/patched_mha_with_cache_onnx.py | 1 | CODE | |
| LOW | GPT_SoVITS/AR/modules/patched_mha_with_cache.py | 1 | CODE | |
| LOW | GPT_SoVITS/text/en_normalization/expend.py | 3 | CODE | |
| LOW | GPT_SoVITS/text/g2pw/__init__.py | 1 | CODE | |
| LOW | GPT_SoVITS/text/LangSegmenter/__init__.py | 1 | CODE | |
| LOW | GPT_SoVITS/text/zh_normalization/__init__.py | 14 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tools/uvr5/webui.py | 12 | logger = logging.getLogger(__name__) | CODE |
| LOW | tools/uvr5/vr.py | 6 | logger = logging.getLogger(__name__) | CODE |
| LOW | tools/uvr5/mdxnet.py | 4 | logger = logging.getLogger(__name__) | CODE |
| LOW | GPT_SoVITS/eres2net/kaldi.py | 7 | __all__ = [ | CODE |
| LOW | GPT_SoVITS/TTS_infer_pack/TTS.py | 399 | def update_version(self, version: str) -> None: | CODE |
| LOW | GPT_SoVITS/AR/data/bucket_sampler.py | 13 | __all__ = [ | CODE |
| LOW | GPT_SoVITS/AR/data/bucket_sampler.py | 140 | def set_epoch(self, epoch: int) -> None: | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | tools/assets.py | 7 | const newUrl = `${window.location.pathname}?${params.toString()}`; | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | GPT_SoVITS/text/japanese.py | 184 | Extract phoneme + prosoody symbol sequence from input full-context labels. The algorithm is based on `Prosodic feat | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | tools/slicer2.py | 4 | # This function is obtained from librosa. | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | GPT_SoVITS/AR/modules/optim.py | 462 | # For parameters with 1 element we just use regular Adam. | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | GPT_SoVITS/AR/modules/activation.py | 274 | # When lifting this restriction, don't forget to either | STRING |
| LOW | GPT_SoVITS/AR/modules/activation.py | 274 | # When lifting this restriction, don't forget to either | STRING |