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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Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/models/losses/dice_loss.py | """Modified from https://github.com/LikeLy-Journey/SegmenTron/blob/master/
segmentron/solver/loss.py (Apache-2.0 License)"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from ..builder import LOSSES
from .utils import get_class_weight, weighted_loss
@weighted_loss
def dice_loss(pred,
... | 4,239 | 34.333333 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/models/losses/lovasz_loss.py | """Modified from https://github.com/bermanmaxim/LovaszSoftmax/blob/master/pytor
ch/lovasz_losses.py Lovasz-Softmax and Jaccard hinge loss in PyTorch Maxim
Berman 2018 ESAT-PSI KU Leuven (MIT License)"""
import annotator.uniformer.mmcv as mmcv
import torch
import torch.nn as nn
import torch.nn.functional as F
from ..b... | 11,419 | 36.565789 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/models/losses/utils.py | import functools
import annotator.uniformer.mmcv as mmcv
import numpy as np
import torch.nn.functional as F
def get_class_weight(class_weight):
"""Get class weight for loss function.
Args:
class_weight (list[float] | str | None): If class_weight is a str,
take it as a file name and read ... | 3,718 | 29.483607 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/models/losses/accuracy.py | import torch.nn as nn
def accuracy(pred, target, topk=1, thresh=None):
"""Calculate accuracy according to the prediction and target.
Args:
pred (torch.Tensor): The model prediction, shape (N, num_class, ...)
target (torch.Tensor): The target of each prediction, shape (N, , ...)
topk (... | 2,970 | 36.607595 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/models/losses/cross_entropy_loss.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from ..builder import LOSSES
from .utils import get_class_weight, weight_reduce_loss
def cross_entropy(pred,
label,
weight=None,
class_weight=None,
reduction='mean',
... | 7,437 | 36.376884 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/models/backbones/hrnet.py | import torch.nn as nn
from annotator.uniformer.mmcv.cnn import (build_conv_layer, build_norm_layer, constant_init,
kaiming_init)
from annotator.uniformer.mmcv.runner import load_checkpoint
from annotator.uniformer.mmcv.utils.parrots_wrapper import _BatchNorm
from annotator.uniformer.mmseg.ops imp... | 21,226 | 37.178058 | 92 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/models/backbones/mobilenet_v2.py | import logging
import torch.nn as nn
from annotator.uniformer.mmcv.cnn import ConvModule, constant_init, kaiming_init
from annotator.uniformer.mmcv.runner import load_checkpoint
from torch.nn.modules.batchnorm import _BatchNorm
from ..builder import BACKBONES
from ..utils import InvertedResidual, make_divisible
@BA... | 6,981 | 37.574586 | 80 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/models/backbones/fast_scnn.py | import torch
import torch.nn as nn
from annotator.uniformer.mmcv.cnn import (ConvModule, DepthwiseSeparableConvModule, constant_init,
kaiming_init)
from torch.nn.modules.batchnorm import _BatchNorm
from annotator.uniformer.mmseg.models.decode_heads.psp_head import PPM
from annotator.uniformer.mms... | 14,436 | 37.396277 | 98 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/models/backbones/resnet.py | import torch.nn as nn
import torch.utils.checkpoint as cp
from annotator.uniformer.mmcv.cnn import (build_conv_layer, build_norm_layer, build_plugin_layer,
constant_init, kaiming_init)
from annotator.uniformer.mmcv.runner import load_checkpoint
from annotator.uniformer.mmcv.utils.parrots_wrapper i... | 24,310 | 34.28447 | 97 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/models/backbones/cgnet.py | import torch
import torch.nn as nn
import torch.utils.checkpoint as cp
from annotator.uniformer.mmcv.cnn import (ConvModule, build_conv_layer, build_norm_layer,
constant_init, kaiming_init)
from annotator.uniformer.mmcv.runner import load_checkpoint
from annotator.uniformer.mmcv.utils.parrots_wrap... | 13,183 | 34.826087 | 89 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/models/backbones/vit.py | """Modified from https://github.com/rwightman/pytorch-image-
models/blob/master/timm/models/vision_transformer.py."""
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint as cp
from annotator.uniformer.mmcv.cnn import (Conv2d, Linear, build_activation_layer, bui... | 18,085 | 38.317391 | 128 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/models/backbones/resnext.py | import math
from annotator.uniformer.mmcv.cnn import build_conv_layer, build_norm_layer
from ..builder import BACKBONES
from ..utils import ResLayer
from .resnet import Bottleneck as _Bottleneck
from .resnet import ResNet
class Bottleneck(_Bottleneck):
"""Bottleneck block for ResNeXt.
If style is "pytorch"... | 5,161 | 34.356164 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/models/backbones/mobilenet_v3.py | import logging
import annotator.uniformer.mmcv as mmcv
import torch.nn as nn
from annotator.uniformer.mmcv.cnn import ConvModule, constant_init, kaiming_init
from annotator.uniformer.mmcv.cnn.bricks import Conv2dAdaptivePadding
from annotator.uniformer.mmcv.runner import load_checkpoint
from torch.nn.modules.batchnorm... | 10,390 | 39.589844 | 80 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/models/backbones/unet.py | import torch.nn as nn
import torch.utils.checkpoint as cp
from annotator.uniformer.mmcv.cnn import (UPSAMPLE_LAYERS, ConvModule, build_activation_layer,
build_norm_layer, constant_init, kaiming_init)
from annotator.uniformer.mmcv.runner import load_checkpoint
from annotator.uniformer.mmcv.utils.pa... | 18,269 | 41.488372 | 94 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/models/backbones/resnest.py | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint as cp
from annotator.uniformer.mmcv.cnn import build_conv_layer, build_norm_layer
from ..builder import BACKBONES
from ..utils import ResLayer
from .resnet import Bottleneck as _Bottleneck
from .resnet import ... | 10,110 | 31.098413 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/models/backbones/uniformer.py | # --------------------------------------------------------
# UniFormer
# Copyright (c) 2022 SenseTime X-Lab
# Licensed under The MIT License [see LICENSE for details]
# Written by Kunchang Li
# --------------------------------------------------------
from collections import OrderedDict
import math
from functools impo... | 18,476 | 42.680851 | 145 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/datasets/custom.py | import os
import os.path as osp
from collections import OrderedDict
from functools import reduce
import annotator.uniformer.mmcv as mmcv
import numpy as np
from annotator.uniformer.mmcv.utils import print_log
from prettytable import PrettyTable
from torch.utils.data import Dataset
from annotator.uniformer.mmseg.core ... | 14,716 | 35.700748 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/datasets/dataset_wrappers.py | from torch.utils.data.dataset import ConcatDataset as _ConcatDataset
from .builder import DATASETS
@DATASETS.register_module()
class ConcatDataset(_ConcatDataset):
"""A wrapper of concatenated dataset.
Same as :obj:`torch.utils.data.dataset.ConcatDataset`, but
concat the group flag for image aspect rati... | 1,499 | 28.411765 | 78 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/datasets/builder.py | import copy
import platform
import random
from functools import partial
import numpy as np
from annotator.uniformer.mmcv.parallel import collate
from annotator.uniformer.mmcv.runner import get_dist_info
from annotator.uniformer.mmcv.utils import Registry, build_from_cfg
from annotator.uniformer.mmcv.utils.parrots_wrap... | 5,951 | 34.011765 | 85 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/datasets/pipelines/formating.py | from collections.abc import Sequence
import annotator.uniformer.mmcv as mmcv
import numpy as np
import torch
from annotator.uniformer.mmcv.parallel import DataContainer as DC
from ..builder import PIPELINES
def to_tensor(data):
"""Convert objects of various python types to :obj:`torch.Tensor`.
Supported ty... | 9,276 | 31.100346 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/ops/wrappers.py | import warnings
import torch.nn as nn
import torch.nn.functional as F
def resize(input,
size=None,
scale_factor=None,
mode='nearest',
align_corners=None,
warning=True):
if warning:
if size is not None and align_corners:
input_h, input_w =... | 1,827 | 34.843137 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmseg/ops/encoding.py | import torch
from torch import nn
from torch.nn import functional as F
class Encoding(nn.Module):
"""Encoding Layer: a learnable residual encoder.
Input is of shape (batch_size, channels, height, width).
Output is of shape (batch_size, num_codes, channels).
Args:
channels: dimension of the ... | 2,788 | 36.186667 | 78 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/ccnet_r50-d8.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='EncoderDecoder',
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 2, 4),
strides=... | 1,258 | 26.977778 | 74 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/ann_r50-d8.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='EncoderDecoder',
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 2, 4),
strides=... | 1,346 | 27.659574 | 74 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/gcnet_r50-d8.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='EncoderDecoder',
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 2, 4),
strides=... | 1,326 | 27.234043 | 74 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/encnet_r50-d8.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='EncoderDecoder',
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 2, 4),
strides=... | 1,435 | 28.306122 | 74 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/danet_r50-d8.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='EncoderDecoder',
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 2, 4),
strides=... | 1,261 | 27.044444 | 74 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/dnl_r50-d8.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='EncoderDecoder',
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 2, 4),
strides=... | 1,316 | 27.021277 | 74 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/pspnet_r50-d8.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='EncoderDecoder',
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 2, 4),
strides=... | 1,271 | 27.266667 | 74 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/upernet_r50.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='EncoderDecoder',
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 1, 1),
strides=... | 1,301 | 27.933333 | 74 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/apcnet_r50-d8.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='EncoderDecoder',
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 2, 4),
strides=... | 1,302 | 27.955556 | 74 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/psanet_r50-d8.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='EncoderDecoder',
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 2, 4),
strides=... | 1,406 | 27.14 | 74 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/deeplabv3plus_r50-d8.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='EncoderDecoder',
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 2, 4),
strides=... | 1,343 | 27.595745 | 74 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/emanet_r50-d8.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='EncoderDecoder',
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 2, 4),
strides=... | 1,329 | 26.708333 | 74 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/dmnet_r50-d8.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='EncoderDecoder',
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 2, 4),
strides=... | 1,302 | 27.955556 | 74 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/fpn_r50.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='EncoderDecoder',
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 1, 1),
strides=... | 1,056 | 27.567568 | 74 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/deeplabv3_r50-d8.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='EncoderDecoder',
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 2, 4),
strides=... | 1,273 | 27.311111 | 74 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/pointrend_r50.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='CascadeEncoderDecoder',
num_stages=2,
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1... | 1,704 | 28.912281 | 78 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/ocrnet_r50-d8.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='CascadeEncoderDecoder',
num_stages=2,
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1... | 1,385 | 27.875 | 78 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/nonlocal_r50-d8.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='EncoderDecoder',
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 2, 4),
strides=... | 1,315 | 27 | 74 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/configs/_base_/models/fcn_r50-d8.py | # model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='EncoderDecoder',
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 2, 4),
strides=... | 1,285 | 26.956522 | 74 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/image/misc.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import annotator.uniformer.mmcv as mmcv
try:
import torch
except ImportError:
torch = None
def tensor2imgs(tensor, mean=(0, 0, 0), std=(1, 1, 1), to_rgb=True):
"""Convert tensor to 3-channel images.
Args:
tensor (torch.Tenso... | 1,410 | 30.355556 | 77 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/resnet.py | # Copyright (c) OpenMMLab. All rights reserved.
import logging
import torch.nn as nn
import torch.utils.checkpoint as cp
from .utils import constant_init, kaiming_init
def conv3x3(in_planes, out_planes, stride=1, dilation=1):
"""3x3 convolution with padding."""
return nn.Conv2d(
in_planes,
o... | 9,955 | 30.40694 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/vgg.py | # Copyright (c) OpenMMLab. All rights reserved.
import logging
import torch.nn as nn
from .utils import constant_init, kaiming_init, normal_init
def conv3x3(in_planes, out_planes, dilation=1):
"""3x3 convolution with padding."""
return nn.Conv2d(
in_planes,
out_planes,
kernel_size=3,... | 6,053 | 33.397727 | 77 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .alexnet import AlexNet
# yapf: disable
from .bricks import (ACTIVATION_LAYERS, CONV_LAYERS, NORM_LAYERS,
PADDING_LAYERS, PLUGIN_LAYERS, UPSAMPLE_LAYERS,
ContextBlock, Conv2d, Conv3d, ConvAWS2d, ConvModule,
... | 2,438 | 57.071429 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/alexnet.py | # Copyright (c) OpenMMLab. All rights reserved.
import logging
import torch.nn as nn
class AlexNet(nn.Module):
"""AlexNet backbone.
Args:
num_classes (int): number of classes for classification.
"""
def __init__(self, num_classes=-1):
super(AlexNet, self).__init__()
self.num... | 1,990 | 31.112903 | 74 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/activation.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
import torch.nn.functional as F
from annotator.uniformer.mmcv.utils import TORCH_VERSION, build_from_cfg, digit_version
from .registry import ACTIVATION_LAYERS
for module in [
nn.ReLU, nn.LeakyReLU, nn.PReLU, nn.RReLU, nn.ReLU6... | 2,508 | 25.978495 | 87 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/hsigmoid.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from .registry import ACTIVATION_LAYERS
@ACTIVATION_LAYERS.register_module()
class HSigmoid(nn.Module):
"""Hard Sigmoid Module. Apply the hard sigmoid function:
Hsigmoid(x) = min(max((x + bias) / divisor, min_value), max_value)
Default... | 1,097 | 30.371429 | 76 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/depthwise_separable_conv_module.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from .conv_module import ConvModule
class DepthwiseSeparableConvModule(nn.Module):
"""Depthwise separable convolution module.
See https://arxiv.org/pdf/1704.04861.pdf for details.
This module can replace a ConvModule with the conv bl... | 4,142 | 41.71134 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/non_local.py | # Copyright (c) OpenMMLab. All rights reserved.
from abc import ABCMeta
import torch
import torch.nn as nn
from ..utils import constant_init, normal_init
from .conv_module import ConvModule
from .registry import PLUGIN_LAYERS
class _NonLocalNd(nn.Module, metaclass=ABCMeta):
"""Basic Non-local module.
This ... | 11,012 | 34.872964 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/norm.py | # Copyright (c) OpenMMLab. All rights reserved.
import inspect
import torch.nn as nn
from annotator.uniformer.mmcv.utils import is_tuple_of
from annotator.uniformer.mmcv.utils.parrots_wrapper import SyncBatchNorm, _BatchNorm, _InstanceNorm
from .registry import NORM_LAYERS
NORM_LAYERS.register_module('BN', module=nn... | 5,154 | 34.551724 | 99 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/conv2d_adaptive_padding.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
from torch import nn
from torch.nn import functional as F
from .registry import CONV_LAYERS
@CONV_LAYERS.register_module()
class Conv2dAdaptivePadding(nn.Conv2d):
"""Implementation of 2D convolution in tensorflow with `padding` as "same",
which app... | 2,514 | 38.920635 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/scale.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
class Scale(nn.Module):
"""A learnable scale parameter.
This layer scales the input by a learnable factor. It multiplies a
learnable scale parameter of shape (1,) with input of any shape.
Args:
scale (float): ... | 577 | 25.272727 | 73 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/conv_ws.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
import torch.nn.functional as F
from .registry import CONV_LAYERS
def conv_ws_2d(input,
weight,
bias=None,
stride=1,
padding=0,
dilation=1,
grou... | 5,417 | 35.362416 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/conv_module.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import torch.nn as nn
from annotator.uniformer.mmcv.utils import _BatchNorm, _InstanceNorm
from ..utils import constant_init, kaiming_init
from .activation import build_activation_layer
from .conv import build_conv_layer
from .norm import build_norm_laye... | 8,760 | 41.323671 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/context_block.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from torch import nn
from ..utils import constant_init, kaiming_init
from .registry import PLUGIN_LAYERS
def last_zero_init(m):
if isinstance(m, nn.Sequential):
constant_init(m[-1], val=0)
else:
constant_init(m, val=0)
@PLUGIN_LAY... | 4,681 | 36.15873 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/hswish.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from .registry import ACTIVATION_LAYERS
@ACTIVATION_LAYERS.register_module()
class HSwish(nn.Module):
"""Hard Swish Module.
This module applies the hard swish function:
.. math::
Hswish(x) = x * ReLU6(x + 3) / 6
Args:
... | 651 | 20.733333 | 65 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/wrappers.py | # Copyright (c) OpenMMLab. All rights reserved.
r"""Modified from https://github.com/facebookresearch/detectron2/blob/master/detectron2/layers/wrappers.py # noqa: E501
Wrap some nn modules to support empty tensor input. Currently, these wrappers
are mainly used in mask heads like fcn_mask_head and maskiou_heads since... | 6,961 | 37.464088 | 120 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/transformer.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import warnings
import torch
import torch.nn as nn
from annotator.uniformer.mmcv import ConfigDict, deprecated_api_warning
from annotator.uniformer.mmcv.cnn import Linear, build_activation_layer, build_norm_layer
from annotator.uniformer.mmcv.runner.base_mod... | 24,637 | 40.338926 | 129 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/swish.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from .registry import ACTIVATION_LAYERS
@ACTIVATION_LAYERS.register_module()
class Swish(nn.Module):
"""Swish Module.
This module applies the swish function:
.. math::
Swish(x) = x * Sigmoid(x)
Returns:
... | 485 | 17.692308 | 47 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/conv.py | # Copyright (c) OpenMMLab. All rights reserved.
from torch import nn
from .registry import CONV_LAYERS
CONV_LAYERS.register_module('Conv1d', module=nn.Conv1d)
CONV_LAYERS.register_module('Conv2d', module=nn.Conv2d)
CONV_LAYERS.register_module('Conv3d', module=nn.Conv3d)
CONV_LAYERS.register_module('Conv', module=nn.C... | 1,446 | 31.155556 | 78 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/upsample.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
import torch.nn.functional as F
from ..utils import xavier_init
from .registry import UPSAMPLE_LAYERS
UPSAMPLE_LAYERS.register_module('nearest', module=nn.Upsample)
UPSAMPLE_LAYERS.register_module('bilinear', module=nn.Upsample)
@UPSAMPLE_LAYERS.... | 2,880 | 32.894118 | 76 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/generalized_attention.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from ..utils import kaiming_init
from .registry import PLUGIN_LAYERS
@PLUGIN_LAYERS.register_module()
class GeneralizedAttention(nn.Module):
"""GeneralizedAttention m... | 15,999 | 37.74092 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/padding.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from .registry import PADDING_LAYERS
PADDING_LAYERS.register_module('zero', module=nn.ZeroPad2d)
PADDING_LAYERS.register_module('reflect', module=nn.ReflectionPad2d)
PADDING_LAYERS.register_module('replicate', module=nn.ReplicationPad2d)
def buil... | 1,127 | 29.486486 | 75 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/bricks/drop.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from annotator.uniformer.mmcv import build_from_cfg
from .registry import DROPOUT_LAYERS
def drop_path(x, drop_prob=0., training=False):
"""Drop paths (Stochastic Depth) per sample (when applied in main path of
residual blocks... | 2,172 | 31.924242 | 140 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/utils/sync_bn.py | import torch
import annotator.uniformer.mmcv as mmcv
class _BatchNormXd(torch.nn.modules.batchnorm._BatchNorm):
"""A general BatchNorm layer without input dimension check.
Reproduced from @kapily's work:
(https://github.com/pytorch/pytorch/issues/41081#issuecomment-783961547)
The only difference bet... | 2,327 | 37.8 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/utils/weight_init.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import math
import warnings
import numpy as np
import torch
import torch.nn as nn
from torch import Tensor
from annotator.uniformer.mmcv.utils import Registry, build_from_cfg, get_logger, print_log
INITIALIZERS = Registry('initializer')
def update_init_in... | 26,006 | 36.966423 | 99 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/utils/fuse_conv_bn.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
def _fuse_conv_bn(conv, bn):
"""Fuse conv and bn into one module.
Args:
conv (nn.Module): Conv to be fused.
bn (nn.Module): BN to be fused.
Returns:
nn.Module: Fused module.
"""
conv_w = co... | 1,881 | 30.366667 | 77 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/utils/flops_counter.py | # Modified from flops-counter.pytorch by Vladislav Sovrasov
# original repo: https://github.com/sovrasov/flops-counter.pytorch
# MIT License
# Copyright (c) 2018 Vladislav Sovrasov
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (th... | 22,104 | 35.841667 | 128 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/cnn/utils/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .flops_counter import get_model_complexity_info
from .fuse_conv_bn import fuse_conv_bn
from .sync_bn import revert_sync_batchnorm
from .weight_init import (INITIALIZERS, Caffe2XavierInit, ConstantInit,
KaimingInit, NormalInit, PretrainedInit... | 1,023 | 50.2 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/parallel/data_parallel.py | # Copyright (c) OpenMMLab. All rights reserved.
from itertools import chain
from torch.nn.parallel import DataParallel
from .scatter_gather import scatter_kwargs
class MMDataParallel(DataParallel):
"""The DataParallel module that supports DataContainer.
MMDataParallel has two main differences with PyTorch ... | 3,912 | 42.477778 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/parallel/_functions.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from torch.nn.parallel._functions import _get_stream
def scatter(input, devices, streams=None):
"""Scatters tensor across multiple GPUs."""
if streams is None:
streams = [None] * len(devices)
if isinstance(input, list):
chunk_si... | 2,830 | 34.3875 | 76 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/parallel/registry.py | # Copyright (c) OpenMMLab. All rights reserved.
from torch.nn.parallel import DataParallel, DistributedDataParallel
from annotator.uniformer.mmcv.utils import Registry
MODULE_WRAPPERS = Registry('module wrapper')
MODULE_WRAPPERS.register_module(module=DataParallel)
MODULE_WRAPPERS.register_module(module=DistributedDa... | 332 | 36 | 67 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/parallel/data_container.py | # Copyright (c) OpenMMLab. All rights reserved.
import functools
import torch
def assert_tensor_type(func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
if not isinstance(args[0].data, torch.Tensor):
raise AttributeError(
f'{args[0].__class__.__name__} has no attr... | 2,365 | 25.288889 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/parallel/distributed_deprecated.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.distributed as dist
import torch.nn as nn
from torch._utils import (_flatten_dense_tensors, _take_tensors,
_unflatten_dense_tensors)
from annotator.uniformer.mmcv.utils import TORCH_VERSION, digit_version
from .registry... | 2,837 | 38.971831 | 78 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/parallel/scatter_gather.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from torch.nn.parallel._functions import Scatter as OrigScatter
from ._functions import Scatter
from .data_container import DataContainer
def scatter(inputs, target_gpus, dim=0):
"""Scatter inputs to target gpus.
The only difference from original ... | 2,307 | 37.466667 | 78 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/parallel/distributed.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from torch.nn.parallel.distributed import (DistributedDataParallel,
_find_tensors)
from annotator.uniformer.mmcv import print_log
from annotator.uniformer.mmcv.utils import TORCH_VERSION, digit_version
from .scatter... | 4,857 | 41.99115 | 78 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/parallel/collate.py | # Copyright (c) OpenMMLab. All rights reserved.
from collections.abc import Mapping, Sequence
import torch
import torch.nn.functional as F
from torch.utils.data.dataloader import default_collate
from .data_container import DataContainer
def collate(batch, samples_per_gpu=1):
"""Puts each data field into a tenso... | 3,665 | 42.129412 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/engine/test.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import pickle
import shutil
import tempfile
import time
import torch
import torch.distributed as dist
import annotator.uniformer.mmcv as mmcv
from annotator.uniformer.mmcv.runner import get_dist_info
def single_gpu_test(model, data_loader):
"... | 7,196 | 34.453202 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/checkpoint.py | # Copyright (c) OpenMMLab. All rights reserved.
import io
import os
import os.path as osp
import pkgutil
import re
import time
import warnings
from collections import OrderedDict
from importlib import import_module
from tempfile import TemporaryDirectory
import torch
import torchvision
from torch.optim import Optimize... | 25,136 | 34.504237 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/dist_utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import functools
import os
import subprocess
from collections import OrderedDict
import torch
import torch.multiprocessing as mp
from torch import distributed as dist
from torch._utils import (_flatten_dense_tensors, _take_tensors,
_unflatten_de... | 5,395 | 31.70303 | 78 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import os
import random
import sys
import time
import warnings
from getpass import getuser
from socket import gethostname
import numpy as np
import torch
import annotator.uniformer.mmcv as mmcv
def get_host_info():
"""Get hostname and username.
Return empty s... | 2,936 | 30.244681 | 77 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/iter_based_runner.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import platform
import shutil
import time
import warnings
import torch
from torch.optim import Optimizer
import annotator.uniformer.mmcv as mmcv
from .base_runner import BaseRunner
from .builder import RUNNERS
from .checkpoint import save_checkpoin... | 11,062 | 39.375912 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/base_runner.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import logging
import os.path as osp
import warnings
from abc import ABCMeta, abstractmethod
import torch
from torch.optim import Optimizer
import annotator.uniformer.mmcv as mmcv
from ..parallel import is_module_wrapper
from .checkpoint import load_checkpoi... | 20,846 | 37.392265 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/fp16_utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import functools
import warnings
from collections import abc
from inspect import getfullargspec
import numpy as np
import torch
import torch.nn as nn
from annotator.uniformer.mmcv.utils import TORCH_VERSION, digit_version
from .dist_utils import allreduce_grads as _allr... | 15,784 | 37.406326 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/base_module.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import warnings
from abc import ABCMeta
from collections import defaultdict
from logging import FileHandler
import torch.nn as nn
from annotator.uniformer.mmcv.runner.dist_utils import master_only
from annotator.uniformer.mmcv.utils.logging import get_logger... | 7,502 | 37.280612 | 92 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/epoch_based_runner.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import platform
import shutil
import time
import warnings
import torch
import annotator.uniformer.mmcv as mmcv
from .base_runner import BaseRunner
from .builder import RUNNERS
from .checkpoint import save_checkpoint
from .utils import get_host_info... | 7,565 | 39.244681 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/hooks/memory.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from .hook import HOOKS, Hook
@HOOKS.register_module()
class EmptyCacheHook(Hook):
def __init__(self, before_epoch=False, after_epoch=True, after_iter=False):
self._before_epoch = before_epoch
self._after_epoch = after_epoch
se... | 657 | 24.307692 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/hooks/sampler_seed.py | # Copyright (c) OpenMMLab. All rights reserved.
from .hook import HOOKS, Hook
@HOOKS.register_module()
class DistSamplerSeedHook(Hook):
"""Data-loading sampler for distributed training.
When distributed training, it is only useful in conjunction with
:obj:`EpochBasedRunner`, while :obj:`IterBasedRunner` ... | 847 | 39.380952 | 76 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/hooks/lr_updater.py | # Copyright (c) OpenMMLab. All rights reserved.
import numbers
from math import cos, pi
import annotator.uniformer.mmcv as mmcv
from .hook import HOOKS, Hook
class LrUpdaterHook(Hook):
"""LR Scheduler in MMCV.
Args:
by_epoch (bool): LR changes epoch by epoch
warmup (string): Type of warmup u... | 26,034 | 37.800298 | 108 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/hooks/evaluation.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import warnings
from math import inf
import torch.distributed as dist
from torch.nn.modules.batchnorm import _BatchNorm
from torch.utils.data import DataLoader
from annotator.uniformer.mmcv.fileio import FileClient
from annotator.uniformer.mmcv.uti... | 22,448 | 43.017647 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/hooks/profiler.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
from typing import Callable, List, Optional, Union
import torch
from ..dist_utils import master_only
from .hook import HOOKS, Hook
@HOOKS.register_module()
class ProfilerHook(Hook):
"""Profiler to analyze performance during training.
PyTorch P... | 8,041 | 43.430939 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/hooks/optimizer.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
from collections import defaultdict
from itertools import chain
from torch.nn.utils import clip_grad
from annotator.uniformer.mmcv.utils import TORCH_VERSION, _BatchNorm, digit_version
from ..dist_utils import allreduce_grads
from ..fp16_utils import LossSca... | 21,652 | 41.540275 | 83 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/hooks/logger/base.py | # Copyright (c) OpenMMLab. All rights reserved.
import numbers
from abc import ABCMeta, abstractmethod
import numpy as np
import torch
from ..hook import Hook
class LoggerHook(Hook):
"""Base class for logger hooks.
Args:
interval (int): Logging interval (every k iterations).
ignore_last (bo... | 5,451 | 31.646707 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/hooks/logger/pavi.py | # Copyright (c) OpenMMLab. All rights reserved.
import json
import os
import os.path as osp
import torch
import yaml
import annotator.uniformer.mmcv as mmcv
from ....parallel.utils import is_module_wrapper
from ...dist_utils import master_only
from ..hook import HOOKS
from .base import LoggerHook
@HOOKS.register_mo... | 4,378 | 36.110169 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/hooks/logger/mlflow.py | # Copyright (c) OpenMMLab. All rights reserved.
from ...dist_utils import master_only
from ..hook import HOOKS
from .base import LoggerHook
@HOOKS.register_module()
class MlflowLoggerHook(LoggerHook):
def __init__(self,
exp_name=None,
tags=None,
log_model=True,
... | 2,838 | 34.936709 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/hooks/logger/tensorboard.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
from annotator.uniformer.mmcv.utils import TORCH_VERSION, digit_version
from ...dist_utils import master_only
from ..hook import HOOKS
from .base import LoggerHook
@HOOKS.register_module()
class TensorboardLoggerHook(LoggerHook):
def __init__... | 2,077 | 34.827586 | 77 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/hooks/logger/text.py | # Copyright (c) OpenMMLab. All rights reserved.
import datetime
import os
import os.path as osp
from collections import OrderedDict
import torch
import torch.distributed as dist
import annotator.uniformer.mmcv as mmcv
from annotator.uniformer.mmcv.fileio.file_client import FileClient
from annotator.uniformer.mmcv.uti... | 10,684 | 40.575875 | 79 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/optimizer/default_constructor.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import torch
from torch.nn import GroupNorm, LayerNorm
from annotator.uniformer.mmcv.utils import _BatchNorm, _InstanceNorm, build_from_cfg, is_list_of
from annotator.uniformer.mmcv.utils.ext_loader import check_ops_exist
from .builder import OPTIMIZER_B... | 11,803 | 46.216 | 96 | py |
Text2Video-Zero | Text2Video-Zero-main/annotator/uniformer/mmcv/runner/optimizer/builder.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import inspect
import torch
from ...utils import Registry, build_from_cfg
OPTIMIZERS = Registry('optimizer')
OPTIMIZER_BUILDERS = Registry('optimizer builder')
def register_torch_optimizers():
torch_optimizers = []
for module_name in dir(torch.opt... | 1,346 | 28.933333 | 73 | py |
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