python_code stringlengths 0 992k | repo_name stringlengths 8 46 | file_path stringlengths 5 162 |
|---|---|---|
# 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
src_ckpt = "/checkpoint/wnhsu/w2v/archived/hubert_base_ls960_it2.pt"
ref_ckpt = "/checkpoint/wnhsu/w2v/hubert_icassp_oss_v3/iter... | EXA-1-master | exa/libraries/fairseq/examples/hubert/update_ckpt.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 numpy as np
import os.path as op
import re
from tabulate import tabulate
from collections import Counter
def comp_purity(p_xy, axis):... | EXA-1-master | exa/libraries/fairseq/examples/hubert/measure_teacher_quality.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
import os
import sys
import numpy as np
import joblib
import torch
import tqdm
logging.basicConfig(
format="%(asctime)s ... | EXA-1-master | exa/libraries/fairseq/examples/hubert/simple_kmeans/dump_km_label.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
import os
import sys
import fairseq
import soundfile as sf
import torch
import torch.nn.functional as F
from feature_utils im... | EXA-1-master | exa/libraries/fairseq/examples/hubert/simple_kmeans/dump_hubert_feature.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 csv
import io
import logging
import os
import os.path as op
import sys
from dump_hubert_feature import HubertFeatureReader
from featur... | EXA-1-master | exa/libraries/fairseq/examples/hubert/simple_kmeans/dump_hubert_feature_s2t.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
import os
import sys
import tqdm
from npy_append_array import NpyAppendArray
logging.basicConfig(
format="%(asctime)s | ... | EXA-1-master | exa/libraries/fairseq/examples/hubert/simple_kmeans/feature_utils.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
import os
import sys
import numpy as np
from sklearn.cluster import MiniBatchKMeans
import joblib
logging.basicConfig(
f... | EXA-1-master | exa/libraries/fairseq/examples/hubert/simple_kmeans/learn_kmeans.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
import os
import sys
import soundfile as sf
import torch
import torchaudio
from feature_utils import get_path_iterator, dump_... | EXA-1-master | exa/libraries/fairseq/examples/hubert/simple_kmeans/dump_mfcc_feature.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
import os
import sys
import fairseq
import soundfile as sf
import torch
import torch.nn.functional as F
from feature_utils im... | EXA-1-master | exa/libraries/fairseq/examples/hubert/simple_kmeans/dump_w2v2_feature.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
def main():
"""
Create code file with the following format:
{'audio': 'file1', 'unitA': 'file1_chnl1_units',... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/dgslm/create_code_file.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 numpy as np
import torch
import json
from fairseq import utils
from fairseq.models.text_to_speech.vocoder import CodeHiFiGANVocoder
#... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/dgslm/dgslm_utils.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 os
import ast
import argparse
import logging
import torch
from fairseq import utils
from fairseq.models.speech_dlm import SpeechDLM
l... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/dgslm/sample_speech_dlm.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 ast
import argparse
import json
import logging
from pathlib import Path
import soundfile as sf
import torch
from tqdm import tqdm
fro... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/dgslm/vocoder_hifigan/generate_stereo_waveform.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 collections import defaultdict
from functools import partial
import numpy as np
import torch
from tqdm import tqdm
from data_utils impor... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/pgslm/quantize_f0.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 multiprocessing import Pool
import os
from collections import defaultdict
from itertools import starmap
import torch
from npy_append_arr... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/pgslm/prepare_dataset.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 warnings
def truncated_laplace(mean, T, truncate_by_zero=False):
"""Generating a sample from a Laplace distribution, ... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/pgslm/truncated_laplace.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 ast
import argparse
import json
import logging
from pathlib import Path
import soundfile as sf
import torch
from tqdm import tqdm
fro... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/pgslm/generate_waveform.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 os
import torch
from tqdm import tqdm
from data_utils import load_audio_path
from fairseq.data.codedataset import get_f0_by_filename
d... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/pgslm/preprocess_f0.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 warnings
class Naive_F0_Decoder(torch.nn.Module):
def __init__(self, bounds_path, n_units=32):
super().__init... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/pgslm/naive_decoder.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 os
import torch
from tqdm import tqdm
class Stat:
def __init__(self, keep_raw=False):
self.x = 0.0
self.x2 = 0.0
... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/pgslm/data_utils.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
class InferenceDataset:
def __init__(
self,
dataset,
prefix,
only_prefix=True,
pres... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/pgslm/inference_dataset.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 json
import argparse
import pathlib
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--manifest", required=... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/pgslm/scripts/join_units_manifest.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.
| EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/pgslm/sample/__init__.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 os
import torch.multiprocessing as mp
import numpy as np
import json
import torch
from torch.distributions.categorical import Categori... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/pgslm/sample/sample.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 os
import numpy as np
import scipy
import torch
import torch.multiprocessing as mp
from fairseq import checkpoint_utils, options
from ... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/pgslm/eval/cont_metrics.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.
| EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/pgslm/eval/__init__.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 logging
import os
import joblib
import numpy as np
from examples.textless_nlp.gslm.speech2unit.clustering.utils impor... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/metrics/abx_metrics/dump_abx_feats.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 numpy as np
import nltk
from misc.bleu_utils import sentence_bleu
import warnings
def get_target_sequences(manifest, ground_truth, to... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/metrics/asr_metrics/self_auto_bleu.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 collections import defaultdict
import numpy as np
from misc.bleu_utils import sentence_bleu
import json
import warnings
def get_args()... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/metrics/asr_metrics/continuation_eval.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 numpy as np
import warnings
def get_target_sequences(manifest, ground_truth, to_take=1000):
import json
import ... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/metrics/asr_metrics/ppx.py |
"""
TODO: the code is take from Apache-2 Licensed NLTK: make sure we do this properly!
Copied over from nltk.tranlate.bleu_score. This code has two major changes:
- allows to turn off length/brevity penalty --- it has no sense for self-bleu,
- allows to use arithmetic instead of geometric mean
"""
import math
imp... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/metrics/asr_metrics/misc/bleu_utils.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 torchaudio
import argparse
import json
import pathlib
def get_args():
parser = argparse.ArgumentParser(
"Assuring genera... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/metrics/asr_metrics/misc/cut_as.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 gc
import logging
import os
import joblib
import soundfile as sf
import torch
from examples.textless_nlp.gslm.speech2u... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/tools/resynthesize_speech.py |
EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/speech2unit/__init__.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 logging
from examples.textless_nlp.gslm.speech2unit.pretrained.utils import (
get_and_dump_features,
)
def get_p... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/speech2unit/clustering/dump_feats.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 logging
import os
import time
import numpy as np
from sklearn.cluster import MiniBatchKMeans
import joblib
from examp... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/speech2unit/clustering/cluster_kmeans.py |
EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/speech2unit/clustering/__init__.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 List, Tuple
def get_audio_files(manifest_path: str) -> Tuple[str, List[str], List[int]]:
fnames, sizes = [], []
w... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/speech2unit/clustering/utils.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 logging
import os
import numpy as np
import joblib
from examples.textless_nlp.gslm.speech2unit.clustering.utils impor... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/speech2unit/clustering/quantize_with_kmeans.py |
import soundfile as sf
import torch
import torch.nn as nn
import torch.nn.functional as F
class CpcFeatureReader:
"""
Wrapper class to run inference on CPC model.
Helps extract features for a given audio file.
"""
def __init__(
self,
checkpoint_path,
layer,
use_enc... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/speech2unit/pretrained/cpc_feature_reader.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 fairseq
import soundfile as sf
import torch.nn.functional as F
class HubertFeatureReader:
"""
Wrapper class to r... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/speech2unit/pretrained/hubert_feature_reader.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 gc
import os
import random
import shutil
import numpy as np
import torch
import tqdm
from examples.textless_nlp.gslm.speech2unit.pretr... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/speech2unit/pretrained/utils.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 fairseq
import soundfile as sf
class Wav2VecFeatureReader:
"""
Wrapper class to run inference on Wav2Vec 2.0 mod... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/speech2unit/pretrained/w2v2_feature_reader.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 soundfile as sf
import torch
import torchaudio.compliance.kaldi as kaldi
class LogMelFeatureReader:
"""
Wrapper class to run ... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/speech2unit/pretrained/logmel_feature_reader.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 logging
import os
import soundfile as sf
from examples.textless_nlp.gslm.unit2speech.tts_data import (
TacotronInp... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/unit2speech/synthesize_audio_from_units.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 numpy as np
from examples.textless_nlp.gslm.unit2speech.tacotron2.text import (
EOS_TOK,
SOS_TOK,
code_to_seq... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/unit2speech/tts_data.py |
# *****************************************************************************
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/unit2speech/glow.py |
import os
import shlex
import subprocess
import progressbar
from time import time
from pathlib import Path
def find_all_files(path_dir, extension):
out = []
for root, dirs, filenames in os.walk(path_dir):
for f in filenames:
if f.endswith(extension):
out.append(((str(Path(f)... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/unit2speech/convert_to_16k.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 examples.textless_nlp.gslm.unit2speech.tacotron2.model import Tacotron2
from examples.textless_nlp.gslm.unit2speech.tacotro... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/unit2speech/utils.py |
import os
import time
import torch
import sys
import subprocess
argslist = list(sys.argv)[1:]
log_dir = argslist[-1]
num_gpus = torch.cuda.device_count()
argslist.append('--n_gpus={}'.format(num_gpus))
workers = []
job_id = time.strftime("%Y_%m_%d-%H%M%S")
argslist.append("--group_name=group_{}".format(job_id))
print... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/unit2speech/multiproc.py |
""" from https://github.com/keithito/tacotron """
import re
valid_symbols = [
'AA', 'AA0', 'AA1', 'AA2', 'AE', 'AE0', 'AE1', 'AE2', 'AH', 'AH0', 'AH1', 'AH2',
'AO', 'AO0', 'AO1', 'AO2', 'AW', 'AW0', 'AW1', 'AW2', 'AY', 'AY0', 'AY1', 'AY2',
'B', 'CH', 'D', 'DH', 'EH', 'EH0', 'EH1', 'EH2', 'ER', 'ER0', 'ER1', 'E... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/unit2speech/tacotron2/cmudict.py |
# import sys
# sys.path.append('tacotron2')
import torch
from .layers import STFT
class Denoiser(torch.nn.Module):
""" Removes model bias from audio produced with waveglow """
def __init__(self, waveglow, filter_length=1024, n_overlap=4,
win_length=1024, mode='zeros'):
super(Denoiser... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/unit2speech/tacotron2/waveglow_denoiser.py |
EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/unit2speech/tacotron2/__init__.py | |
import torch
import numpy as np
from scipy.signal import get_window
import librosa.util as librosa_util
def window_sumsquare(window, n_frames, hop_length=200, win_length=800,
n_fft=800, dtype=np.float32, norm=None):
"""
# from librosa 0.6
Compute the sum-square envelope of a window fu... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/unit2speech/tacotron2/audio_processing.py |
""" from https://github.com/keithito/tacotron """
import inflect
import re
_inflect = inflect.engine()
_comma_number_re = re.compile(r'([0-9][0-9\,]+[0-9])')
_decimal_number_re = re.compile(r'([0-9]+\.[0-9]+)')
_pounds_re = re.compile(r'£([0-9\,]*[0-9]+)')
_dollars_re = re.compile(r'\$([0-9\.\,]*[0-9]+)')
_ordinal_r... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/unit2speech/tacotron2/numbers.py |
from math import sqrt
import torch
import torch.distributions as distr
from torch.autograd import Variable
from torch import nn
from torch.nn import functional as F
from .layers import ConvNorm, LinearNorm, GlobalAvgPool
from .utils import to_gpu, get_mask_from_lengths
class LocationLayer(nn.Module):
def __init__... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/unit2speech/tacotron2/model.py |
"""
BSD 3-Clause License
Copyright (c) 2017, Prem Seetharaman
All rights reserved.
* Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice,
this list of... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/unit2speech/tacotron2/stft.py |
""" from https://github.com/keithito/tacotron """
'''
Defines the set of symbols used in text input to the model.
The default is a set of ASCII characters that works well for English or text that has been run through Unidecode. For other data, you can modify _characters. See TRAINING_DATA.md for details. '''
from . i... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/unit2speech/tacotron2/symbols.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 collections
import io
import json
import librosa
import numpy as np
import soundfile as sf
import time
import torch
from scipy.io.wavfi... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/unit2speech/tacotron2/utils.py |
""" from https://github.com/keithito/tacotron """
import numpy as np
import re
from . import cleaners
from .symbols import symbols
# Mappings from symbol to numeric ID and vice versa:
_symbol_to_id = {s: i for i, s in enumerate(symbols)}
_id_to_symbol = {i: s for i, s in enumerate(symbols)}
# Regular expression matc... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/unit2speech/tacotron2/text.py |
""" from https://github.com/keithito/tacotron """
'''
Cleaners are transformations that run over the input text at both training and eval time.
Cleaners can be selected by passing a comma-delimited list of cleaner names as the "cleaners"
hyperparameter. Some cleaners are English-specific. You'll typically want to use... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/unit2speech/tacotron2/cleaners.py |
import torch
from librosa.filters import mel as librosa_mel_fn
from .audio_processing import dynamic_range_compression
from .audio_processing import dynamic_range_decompression
from .stft import STFT
from .utils import get_mask_from_lengths
class LinearNorm(torch.nn.Module):
def __init__(self, in_dim, out_dim, bi... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/unit2speech/tacotron2/layers.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.
"""
Sample from a trained LM; hacked fairseq-interactive
"""
from collections import namedtuple
import os
import ast
... | EXA-1-master | exa/libraries/fairseq/examples/textless_nlp/gslm/ulm/sample.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 torch
from omegaconf import OmegaConf
from fairseq.criterions.model_criterion import ModelCrit... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/fb_convert_beit_cp.py |
EXA-1-master | exa/libraries/fairseq/examples/data2vec/__init__.py | |
# Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import logging
import sys
import t... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/tasks/mae_image_classification.py |
# Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import os.path as osp
import loggi... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/tasks/image_classification.py |
# Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import sys
from dataclasses impor... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/tasks/multimodal.py |
# Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import logging
import os
import nu... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/tasks/audio_classification.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 .image_pretraining import ImagePretrainingTask, ImagePretrainingConfig
from .image_classification import ImageClassificationTask, ImageCl... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/tasks/__init__.py |
# Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import logging
import sys
import o... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/tasks/image_pretraining.py |
# Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import logging
import sys
from ty... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/tasks/mae_image_pretraining.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.
# The code in this file is adapted from the BeiT implementation which can be found here:
# https://github.com/microsoft/unilm/tree/master/beit... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/models/data2vec_text_classification.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
from typing import Optional
import logging
import math
import torch
import torch.nn as nn
import tor... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/models/data2vec_text.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.
# The code in this file is adapted from the BeiT implementation which can be found here:
# https://github.com/microsoft/unilm/tree/master/beit... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/models/mae_image_classification.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.
# The code in this file is adapted from the BeiT implementation which can be found here:
# https://github.com/microsoft/unilm/tree/master/beit... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/models/mae.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
import math
from dataclasses import dataclass, field
from typing import Optional, Callable
from functools import partial
import... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/models/data2vec2.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 contextlib
import logging
import re
from dataclasses import dataclass, field
from typing import Any, Optional
import torch
import torc... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/models/audio_classification.py |
EXA-1-master | exa/libraries/fairseq/examples/data2vec/models/__init__.py | |
import math
import torch
def get_alibi(
max_positions: int,
attention_heads: int,
):
def get_slopes(n):
def get_slopes_power_of_2(n):
start = 2 ** (-(2 ** -(math.log2(n) - 3)))
ratio = start
return [start * ratio ** i for i in range(n)]
# In the paper, w... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/models/utils.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
import math
from dataclasses import dataclass, field
from typing import Optional
from omegaconf import II
import torch
import... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/models/data2vec_audio.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.
# The code in this file is adapted from the BeiT implementation which can be found here:
# https://github.com/microsoft/unilm/tree/master/beit... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/models/data2vec_image_classification.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.
# The code in this file is adapted from the BeiT implementation which can be found here:
# https://github.com/microsoft/unilm/tree/master/beit... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/models/data2vec_vision.py |
EXA-1-master | exa/libraries/fairseq/examples/data2vec/models/modalities/__init__.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
from functools import partial
from typing import Callable, Dict, Optional
import torch.nn as nn... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/models/modalities/text.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
import torch.nn.functional as F
import numpy as np
from functools import partial
from dataclasses import da... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/models/modalities/images.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 functools import partial
import torch
import torch.nn as nn
import numpy as np
from dataclasses import dataclass, field
from typing impor... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/models/modalities/audio.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
import torch.nn.functional as F
import numpy as np
from dataclasses import dataclass
from fairseq.modules i... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/models/modalities/modules.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
import math
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from collections import named... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/models/modalities/base.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 os
def get_parser():
parser = argparse.ArgumentParser(description="convert audioset labels... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/scripts/convert_audioset_labels.py |
from valids import parser, main as valids_main
import os.path as osp
args = parser.parse_args()
args.target = "valid_accuracy"
args.best_biggest = True
args.best = True
args.last = 0
args.path_contains = None
res = valids_main(args, print_output=False)
grouped = {}
for k, v in res.items():
k = osp.dirname(k)
... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/scripts/text/glue.py |
import os, argparse, re, json, copy, math
from collections import OrderedDict
import numpy as np
parser = argparse.ArgumentParser(description='Process some integers.')
parser.add_argument('base', help='base log path')
parser.add_argument('--file_name', default='train.log', help='the log file name')
parser.add_argument... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/scripts/text/valids.py |
import json
import os
import tqdm
from fairseq.data import Dictionary, data_utils
def load_dictionary(dict_path):
return Dictionary.load(dict_path)
def load_dataset(split_path, src_dict):
dataset = data_utils.load_indexed_dataset(
split_path,
src_dict,
combine=False, # set to true fo... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/scripts/text/unprocess_data.py |
import os.path as osp
import re
from collections import defaultdict
from valids import parser, main as valids_main
TASK_TO_METRIC = {
"cola": "mcc",
"qnli": "accuracy",
"mrpc": "acc_and_f1",
"rte": "accuracy",
"sst_2": "accuracy",
"mnli": "accuracy",
"qqp": "acc_and_f1",
"sts_b": "pea... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/scripts/text/glue_lr.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 functools import partial
import logging
import math
import random
import time
import numpy as np
import os
import torch
from torchvis... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/data/mae_image_dataset.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.data import BaseWrapperDataset, data_utils
class AddClassTargetDataset(BaseWrapperDataset):
def __init__(
... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/data/add_class_target_dataset.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
import numpy as np
import os
from typing import Optional, Callable, Set
import torch
from torchvision.datasets.vision impor... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/data/image_dataset.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 .image_dataset import ImageDataset
from .path_dataset import PathDataset
from .mae_image_dataset import MaeImageDataset
from .mae_finetun... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/data/__init__.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
import numpy as np
import os
import torch
from torchvision import datasets, transforms
from timm.data import create_transf... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/data/mae_finetuning_image_dataset.py |
# Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
from enum import Enum, auto
clas... | EXA-1-master | exa/libraries/fairseq/examples/data2vec/data/modality.py |
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