python_code stringlengths 0 66.4k |
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# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the 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 torch.autograd import grad
def gPenalty(inputs, loss, la... |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#
""" Some utilities """
import os
import math
import warnings
import configargparse
import torch
from nets import ConvNe... |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#
import os
import time
import torch
import torch.nn.functional as F
from torch.autograd import grad
from data import CIF... |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#
import math
import time
import numpy as np
import scipy.stats as st
from functools import partial
import torch
from torc... |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#
import os
import numpy as np
from PIL import Image
import torch
from torch.utils.data.sampler import SubsetRandomSampler... |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#
from functools import reduce
import torch.nn as nn
import torch.nn.functional as F
class Identity(nn.Module):
def ... |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import detectron2.utils.comm as comm
from detectron2.checkpoint import DetectionCheckpointer
from detectron2.config import get_cfg
from detectron2.engine import default_argument_parser, default_setup, launch
from adapteacher... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from detectron2.config import CfgNode as CN
def add_ateacher_config(cfg):
"""
Add config for semisupnet.
"""
_C = cfg
_C.TEST.VAL_LOSS = True
_C.MODEL.RPN.UNSUP_LOSS_WEIGHT = 1.0
_C.MODEL.RPN.LOSS = "CrossEntropy"
... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from .config import add_ateacher_config
|
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from detectron2.checkpoint.c2_model_loading import align_and_update_state_dicts
from detectron2.checkpoint import DetectionCheckpointer
# for load_student_model
from typing import Any
from fvcore.common.checkpoint import _strip_prefix_if_present, _... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
from detectron2.config import CfgNode
from detectron2.solver.lr_scheduler import WarmupCosineLR, WarmupMultiStepLR
from .lr_scheduler import WarmupTwoStageMultiStepLR
def build_lr_scheduler(
cfg: CfgNode, optimizer: torch.optim.Op... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from bisect import bisect_right
from typing import List
import torch
from detectron2.solver.lr_scheduler import _get_warmup_factor_at_iter
class WarmupTwoStageMultiStepLR(torch.optim.lr_scheduler._LRScheduler):
def __init__(
self,
... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import numpy as np
import torch
import torch.nn as nn
from torch.nn import functional as F
from detectron2.modeling.meta_arch.build import META_ARCH_REGISTRY
from detectron2.modeling.meta_arch.rcnn import GeneralizedRCNN
from detectron2.config impo... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch.nn as nn
import copy
import torch
from typing import Union, List, Dict, Any, cast
from detectron2.modeling.backbone import (
ResNet,
Backbone,
build_resnet_backbone,
BACKBONE_REGISTRY
)
from detectron2.modeling.backbone.... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from torch.nn.parallel import DataParallel, DistributedDataParallel
import torch.nn as nn
class EnsembleTSModel(nn.Module):
def __init__(self, modelTeacher, modelStudent):
super(EnsembleTSModel, self).__init__()
if isinstance(... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from typing import Dict, Optional
import torch
from detectron2.structures import ImageList, Instances
from detectron2.modeling.proposal_generator import RPN
from detectron2.modeling.proposal_generator.build import PROPOSAL_GENERATOR_REGISTRY
@PRO... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.modeling.roi_heads.fast_rcnn import (
FastRCNNOutputLayers,
FastRCNNOutputs,
)
# focal loss
class FastRCNNFocaltLossOutputLayers(FastRCNNOutputLayers):
... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
from typing import Dict, List, Optional, Tuple, Union
from detectron2.structures import Boxes, ImageList, Instances, pairwise_iou
from detectron2.modeling.proposal_generator.proposal_utils import (
add_ground_truth_to_proposals,
)
f... |
# Copyright (c) Facebook, Inc. and its affiliates.
from .coco_evaluation import COCOEvaluator
from .pascal_voc_evaluation import PascalVOCDetectionEvaluator
# __all__ = [k for k in globals().keys() if not k.startswith("_")]
__all__ = [
"COCOEvaluator",
"PascalVOCDetectionEvaluator"
]
|
# Copyright (c) Facebook, Inc. and its affiliates.
import contextlib
import copy
import io
import itertools
import json
import logging
import numpy as np
import os
import pickle
from collections import OrderedDict
import pycocotools.mask as mask_util
import torch
from pycocotools.coco import COCO
from pycocotools.cocoe... |
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import logging
import numpy as np
import os
import tempfile
import xml.etree.ElementTree as ET
from collections import OrderedDict, defaultdict
from functools import lru_cache
import torch
from detectron2.data import MetadataCatalog
from detec... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import numpy as np
import operator
import json
import torch.utils.data
from detectron2.utils.comm import get_world_size
from detectron2.data.common import (
DatasetFromList,
MapDataset,
)
from detectron2.data.dataset_mapper im... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from .build import (
build_detection_test_loader,
build_detection_semisup_train_loader,
)
|
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import torchvision.transforms as transforms
from adapteacher.data.transforms.augmentation_impl import (
GaussianBlur,
)
def build_strong_augmentation(cfg, is_train):
"""
Create a list of :class:`Augmentation` from config... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import copy
import logging
import numpy as np
from PIL import Image
import torch
import detectron2.data.detection_utils as utils
import detectron2.data.transforms as T
from detectron2.data.dataset_mapper import DatasetMapper
from adapteacher.data.d... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
from detectron2.data.common import MapDataset, AspectRatioGroupedDataset
class MapDatasetTwoCrop(MapDataset):
"""
Map a function over the elements in a dataset.
This customized MapDataset transforms an image with two au... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import os
import contextlib
from detectron2.data import DatasetCatalog, MetadataCatalog
from fvcore.common.timer import Timer
# from fvcore.common.file_io import PathManager
from iopath.common.file_io import PathManager
from detectron2.data.dataset... |
# Copyright (c) Facebook, Inc. and its affiliates.
import functools
import json
import logging
import multiprocessing as mp
import numpy as np
import os
from itertools import chain
import pycocotools.mask as mask_util
from PIL import Image
from detectron2.structures import BoxMode
from detectron2.utils.comm import get... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import random
from PIL import ImageFilter
class GaussianBlur:
"""
Gaussian blur augmentation in SimCLR https://arxiv.org/abs/2002.05709
Adapted from MoCo:
https://github.com/facebookresearch/moco/blob/master/moco/loader.py
Note... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from detectron2.engine.hooks import HookBase
import detectron2.utils.comm as comm
import torch
import numpy as np
from contextlib import contextmanager
class LossEvalHook(HookBase):
def __init__(self, eval_period, model, data_loader, model_ou... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from detectron2.structures import pairwise_iou
class OpenMatchTrainerProbe:
def __init__(self, cfg):
self.BOX_AP = 0.5
self.NUM_CLASSES = cfg.MODEL.ROI_HEADS.NUM_CLASSES
# self.bbox_stat_list = ['compute_fp_gtoutlier', 'c... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import os
import time
import logging
import torch
from torch.nn.parallel import DistributedDataParallel
from fvcore.nn.precise_bn import get_bn_modules
import numpy as np
from collections import OrderedDict
import detectron2.utils.comm as comm
from... |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
# from d2go.config import CfgNode as CN
def add_aut_config(cfg):
"""
Add config for SemiSupSegRunner.
"""
_C = cfg
#New added for discriminator
_C.UNBIASEDTEACHER.DIS_LOSS_WEIGHT = 0.1
_C.UNBIASED... |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import os
from collections import OrderedDict
from functools import lru_cache
import d2go.utils.abnormal_checker as abnormal_checker
import detectron2.utils.comm as comm
from d2go.config import CONFIG_SCALING... |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
# from .runner import SemiSupSegRunner, SemiSupHandTrackingRunner # noqa
from .runner import BaseUnbiasedTeacherRunner # noqa
from .runner import DAobjUnbiasedTeacherRunner # noqa
|
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch.nn as nn
import copy
import torch
from typing import Union, List, Dict, Any, cast
from detectron2.modeling.backbone import (
ResNet,
Backbone,
build_resnet_backbone,
BACKBONE_REGISTRY
)
from detec... |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import numpy as np
import torch
import torch.nn as nn
from torch.nn import functional as F
from detectron2.data.detection_utils import convert_image_to_rgb
from detectron2.modeling import META_ARCH_REGISTRY, GeneralizedRCNN
... |
# Copyright (c) Facebook, Inc. and its affiliates.
from .coco_evaluation import COCOEvaluator
from .pascal_voc_evaluation import PascalVOCDetectionEvaluator
# __all__ = [k for k in globals().keys() if not k.startswith("_")]
__all__ = [
"COCOEvaluator",
"PascalVOCDetectionEvaluator"
]
|
# Copyright (c) Facebook, Inc. and its affiliates.
import contextlib
import copy
import io
import itertools
import json
import logging
import numpy as np
import os
import pickle
from collections import OrderedDict
import pycocotools.mask as mask_util
import torch
from pycocotools.coco import COCO
from pycocotools.cocoe... |
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import logging
import numpy as np
import os
import tempfile
import xml.etree.ElementTree as ET
from collections import OrderedDict, defaultdict
from functools import lru_cache
import torch
from detectron2.data import MetadataCatalog
from detec... |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import contextlib
import io
import logging
import os
import json
from detectron2.data import DatasetCatalog, MetadataCatalog
from d2go.data.utils import CallFuncWithJsonFile
from detectron2.utils.file_io import PathManager
f... |
# Copyright (c) Facebook, Inc. and its affiliates.
import functools
import json
import logging
import multiprocessing as mp
import numpy as np
import os
from itertools import chain
import pycocotools.mask as mask_util
from PIL import Image
from detectron2.structures import BoxMode
from detectron2.utils.comm import get... |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from detectron2.structures import pairwise_iou
class OpenMatchTrainerProbe:
def __init__(self, cfg):
self.BOX_AP = 0.5
self.NUM_CLASSES = cfg.MODEL.ROI_HEADS.NUM_CLASSES
# self.bbox_stat_list = ['c... |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import time
from collections import OrderedDict
from typing import Dict
import detectron2.utils.comm as comm
import numpy as np
import torch
from detectron2.engine import SimpleTrainer
from detectron2.structur... |
# Copyright (c) Facebook, Inc. and its affiliates.
import torch
import datetime
import logging
import math
import time
import sys
from torch.distributed.distributed_c10d import reduce
from utils.ap_calculator import APCalculator
from utils.misc import SmoothedValue
from utils.dist import (
all_gather_dict,
all... |
# Copyright (c) Facebook, Inc. and its affiliates.
import torch
def build_optimizer(args, model):
params_with_decay = []
params_without_decay = []
for name, param in model.named_parameters():
if param.requires_grad is False:
continue
if args.filter_biases_wd and (len(param.sha... |
# Copyright (c) Facebook, Inc. and its affiliates.
import torch
import torch.nn as nn
import numpy as np
import torch.nn.functional as F
from utils.box_util import generalized_box3d_iou
from utils.dist import all_reduce_average
from utils.misc import huber_loss
from scipy.optimize import linear_sum_assignment
class M... |
# Copyright (c) Facebook, Inc. and its affiliates.
import argparse
import os
import sys
import pickle
import numpy as np
import torch
from torch.multiprocessing import set_start_method
from torch.utils.data import DataLoader, DistributedSampler
# 3DETR codebase specific imports
from datasets import build_dataset
fro... |
# Copyright (c) Facebook, Inc. and its affiliates.
"""
Modified from https://github.com/facebookresearch/votenet
Dataset for 3D object detection on SUN RGB-D (with support of vote supervision).
A sunrgbd oriented bounding box is parameterized by (cx,cy,cz), (l,w,h) -- (dx,dy,dz) in upright depth coord
(Z is up, Y i... |
# Copyright (c) Facebook, Inc. and its affiliates.
from .scannet import ScannetDetectionDataset, ScannetDatasetConfig
from .sunrgbd import SunrgbdDetectionDataset, SunrgbdDatasetConfig
DATASET_FUNCTIONS = {
"scannet": [ScannetDetectionDataset, ScannetDatasetConfig],
"sunrgbd": [SunrgbdDetectionDataset, Sunrgb... |
# Copyright (c) Facebook, Inc. and its affiliates.
"""
Modified from https://github.com/facebookresearch/votenet
Dataset for object bounding box regression.
An axis aligned bounding box is parameterized by (cx,cy,cz) and (dx,dy,dz)
where (cx,cy,cz) is the center point of the box, dx is the x-axis length of the box.
"... |
# Copyright (c) Facebook, Inc. and its affiliates.
import torch
import numpy as np
from collections import deque
from typing import List
from utils.dist import is_distributed, barrier, all_reduce_sum
def my_worker_init_fn(worker_id):
np.random.seed(np.random.get_state()[1][0] + worker_id)
@torch.jit.ignore
def ... |
# Copyright (c) Facebook, Inc. and its affiliates.
from setuptools import setup, Extension
from Cython.Build import cythonize
import numpy as np
# hacky way to find numpy include path
# replace with actual path if this does not work
np_include_path = np.__file__.replace("__init__.py", "core/include/")
INCLUDE_PATH =... |
# Copyright (c) Facebook, Inc. and its affiliates.
""" Generic Code for Object Detection Evaluation
Input:
For each class:
For each image:
Predictions: box, score
Groundtruths: box
Output:
For each class:
precision-recal and average precision
Autho... |
# Copyright (c) Facebook, Inc. and its affiliates.
""" Utility functions for processing point clouds.
Author: Charles R. Qi and Or Litany
"""
import os
import sys
import torch
# Point cloud IO
import numpy as np
from plyfile import PlyData, PlyElement
# Mesh IO
import trimesh
# -----------------------------------... |
# Copyright (c) Facebook, Inc. and its affiliates.
import torch
import os
from utils.dist import is_primary
def save_checkpoint(
checkpoint_dir,
model_no_ddp,
optimizer,
epoch,
args,
best_val_metrics,
filename=None,
):
if not is_primary():
return
if filename is None:
... |
# Copyright (c) Facebook, Inc. and its affiliates.
import os
from urllib import request
import torch
import pickle
## Define the weights you want and where to store them
dataset = "scannet"
encoder = "_masked" # or ""
epoch = 1080
base_url = "https://dl.fbaipublicfiles.com/3detr/checkpoints"
local_dir = "/tmp/"
###... |
# Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
# boxes are axis aigned 2D boxes of shape (n,5) in FLOAT numbers with (x1,y1,x2,y2,score)
""" Ref: https://www.pyimagesearch.com/2015/02/16/faster-non-maximum-suppression-python/
Ref: https://github.com/vickyboy47/nms-python/blob/master/nms.py
"""... |
# Copyright (c) Facebook, Inc. and its affiliates.
import torch
try:
from tensorboardX import SummaryWriter
except ImportError:
print("Cannot import tensorboard. Will log to txt files only.")
SummaryWriter = None
from utils.dist import is_primary
class Logger(object):
def __init__(self, log_dir=Non... |
# Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
def check_aspect(crop_range, aspect_min):
xy_aspect = np.min(crop_range[:2]) / np.max(crop_range[:2])
xz_aspect = np.min(crop_range[[0, 2]]) / np.max(crop_range[[0, 2]])
yz_aspect = np.min(crop_range[1:]) / np.max(crop_range[1:])
re... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
Utilities for bounding box manipulation and GIoU.
"""
import torch
from torchvision.ops.boxes import box_area
from typing import List
try:
from box_intersection import batch_intersect
except ImportError:
print("Could not import cythonize... |
# Copyright (c) Facebook, Inc. and its affiliates.
""" Helper functions for calculating 2D and 3D bounding box IoU.
Collected and written by Charles R. Qi
Last modified: Apr 2021 by Ishan Misra
"""
import torch
import numpy as np
from scipy.spatial import ConvexHull, Delaunay
from utils.misc import to_list_1d, to_lis... |
# 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 functions and class to calculate Average Precisions for 3D object detection.
"""
import logging
import os
import sys
from collectio... |
# Copyright (c) Facebook, Inc. and its affiliates.
import pickle
import torch
import torch.distributed as dist
def is_distributed():
if not dist.is_available() or not dist.is_initialized():
return False
return True
def get_rank():
if not is_distributed():
return 0
return dist.get_ra... |
# Copyright (c) Facebook, Inc. and its affiliates.
import math
from functools import partial
import numpy as np
import torch
import torch.nn as nn
from third_party.pointnet2.pointnet2_modules import PointnetSAModuleVotes
from third_party.pointnet2.pointnet2_utils import furthest_point_sample
from utils.pc_util import ... |
# Copyright (c) Facebook, Inc. and its affiliates.
from .model_3detr import build_3detr
MODEL_FUNCS = {
"3detr": build_3detr,
}
def build_model(args, dataset_config):
model, processor = MODEL_FUNCS[args.model_name](args, dataset_config)
return model, processor |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
Modified from DETR Transformer class.
Copy-paste from torch.nn.Transformer with modifications:
* positional encodings are passed in MHattention
* extra LN at the end of encoder is removed
* decoder returns a stack of activations fro... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
Various positional encodings for the transformer.
"""
import math
import torch
from torch import nn
import numpy as np
from utils.pc_util import shift_scale_points
class PositionEmbeddingCoordsSine(nn.Module):
def __init__(
self,
... |
# Copyright (c) Facebook, Inc. and its affiliates.
import torch.nn as nn
from functools import partial
import copy
class BatchNormDim1Swap(nn.BatchNorm1d):
"""
Used for nn.Transformer that uses a HW x N x C rep
"""
def forward(self, x):
"""
x: HW x N x C
permute to N x C x HW
... |
# Copyright (c) Facebook, Inc. and its affiliates.
''' Modified based on Ref: https://github.com/erikwijmans/Pointnet2_PyTorch '''
import torch
import torch.nn as nn
from typing import List, Tuple
class SharedMLP(nn.Sequential):
def __init__(
self,
args: List[int],
*,
... |
# 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 setuptools import setup
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
import glob
import os.path as osp
this_dir ... |
# Copyright (c) Facebook, Inc. and its affiliates.
''' Modified based on: https://github.com/erikwijmans/Pointnet2_PyTorch '''
from __future__ import (
division,
absolute_import,
with_statement,
print_function,
unicode_literals,
)
import torch
from torch.autograd import Function
import torch.nn as ... |
# Copyright (c) Facebook, Inc. and its affiliates.
''' Testing customized ops. '''
import torch
from torch.autograd import gradcheck
import numpy as np
import os
import sys
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
sys.path.append(BASE_DIR)
import pointnet2_utils
def test_interpolation_grad():
batch... |
# Copyright (c) Facebook, Inc. and its affiliates.
''' Pointnet2 layers.
Modified based on: https://github.com/erikwijmans/Pointnet2_PyTorch
Extended with the following:
1. Uniform sampling in each local region (sample_uniformly)
2. Return sampled points indices to support votenet.
'''
import torch
import torch.nn as ... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import pickle
import numpy as np
import os
np.random.seed(1234)
# we want 500 for training, 100 for test for wach class
n = ... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import sys, time, os
import numpy as np
import torch
import copy
import utils
from copy import deepcopy
from tqdm import tqd... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import os
import numpy as np
from copy import deepcopy
import pickle
import time
import uuid
from subprocess import call
#####... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import os,argparse,time
import numpy as np
from omegaconf import OmegaConf
from copy import deepcopy
import torch
import torc... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import print_function
from PIL import Image
import os
import os.path
import sys
if sys.version_info[0] == 2:... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
# https://github.com/pytorch/vision/blob/8635be94d1216f10fb8302da89233bd86445e449/torchvision/datasets/utils.py
import os
im... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import print_function
from PIL import Image
import os
import os.path
import sys
if sys.version_info[0] == 2:
... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import print_function
import os.path
import sys
import warnings
import urllib.request
if sys.version_info[0]... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import torch
import utils
class Shared(torch.nn.Module):
def __init__(self,args):
super(Shared, self).__init__()... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
class Shared(torch.nn.Module):
def __init__(self,args):
super(Shared, self)... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import torch
class Private(torch.nn.Module):
def __init__(self, args):
super(Private, self).__init__()
... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import torch
import utils
class Discriminator(torch.nn.Module):
def __init__(self,args,task_id):
super(Discrimina... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import pickle
import numpy as np
import os
np.random.seed(1234)
# we want 500 for training, 100 for test for wach class
n = ... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import sys, time, os
import numpy as np
import torch
import copy
import utils
from copy import deepcopy
from tqdm import tqd... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import os
import numpy as np
from copy import deepcopy
import pickle
import time
import uuid
from subprocess import call
#####... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import os,argparse,time
import numpy as np
from omegaconf import OmegaConf
import torch
import torch.backends.cudnn as cudnn... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import print_function
from PIL import Image
import os
import os.path
import sys
if sys.version_info[0] == 2:... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import print_function
import sys
if sys.version_info[0] == 2:
import cPickle as pickle
else:
import p... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
# https://github.com/pytorch/vision/blob/8635be94d1216f10fb8302da89233bd86445e449/torchvision/datasets/utils.py
import os
im... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import print_function
from PIL import Image
import os
import os.path
import sys
if sys.version_info[0] == 2:
... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import print_function
from PIL import Image
import torch
import numpy as np
import os.path
import sys
import ... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import torch
import sys, os
import numpy as np
from PIL import Image
import torch.utils.data as data
from torchvision import d... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import print_function
import os.path
import sys
import warnings
import urllib.request
if sys.version_info[0]... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import torch
import utils
class Shared(torch.nn.Module):
def __init__(self,args):
super(Shared, self).__init__()... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import torch
class Private(torch.nn.Module):
def __init__(self, args):
super(Private, self).__init__()
... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import torch
import utils
class Discriminator(torch.nn.Module):
def __init__(self,args,task_id):
super(Discrimina... |
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