repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
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NorCal | NorCal-main/projects/TensorMask/setup.py | #!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates.
import glob
import os
from setuptools import find_packages, setup
import torch
from torch.utils.cpp_extension import CUDA_HOME, CppExtension, CUDAExtension
def get_extensions():
this_dir = os.path.dirname(os.path.abspath(__file__))
exte... | 2,040 | 28.157143 | 100 | py |
NorCal | NorCal-main/projects/TensorMask/tensormask/arch.py | # Copyright (c) Facebook, Inc. and its affiliates.
import copy
import math
from typing import List
import torch
import torch.nn.functional as F
from fvcore.nn import sigmoid_focal_loss_star_jit, smooth_l1_loss
from torch import nn
from detectron2.layers import ShapeSpec, batched_nms, cat, paste_masks_in_image
from det... | 42,127 | 45.091904 | 100 | py |
NorCal | NorCal-main/projects/TensorMask/tensormask/layers/swap_align2nat.py | # Copyright (c) Facebook, Inc. and its affiliates.
from torch import nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from tensormask import _C
class _SwapAlign2Nat(Function):
@staticmethod
def forward(ctx, X, lambda_val, pad_val):
ctx.lambda_val = lambda... | 2,083 | 32.612903 | 89 | py |
NorCal | NorCal-main/projects/TensorMask/tests/test_swap_align2nat.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
import unittest
import torch
from torch.autograd import gradcheck
from tensormask.layers.swap_align2nat import SwapAlign2Nat
class SwapAlign2NatTest(unittest.TestCase):
@unittest.skipIf(not torch.cuda.is_available(), "CUDA not available")... | 1,048 | 30.787879 | 84 | py |
NorCal | NorCal-main/projects/NorCal/train_net.py | #!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates.
"""
A main training script.
This scripts reads a given config file and runs the training or evaluation.
It is an entry point that is made to train standard models in detectron2.
In order to let one script support training of many models,
this sc... | 6,180 | 34.522989 | 99 | py |
NorCal | NorCal-main/projects/NorCal/norcal/lvis_v0_5_categories.py | # Copyright (c) Facebook, Inc. and its affiliates.
# Autogen with
# with open("lvis_v0.5_train.json", "r") as f:
# a = json.load(f)
# c = a["categories"]
# LVIS_CATEGORIES = repr(c) + " # noqa"
# with open("/tmp/lvis_categories.py", "wt") as f:
# f.write(f"LVIS_CATEGORIES = {LVIS_CATEGORIES}")
# Then paste the... | 274,614 | 19,614.357143 | 274,242 | py |
NorCal | NorCal-main/projects/NorCal/norcal/roi_heads.py | from typing import List, Tuple
import torch
from torch.nn import functional as F
from detectron2.config import configurable
from detectron2.layers import ShapeSpec
from detectron2.modeling import (
ROI_HEADS_REGISTRY,
StandardROIHeads,
build_box_head,
FastRCNNOutputLayers,
)
from detectron2.modeling.p... | 4,571 | 36.170732 | 99 | py |
NorCal | NorCal-main/projects/NorCal/norcal/lvis_v1_categories.py | # Copyright (c) Facebook, Inc. and its affiliates.
# Autogen with
# with open("lvis_v1_train.json", "r") as f:
# a = json.load(f)
# c = a["categories"]
# LVIS_CATEGORIES = repr(c) + " # noqa"
# with open("/tmp/lvis_categories.py", "wt") as f:
# f.write(f"LVIS_CATEGORIES = {LVIS_CATEGORIES}")
# Then paste the c... | 269,343 | 19,237.857143 | 268,973 | py |
NorCal | NorCal-main/projects/Panoptic-DeepLab/train_net.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
"""
Panoptic-DeepLab Training Script.
This script is a simplified version of the training script in detectron2/tools.
"""
import os
import torch
import detectron2.data.transforms as T
import detectron2.utils.comm as comm
from detectron2.checkp... | 6,311 | 34.863636 | 97 | py |
NorCal | NorCal-main/projects/Panoptic-DeepLab/panoptic_deeplab/post_processing.py | # Copyright (c) Facebook, Inc. and its affiliates.
# Reference: https://github.com/bowenc0221/panoptic-deeplab/blob/master/segmentation/model/post_processing/instance_post_processing.py # noqa
from collections import Counter
import torch
import torch.nn.functional as F
def find_instance_center(center_heatmap, thres... | 9,600 | 39.855319 | 142 | py |
NorCal | NorCal-main/projects/Panoptic-DeepLab/panoptic_deeplab/dataset_mapper.py | # Copyright (c) Facebook, Inc. and its affiliates.
import copy
import logging
import numpy as np
from typing import Callable, List, Union
import torch
from panopticapi.utils import rgb2id
from detectron2.config import configurable
from detectron2.data import MetadataCatalog
from detectron2.data import detection_utils ... | 4,456 | 37.094017 | 99 | py |
NorCal | NorCal-main/projects/Panoptic-DeepLab/panoptic_deeplab/target_generator.py | # Copyright (c) Facebook, Inc. and its affiliates.
# Reference: https://github.com/bowenc0221/panoptic-deeplab/blob/aa934324b55a34ce95fea143aea1cb7a6dbe04bd/segmentation/data/transforms/target_transforms.py#L11 # noqa
import numpy as np
import torch
class PanopticDeepLabTargetGenerator(object):
"""
Generates... | 7,653 | 48.064103 | 167 | py |
NorCal | NorCal-main/projects/Panoptic-DeepLab/panoptic_deeplab/panoptic_seg.py | # Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
from typing import Callable, Dict, List, Union
import fvcore.nn.weight_init as weight_init
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.config import configurable
from detectron2.data import MetadataCatalog
... | 23,513 | 40.036649 | 100 | py |
NorCal | NorCal-main/tests/test_checkpoint.py | # Copyright (c) Facebook, Inc. and its affiliates.
import unittest
from collections import OrderedDict
import torch
from torch import nn
from detectron2.checkpoint.c2_model_loading import align_and_update_state_dicts
from detectron2.utils.logger import setup_logger
class TestCheckpointer(unittest.TestCase):
def ... | 1,705 | 33.12 | 79 | py |
NorCal | NorCal-main/tests/test_model_analysis.py | # Copyright (c) Facebook, Inc. and its affiliates.
import unittest
import torch
from torch import nn
from detectron2.utils.analysis import find_unused_parameters, flop_count_operators, parameter_count
from detectron2.utils.testing import get_model_no_weights
class RetinaNetTest(unittest.TestCase):
def setUp(se... | 2,095 | 32.806452 | 99 | py |
NorCal | NorCal-main/tests/test_export_torchscript.py | # Copyright (c) Facebook, Inc. and its affiliates.
import json
import os
import tempfile
import unittest
import torch
from torch import Tensor, nn
from detectron2 import model_zoo
from detectron2.config import get_cfg
from detectron2.config.instantiate import dump_dataclass, instantiate
from detectron2.export import ... | 9,506 | 36.72619 | 100 | py |
NorCal | NorCal-main/tests/test_registry.py | # Copyright (c) Facebook, Inc. and its affiliates.
import unittest
import torch
from detectron2.modeling.meta_arch import GeneralizedRCNN
from detectron2.utils.registry import _convert_target_to_string, locate
class A:
class B:
pass
class TestLocate(unittest.TestCase):
def _test_obj(self, obj):
... | 1,243 | 26.043478 | 71 | py |
NorCal | NorCal-main/tests/test_export_caffe2.py | # Copyright (c) Facebook, Inc. and its affiliates.
# -*- coding: utf-8 -*-
import copy
import os
import tempfile
import unittest
import torch
from detectron2 import model_zoo
from detectron2.utils.logger import setup_logger
from detectron2.utils.testing import get_sample_coco_image
@unittest.skipIf(os.environ.get("... | 1,999 | 34.714286 | 95 | py |
NorCal | NorCal-main/tests/test_engine.py | # Copyright (c) Facebook, Inc. and its affiliates.
import json
import math
import os
import tempfile
import time
import unittest
from unittest import mock
import torch
from fvcore.common.checkpoint import Checkpointer
from torch import nn
from detectron2 import model_zoo
from detectron2.config import configurable, ge... | 7,529 | 39.053191 | 98 | py |
NorCal | NorCal-main/tests/test_visualizer.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
import os
import tempfile
import unittest
import cv2
import torch
from detectron2.data import MetadataCatalog
from detectron2.structures import BoxMode, Instances, RotatedBoxes
from detectron2.utils.visualizer import ColorMo... | 9,775 | 36.455939 | 93 | py |
NorCal | NorCal-main/tests/test_scheduler.py | # Copyright (c) Facebook, Inc. and its affiliates.
import math
import numpy as np
from unittest import TestCase
import torch
from fvcore.common.param_scheduler import CosineParamScheduler, MultiStepParamScheduler
from torch import nn
from detectron2.solver import LRMultiplier, WarmupParamScheduler
class TestSchedul... | 2,202 | 30.927536 | 87 | py |
NorCal | NorCal-main/tests/config/test_yacs_config.py | #!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates.
import os
import tempfile
import unittest
import torch
from omegaconf import OmegaConf
from detectron2 import model_zoo
from detectron2.config import configurable, downgrade_config, get_cfg, upgrade_config
from detectron2.layers import ShapeSpe... | 8,458 | 30.214022 | 95 | py |
NorCal | NorCal-main/tests/layers/test_mask_ops.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import contextlib
import io
import numpy as np
import unittest
from collections import defaultdict
import torch
import tqdm
from fvcore.common.benchmark import benchmark
from pycocotools.coco import COCO
from tabulate import tabulate
from torch... | 7,262 | 34.778325 | 100 | py |
NorCal | NorCal-main/tests/layers/test_roi_align_rotated.py | # Copyright (c) Facebook, Inc. and its affiliates.
import logging
import unittest
import cv2
import torch
from torch.autograd import Variable, gradcheck
from detectron2.layers.roi_align import ROIAlign
from detectron2.layers.roi_align_rotated import ROIAlignRotated
logger = logging.getLogger(__name__)
class ROIAlig... | 6,716 | 36.949153 | 100 | py |
NorCal | NorCal-main/tests/layers/test_blocks.py | # Copyright (c) Facebook, Inc. and its affiliates.
import unittest
import torch
from torch import nn
from detectron2.layers import ASPP, DepthwiseSeparableConv2d, FrozenBatchNorm2d
from detectron2.modeling.backbone.resnet import BasicStem, ResNet
"""
Test for misc layers.
"""
class TestBlocks(unittest.TestCase):
... | 1,807 | 33.769231 | 99 | py |
NorCal | NorCal-main/tests/layers/test_deformable.py | # Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
import unittest
import torch
from detectron2.layers import DeformConv, ModulatedDeformConv
class DeformableTest(unittest.TestCase):
@unittest.skipIf(not torch.cuda.is_available(), "Deformable not supported for cpu")
def test_forward_output... | 7,462 | 42.643275 | 97 | py |
NorCal | NorCal-main/tests/layers/test_nms.py | # Copyright (c) Facebook, Inc. and its affiliates.
from __future__ import absolute_import, division, print_function, unicode_literals
import unittest
import torch
from detectron2.layers import batched_nms
from detectron2.utils.testing import random_boxes
class TestNMS(unittest.TestCase):
def _create_tensors(self... | 1,176 | 33.617647 | 94 | py |
NorCal | NorCal-main/tests/layers/test_nms_rotated.py | # Copyright (c) Facebook, Inc. and its affiliates.
from __future__ import absolute_import, division, print_function, unicode_literals
import numpy as np
import unittest
from copy import deepcopy
import torch
from torchvision import ops
from detectron2.layers import batched_nms, batched_nms_rotated, nms_rotated
from de... | 7,367 | 41.589595 | 96 | py |
NorCal | NorCal-main/tests/layers/test_losses.py | # Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
import unittest
import torch
from detectron2.layers import ciou_loss, diou_loss
class TestLosses(unittest.TestCase):
def test_diou_loss(self):
"""
loss = 1 - iou + d/c
where,
d = (distance between centers of the... | 3,045 | 35.698795 | 82 | py |
NorCal | NorCal-main/tests/layers/test_roi_align.py | # Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
import unittest
from copy import copy
import cv2
import torch
from fvcore.common.benchmark import benchmark
from torch.nn import functional as F
from detectron2.layers.roi_align import ROIAlign, roi_align
class ROIAlignTest(unittest.TestCase):
... | 7,766 | 35.810427 | 99 | py |
NorCal | NorCal-main/tests/data/test_dataset.py | # Copyright (c) Facebook, Inc. and its affiliates.
import os
import pickle
import sys
import unittest
from functools import partial
import torch
from iopath.common.file_io import LazyPath
from detectron2 import model_zoo
from detectron2.config import instantiate
from detectron2.data import (
DatasetFromList,
... | 4,309 | 32.410853 | 91 | py |
NorCal | NorCal-main/tests/data/test_sampler.py | # Copyright (c) Facebook, Inc. and its affiliates.
import itertools
import math
import operator
import unittest
import torch
from torch.utils import data
from torch.utils.data.sampler import SequentialSampler
from detectron2.data.build import worker_init_reset_seed
from detectron2.data.common import DatasetFromList, T... | 3,907 | 33.892857 | 96 | py |
NorCal | NorCal-main/tests/data/test_coco_evaluation.py | # Copyright (c) Facebook, Inc. and its affiliates.
import contextlib
import copy
import io
import json
import numpy as np
import os
import tempfile
import unittest
import torch
from pycocotools.coco import COCO
from pycocotools.cocoeval import COCOeval
from detectron2.data import DatasetCatalog
from detectron2.evaluat... | 8,863 | 62.314286 | 2,000 | py |
NorCal | NorCal-main/tests/data/test_transforms.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import logging
import numpy as np
import unittest
from unittest import mock
import torch
from PIL import Image, ImageOps
from torch.nn import functional as F
from detectron2.config import get_cfg
from detectron2.data import detection_utils
fro... | 10,866 | 41.449219 | 98 | py |
NorCal | NorCal-main/tests/modeling/test_matcher.py | # Copyright (c) Facebook, Inc. and its affiliates.
import unittest
from typing import List
import torch
from detectron2.config import get_cfg
from detectron2.modeling.matcher import Matcher
class TestMatcher(unittest.TestCase):
def test_scriptability(self):
cfg = get_cfg()
anchor_matcher = Matche... | 1,663 | 37.697674 | 98 | py |
NorCal | NorCal-main/tests/modeling/test_roi_pooler.py | # Copyright (c) Facebook, Inc. and its affiliates.
import logging
import unittest
import torch
from detectron2.modeling.poolers import ROIPooler
from detectron2.structures import Boxes, RotatedBoxes
from detectron2.utils.testing import random_boxes
logger = logging.getLogger(__name__)
class TestROIPooler(unittest.T... | 5,694 | 33.307229 | 87 | py |
NorCal | NorCal-main/tests/modeling/test_fast_rcnn.py | # Copyright (c) Facebook, Inc. and its affiliates.
import logging
import unittest
import torch
from detectron2.layers import ShapeSpec
from detectron2.modeling.box_regression import Box2BoxTransform, Box2BoxTransformRotated
from detectron2.modeling.roi_heads.fast_rcnn import FastRCNNOutputLayers
from detectron2.modeli... | 7,038 | 39.924419 | 100 | py |
NorCal | NorCal-main/tests/modeling/test_model_e2e.py | # Copyright (c) Facebook, Inc. and its affiliates.
import itertools
import unittest
from contextlib import contextmanager
from copy import deepcopy
import torch
from detectron2.structures import BitMasks, Boxes, ImageList, Instances
from detectron2.utils.events import EventStorage
from detectron2.utils.testing impor... | 8,533 | 37.098214 | 99 | py |
NorCal | NorCal-main/tests/modeling/test_box2box_transform.py | # Copyright (c) Facebook, Inc. and its affiliates.
import logging
import unittest
import torch
from detectron2.modeling.box_regression import Box2BoxTransform, Box2BoxTransformRotated
from detectron2.utils.testing import random_boxes
logger = logging.getLogger(__name__)
class TestBox2BoxTransform(unittest.TestCase)... | 2,863 | 37.702703 | 99 | py |
NorCal | NorCal-main/tests/modeling/test_rpn.py | # Copyright (c) Facebook, Inc. and its affiliates.
import logging
import unittest
import torch
from detectron2.config import get_cfg
from detectron2.export import scripting_with_instances
from detectron2.layers import ShapeSpec
from detectron2.modeling.backbone import build_backbone
from detectron2.modeling.proposal_g... | 11,270 | 41.855513 | 99 | py |
NorCal | NorCal-main/tests/modeling/test_mmdet.py | # Copyright (c) Facebook, Inc. and its affiliates.
import unittest
from detectron2.layers import ShapeSpec
from detectron2.modeling.mmdet_wrapper import MMDetBackbone, MMDetDetector
try:
import mmdet.models # noqa
HAS_MMDET = True
except ImportError:
HAS_MMDET = False
@unittest.skipIf(not HAS_MMDET, "... | 7,426 | 38.716578 | 99 | py |
NorCal | NorCal-main/tests/modeling/test_backbone.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import unittest
import torch
import detectron2.export.torchscript # apply patch # noqa
from detectron2 import model_zoo
from detectron2.config import get_cfg
from detectron2.layers import ShapeSpec
from detectron2.modeling.backbone import build_r... | 1,181 | 32.771429 | 80 | py |
NorCal | NorCal-main/tests/modeling/test_anchor_generator.py | # Copyright (c) Facebook, Inc. and its affiliates.
import logging
import unittest
import torch
from detectron2.config import get_cfg
from detectron2.layers import ShapeSpec
from detectron2.modeling.anchor_generator import DefaultAnchorGenerator, RotatedAnchorGenerator
logger = logging.getLogger(__name__)
class Test... | 4,723 | 38.041322 | 95 | py |
NorCal | NorCal-main/tests/modeling/test_roi_heads.py | # Copyright (c) Facebook, Inc. and its affiliates.
import logging
import unittest
from copy import deepcopy
import torch
from torch import nn
from detectron2 import model_zoo
from detectron2.config import get_cfg
from detectron2.export.torchscript_patch import (
freeze_training_mode,
patch_builtin_len,
pat... | 13,989 | 42.179012 | 99 | py |
NorCal | NorCal-main/tests/structures/test_rotated_boxes.py | # Copyright (c) Facebook, Inc. and its affiliates.
from __future__ import absolute_import, division, print_function, unicode_literals
import logging
import math
import random
import unittest
import torch
from fvcore.common.benchmark import benchmark
from detectron2.layers.rotated_boxes import pairwise_iou_rotated
from... | 18,603 | 41.474886 | 100 | py |
NorCal | NorCal-main/tests/structures/test_boxes.py | # Copyright (c) Facebook, Inc. and its affiliates.
import json
import math
import numpy as np
import unittest
import torch
from detectron2.structures import Boxes, BoxMode, pairwise_ioa, pairwise_iou
from detectron2.utils.testing import reload_script_model
class TestBoxMode(unittest.TestCase):
def _convert_xy_to... | 8,354 | 36.299107 | 100 | py |
NorCal | NorCal-main/tests/structures/test_imagelist.py | # Copyright (c) Facebook, Inc. and its affiliates.
import unittest
from typing import List, Sequence, Tuple
import torch
from detectron2.structures import ImageList
class TestImageList(unittest.TestCase):
def test_imagelist_padding_tracing(self):
# test that the trace does not contain hard-coded constan... | 2,976 | 38.171053 | 86 | py |
NorCal | NorCal-main/tests/structures/test_masks.py | # Copyright (c) Facebook, Inc. and its affiliates.
import unittest
import torch
from detectron2.structures.masks import BitMasks, PolygonMasks, polygons_to_bitmask
class TestBitMask(unittest.TestCase):
def test_get_bounding_box(self):
masks = torch.tensor(
[
[
... | 2,003 | 36.111111 | 96 | py |
NorCal | NorCal-main/tests/structures/test_keypoints.py | # Copyright (c) Facebook, Inc. and its affiliates.
import unittest
import torch
from detectron2.structures.keypoints import Keypoints
class TestKeypoints(unittest.TestCase):
def test_cat_keypoints(self):
keypoints1 = Keypoints(torch.rand(2, 21, 3))
keypoints2 = Keypoints(torch.rand(4, 21, 3))
... | 610 | 29.55 | 88 | py |
NorCal | NorCal-main/tests/structures/test_instances.py | # Copyright (c) Facebook, Inc. and its affiliates.
import unittest
import torch
from torch import Tensor
from detectron2.export.torchscript import patch_instances
from detectron2.structures import Boxes, Instances
from detectron2.utils.testing import convert_scripted_instances
class TestInstances(unittest.TestCase):... | 8,466 | 37.486364 | 98 | py |
NorCal | NorCal-main/demo/predictor.py | # Copyright (c) Facebook, Inc. and its affiliates.
import atexit
import bisect
import multiprocessing as mp
from collections import deque
import cv2
import torch
from detectron2.data import MetadataCatalog
from detectron2.engine.defaults import DefaultPredictor
from detectron2.utils.video_visualizer import VideoVisual... | 7,844 | 34.497738 | 96 | py |
NorCal | NorCal-main/configs/common/optim.py | import torch
from detectron2.config import LazyCall as L
from detectron2.solver.build import get_default_optimizer_params
SGD = L(torch.optim.SGD)(
params=L(get_default_optimizer_params)(
# params.model is meant to be set to the model object, before instantiating
# the optimizer.
weight_de... | 396 | 23.8125 | 83 | py |
NorCal | NorCal-main/configs/new_baselines/mask_rcnn_R_50_FPN_100ep_LSJ.py | import detectron2.data.transforms as T
from detectron2.config.lazy import LazyCall as L
from detectron2.layers.batch_norm import NaiveSyncBatchNorm
from detectron2.solver import WarmupParamScheduler
from fvcore.common.param_scheduler import MultiStepParamScheduler
from ..common.data.coco import dataloader
from ..commo... | 2,515 | 33.465753 | 166 | py |
NorCal | NorCal-main/configs/Misc/torchvision_imagenet_R_50.py | """
An example config file to train a ImageNet classifier with detectron2.
Model and dataloader both come from torchvision.
This shows how to use detectron2 as a general engine for any new models and tasks.
To run, use the following command:
python tools/lazyconfig_train_net.py --config-file configs/Misc/torchvision_... | 4,497 | 28.788079 | 99 | py |
NorCal | NorCal-main/configs/Misc/mmdet_mask_rcnn_R_50_FPN_1x.py | # An example config to train a mmdetection model using detectron2.
from ..common.data.coco import dataloader
from ..common.coco_schedule import lr_multiplier_1x as lr_multiplier
from ..common.optim import SGD as optimizer
from ..common.train import train
from detectron2.modeling.mmdet_wrapper import MMDetDetector
fro... | 5,304 | 33.901316 | 96 | py |
NorCal | NorCal-main/docs/conf.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
# flake8: noqa
# Configuration file for the Sphinx documentation builder.
#
# This file does only contain a selection of the most common options. For a
# full list see the documentation:
# http://www.sphinx-doc.org/en/master/config
# -- Path ... | 12,811 | 32.364583 | 140 | py |
NorCal | NorCal-main/dev/packaging/gen_install_table.py | #!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates.
# -*- coding: utf-8 -*-
import argparse
template = """<details><summary> install </summary><pre><code>\
python -m pip install detectron2{d2_version} -f \\
https://dl.fbaipublicfiles.com/detectron2/wheels/{cuda}/torch{torch}/index.html
</code><... | 1,960 | 31.147541 | 95 | py |
gan-vae-pretrained-pytorch | gan-vae-pretrained-pytorch-master/mnist_classifier/lenet.py | import torch.nn as nn
from collections import OrderedDict
class LeNet5(nn.Module):
"""
Input - 1x32x32
C1 - 6@28x28 (5x5 kernel)
tanh
S2 - 6@14x14 (2x2 kernel, stride 2) Subsampling
C3 - 16@10x10 (5x5 kernel, complicated shit)
tanh
S4 - 16@5x5 (2x2 kernel, stride 2) Subsampling
C5 ... | 1,305 | 28.022222 | 63 | py |
gan-vae-pretrained-pytorch | gan-vae-pretrained-pytorch-master/mnist_classifier/train.py | from lenet import LeNet5
import torch
import torch.nn as nn
import torch.optim as optim
from torchvision.datasets.mnist import MNIST
import torchvision.transforms as transforms
from torch.utils.data import DataLoader
import random
data_root = '/scratch/users/vision/yu_dl/raaz.rsk/data/mnist'
random.seed(13)
torch.manu... | 2,445 | 27.114943 | 101 | py |
gan-vae-pretrained-pytorch | gan-vae-pretrained-pytorch-master/cifar10_dcgan/dcgan.py | # https://raw.githubusercontent.com/pytorch/examples/master/dcgan/main.py
from __future__ import print_function
import argparse
import os
import random
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.optim as optim
import torch.utils.data
import torchvision... | 9,094 | 38.543478 | 163 | py |
gan-vae-pretrained-pytorch | gan-vae-pretrained-pytorch-master/mnist_gan_mlp/gan_mnist.py | # https://github.com/BeierZhu/GAN-MNIST-Pytorch/blob/master/main.py
import os
import torch
import torchvision
import torch.nn as nn
from torchvision import transforms
from torchvision.utils import save_image
from torch.autograd import Variable
import matplotlib.pyplot as plt
import pylab
import numpy as np
# Hyper-par... | 7,722 | 37.615 | 115 | py |
gan-vae-pretrained-pytorch | gan-vae-pretrained-pytorch-master/cifar100_dcgan_grayscale/dcgan.py | # https://raw.githubusercontent.com/pytorch/examples/master/dcgan/main.py
from __future__ import print_function
import argparse
import os
import random
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.optim as optim
import torch.utils.data
import torchvision... | 12,466 | 39.74183 | 168 | py |
gan-vae-pretrained-pytorch | gan-vae-pretrained-pytorch-master/mnist_vae/vae.py | from __future__ import print_function
import argparse
import torch
import torch.utils.data
from torch import nn, optim
from torch.nn import functional as F
from torchvision import datasets, transforms
from torchvision.utils import save_image
import os
from os.path import join as oj
parser = argparse.ArgumentParser(des... | 5,158 | 36.115108 | 89 | py |
gan-vae-pretrained-pytorch | gan-vae-pretrained-pytorch-master/mnist_dcgan/dcgan.py | # https://raw.githubusercontent.com/pytorch/examples/master/dcgan/main.py
from __future__ import print_function
import argparse
import os
import random
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.optim as optim
import torch.utils.data
import torchvision... | 8,856 | 38.540179 | 153 | py |
gan-vae-pretrained-pytorch | gan-vae-pretrained-pytorch-master/cifar10_classifier/model.py | import torch.nn as nn
import torch.utils.model_zoo as model_zoo
from IPython import embed
from collections import OrderedDict
model_urls = {
'cifar10': 'http://ml.cs.tsinghua.edu.cn/~chenxi/pytorch-models/cifar10-d875770b.pth',
'cifar100': 'http://ml.cs.tsinghua.edu.cn/~chenxi/pytorch-models/cifar100-3a55a987.... | 2,764 | 38.5 | 122 | py |
gan-vae-pretrained-pytorch | gan-vae-pretrained-pytorch-master/cifar10_classifier/train.py | import argparse
import os
import time
from utee import misc
import torch
import torch.nn.functional as F
import torch.optim as optim
from torch.autograd import Variable
import dataset
import model
from IPython import embed
parser = argparse.ArgumentParser(description='PyTorch CIFAR-X Example')
parser.add_argument('... | 5,776 | 42.43609 | 125 | py |
scanninglaw | scanninglaw-main/docs/conf.py | # -*- coding: utf-8 -*-
#
# dustmaps documentation build configuration file, created by
# sphinx-quickstart on Fri Oct 14 17:20:58 2016.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# ... | 11,378 | 27.4475 | 80 | py |
global-local-self-distillation | global-local-self-distillation-main/main_global_local_self_distillation.py | # THIS IS A TEST WRITTEN FROM LOCAL NICKELINE
# Modified by Chunyuan Li (chunyl@microsoft.com)
#
# Copyright (c) Facebook, Inc. and its affiliates.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the Licen... | 29,284 | 42.708955 | 186 | py |
global-local-self-distillation | global-local-self-distillation-main/utils.py |
# Modified by Chunyuan Li (chunyl@microsoft.com)
#
# Copyright (c) Facebook, Inc. and its affiliates.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses... | 22,703 | 31.62069 | 115 | py |
global-local-self-distillation | global-local-self-distillation-main/models/swin_transformer.py | # --------------------------------------------------------
# Modified by Chunyuan Li (chunyl@microsoft.com)
# Swin Transformer
# Copyright (c) 2021 Microsoft
# Written by Ze Liu
# --------------------------------------------------------
import os
import logging
import torch
import torch.nn as nn
import torch.nn.functi... | 38,876 | 38.629969 | 119 | py |
global-local-self-distillation | global-local-self-distillation-main/models/vision_longformer.py | import math
from functools import partial
import logging
import torch
from torch import nn
from timm.models.layers import DropPath, trunc_normal_, to_2tuple
from layers import (
Long2DSCSelfAttention,
FastAttention,
PerformerSelfAttention,
LinformerSelfAttention,
SRSelfAttention
)
from layers.se_lay... | 31,125 | 37.665839 | 195 | py |
global-local-self-distillation | global-local-self-distillation-main/models/vision_transformer.py | # Modified by Chunyuan Li (chunyl@microsoft.com)
#
# Copyright (c) Facebook, Inc. and its affiliates.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/... | 15,838 | 36.711905 | 124 | py |
global-local-self-distillation | global-local-self-distillation-main/models/cvt_v4_transformer.py | import logging
import os
import torch
import torch.nn.functional as F
from functools import partial
from torch import nn, einsum
import collections.abc as container_abcs
import numpy as np
from einops import rearrange, repeat
from einops.layers.torch import Rearrange
from timm.models.layers import DropPath, trunc_norm... | 22,590 | 30.908192 | 104 | py |
global-local-self-distillation | global-local-self-distillation-main/datasets/zipdata.py | import os.path as op
from zipfile import ZipFile, BadZipFile
import torch.utils.data as data
from PIL import Image
from io import BytesIO
import multiprocessing
_VALID_IMAGE_TYPES = ['.jpg', '.jpeg', '.tiff', '.bmp', '.png']
class ZipData(data.Dataset):
_IGNORE_ATTRS = {'_zip_file'}
def __init__(self, path, ... | 3,451 | 36.11828 | 110 | py |
global-local-self-distillation | global-local-self-distillation-main/datasets/comm.py | """
This file contains primitives for multi-gpu communication.
This is useful when doing distributed training.
"""
import pickle
import torch
import torch.distributed as dist
class Comm(object):
def __init__(self, local_rank=0):
self.local_rank = 0
@property
def world_size(self):
if not... | 3,973 | 27.589928 | 84 | py |
global-local-self-distillation | global-local-self-distillation-main/datasets/tsv.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
from io import BytesIO
import json
import logging
import base64
import random
from typing import Callable, List, Tuple, Union
from PIL import Image
from PIL import ImageFile
import torch.utils.data as... | 8,447 | 33.622951 | 107 | py |
global-local-self-distillation | global-local-self-distillation-main/datasets/tsv_openimage.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from io import BytesIO
import json
import logging
import base64
import numpy as np
from PIL import Image
import torch.utils.data as data
from .tsv_file import TSVFile
def is_json(string):
try:
j... | 3,472 | 25.51145 | 77 | py |
global-local-self-distillation | global-local-self-distillation-main/datasets/build.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import logging
import os
import torch
from torchvision import datasets, transforms
from torch.utils.data import Dataset, DataLoader
from PIL import Image
import utils
from .tsv import TSVDataset
from .tsv_openi... | 12,779 | 34.303867 | 131 | py |
global-local-self-distillation | global-local-self-distillation-main/datasets/samplers/ra_sampler.py | # Copyright (c) 2015-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the CC-by-NC license found in the
# LICENSE file in the root directory of this source tree.
#
import torch
import torch.distributed as dist
import math
class RASampler(torch.utils.data.Sampler):
"""Sampler t... | 2,425 | 36.90625 | 103 | py |
global-local-self-distillation | global-local-self-distillation-main/datasets/samplers/class_aware_sampler.py | """
Inspired and partially adopted from
https://github.com/zhmiao/OpenLongTailRecognition-OLTR/blob/master/data/ClassAwareSampler.py
"""
import math
import random
import logging
import torch.distributed as dist
from torch.utils.data.sampler import Sampler
class CycleIter:
def __init__(self, data, shuffle=Tru... | 7,973 | 38.475248 | 118 | py |
global-local-self-distillation | global-local-self-distillation-main/datasets/samplers/distributed_chunk_sampler.py | import math
import torch
from torch.utils.data import Sampler
import torch.distributed as dist
import random
import logging
import threading
def pre_fetch(fn_fetch, index):
logging.debug(f'Pre-loading file index: {index} ...')
fn_fetch(index)
logging.debug(f'Pre-loading ended file index: {index} ...')
c... | 7,686 | 34.753488 | 116 | py |
global-local-self-distillation | global-local-self-distillation-main/layers/batch_norm.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import torch
from torch import nn
from torch.nn import functional as F
from .wrappers import BatchNorm2d
class FrozenBatchNorm2d(nn.Module):
"""
BatchNorm2d where the batch statistics and the affine parameters are fixed.
... | 5,686 | 37.687075 | 99 | py |
global-local-self-distillation | global-local-self-distillation-main/layers/srformer.py | import torch
from torch import nn
class SRSelfAttention(nn.Module):
def __init__(self, dim, rratio=2, num_heads=8, qkv_bias=False,
qk_scale=None, attn_drop=0., proj_drop=0.):
super().__init__()
assert (dim % num_heads) == 0, 'dimension must be divisible by the number of heads'
... | 2,227 | 36.762712 | 91 | py |
global-local-self-distillation | global-local-self-distillation-main/layers/dropblock.py | import logging
import torch
class DropBlock(torch.nn.Module):
def __init__(self,
block_size=7,
keep_prob=0.9,
current_step=0.,
train_steps=1.):
super(DropBlock, self).__init__()
self.block_size = block_size
self.keep_prob... | 2,573 | 32.868421 | 83 | py |
global-local-self-distillation | global-local-self-distillation-main/layers/se_layer.py | from torch import nn
class SELayer(nn.Module):
def __init__(self, channel, reduction=16):
super(SELayer, self).__init__()
self.avg_pool = nn.AdaptiveAvgPool2d(1)
self.fc = nn.Sequential(
nn.Linear(channel, channel // reduction, bias=False),
nn.ReLU(inplace=True),
... | 2,216 | 30.225352 | 96 | py |
global-local-self-distillation | global-local-self-distillation-main/layers/shape_spec.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from collections import namedtuple
class ShapeSpec(namedtuple("_ShapeSpec", ["channels", "height", "width", "stride"])):
"""
A simple structure that contains basic shape specification about a tensor.
It is often... | 672 | 31.047619 | 85 | py |
global-local-self-distillation | global-local-self-distillation-main/layers/slidingchunk_2d.py |
from functools import lru_cache
import torch
from torch import einsum
from torch.cuda.amp import autocast
class SlidingChunk2D(torch.autograd.Function):
"""
Class to encapsulate for sliding chunk implementation of vision longformer
"""
mode_dict = {
1: (1, 1), # -1, -1
2: (1, 0), # ... | 14,929 | 39.79235 | 103 | py |
global-local-self-distillation | global-local-self-distillation-main/layers/dy_relu.py | import logging
import torch
import torch.functional as F
import torch.nn as nn
def _make_divisible(v, divisor, min_value=None):
if min_value is None:
min_value = divisor
new_v = max(min_value, int(v + divisor / 2) // divisor * divisor)
# Make sure that round down does not go down by more than 10%... | 5,522 | 31.110465 | 88 | py |
global-local-self-distillation | global-local-self-distillation-main/layers/linformer.py | # mainly modified from
# https://github.com/lucidrains/linformer/blob/master/linformer/linformer.py
import math
import torch
from torch import nn
def init_(tensor):
dim = tensor.shape[-1]
std = 1 / math.sqrt(dim)
tensor.uniform_(-std, std)
return tensor
class LinformerSelfAttention(nn.Module):
d... | 2,703 | 36.555556 | 121 | py |
global-local-self-distillation | global-local-self-distillation-main/layers/wrappers.py |
"""
Wrappers around on some nn functions, mainly to support empty tensors.
Ideally, add support directly in PyTorch to empty tensors in those functions.
These can be removed once https://github.com/pytorch/pytorch/issues/12013
is implemented
"""
import math
from typing import List
import torch
from torch.nn.modules... | 7,964 | 34.088106 | 97 | py |
global-local-self-distillation | global-local-self-distillation-main/layers/performer.py | # mainly modified from
# https://github.com/lucidrains/performer-pytorch/blob/main/performer_pytorch/performer_pytorch.py
import math
from scipy.stats import ortho_group
import torch
from torch import nn
from einops import rearrange, repeat
from functools import partial
# helpers
def exists(val):
return val is ... | 7,231 | 34.45098 | 111 | py |
global-local-self-distillation | global-local-self-distillation-main/layers/longformer2d.py |
import random
import torch
from torch import nn, einsum
import torch.nn.functional as F
from einops import rearrange
from timm.models.layers import trunc_normal_
from .slidingchunk_2d import slidingchunk_2d, mask_invalid_locations, slidingchunk_2dautograd
class Long2DSCSelfAttention(nn.Module):
def __init__(self... | 16,209 | 47.97281 | 154 | py |
global-local-self-distillation | global-local-self-distillation-main/layers/attention.py | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
def swish(x, inplace: bool = False):
"""
Swish - Described in: https://arxiv.org/abs/1710.05941
"""
return x.mul_(x.sigmoid()) if inplace else x.mul(x.sigmoid())
class Swish(nn.Module):
def __init__(self, inplace: bo... | 55,986 | 38.820057 | 117 | py |
global-local-self-distillation | global-local-self-distillation-main/layers/t2t.py | # adapted from https://github.com/yitu-opensource/T2T-ViT
import numpy as np
import torch
import torch.nn as nn
from timm.models.layers import DropPath
from .attention import AxialAttention
from .attention import Attention as QKVConvAttention
class Mlp(nn.Module):
def __init__(self, in_features, hidden_features=... | 20,001 | 40.497925 | 119 | py |
global-local-self-distillation | global-local-self-distillation-main/layers/blocks.py |
from torch import nn
# from .batch_norm import FrozenBatchNorm2d
class CNNBlockBase(nn.Module):
"""
A CNN block is assumed to have input channels, output channels and a stride.
The input and output of `forward()` method must be NCHW tensors.
The method can perform arbitrary computation but must matc... | 1,311 | 26.914894 | 82 | py |
global-local-self-distillation | global-local-self-distillation-main/my_utils/parser.py | import argparse
def bool_flag(s):
"""
Parse boolean arguments from the command line.
"""
FALSY_STRINGS = {"off", "false", "0"}
TRUTHY_STRINGS = {"on", "true", "1"}
if s.lower() in FALSY_STRINGS:
return False
elif s.lower() in TRUTHY_STRINGS:
return True
else:
ra... | 12,385 | 68.195531 | 243 | py |
arf_paper | arf_paper-master/generative_benchmark/5.2_Real_Data/grf.py | try:
exec(open("benchmark_individual.py").read())
except:
pass
exec(open("benchmark_individual.py").read())
import numpy as np
import torch
from os import path
import rpy2
import rpy2.robjects as robjects
import rpy2.robjects.packages as rpackages
from rpy2.robjects import pandas2ri
base = rpackages.import... | 3,618 | 38.336957 | 148 | py |
arf_paper | arf_paper-master/generative_benchmark/5.2_Real_Data/benchmark_individual.py | import time
import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sdgym.datasets import load_dataset
from sdgym.datasets import load_tables
from sklearn.metrics import f1_score, accuracy_score, r2_score
from sdv.metrics.tabular import BinaryDecisionTreeClassifier,BinaryAdaBoos... | 6,084 | 44.75188 | 216 | py |
arf_paper | arf_paper-master/generative_benchmark/5.3_Runtime/CTABGAN_runtime_main.py | # this is a special runtime_main.py script for CTABGAN
# basically the same code as runtime_main.py, but with different imports (because of environment issues)
# and some special adjustments for CTABGAN (e.g. write out every subset results as .csv)
import time
import pandas as pd
import numpy as np
from sdgym.datasets... | 5,637 | 43.046875 | 134 | py |
arf_paper | arf_paper-master/generative_benchmark/5.3_Runtime/CTABGAN_gpu_cpu.py | try:
exec(open("CTABGAN_runtime_main.py").read())
except:
pass
exec(open("CTABGAN_runtime_main.py").read())
import os
print(os.getcwd())
os.chdir("..")
os.chdir("./CTABGAN")
print(os.getcwd())
print(os.listdir())
import sys
print(sys.path)
sys.path.append("")
print(sys.path)
from model.ctabgan import CTABGAN... | 2,999 | 42.478261 | 156 | py |
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