Sourcery refactored main branch #1
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| ## Load the models one by one. | ||
| print("Preparing the encoder, the synthesizer and the vocoder...") | ||
| encoder.load_model(enc_model_fpath) | ||
| synthesizer = Synthesizer(syn_model_fpath) | ||
| vocoder.load_model(voc_model_fpath) | ||
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| texts_array = [] | ||
| with open('documentation/voice_cloning/sample_text.txt', 'r') as voice_cloning_para: | ||
| texts_array = voice_cloning_para.readlines() | ||
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Function voice_creation_build refactored with the following changes:
- Replace assignment with augmented assignment (
aug-assign)
| if isinstance(fpath_or_wav, str) or isinstance(fpath_or_wav, Path): | ||
| if isinstance(fpath_or_wav, (str, Path)): | ||
| wav, source_sr = librosa.load(str(fpath_or_wav), sr=None) | ||
| else: | ||
| wav = fpath_or_wav | ||
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| # Resample the wav if needed | ||
| if source_sr is not None and source_sr != sampling_rate: | ||
| wav = librosa.resample(wav, source_sr, sampling_rate) | ||
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| # Apply the preprocessing: normalize volume and shorten long silences | ||
| if normalize: | ||
| wav = normalize_volume(wav, audio_norm_target_dBFS, increase_only=True) | ||
| if webrtcvad and trim_silence: | ||
| wav = trim_long_silences(wav) | ||
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Function preprocess_wav refactored with the following changes:
- Merge isinstance calls (
merge-is-instance)
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| frames = torch.from_numpy(frames_batch).to(_device) | ||
| embed = _model.forward(frames).detach().cpu().numpy() | ||
| return embed | ||
| return _model.forward(frames).detach().cpu().numpy() |
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Function embed_frames_batch refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
| self.sample_data = dict() | ||
| self.sample_data = {} | ||
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Function DatasetLog.__init__ refactored with the following changes:
- Replace dict() with {} (
dict-literal)
| if not param_name in self.sample_data: | ||
| if param_name not in self.sample_data: |
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Function DatasetLog.add_sample refactored with the following changes:
- Simplify logical expression using De Morgan identities (
de-morgan)
| y = g * F.relu(x1) + (1. - g) * x | ||
| return y | ||
| return g * F.relu(x1) + (1. - g) * x |
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Function HighwayNetwork.forward refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
| if speaker_embedding.dim() == 1: | ||
| idx = 0 | ||
| else: | ||
| idx = 1 | ||
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| idx = 0 if speaker_embedding.dim() == 1 else 1 |
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Function Encoder.add_speaker_embedding refactored with the following changes:
- Replace if statement with if expression (
assign-if-exp)
| for i in range(num_highways): | ||
| for _ in range(num_highways): |
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Function CBHG.__init__ refactored with the following changes:
- Replace unused for index with underscore (
for-index-underscore)
| parameters = sum([np.prod(p.size()) for p in parameters]) / 1_000_000 | ||
| parameters = sum(np.prod(p.size()) for p in parameters) / 1_000_000 |
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Function Tacotron.num_params refactored with the following changes:
- Replace unneeded comprehension with generator (
comprehension-to-generator)
| return "\n".join([" ".join(seq[i:i + max_words]) for i in range(0, len(seq), max_words)]) | ||
| return "\n".join( | ||
| " ".join(seq[i:i + max_words]) for i in range(0, len(seq), max_words)) |
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Function split_title_line refactored with the following changes:
- Replace unneeded comprehension with generator (
comprehension-to-generator)
| def decode_mu_law(y, mu, from_labels=True) : | ||
| def decode_mu_law(y, mu, from_labels=True): | ||
| if from_labels: | ||
| y = label_2_float(y, math.log2(mu)) | ||
| mu = mu - 1 | ||
| x = np.sign(y) / mu * ((1 + mu) ** np.abs(y) - 1) | ||
| return x | ||
| return np.sign(y) / mu * ((1 + mu) ** np.abs(y) - 1) |
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Function decode_mu_law refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
| bar = '' | ||
| for i in range(size): | ||
| bar += '█' if i <= done else '░' | ||
| return bar | ||
| return ''.join('█' if i <= done else '░' for i in range(size)) |
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Function progbar refactored with the following changes:
- Use str.join() instead of for loop (
use-join) - Inline variable that is immediately returned (
inline-immediately-returned-variable)
| def simple_table(item_tuples) : | ||
| def simple_table(item_tuples): | ||
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| border_pattern = '+---------------------------------------' | ||
| whitespace = ' ' | ||
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| headings, cells, = [], [] | ||
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| for item in item_tuples : | ||
| for item in item_tuples: | ||
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| heading, cell = str(item[0]), str(item[1]) | ||
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| pad_head = True if len(heading) < len(cell) else False | ||
| pad_head = len(heading) < len(cell) |
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Function simple_table refactored with the following changes:
- Simplify boolean if expression (
boolean-if-exp-identity)
| def time_since(started) : | ||
| def time_since(started): | ||
| elapsed = time.time() - started | ||
| m = int(elapsed // 60) | ||
| s = int(elapsed % 60) | ||
| if m >= 60 : | ||
| h = int(m // 60) | ||
| m = m % 60 | ||
| return f'{h}h {m}m {s}s' | ||
| else : | ||
| if m < 60: | ||
| return f'{m}m {s}s' | ||
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| h = int(m // 60) | ||
| m %= 60 | ||
| return f'{h}h {m}m {s}s' |
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Function time_since refactored with the following changes:
- Replace assignment with augmented assignment (
aug-assign) - Swap if/else branches (
swap-if-else-branches) - Remove unnecessary else after guard condition (
remove-unnecessary-else)
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| if normalize: | ||
| mel = mel / hp.mel_max_abs_value | ||
| mel = torch.from_numpy(mel[None, ...]) | ||
| wav = _model.generate(mel, batched, target, overlap, hp.mu_law, progress_callback) | ||
| return wav | ||
| return _model.generate( | ||
| mel, batched, target, overlap, hp.mu_law, progress_callback | ||
| ) |
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Function infer_waveform refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
| if torch.cuda.is_available(): | ||
| mels = mels.cuda() | ||
| else: | ||
| mels = mels.cpu() | ||
| mels = mels.cuda() if torch.cuda.is_available() else mels.cpu() |
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Function WaveRNN.generate refactored with the following changes:
- Replace if statement with if expression (
assign-if-exp)
| if side == 'before' or side == 'both': | ||
| if side in ['before', 'both']: |
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Function WaveRNN.pad_tensor refactored with the following changes:
- Replace multiple comparisons of same variable with
inoperator (merge-comparisons)
| parameters = sum([np.prod(p.size()) for p in parameters]) / 1_000_000 | ||
| parameters = sum(np.prod(p.size()) for p in parameters) / 1_000_000 |
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Function WaveRNN.num_params refactored with the following changes:
- Replace unneeded comprehension with generator (
comprehension-to-generator)
| image_list = list() | ||
| image_list = [] | ||
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| if not 'user_id' in user_dict: | ||
| if 'user_id' not in user_dict: | ||
| raise create_error_message('Bad Request') | ||
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| if user_dict['image_id'] == '': | ||
| image_list = user_table.find_one({'_id': ObjectId(user_dict['user_id'])})['images'] | ||
| image_table.delete(image_list) | ||
| return user_table.delete_one({'_id': ObjectId(user_dict['user_id'])}) | ||
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Function delete refactored with the following changes:
- Replace list() with [] (
list-literal) - Simplify logical expression using De Morgan identities (
de-morgan)
| return True if user_table.find_one({'name': user.get_name()}) else False | ||
| return bool(user_table.find_one({'name': user.get_name()})) |
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Function user_already_exists refactored with the following changes:
- Simplify boolean if expression (
boolean-if-exp-identity)
Sourcery Code Quality Report✅ Merging this PR will increase code quality in the affected files by 0.14%.
Here are some functions in these files that still need a tune-up:
Legend and ExplanationThe emojis denote the absolute quality of the code:
The 👍 and 👎 indicate whether the quality has improved or gotten worse with this pull request. Please see our documentation here for details on how these metrics are calculated. We are actively working on this report - lots more documentation and extra metrics to come! Let us know what you think of it by mentioning @sourcery-ai in a comment. |
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