repo stringclasses 454
values | file_path stringlengths 5 201 | extension stringclasses 1
value | content stringlengths 8 509k | num_lines int64 3 16.9k | size_bytes int64 8 511k |
|---|---|---|---|---|---|
fairseq | examples/speech_text_joint_to_text/criterions/multi_modality_cross_entropy.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
from fairseq import utils
from fairseq.criterions import register_criterion
from fairseq.criterions.label_smoothed_cross_entropy ... | 102 | 4,105 |
fairseq | examples/speech_text_joint_to_text/criterions/text_guide_cross_entropy_acc.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
import torch
import torch.nn.functional as F
from fairseq import utils
from fairseq.criterions import FairseqCriterion, register_c... | 225 | 11,031 |
fairseq | examples/speech_text_joint_to_text/scripts/g2p_encode.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import itertools
import logging
import re
import time
from g2p_en import G2p
logger = logging.getLogger(__name__)
FAIL_SENT... | 192 | 5,844 |
fairseq | examples/speech_text_joint_to_text/scripts/convert_model.py | .py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import re
from collections import OrderedDict
import torch
from fairseq.file_io import PathManager
... | 72 | 1,866 |
fairseq | examples/speech_text_joint_to_text/data/pair_denoising_dataset.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import copy
import math
import re
import torch
from fairseq.data import data_utils
from fairseq.data.language_pair_dataset import LanguagePa... | 319 | 11,448 |
fairseq | examples/speech_text_joint_to_text/models/s2t_dualinputwavtransformer.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
from collections import OrderedDict, namedtuple
import torch.nn as nn
from fairseq import checkpoint_utils, utils
from fairse... | 527 | 21,145 |
fairseq | examples/speech_text_joint_to_text/models/s2t_dualinputtransformer.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
from collections import namedtuple
import torch
import torch.nn as nn
from fairseq import checkpoint_utils
from fairseq import... | 1,094 | 45,047 |
fairseq | examples/speech_text_joint_to_text/models/s2t_dualinputxmtransformer.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import copy
import torch.nn as nn
from fairseq import checkpoint_utils
from fairseq import utils
from fairseq.data.data_utils import lengths_... | 585 | 21,461 |
fairseq | examples/speech_text_joint_to_text/models/joint_speech_text_pretrain_transformer.py | .py | #!/usr/bin/env python3
import logging
from collections import OrderedDict, namedtuple
from typing import Dict, Optional
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch import Tensor
from fairseq import checkpoint_utils, utils
from fairseq.file_io import PathManager
from fairseq.models i... | 699 | 28,546 |
fairseq | examples/discriminative_reranking_nmt/drnmt_rerank.py | .py | #!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Score raw text with a trained model.
"""
from collections import namedtuple
import logging
from multiprocessing ... | 365 | 11,312 |
fairseq | examples/discriminative_reranking_nmt/tasks/__init__.py | .py | from .discriminative_reranking_task import DiscriminativeRerankingNMTTask
__all__ = [
"DiscriminativeRerankingNMTTask",
]
| 7 | 128 |
fairseq | examples/discriminative_reranking_nmt/tasks/discriminative_reranking_task.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from dataclasses import dataclass, field
import itertools
import logging
import os
import numpy as np
import torch
from fairseq.logging imp... | 491 | 17,739 |
fairseq | examples/discriminative_reranking_nmt/criterions/discriminative_reranking_criterion.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
from dataclasses import dataclass, field
import torch
import torch.nn.functional as F
from fairseq import utils
from fairseq.log... | 140 | 5,024 |
fairseq | examples/discriminative_reranking_nmt/criterions/__init__.py | .py | from .discriminative_reranking_criterion import KLDivergenceRerankingCriterion
__all__ = [
"KLDivergenceRerankingCriterion",
]
| 7 | 133 |
fairseq | examples/discriminative_reranking_nmt/scripts/prep_data.py | .py | #!/usr/bin/env python
import argparse
from multiprocessing import Pool
from pathlib import Path
import sacrebleu
import sentencepiece as spm
def read_text_file(filename):
with open(filename, "r") as f:
output = [line.strip() for line in f]
return output
def get_bleu(in_sent, target_sent):
ble... | 137 | 4,872 |
fairseq | examples/discriminative_reranking_nmt/models/discriminative_reranking_model.py | .py | from dataclasses import dataclass, field
import os
import torch
import torch.nn as nn
from fairseq import utils
from fairseq.dataclass import ChoiceEnum, FairseqDataclass
from fairseq.models import (
BaseFairseqModel,
register_model,
)
from fairseq.models.roberta.model import RobertaClassificationHead
from ... | 366 | 13,714 |
fairseq | examples/discriminative_reranking_nmt/models/__init__.py | .py | from .discriminative_reranking_model import DiscriminativeNMTReranker
__all__ = [
"DiscriminativeNMTReranker",
]
| 7 | 119 |
fairseq | examples/latent_depth/latent_depth_src/multilingual_translation_latent_depth.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from fairseq.tasks import register_task
from fairseq.tasks.multilingual_translation import MultilingualTranslationTask
from fairseq.utils impo... | 196 | 8,592 |
fairseq | examples/latent_depth/latent_depth_src/loss/latent_depth.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
import torch
from torch.nn.modules.loss import _Loss
class LatentLayersKLLoss(_Loss):
def __init__(self, args):
sup... | 100 | 3,802 |
fairseq | examples/latent_depth/latent_depth_src/modules/latent_layers.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
class LayerSelect(nn.Module):
"""Compute samples (from a Gumbel-Sigmoid distribution) which is used a... | 76 | 2,605 |
fairseq | examples/latent_depth/latent_depth_src/models/latent_multilingual_transformer.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from fairseq.models import register_model, register_model_architecture
from fairseq.models.multilingual_transformer import MultilingualTransfo... | 77 | 3,211 |
fairseq | examples/latent_depth/latent_depth_src/models/latent_transformer.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Any, Dict, Optional
import torch.nn as nn
from fairseq.models.fairseq_encoder import EncoderOut
from fairseq.models.transf... | 157 | 5,584 |
fairseq | fairseq_cli/generate.py | .py | #!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Translate pre-processed data with a trained model.
"""
import ast
import logging
import math
import os
import sy... | 418 | 15,805 |
fairseq | fairseq_cli/preprocess.py | .py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Data pre-processing: build vocabularies and binarize training data.
"""
import logging
import os
import shutil
impo... | 394 | 12,218 |
fairseq | fairseq_cli/score.py | .py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
BLEU scoring of generated translations against reference translations.
"""
import argparse
import os
import sys
fr... | 103 | 3,287 |
fairseq | fairseq_cli/train.py | .py | #!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Train a new model on one or across multiple GPUs.
"""
import argparse
import logging
import math
import os
impor... | 582 | 20,723 |
fairseq | fairseq_cli/hydra_validate.py | .py | #!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
import os
import sys
from itertools import chain
import torch
from hydra.core.hydra_config import Hy... | 189 | 6,420 |
fairseq | fairseq_cli/eval_lm.py | .py | #!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Evaluate the perplexity of a trained language model.
"""
import logging
import math
import os
import sys
from a... | 348 | 11,960 |
fairseq | fairseq_cli/validate.py | .py | #!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
import os
import sys
from argparse import Namespace
from itertools import chain
import torch
from om... | 154 | 5,228 |
fairseq | fairseq_cli/interactive.py | .py | #!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Translate raw text with a trained model. Batches data on-the-fly.
"""
import ast
import fileinput
import logging... | 318 | 11,465 |
fairseq | fairseq_cli/hydra_train.py | .py | #!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
import os
import hydra
import torch
from hydra.core.hydra_config import HydraConfig
from omegaconf i... | 92 | 2,714 |
fish-speech | tools/run_webui.py | .py | import os
from argparse import ArgumentParser
from pathlib import Path
import pyrootutils
import torch
from loguru import logger
pyrootutils.setup_root(__file__, indicator=".project-root", pythonpath=True)
from fish_speech.inference_engine import TTSInferenceEngine
from fish_speech.models.dac.inference import load_m... | 108 | 3,377 |
fish-speech | tools/api_server.py | .py | import json
import multiprocessing
import os
import re
from argparse import Namespace
from threading import Lock
import pyrootutils
import uvicorn
from kui.asgi import (
Depends,
FactoryClass,
HTTPException,
HttpRoute,
Kui,
OpenAPI,
Routes,
)
from kui.cors import CORSConfig
from kui.openapi... | 146 | 4,408 |
fish-speech | tools/api_client.py | .py | import argparse
import base64
import time
import wave
import ormsgpack
import pyaudio
import requests
from pydub import AudioSegment
from pydub.playback import play
from fish_speech.utils.file import audio_to_bytes, read_ref_text
from fish_speech.utils.schema import ServeReferenceAudio, ServeTTSRequest
def parse_ar... | 240 | 7,704 |
fish-speech | tools/server/inference.py | .py | from http import HTTPStatus
import numpy as np
from kui.asgi import HTTPException
from fish_speech.inference_engine import TTSInferenceEngine
from fish_speech.utils.schema import ServeTTSRequest
AMPLITUDE = 32768 # Needs an explaination
def inference_wrapper(req: ServeTTSRequest, engine: TTSInferenceEngine):
... | 46 | 1,352 |
fish-speech | tools/server/exception_handler.py | .py | import traceback
from http import HTTPStatus
from kui.asgi import HTTPException, JSONResponse
class ExceptionHandler:
async def http_exception_handler(self, exc: HTTPException):
return JSONResponse(
dict(
statusCode=exc.status_code,
message=exc.content,
... | 28 | 729 |
fish-speech | tools/server/views.py | .py | import io
import os
import re
import shutil
import tempfile
import time
from http import HTTPStatus
from pathlib import Path
import numpy as np
import ormsgpack
import soundfile as sf
import torch
from kui.asgi import (
Body,
HTTPException,
HttpView,
JSONResponse,
Routes,
StreamResponse,
Up... | 489 | 17,012 |
fish-speech | tools/server/model_utils.py | .py | import io
import re
import librosa
import torch
import torchaudio
from cachetools import LRUCache, cached
CACHE_MAXSIZE = 10000
MICRO_BATCH_SIZE = 8
ASR_SAMPLE_RATE = 16000
HUGE_GAP_THRESHOLD = 4000
@torch.no_grad()
@torch.autocast(device_type="cuda", dtype=torch.half)
def batch_encode(model, audios_list: list[byte... | 87 | 2,643 |
fish-speech | tools/server/model_manager.py | .py | import torch
from loguru import logger
from fish_speech.inference_engine import TTSInferenceEngine
from fish_speech.models.dac.inference import load_model as load_decoder_model
from fish_speech.models.text2semantic.inference import launch_thread_safe_queue
from fish_speech.utils.schema import ServeTTSRequest
from tool... | 94 | 2,974 |
fish-speech | tools/server/api_utils.py | .py | from argparse import ArgumentParser
from http import HTTPStatus
from typing import Annotated, Any
import ormsgpack
from baize.datastructures import ContentType
from kui.asgi import (
HTTPException,
HttpRequest,
JSONResponse,
request,
)
from loguru import logger
from pydantic import BaseModel
from fish... | 152 | 4,451 |
fish-speech | tools/webui/inference.py | .py | import html
from functools import partial
from typing import Any, Callable
from fish_speech.i18n import i18n
from fish_speech.utils.schema import ServeReferenceAudio, ServeTTSRequest
def inference_wrapper(
text,
reference_id,
reference_audio,
reference_text,
max_new_tokens,
chunk_length,
... | 90 | 2,109 |
fish-speech | tools/webui/__init__.py | .py | from typing import Callable
import gradio as gr
from fish_speech.i18n import i18n
from tools.webui.variables import HEADER_MD, TEXTBOX_PLACEHOLDER
def build_app(inference_fct: Callable, theme: str = "light") -> gr.Blocks:
with gr.Blocks(theme=gr.themes.Base()) as app:
gr.Markdown(HEADER_MD)
# U... | 156 | 6,167 |
fish-speech | tools/webui/variables.py | .py | from fish_speech.i18n import i18n
HEADER_MD = f"""# Fish Speech
{i18n("A text-to-speech model based on VQ-GAN and Llama developed by [Fish Audio](https://fish.audio).")}
{i18n("You can find the source code [here](https://github.com/fishaudio/fish-speech) and models [here](https://huggingface.co/fishaudio/fish-spee... | 15 | 605 |
fish-speech | tools/vqgan/extract_vq.py | .py | import os
import subprocess as sp
import sys
import time
from datetime import timedelta
from functools import lru_cache
from pathlib import Path
from random import Random
import click
import numpy as np
import torch
import torchaudio
from hydra import compose, initialize
from hydra.utils import instantiate
from loguru... | 241 | 7,116 |
fish-speech | tools/vqgan/create_train_split.py | .py | import math
from pathlib import Path
from random import Random
import click
from loguru import logger
from pydub import AudioSegment
from tqdm import tqdm
from fish_speech.utils.file import AUDIO_EXTENSIONS, list_files, load_filelist
@click.command()
@click.argument("root", type=click.Path(exists=True, path_type=Pa... | 84 | 3,008 |
fish-speech | tools/llama/merge_lora.py | .py | import shutil
from copy import deepcopy
from pathlib import Path
import click
import hydra
import torch
from hydra import compose, initialize
from hydra.utils import instantiate
from loguru import logger
from fish_speech.models.text2semantic.llama import BaseTransformer
from fish_speech.models.text2semantic.lora impo... | 97 | 3,369 |
fish-speech | tools/llama/eval_in_context.py | .py | import pyrootutils
import torch
import torch.nn.functional as F
from matplotlib import pyplot as plt
from transformers import AutoTokenizer
# register eval resolver and root
pyrootutils.setup_root(__file__, indicator=".project-root", pythonpath=True)
from torch.utils.data import DataLoader
from fish_speech.datasets.... | 172 | 4,641 |
fish-speech | tools/llama/quantize.py | .py | # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
import datetime
import shutil
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import time
from pathlib import Path
import click
import torch
import torch.nn as nn
import ... | 498 | 16,589 |
fish-speech | tools/llama/build_dataset.py | .py | import itertools
import os
import re
from collections import defaultdict
from functools import partial
from multiprocessing import Pool
from pathlib import Path
import click
import numpy as np
from loguru import logger
from tqdm import tqdm
from fish_speech.datasets.protos.text_data_pb2 import Semantics, Sentence, Te... | 170 | 4,910 |
fish-speech | fish_speech/scheduler.py | .py | import math
def get_cosine_schedule_with_warmup_lr_lambda(
current_step: int,
*,
num_warmup_steps: int | float,
num_training_steps: int,
num_cycles: float = 0.5,
final_lr_ratio: float = 0.0,
):
if 0 < num_warmup_steps < 1: # float mode
num_warmup_steps = int(num_warmup_steps * num... | 41 | 1,101 |
fish-speech | fish_speech/train.py | .py | import os
os.environ["USE_LIBUV"] = "0"
import sys
from typing import Optional
import hydra
import lightning as L
import pyrootutils
import torch
from lightning import Callback, LightningDataModule, LightningModule, Trainer
from lightning.pytorch.loggers import Logger
from lightning.pytorch.strategies import DDPStrat... | 142 | 4,470 |
fish-speech | fish_speech/content_sequence.py | .py | from dataclasses import dataclass, field
from typing import List, Literal, Union
import numpy as np
import torch
from fish_speech.tokenizer import (
IM_END_TOKEN,
MODALITY_TOKENS,
FishTokenizer,
)
def restore_ndarray(obj, to_tensor: bool = False):
if isinstance(obj, dict) and "__ndarray__" in obj:
... | 404 | 14,345 |
fish-speech | fish_speech/tokenizer.py | .py | import json
import logging
from pathlib import Path
from typing import TYPE_CHECKING, List, Union
import torch
from transformers import AutoTokenizer
if TYPE_CHECKING:
from transformers import PreTrainedTokenizerFast
logger = logging.getLogger(__name__)
# Constants definitions
EOS_TOKEN = "<|endoftext|>"
PAD_TO... | 130 | 3,948 |
fish-speech | fish_speech/conversation.py | .py | from copy import deepcopy
from dataclasses import dataclass, field
from typing import Literal
import torch
from transformers import PreTrainedTokenizerFast
from fish_speech.content_sequence import (
AudioPart,
BasePart,
ContentSequence,
EncodedMessage,
TextPart,
VQPart,
)
from fish_speech.toke... | 175 | 5,602 |
fish-speech | fish_speech/text/clean.py | .py | import re
SYMBOLS_MAPPING = {
"‘": "'",
"’": "'",
}
REPLACE_SYMBOL_REGEX = re.compile(
"|".join(re.escape(p) for p in SYMBOLS_MAPPING.keys())
)
EMOJI_REGEX = re.compile(
"["
"\U0001f600-\U0001f64f" # emoticons
"\U0001f300-\U0001f5ff" # symbols & pictographs
"\U0001f680-\U0001f6ff" # t... | 38 | 832 |
fish-speech | fish_speech/text/__init__.py | .py | from .clean import clean_text
__all__ = ["clean_text"]
| 4 | 56 |
fish-speech | fish_speech/i18n/scan.py | .py | import ast
import glob
import json
from collections import OrderedDict
from pathlib import Path
from loguru import logger
from .core import DEFAULT_LANGUAGE, I18N_FILE_PATH
def extract_i18n_strings(node):
i18n_strings = []
if (
isinstance(node, ast.Call)
and isinstance(node.func, ast.Name)
... | 123 | 3,751 |
fish-speech | fish_speech/i18n/__init__.py | .py | from .core import i18n
__all__ = ["i18n"]
| 4 | 43 |
fish-speech | fish_speech/i18n/core.py | .py | import json
import locale
from pathlib import Path
I18N_FILE_PATH = Path(__file__).parent / "locale"
DEFAULT_LANGUAGE = "en_US"
def load_language_list(language):
with open(I18N_FILE_PATH / f"{language}.json", "r", encoding="utf-8") as f:
language_list = json.load(f)
return language_list
class I18n... | 41 | 1,036 |
fish-speech | fish_speech/inference_engine/reference_loader.py | .py | import io
import re
from hashlib import sha256
from pathlib import Path
from typing import Callable, Literal, Tuple
import torch
import torchaudio
from loguru import logger
from fish_speech.models.dac.modded_dac import DAC
from fish_speech.utils.file import (
AUDIO_EXTENSIONS,
audio_to_bytes,
list_files,
... | 286 | 9,567 |
fish-speech | fish_speech/inference_engine/utils.py | .py | import io
import wave
from dataclasses import dataclass
from typing import Literal, Optional, Tuple
import numpy as np
@dataclass
class InferenceResult:
code: Literal["header", "segment", "error", "final"]
audio: Optional[Tuple[int, np.ndarray]]
error: Optional[Exception]
def wav_chunk_header(
samp... | 30 | 685 |
fish-speech | fish_speech/inference_engine/__init__.py | .py | import gc
import queue
from typing import Generator
import numpy as np
import torch
from loguru import logger
from fish_speech.inference_engine.reference_loader import ReferenceLoader
from fish_speech.inference_engine.utils import InferenceResult, wav_chunk_header
from fish_speech.inference_engine.vq_manager import V... | 193 | 6,261 |
fish-speech | fish_speech/inference_engine/vq_manager.py | .py | from typing import Callable
import torch
from loguru import logger
from fish_speech.models.dac.modded_dac import DAC
class VQManager:
def __init__(self):
# Make Pylance happy (attribut/method not defined...)
self.decoder_model: DAC
self.load_audio: Callable
def decode_vq_tokens(sel... | 54 | 1,952 |
fish-speech | fish_speech/datasets/vqgan.py | .py | from dataclasses import dataclass
from pathlib import Path
from typing import Optional
import librosa
import numpy as np
import torch
from lightning import LightningDataModule
from torch.utils.data import DataLoader, Dataset
from fish_speech.utils import RankedLogger
logger = RankedLogger(__name__, rank_zero_only=Fa... | 146 | 3,933 |
fish-speech | fish_speech/datasets/concat_repeat.py | .py | import bisect
import random
from typing import Iterable
from torch.utils.data import Dataset, IterableDataset
class ConcatRepeatDataset(Dataset):
datasets: list[Dataset]
cumulative_sizes: list[int]
repeats: list[int]
@staticmethod
def cumsum(sequence, repeats):
r, s = [], 0
for d... | 54 | 1,498 |
fish-speech | fish_speech/datasets/semantic.py | .py | import random
from dataclasses import dataclass
from itertools import chain
from pathlib import Path
from random import Random
from typing import Optional, Union
import numpy as np
import pyarrow.parquet as pq
import torch
import torch.nn.functional as F
from datasets.download.streaming_download_manager import xopen
f... | 628 | 20,572 |
fish-speech | fish_speech/datasets/protos/text_data_stream.py | .py | import struct
from .text_data_pb2 import TextData
def read_pb_stream(f):
while True:
buf = f.read(4)
if len(buf) == 0:
break
size = struct.unpack("I", buf)[0]
buf = f.read(size)
text_data = TextData()
text_data.ParseFromString(buf)
yield text_da... | 37 | 781 |
fish-speech | fish_speech/utils/logger.py | .py | import logging
from typing import Mapping, Optional
from lightning_utilities.core.rank_zero import rank_prefixed_message, rank_zero_only
class RankedLogger(logging.LoggerAdapter):
"""A multi-GPU-friendly python command line logger."""
def __init__(
self,
name: str = __name__,
rank_ze... | 56 | 2,467 |
fish-speech | fish_speech/utils/utils.py | .py | import random
import warnings
from importlib.util import find_spec
from typing import Callable
import numpy as np
import torch
from omegaconf import DictConfig
from .logger import RankedLogger
from .rich_utils import enforce_tags, print_config_tree
log = RankedLogger(__name__, rank_zero_only=True)
def extras(cfg: ... | 137 | 4,283 |
fish-speech | fish_speech/utils/braceexpand.py | .py | """
Bash-style brace expansion
Copied from: https://github.com/trendels/braceexpand/blob/main/src/braceexpand/__init__.py
License: MIT
"""
import re
import string
from itertools import chain, product
from typing import Iterable, Iterator, Optional
__all__ = ["braceexpand", "alphabet", "UnbalancedBracesError"]
class... | 218 | 6,724 |
fish-speech | fish_speech/utils/rich_utils.py | .py | from pathlib import Path
from typing import Sequence
import rich
import rich.syntax
import rich.tree
from hydra.core.hydra_config import HydraConfig
from lightning.pytorch.utilities import rank_zero_only
from omegaconf import DictConfig, OmegaConf, open_dict
from rich.prompt import Prompt
from fish_speech.utils impor... | 101 | 3,105 |
fish-speech | fish_speech/utils/__init__.py | .py | from .braceexpand import braceexpand
from .context import autocast_exclude_mps
from .file import get_latest_checkpoint
from .instantiators import instantiate_callbacks, instantiate_loggers
from .logger import RankedLogger
from .logging_utils import log_hyperparameters
from .rich_utils import enforce_tags, print_config_... | 25 | 706 |
fish-speech | fish_speech/utils/logging_utils.py | .py | from lightning.pytorch.utilities import rank_zero_only
from fish_speech.utils import logger as log
@rank_zero_only
def log_hyperparameters(object_dict: dict) -> None:
"""Controls which config parts are saved by lightning loggers.
Additionally saves:
- Number of model parameters
"""
hparams = {}... | 49 | 1,384 |
fish-speech | fish_speech/utils/instantiators.py | .py | from typing import List
import hydra
from omegaconf import DictConfig
from pytorch_lightning import Callback
from pytorch_lightning.loggers import Logger
from .logger import RankedLogger
log = RankedLogger(__name__, rank_zero_only=True)
def instantiate_callbacks(callbacks_cfg: DictConfig) -> List[Callback]:
""... | 51 | 1,514 |
fish-speech | fish_speech/utils/schema.py | .py | import base64
import os
import queue
from dataclasses import dataclass
from typing import Literal
import torch
from pydantic import BaseModel, Field, conint, model_validator
from pydantic.functional_validators import SkipValidation
from typing_extensions import Annotated
from fish_speech.content_sequence import TextP... | 139 | 3,912 |
fish-speech | fish_speech/utils/context.py | .py | from contextlib import nullcontext
import torch
def autocast_exclude_mps(
device_type: str, dtype: torch.dtype
) -> nullcontext | torch.autocast:
return (
nullcontext()
if torch.backends.mps.is_available()
else torch.autocast(device_type, dtype)
)
| 14 | 287 |
fish-speech | fish_speech/utils/file.py | .py | import os
from pathlib import Path
from typing import Union
from loguru import logger
from natsort import natsorted
AUDIO_EXTENSIONS = {
".mp3",
".wav",
".flac",
".ogg",
".m4a",
".wma",
".aac",
".aiff",
".aif",
".aifc",
}
VIDEO_EXTENSIONS = {
".mp4",
".avi",
}
def ge... | 140 | 3,354 |
fish-speech | fish_speech/utils/spectrogram.py | .py | import torch
import torchaudio.functional as F
from torch import Tensor, nn
from torchaudio.transforms import MelScale
class LinearSpectrogram(nn.Module):
def __init__(
self,
n_fft=2048,
win_length=2048,
hop_length=512,
center=False,
mode="pow2_sqrt",
):
... | 125 | 3,325 |
fish-speech | fish_speech/callbacks/grad_norm.py | .py | from typing import Optional, Union
import lightning.pytorch as pl
import torch
from lightning import LightningModule, Trainer
from lightning.pytorch.callbacks import Callback
from torch import Tensor, nn
from torch.utils._foreach_utils import (
_group_tensors_by_device_and_dtype,
_has_foreach_support,
)
@tor... | 114 | 3,436 |
fish-speech | fish_speech/callbacks/__init__.py | .py | from .grad_norm import GradNormMonitor
from .progress_bar import GradAccumProgressBar
__all__ = ["GradNormMonitor", "GradAccumProgressBar"]
| 5 | 141 |
fish-speech | fish_speech/callbacks/progress_bar.py | .py | from lightning.pytorch.callbacks import TQDMProgressBar
class GradAccumProgressBar(TQDMProgressBar):
"""
Progress bar that accounts for gradient accumulation so the total
reflects actual forward passes rather than optimizer steps.
"""
@property
def total_train_batches(self):
total = s... | 17 | 518 |
fish-speech | fish_speech/models/dac/rvq.py | .py | import math
import typing as tp
from dataclasses import dataclass
import torch
import torch.nn as nn
import torch.nn.functional as F
from dac.nn.quantize import ResidualVectorQuantize
from torch.nn.utils.parametrizations import weight_norm
from torch.nn.utils.parametrize import remove_parametrizations
def unpad1d(x:... | 400 | 13,143 |
fish-speech | fish_speech/models/dac/inference.py | .py | from pathlib import Path
import click
import hydra
import numpy as np
import pyrootutils
import soundfile as sf
import torch
import torchaudio
from hydra import compose, initialize
from hydra.utils import instantiate
from loguru import logger
from omegaconf import OmegaConf
pyrootutils.setup_root(__file__, indicator=... | 127 | 3,895 |
fish-speech | fish_speech/models/dac/modded_dac.py | .py | import math
import typing as tp
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from audiotools import AudioSignal
from audiotools.ml import BaseModel
from dac.model.base import CodecMixin
from dac.nn.layers import Snake1d, WNConv1d, WNConvTranspose1d
from tor... | 1,046 | 35,062 |
fish-speech | fish_speech/models/text2semantic/inference.py | .py | import os
import queue
import re
import threading
import time
import traceback
from copy import deepcopy
from dataclasses import dataclass
from pathlib import Path
from typing import Callable, Literal, Optional, Tuple, Union
import click
import numpy as np
import torch
import torch._inductor.config
from loguru import ... | 967 | 31,250 |
fish-speech | fish_speech/models/text2semantic/lit_module.py | .py | from typing import Any, Optional
import lightning as L
import torch
import torch.nn.functional as F
from lightning.pytorch.utilities.types import OptimizerLRScheduler
import fish_speech.utils as utils
CODEBOOK_PAD_TOKEN_ID = 0
from fish_speech.models.text2semantic.llama import NaiveTransformer
log = utils.RankedLog... | 211 | 6,935 |
fish-speech | fish_speech/models/text2semantic/lora.py | .py | from dataclasses import dataclass, field
import loralib as lora
@dataclass
class LoraConfig:
r: int
lora_alpha: float
lora_dropout: float = 0.0
# Valid values: "attention", "mlp", "embeddings", "output",
# "fast_attention", "fast_mlp", "fast_embeddings", "fast_output"
# Unprefix... | 119 | 4,084 |
fish-speech | fish_speech/models/text2semantic/llama.py | .py | import dataclasses
import json
import math
from collections import OrderedDict
from dataclasses import dataclass
from pathlib import Path
from typing import Optional
import torch
import torch.nn as nn
from einops import rearrange
from loguru import logger
from torch import Tensor
from torch.nn import functional as F
f... | 1,039 | 36,007 |
sglang | experimental/sgl-router/tests/scripts/generate_kv_events_hash_parity.py | .py | """
Generator + validator for KV-event block-hash parity fixtures.
Two modes:
python3 experimental/sgl-router/tests/scripts/generate_kv_events_hash_parity.py
Regenerate the committed JSON fixture from the locally-replicated
algorithm. Run this when changing block-hash logic or adding new
shape cov... | 238 | 7,963 |
sglang | experimental/sgl-router/tests/scripts/generate_parity_fixtures.py | .py | """
One-shot generator for tokenizer parity fixtures.
Run manually when adding a model or changing a prompt shape:
python3 -m venv /tmp/parity-fixture-venv
/tmp/parity-fixture-venv/bin/pip install transformers
/tmp/parity-fixture-venv/bin/python experimental/sgl-router/tests/scripts/generate_parity_fixture... | 116 | 4,277 |
sglang | experimental/sgl-router/tests/e2e/test_tokenize_smoke.py | .py | """
Smoke test for /v1/tokenize and /v1/detokenize round-trip.
"""
from __future__ import annotations
import httpx
MODEL = "Qwen/Qwen3-0.6B"
TEXT = "Hello, world!"
def test_tokenize_round_trip(router: str) -> None:
"""POST /v1/tokenize then /v1/detokenize must recover the original text."""
# Tokenize
t... | 38 | 1,053 |
sglang | experimental/sgl-router/tests/e2e/test_chat_smoke.py | .py | """
Smoke tests for /v1/models and /v1/chat/completions (streaming + non-streaming).
"""
from __future__ import annotations
import httpx
import pytest
MODEL = "Qwen/Qwen3-0.6B"
def test_models(router: str) -> None:
"""GET /v1/models must list the configured model."""
resp = httpx.get(f"{router}/v1/models",... | 65 | 2,038 |
sglang | experimental/sgl-router/tests/e2e/conftest.py | .py | """Pytest fixtures for ``experimental/sgl-router/tests/e2e/``.
Two flavors of fixtures coexist here:
1. **Session-scoped sanity fixtures** (``sglang_server`` + ``router``) —
launch ONE SGLang worker + ONE router on fixed ports for the whole
test session. Used by the lightweight ``test_chat_smoke.py`` /
... | 311 | 10,135 |
sglang | experimental/sgl-router/tests/e2e/infra/model_pool.py | .py | """Minimal SGLang worker spawner for sgl-router e2e tests.
Adapted from SMG's e2e_test/infra/model_pool.py — the 1200-line original
manages a pool of long-lived workers across many tests; here we only
need a thin wrapper around ``sglang.launch_server`` that:
- allocates GPU(s) for the worker (via ``CUDA_VISIBLE_DEV... | 218 | 6,964 |
sglang | experimental/sgl-router/tests/e2e/infra/gateway.py | .py | """Minimal sgl-router Gateway class for e2e tests.
sgl-router is a Rust binary
(`experimental/sgl-router/target/release/sgl-router`) configured entirely
through CLI flags. This Gateway execs the binary with `--worker-urls <...>`
(static discovery) plus the model + policy flags.
Supported lifecycles:
- Regular mode:... | 378 | 13,977 |
sglang | experimental/sgl-router/tests/e2e/infra/model_specs.py | .py | """Model specifications for sgl-router e2e tests.
Adapted from SMG's e2e_test/infra/model_specs.py. The same dict-of-dicts
shape (so test code reads the same) but the entries are narrower —
sgl-router tests today target small/medium models only; the larger
function-calling / reasoning models from SMG are out of scope.... | 78 | 2,636 |
sglang | experimental/sgl-router/tests/e2e/k8s_integration/test_discovery.py | .py | """E2E: sgl-router K8s discovery — basic routing.
Verifies that sgl-router, configured with the k8s EndpointSlice backend,
discovers the 3 fake-worker replicas deployed by setup.sh and successfully
routes chat-completion requests to them.
"""
from __future__ import annotations
import httpx
import pytest
from conftes... | 85 | 2,613 |
sglang | experimental/sgl-router/tests/e2e/k8s_integration/test_reconciliation.py | .py | """K8s discovery reconciliation integration tests.
Tests verify that:
1. The K8s EndpointSlice watcher correctly discovers new workers as Services
and backing Deployments are updated.
2. Workers are removed from the router's registry after the backing EndpointSlice
entries disappear (pod deleted / deployment sca... | 164 | 5,596 |
sglang | experimental/sgl-router/tests/e2e/k8s_integration/fake_worker.py | .py | """Minimal fake SGLang worker for kind E2E integration testing.
Responds to:
GET /health -> {"status": "ok"}
GET /server_info -> {"served_model_name": MODEL_ID}
GET /v1/models -> list with a single MODEL_ID model entry
POST /v1/chat/completions -> echoes th... | 74 | 1,898 |
sglang | experimental/sgl-router/tests/e2e/k8s_integration/test_cross_namespace.py | .py | """Cross-namespace service discovery integration test.
Validates that a sgl-router instance with cluster-wide RBAC and no namespace
filter in its k8s discovery config watches EndpointSlices in all namespaces.
Workers deployed in a second namespace (sgl-router-test-extra) must be
discovered alongside those in the prima... | 226 | 7,785 |
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