repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
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MICCAI21_MMQ | MICCAI21_MMQ-main/tools/compute_softscore.py | """
This code is slightly modified from Hengyuan Hu's repository.
https://github.com/hengyuan-hu/bottom-up-attention-vqa
"""
from __future__ import print_function
import os
import sys
import json
import numpy as np
import re
import _pickle as cPickle
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__fi... | 10,849 | 36.673611 | 117 | py |
MICCAI21_MMQ | MICCAI21_MMQ-main/tools/create_dictionary.py | """
This code is from Hengyuan Hu's repository.
https://github.com/hengyuan-hu/bottom-up-attention-vqa
"""
from __future__ import print_function
import os
import sys
import json
import numpy as np
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from dataset_VQA import Dictionary
def create... | 1,702 | 29.410714 | 76 | py |
MICCAI21_MMQ | MICCAI21_MMQ-main/mmq_maml/VQA_RAD_train.py | import torch, os
import numpy as np
from VQA_RAD import VQARAD_maml
import scipy.stats
from torch.utils.data import DataLoader
import argparse
import time
from meta import Meta
def mean_confidence_interval(accs, confidence=0.95):
n = accs.shape[0]
m, se = np.mean(accs), scipy.stats.sem(accs)
h =... | 4,249 | 37.990826 | 137 | py |
MICCAI21_MMQ | MICCAI21_MMQ-main/mmq_maml/VQA_RAD_fuse.py | import torch, os
import numpy as np
from VQA_RAD import VQARAD_maml
import scipy.stats
from torch.utils.data import DataLoader
import argparse
import time
from meta import Meta
import pickle as p
def mean_confidence_interval(accs, confidence=0.95):
n = accs.shape[0]
m, se = np.mean(accs), scipy.stat... | 7,237 | 40.597701 | 145 | py |
MICCAI21_MMQ | MICCAI21_MMQ-main/mmq_maml/pathVQA_maml.py | import os
import torch
from torch.utils.data import Dataset
from torchvision.transforms import transforms
import numpy as np
from PIL import Image
import random
class PathVQA_maml(Dataset):
"""
NOTICE: meta-learning is different from general supervised learning, especially the concept of batch and set.
ba... | 12,430 | 47.74902 | 155 | py |
MICCAI21_MMQ | MICCAI21_MMQ-main/mmq_maml/learner.py | import torch
from torch import nn
from torch.nn import functional as F
import numpy as np
class Learner(nn.Module):
"""
"""
def __init__(self, config, imgc, imgsz):
"""
:param config: network config file, type:list of (string, list)
:param imgc: 1 or 3
:param im... | 7,789 | 34.733945 | 111 | py |
MICCAI21_MMQ | MICCAI21_MMQ-main/mmq_maml/VQA_RAD.py | import os
import torch
from torch.utils.data import Dataset
from torchvision.transforms import transforms
import numpy as np
from PIL import Image
import random
class VQARAD_maml(Dataset):
"""
NOTICE: meta-learning is different from general supervised learning, especially the concept of batch and set.
bat... | 11,779 | 46.692308 | 155 | py |
MICCAI21_MMQ | MICCAI21_MMQ-main/mmq_maml/pathVQA_maml_train.py | import torch, os
import numpy as np
from pathVQA_maml import PathVQA_maml
import scipy.stats
from torch.utils.data import DataLoader
import argparse
import time
from meta import Meta
def mean_confidence_interval(accs, confidence=0.95):
n = accs.shape[0]
m, se = np.mean(accs), scipy.stats.sem(accs)
... | 5,532 | 40.291045 | 143 | py |
MICCAI21_MMQ | MICCAI21_MMQ-main/mmq_maml/pathVQA_maml_fuse.py | import torch, os
import numpy as np
from pathVQA_maml import PathVQA_maml
import scipy.stats
from torch.utils.data import DataLoader
import argparse
import time
from meta import Meta
import pickle as p
def mean_confidence_interval(accs, confidence=0.95):
n = accs.shape[0]
m, se = np.mean(accs), scipy... | 7,202 | 39.926136 | 141 | py |
MICCAI21_MMQ | MICCAI21_MMQ-main/mmq_maml/VQA_RAD_half.py | import torch, os
import numpy as np
from VQA_RAD import VQARAD_maml
import scipy.stats
from torch.utils.data import DataLoader
import argparse
import time
from meta import Meta
import shutil
def mean_confidence_interval(accs, confidence=0.95):
n = accs.shape[0]
m, se = np.mean(accs), scipy.stats.sem(... | 8,795 | 38.621622 | 138 | py |
MICCAI21_MMQ | MICCAI21_MMQ-main/mmq_maml/meta.py | import torch
from torch import nn
from torch import optim
from torch.nn import functional as F
from torch.utils.data import TensorDataset, DataLoader
from torch import optim
import numpy as np
from learner import Learner
from copy import deepcopy
class Meta(nn.Module):
"""
Meta Learne... | 12,796 | 34.350829 | 110 | py |
MICCAI21_MMQ | MICCAI21_MMQ-main/mmq_maml/pathVQA_maml_half.py | import torch, os
import numpy as np
from pathVQA_maml import PathVQA_maml
import scipy.stats
from torch.utils.data import DataLoader
import argparse
import time
from meta import Meta
import shutil
def mean_confidence_interval(accs, confidence=0.95):
n = accs.shape[0]
m, se = np.mean(accs), scipy.stat... | 8,907 | 38.591111 | 144 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/test.py | """General-purpose test script for image-to-image translation.
Once you have trained your model with train.py, you can use this script to test the model.
It will load a saved model from '--checkpoints_dir' and save the results to '--results_dir'.
It first creates model and dataset given the option. It will hard-code ... | 4,545 | 55.123457 | 130 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/train.py | """General-purpose training script for image-to-image translation.
This script works for various models (with option '--model': e.g., pix2pix, cyclegan, colorization) and
different datasets (with option '--dataset_mode': e.g., aligned, unaligned, single, colorization).
You need to specify the dataset ('--dataroot'), e... | 4,933 | 62.25641 | 186 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/options/train_options.py | from .base_options import BaseOptions
class TrainOptions(BaseOptions):
"""This class includes training options.
It also includes shared options defined in BaseOptions.
"""
def initialize(self, parser):
parser = BaseOptions.initialize(self, parser)
# visdom and HTML visualization para... | 3,447 | 83.097561 | 210 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/options/base_options.py | import argparse
import os
from util import util
import torch
import models
import data
class BaseOptions():
"""This class defines options used during both training and test time.
It also implements several helper functions such as parsing, printing, and saving the options.
It also gathers additional opti... | 8,327 | 58.485714 | 235 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/options/__init__.py | """This package options includes option modules: training options, test options, and basic options (used in both training and test)."""
| 136 | 67.5 | 135 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/options/test_options.py | from .base_options import BaseOptions
class TestOptions(BaseOptions):
"""This class includes test options.
It also includes shared options defined in BaseOptions.
"""
def initialize(self, parser):
parser = BaseOptions.initialize(self, parser) # define shared options
parser.add_argum... | 1,158 | 47.291667 | 108 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/models/base_model.py | import os
import torch
from collections import OrderedDict
from abc import ABC, abstractmethod
from . import networks
class BaseModel(ABC):
"""This class is an abstract base class (ABC) for models.
To create a subclass, you need to implement the following five functions:
-- <__init__>: ... | 10,407 | 44.056277 | 260 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/models/colorization_model.py | from .pix2pix_model import Pix2PixModel
import torch
from skimage import color # used for lab2rgb
import numpy as np
class ColorizationModel(Pix2PixModel):
"""This is a subclass of Pix2PixModel for image colorization (black & white image -> colorful images).
The model training requires '-dataset_model color... | 3,013 | 42.681159 | 141 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/models/pix2pix_model.py | import torch
from .base_model import BaseModel
from . import networks
class Pix2PixModel(BaseModel):
""" This class implements the pix2pix model, for learning a mapping from input images to output images given paired data.
The model training requires '--dataset_mode aligned' dataset.
By default, it uses ... | 6,519 | 49.9375 | 162 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/models/networks.py | import torch
import torch.nn as nn
from torch.nn import init
import functools
from torch.optim import lr_scheduler
###############################################################################
# Helper Functions
###############################################################################
class Identity(nn.Modu... | 28,408 | 45.04376 | 167 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/models/template_model.py | """Model class template
This module provides a template for users to implement custom models.
You can specify '--model template' to use this model.
The class name should be consistent with both the filename and its model option.
The filename should be <model>_dataset.py
The class name should be <Model>Dataset.py
It im... | 5,951 | 58.52 | 177 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/models/__init__.py | """This package contains modules related to objective functions, optimizations, and network architectures.
To add a custom model class called 'dummy', you need to add a file called 'dummy_model.py' and define a subclass DummyModel inherited from BaseModel.
You need to implement the following five functions:
-- <__... | 3,072 | 44.191176 | 250 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/models/test_model.py | from .base_model import BaseModel
from . import networks
class TestModel(BaseModel):
""" This TesteModel can be used to generate CycleGAN results for only one direction.
This model will automatically set '--dataset_mode single', which only loads the images from one collection.
See the test instruction fo... | 3,151 | 44.028571 | 160 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/models/cycle_gan_model.py | import torch
import itertools
from util.image_pool import ImagePool
from .base_model import BaseModel
from . import networks
class CycleGANModel(BaseModel):
"""
This class implements the CycleGAN model, for learning image-to-image translation without paired data.
The model training requires '--dataset_mo... | 10,557 | 53.14359 | 362 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/util/image_pool.py | import random
import torch
class ImagePool():
"""This class implements an image buffer that stores previously generated images.
This buffer enables us to update discriminators using a history of generated images
rather than the ones produced by the latest generators.
"""
def __init__(self, pool_... | 2,226 | 39.490909 | 140 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/util/html.py | import dominate
from dominate.tags import meta, h3, table, tr, td, p, a, img, br
import os
class HTML:
"""This HTML class allows us to save images and write texts into a single HTML file.
It consists of functions such as <add_header> (add a text header to the HTML file),
<add_images> (add a row of imag... | 3,223 | 36.057471 | 157 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/util/visualizer.py | import numpy as np
import os
import sys
import ntpath
import time
from . import util, html
from subprocess import Popen, PIPE
try:
import wandb
except ImportError:
print('Warning: wandb package cannot be found. The option "--use_wandb" will result in error.')
if sys.version_info[0] == 2:
VisdomExceptionB... | 11,890 | 45.089147 | 139 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/util/util.py | """This module contains simple helper functions """
from __future__ import print_function
import torch
import numpy as np
from PIL import Image
import os
def tensor2im(input_image, imtype=np.uint8):
""""Converts a Tensor array into a numpy image array.
Parameters:
input_image (tensor) -- the input i... | 3,175 | 29.538462 | 119 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/util/__init__.py | """This package includes a miscellaneous collection of useful helper functions."""
| 83 | 41 | 82 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/util/get_data.py | from __future__ import print_function
import os
import tarfile
import requests
from warnings import warn
from zipfile import ZipFile
from bs4 import BeautifulSoup
from os.path import abspath, isdir, join, basename
class GetData(object):
"""A Python script for downloading CycleGAN or pix2pix datasets.
Paramet... | 3,639 | 31.792793 | 90 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/scripts/test_before_push.py | # Simple script to make sure basic usage
# such as training, testing, saving and loading
# runs without errors.
import os
def run(command):
print(command)
exit_status = os.system(command)
if exit_status > 0:
exit(1)
if __name__ == '__main__':
# download mini datasets
if not os.path.exist... | 2,722 | 51.365385 | 178 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/scripts/edges/batch_hed.py | # HED batch processing script; modified from https://github.com/s9xie/hed/blob/master/examples/hed/HED-tutorial.ipynb
# Step 1: download the hed repo: https://github.com/s9xie/hed
# Step 2: download the models and protoxt, and put them under {caffe_root}/examples/hed/
# Step 3: put this script under {caffe_root}/exampl... | 3,521 | 41.95122 | 141 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/scripts/eval_cityscapes/evaluate.py | import os
import caffe
import argparse
import numpy as np
import scipy.misc
from PIL import Image
from util import segrun, fast_hist, get_scores
from cityscapes import cityscapes
parser = argparse.ArgumentParser()
parser.add_argument("--cityscapes_dir", type=str, required=True, help="Path to the original cityscapes da... | 3,403 | 47.628571 | 170 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/scripts/eval_cityscapes/cityscapes.py | # The following code is modified from https://github.com/shelhamer/clockwork-fcn
import sys
import os
import glob
import numpy as np
from PIL import Image
class cityscapes:
def __init__(self, data_path):
# data_path something like /data2/cityscapes
self.dir = data_path
self.classes = ['roa... | 5,772 | 39.65493 | 138 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/scripts/eval_cityscapes/util.py | # The following code is modified from https://github.com/shelhamer/clockwork-fcn
import numpy as np
def get_out_scoremap(net):
return net.blobs['score'].data[0].argmax(axis=0).astype(np.uint8)
def feed_net(net, in_):
"""
Load prepared input into net.
"""
net.blobs['data'].reshape(1, *in_.shape)
... | 1,051 | 23.465116 | 80 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/datasets/combine_A_and_B.py | import os
import numpy as np
import cv2
import argparse
from multiprocessing import Pool
def image_write(path_A, path_B, path_AB):
im_A = cv2.imread(path_A, 1) # python2: cv2.CV_LOAD_IMAGE_COLOR; python3: cv2.IMREAD_COLOR
im_B = cv2.imread(path_B, 1) # python2: cv2.CV_LOAD_IMAGE_COLOR; python3: cv2.IMREAD_COL... | 3,002 | 43.161765 | 181 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/datasets/prepare_cityscapes_dataset.py | import os
import glob
from PIL import Image
help_msg = """
The dataset can be downloaded from https://cityscapes-dataset.com.
Please download the datasets [gtFine_trainvaltest.zip] and [leftImg8bit_trainvaltest.zip] and unzip them.
gtFine contains the semantics segmentations. Use --gtFine_dir to specify the path to th... | 4,126 | 40.27 | 142 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/datasets/make_dataset_aligned.py | import os
from PIL import Image
def get_file_paths(folder):
image_file_paths = []
for root, dirs, filenames in os.walk(folder):
filenames = sorted(filenames)
for filename in filenames:
input_path = os.path.abspath(root)
file_path = os.path.join(input_path, filename)
... | 2,257 | 34.28125 | 97 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/data/colorization_dataset.py | import os
from data.base_dataset import BaseDataset, get_transform
from data.image_folder import make_dataset
from skimage import color # require skimage
from PIL import Image
import numpy as np
import torchvision.transforms as transforms
class ColorizationDataset(BaseDataset):
"""This dataset class can load a s... | 2,717 | 38.391304 | 141 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/data/base_dataset.py | """This module implements an abstract base class (ABC) 'BaseDataset' for datasets.
It also includes common transformation functions (e.g., get_transform, __scale_width), which can be later used in subclasses.
"""
import random
import numpy as np
import torch.utils.data as data
from PIL import Image
import torchvision.... | 5,895 | 34.095238 | 141 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/data/unaligned_dataset.py | import os
from data.base_dataset import BaseDataset, get_transform
from data.image_folder import make_dataset
from PIL import Image
import random
class UnalignedDataset(BaseDataset):
"""
This dataset class can load unaligned/unpaired datasets.
It requires two directories to host training images from doma... | 3,299 | 44.833333 | 122 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/data/image_folder.py | """A modified image folder class
We modify the official PyTorch image folder (https://github.com/pytorch/vision/blob/master/torchvision/datasets/folder.py)
so that this class can load images from both current directory and its subdirectories.
"""
import torch.utils.data as data
from PIL import Image
import os
IMG_E... | 1,885 | 27.575758 | 122 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/data/aligned_dataset.py | import os
from data.base_dataset import BaseDataset, get_params, get_transform
from data.image_folder import make_dataset
from PIL import Image
class AlignedDataset(BaseDataset):
"""A dataset class for paired image dataset.
It assumes that the directory '/path/to/data/train' contains image pairs in the form ... | 2,497 | 39.95082 | 118 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/data/__init__.py | """This package includes all the modules related to data loading and preprocessing
To add a custom dataset class called 'dummy', you need to add a file called 'dummy_dataset.py' and define a subclass 'DummyDataset' inherited from BaseDataset.
You need to implement four functions:
-- <__init__>: ... | 3,554 | 36.819149 | 176 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/data/template_dataset.py | """Dataset class template
This module provides a template for users to implement custom datasets.
You can specify '--dataset_mode template' to use this dataset.
The class name should be consistent with both the filename and its dataset_mode option.
The filename should be <dataset_mode>_dataset.py
The class name should... | 3,506 | 45.144737 | 156 | py |
pytorch-CycleGAN-and-pix2pix | pytorch-CycleGAN-and-pix2pix-master/data/single_dataset.py | from data.base_dataset import BaseDataset, get_transform
from data.image_folder import make_dataset
from PIL import Image
class SingleDataset(BaseDataset):
"""This dataset class can load a set of images specified by the path --dataroot /path/to/data.
It can be used for generating CycleGAN results only for on... | 1,495 | 35.487805 | 105 | py |
sign-topic | sign-topic-main/setup.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 os
import subprocess
import sys
from setuptools import Extension, find_packages, setup
if sys.version_info < (... | 8,427 | 28.263889 | 92 | py |
sign-topic | sign-topic-main/hubconf.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.
"""isort:skip_file"""
import functools
import importlib
dependencies = [
"dataclasses",
"hydra",
"numpy",
"omegaconf",
"... | 2,099 | 27.378378 | 82 | py |
sign-topic | sign-topic-main/train.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.
"""
Legacy entry point. Use fairseq_cli/train.py or fairseq-train instead.
"""
from fairseq_cli.train import cli_mai... | 366 | 23.466667 | 70 | py |
sign-topic | sign-topic-main/examples/__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.
try:
from fairseq.version import __version__ # noqa
except ImportError:
pass
| 264 | 25.5 | 65 | py |
sign-topic | sign-topic-main/examples/truncated_bptt/transformer_xl_model.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 dataclasses import dataclass, field
from typing import Dict, List, Optional
import torch
from fairseq.dataclass import Fa... | 5,324 | 33.134615 | 86 | py |
sign-topic | sign-topic-main/examples/truncated_bptt/__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 . import transformer_xl_model, truncated_bptt_lm_task # noqa
| 245 | 34.142857 | 66 | py |
sign-topic | sign-topic-main/examples/truncated_bptt/truncated_bptt_lm_task.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
from dataclasses import dataclass, field
from typing import List, Optional, Tuple
import torch
from fairseq import u... | 9,995 | 33.951049 | 86 | py |
sign-topic | sign-topic-main/examples/linformer/linformer_src/__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 .models import linformer_roberta # noqa
| 224 | 31.142857 | 65 | py |
sign-topic | sign-topic-main/examples/linformer/linformer_src/modules/multihead_linear_attention.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 typing import Dict, Optional, Tuple
import torch
import torch.nn.functional as F
from fairseq import utils
from fairseq.incr... | 19,151 | 38.73444 | 98 | py |
sign-topic | sign-topic-main/examples/linformer/linformer_src/modules/linformer_sentence_encoder.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.nn as nn
from fairseq.models.transformer import TransformerEncoder
from .linformer_sentence_encoder_layer import Li... | 2,151 | 38.127273 | 85 | py |
sign-topic | sign-topic-main/examples/linformer/linformer_src/modules/__init__.py | 0 | 0 | 0 | py | |
sign-topic | sign-topic-main/examples/linformer/linformer_src/modules/linformer_sentence_encoder_layer.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.modules import TransformerEncoderLayer
from .multihead_linear_attention import MultiheadL... | 2,743 | 40.575758 | 85 | py |
sign-topic | sign-topic-main/examples/linformer/linformer_src/models/linformer_roberta.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.
"""
Linformer: Self-Attention with Linear Complexity
"""
import logging
import torch
from fairseq import utils
from fairseq.models import reg... | 4,143 | 33.247934 | 84 | py |
sign-topic | sign-topic-main/examples/linformer/linformer_src/models/__init__.py | 0 | 0 | 0 | py | |
sign-topic | sign-topic-main/examples/wav2vec/vq-wav2vec_featurize.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.
"""
Helper script to pre-compute embeddings for a flashlight (previously called wav2letter++) dataset
"""
import argpa... | 7,680 | 29.601594 | 99 | py |
sign-topic | sign-topic-main/examples/wav2vec/wav2vec_manifest.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 argparse
import glob
import os
impor... | 2,513 | 27.568182 | 98 | py |
sign-topic | sign-topic-main/examples/wav2vec/wav2vec_featurize.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.
"""
Helper script to pre-compute embeddings for a flashlight (previously called wav2letter++) dataset
"""
import argpa... | 7,020 | 27.084 | 135 | py |
sign-topic | sign-topic-main/examples/wav2vec/__init__.py | 0 | 0 | 0 | py | |
sign-topic | sign-topic-main/examples/wav2vec/libri_labels.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.
"""
Helper script to pre-compute embeddings for a flashlight (previously called wav2letter++) dataset
"""
import argpa... | 1,875 | 31.912281 | 97 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/w2vu_generate.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.
"""
Run inference for pre-processed data with a trained model.
"""
import ast
from collections import namedtuple
fr... | 22,210 | 30.371469 | 129 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/__init__.py | 0 | 0 | 0 | py | |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/models/wav2vec_u.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
from enum import Enum, auto
import math
import numpy as np
from typing import Tuple, List, Optional, Dict
i... | 20,954 | 31.844828 | 90 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/models/__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 .wav2vec_u import Wav2vec_U
__all__ = [
"Wav2vec_U",
]
| 244 | 19.416667 | 65 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/ltr_to_wrd.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 sys
def main():
for line in sys.stdin:
print(line.replace(" ", "").replace("|", " ").strip())
... | 359 | 20.176471 | 65 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/wav2vec_apply_cluster_faiss.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 argparse
import os
import os.path as osp
import numpy as np
import tqdm
import torch
import sys
import faiss... | 4,015 | 30.131783 | 129 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/merge_clusters.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 argparse
import os
import os.path as osp
import numpy as np
import tqdm
import torch
import random
from shuti... | 3,543 | 29.817391 | 110 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/normalize_and_filter_text.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 fasttext as ft
import os
import regex
import sys
def get_parser():
parser = argparse.Argum... | 1,997 | 26.369863 | 114 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/remove_silence.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.
"""
get intervals from .vads file, specify output data, and this script removes silences and saves the audio data in... | 1,927 | 29.125 | 128 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/normalize_text.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 regex
import sys
def main():
filter_r = regex.compile(r"[^\p{L}\p{N}\p{M}\' \-]")
for line in sys.std... | 489 | 20.304348 | 65 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/phonemize_with_sil.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 argparse
import numpy as np
import sys
def get_parser():
parser = argparse.ArgumentParser(
desc... | 2,045 | 23.357143 | 95 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/filter_lexicon.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 argparse
import sys
from fairseq.data import Dictionary
def get_parser():
parser = argparse.ArgumentPa... | 939 | 21.926829 | 83 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/wrd_to_ltr.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 sys
def main():
for line in sys.stdin:
print(" ".join(list(line.strip().replace(" ", "|"))) + "... | 365 | 20.529412 | 68 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/filter_tsv.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 os
import argparse
import sys
parser = argparse.ArgumentParser()
parser.add_argument("--tsv", required=True... | 955 | 24.157895 | 71 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/g2p_wrd_to_phn.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 argparse
import sys
from g2p_en import G2p
def main():
parser = argparse.ArgumentParser()
parser.a... | 1,104 | 23.021739 | 81 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/apply_pca.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 argparse
import os
import os.path as osp
import math
import numpy as np
import tqdm
import torch
from shutil ... | 2,496 | 31.428571 | 114 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/wav2vec_cluster_faiss.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 argparse
import gc
import os
import os.path as osp
import random
import numpy as np
import tqdm
import torch
... | 6,315 | 28.933649 | 129 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/pca.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 argparse
import os
import os.path as osp
import numpy as np
import faiss
def get_parser():
parser = a... | 1,471 | 26.259259 | 103 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/mean_pool.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 argparse
import os
import os.path as osp
import math
import numpy as np
import tqdm
import torch
import torch... | 3,187 | 30.88 | 144 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/copy_labels.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 sys
for idx, line in enumerate(sys.stdin):
print(f"utt{idx:010d} {line}", end="")
| 298 | 26.181818 | 65 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/vads.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 argparse
import sys
from copy import deepcopy
from scipy.signal import lfilter
import numpy as np
from tqdm... | 2,569 | 24.959596 | 79 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/wav2vec_extract_features.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 argparse
import os
import os.path as osp
import tqdm
import torch
import torch.nn.functional as F
from shutil... | 3,673 | 29.616667 | 105 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/scripts/wer.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.
"""
Implement unsupervised metric for decoding hyperparameter selection:
$$ alpha * LM_PPL + ViterbitUER(%) * 10... | 2,264 | 26.289157 | 87 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/kaldi_self_train/st/local/prepare_data_from_w2v.py | import kaldi_io
import numpy as np
import os
def get_parser():
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("w2v_dir", help="wav2vec feature and text directory")
parser.add_argument("tar_root", help="output data directory in kaldi's format")
parser.add_argument("split", h... | 2,137 | 36.508772 | 84 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/kaldi_self_train/st/local/copy_aligned_text.py | import sys
for idx, line in enumerate(sys.stdin):
print(f"utt{idx:010d} {line}", end='') | 93 | 22.5 | 42 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/kaldi_self_train/st/local/unsup_select.py | """
Implement unsupervised metric for decoding hyperparameter selection:
$$ alpha * LM_PPL + ViterbitUER(%) * 100 $$
"""
import argparse
import logging
import math
import sys
import kenlm
import editdistance
from g2p_en import G2p
logging.root.setLevel(logging.INFO)
logging.basicConfig(stream=sys.stdout, level=lo... | 4,767 | 34.058824 | 134 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/data/random_input_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 random
from typing import List
from fairseq.data import BaseWrapperDataset, data_utils
class RandomInputDataset(BaseWrapperDataset):... | 1,905 | 29.253968 | 78 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/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.
from .extracted_features_dataset import ExtractedFeaturesDataset
from .random_input_dataset import RandomInputDataset
__all__ = [
"Extra... | 370 | 25.5 | 65 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/data/extracted_features_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 os
import contextlib
import numpy as np
import torch
from fairseq.data import FairseqDataset, data_utils
logger = l... | 4,170 | 27.765517 | 87 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/tasks/unpaired_audio_text.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 dataclasses import dataclass,... | 15,435 | 33.455357 | 102 | py |
sign-topic | sign-topic-main/examples/wav2vec/unsupervised/tasks/__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 .unpaired_audio_text import UnpairedAudioText
__all__ = [
"UnpairedAudioText",
]
| 270 | 21.583333 | 65 | py |
sign-topic | sign-topic-main/examples/criss/save_encoder.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 numpy as np
import torch
from fairseq import check... | 7,473 | 33.762791 | 90 | py |
sign-topic | sign-topic-main/examples/criss/sentence_retrieval/encoder_analysis.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 argparse
import glob
import numpy as np
DIM = 1024
def compute_dist(source_embs, target_embs, k=5, return... | 3,278 | 34.258065 | 82 | py |
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