repo stringclasses 454
values | file_path stringlengths 5 201 | extension stringclasses 1
value | content stringlengths 8 509k | num_lines int64 3 16.9k | size_bytes int64 8 511k |
|---|---|---|---|---|---|
ControlNet | annotator/uniformer/mmcv/runner/hooks/checkpoint.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import warnings
from annotator.uniformer.mmcv.fileio import FileClient
from ..dist_utils import allreduce_params, master_only
from .hook import HOOKS, Hook
@HOOKS.register_module()
class CheckpointHook(Hook):
"""Save checkpoints periodically.
... | 168 | 7,317 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/sync_buffer.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from ..dist_utils import allreduce_params
from .hook import HOOKS, Hook
@HOOKS.register_module()
class SyncBuffersHook(Hook):
"""Synchronize model buffers such as running_mean and running_var in BN at
the end of each epoch.
Args:
distributed (bool):... | 23 | 707 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/evaluation.py | .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... | 510 | 22,448 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/profiler.py | .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... | 181 | 8,041 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/__init__.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from .checkpoint import CheckpointHook
from .closure import ClosureHook
from .ema import EMAHook
from .evaluation import DistEvalHook, EvalHook
from .hook import HOOKS, Hook
from .iter_timer import IterTimerHook
from .logger import (DvcliveLoggerHook, LoggerHook, MlflowLo... | 30 | 1,396 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/lr_updater.py | .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... | 671 | 26,034 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/ema.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from ...parallel import is_module_wrapper
from ..hooks.hook import HOOKS, Hook
@HOOKS.register_module()
class EMAHook(Hook):
r"""Exponential Moving Average Hook.
Use Exponential Moving Average on all parameters of model in training
process. All parameters h... | 90 | 3,599 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/closure.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from .hook import HOOKS, Hook
@HOOKS.register_module()
class ClosureHook(Hook):
def __init__(self, fn_name, fn):
assert hasattr(self, fn_name)
assert callable(fn)
setattr(self, fn_name, fn)
| 12 | 269 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/momentum_updater.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import annotator.uniformer.mmcv as mmcv
from .hook import HOOKS, Hook
from .lr_updater import annealing_cos, annealing_linear, format_param
class MomentumUpdaterHook(Hook):
def __init__(self,
by_epoch=True,
warmup=None,
... | 494 | 21,296 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/hook.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from annotator.uniformer.mmcv.utils import Registry, is_method_overridden
HOOKS = Registry('hook')
class Hook:
stages = ('before_run', 'before_train_epoch', 'before_train_iter',
'after_train_iter', 'after_train_epoch', 'before_val_epoch',
... | 93 | 2,761 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/sampler_seed.py | .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` ... | 21 | 847 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/memory.py | .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... | 26 | 657 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/optimizer.py | .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... | 509 | 21,654 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/logger/pavi.py | .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... | 118 | 4,378 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/logger/mlflow.py | .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,
... | 79 | 2,838 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/logger/__init__.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from .base import LoggerHook
from .dvclive import DvcliveLoggerHook
from .mlflow import MlflowLoggerHook
from .neptune import NeptuneLoggerHook
from .pavi import PaviLoggerHook
from .tensorboard import TensorboardLoggerHook
from .text import TextLoggerHook
from .wandb imp... | 16 | 522 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/logger/neptune.py | .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 NeptuneLoggerHook(LoggerHook):
"""Class to log metrics to NeptuneAI.
It requires `neptune-client` to be installed.
Args:
init... | 83 | 3,077 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/logger/wandb.py | .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 WandbLoggerHook(LoggerHook):
def __init__(self,
init_kwargs=None,
interval=10,
ignore_last=... | 57 | 1,694 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/logger/tensorboard.py | .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__... | 58 | 2,077 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/logger/text.py | .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... | 257 | 10,684 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/logger/base.py | .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... | 167 | 5,451 |
ControlNet | annotator/uniformer/mmcv/runner/hooks/logger/dvclive.py | .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 DvcliveLoggerHook(LoggerHook):
"""Class to log metrics with dvclive.
It requires `dvclive`_ to be installed.
Args:
path (str)... | 59 | 1,761 |
ControlNet | annotator/uniformer/mmcv/runner/optimizer/default_constructor.py | .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... | 250 | 11,803 |
ControlNet | annotator/uniformer/mmcv/runner/optimizer/builder.py | .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... | 45 | 1,346 |
ControlNet | annotator/uniformer/mmcv/runner/optimizer/__init__.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from .builder import (OPTIMIZER_BUILDERS, OPTIMIZERS, build_optimizer,
build_optimizer_constructor)
from .default_constructor import DefaultOptimizerConstructor
__all__ = [
'OPTIMIZER_BUILDERS', 'OPTIMIZERS', 'DefaultOptimizerConstructor',
'... | 10 | 370 |
ControlNet | annotator/uniformer/mmcv/utils/trace.py | .py | import warnings
import torch
from annotator.uniformer.mmcv.utils import digit_version
def is_jit_tracing() -> bool:
if (torch.__version__ != 'parrots'
and digit_version(torch.__version__) >= digit_version('1.6.0')):
on_trace = torch.jit.is_tracing()
# In PyTorch 1.6, torch.jit.is_tra... | 24 | 795 |
ControlNet | annotator/uniformer/mmcv/utils/logging.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import logging
import torch.distributed as dist
logger_initialized = {}
def get_logger(name, log_file=None, log_level=logging.INFO, file_mode='w'):
"""Initialize and get a logger by name.
If the logger has not been initialized, this method will initialize the... | 111 | 3,986 |
ControlNet | annotator/uniformer/mmcv/utils/misc.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import collections.abc
import functools
import itertools
import subprocess
import warnings
from collections import abc
from importlib import import_module
from inspect import getfullargspec
from itertools import repeat
# From PyTorch internals
def _ntuple(n):
def p... | 378 | 11,447 |
ControlNet | annotator/uniformer/mmcv/utils/__init__.py | .py | # flake8: noqa
# Copyright (c) OpenMMLab. All rights reserved.
from .config import Config, ConfigDict, DictAction
from .misc import (check_prerequisites, concat_list, deprecated_api_warning,
has_method, import_modules_from_strings, is_list_of,
is_method_overridden, is_seq_of, is_st... | 70 | 3,915 |
ControlNet | annotator/uniformer/mmcv/utils/registry.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import inspect
import warnings
from functools import partial
from .misc import is_seq_of
def build_from_cfg(cfg, registry, default_args=None):
"""Build a module from config dict.
Args:
cfg (dict): Config dict. It should at least contain the key "type".... | 316 | 11,041 |
ControlNet | annotator/uniformer/mmcv/utils/testing.py | .py | # Copyright (c) Open-MMLab.
import sys
from collections.abc import Iterable
from runpy import run_path
from shlex import split
from typing import Any, Dict, List
from unittest.mock import patch
def check_python_script(cmd):
"""Run the python cmd script with `__main__`. The difference between
`os.system` is th... | 141 | 4,289 |
ControlNet | annotator/uniformer/mmcv/utils/path.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import os
import os.path as osp
from pathlib import Path
from .misc import is_str
def is_filepath(x):
return is_str(x) or isinstance(x, Path)
def fopen(filepath, *args, **kwargs):
if is_str(filepath):
return open(filepath, *args, **kwargs)
elif is... | 102 | 3,414 |
ControlNet | annotator/uniformer/mmcv/utils/parrots_wrapper.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from functools import partial
import torch
TORCH_VERSION = torch.__version__
def is_rocm_pytorch() -> bool:
is_rocm = False
if TORCH_VERSION != 'parrots':
try:
from torch.utils.cpp_extension import ROCM_HOME
is_rocm = True if ((... | 108 | 3,536 |
ControlNet | annotator/uniformer/mmcv/utils/parrots_jit.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import os
from .parrots_wrapper import TORCH_VERSION
parrots_jit_option = os.getenv('PARROTS_JIT_OPTION')
if TORCH_VERSION == 'parrots' and parrots_jit_option == 'ON':
from parrots.jit import pat as jit
else:
def jit(func=None,
check_input=None,
... | 42 | 899 |
ControlNet | annotator/uniformer/mmcv/utils/timer.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from time import time
class TimerError(Exception):
def __init__(self, message):
self.message = message
super(TimerError, self).__init__(message)
class Timer:
"""A flexible Timer class.
:Example:
>>> import time
>>> import annotat... | 119 | 2,993 |
ControlNet | annotator/uniformer/mmcv/utils/progressbar.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import sys
from collections.abc import Iterable
from multiprocessing import Pool
from shutil import get_terminal_size
from .timer import Timer
class ProgressBar:
"""A progress bar which can print the progress."""
def __init__(self, task_num=0, bar_width=50, st... | 209 | 7,105 |
ControlNet | annotator/uniformer/mmcv/utils/version_utils.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import os
import subprocess
import warnings
from packaging.version import parse
def digit_version(version_str: str, length: int = 4):
"""Convert a version string into a tuple of integers.
This method is usually used for comparing two versions. For pre-release
... | 91 | 2,673 |
ControlNet | annotator/uniformer/mmcv/utils/config.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import ast
import copy
import os
import os.path as osp
import platform
import shutil
import sys
import tempfile
import uuid
import warnings
from argparse import Action, ArgumentParser
from collections import abc
from importlib import import_module
from addict import Dict... | 689 | 26,263 |
ControlNet | annotator/uniformer/mmcv/utils/env.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
"""This file holding some environment constant for sharing by other files."""
import os.path as osp
import subprocess
import sys
from collections import defaultdict
import cv2
import torch
import annotator.uniformer.mmcv as mmcv
from .parrots_wrapper import get_build_c... | 96 | 3,367 |
ControlNet | annotator/uniformer/mmcv/utils/ext_loader.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import importlib
import os
import pkgutil
import warnings
from collections import namedtuple
import torch
if torch.__version__ != 'parrots':
def load_ext(name, funcs):
ext = importlib.import_module('mmcv.' + name)
for fun in funcs:
asser... | 72 | 2,021 |
ControlNet | annotator/uniformer/mmcv/cnn/builder.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from ..runner import Sequential
from ..utils import Registry, build_from_cfg
def build_model_from_cfg(cfg, registry, default_args=None):
"""Build a PyTorch model from config dict(s). Different from
``build_from_cfg``, if cfg is a list, a ``nn.Sequential`` will b... | 31 | 1,089 |
ControlNet | annotator/uniformer/mmcv/cnn/alexnet.py | .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... | 62 | 1,990 |
ControlNet | annotator/uniformer/mmcv/cnn/resnet.py | .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... | 317 | 9,955 |
ControlNet | annotator/uniformer/mmcv/cnn/__init__.py | .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,
... | 42 | 2,438 |
ControlNet | annotator/uniformer/mmcv/cnn/vgg.py | .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,... | 176 | 6,053 |
ControlNet | annotator/uniformer/mmcv/cnn/utils/flops_counter.py | .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... | 600 | 22,104 |
ControlNet | annotator/uniformer/mmcv/cnn/utils/__init__.py | .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... | 20 | 1,023 |
ControlNet | annotator/uniformer/mmcv/cnn/utils/sync_bn.py | .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... | 60 | 2,327 |
ControlNet | annotator/uniformer/mmcv/cnn/utils/weight_init.py | .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... | 685 | 26,006 |
ControlNet | annotator/uniformer/mmcv/cnn/utils/fuse_conv_bn.py | .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... | 60 | 1,881 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/hswish.py | .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:
... | 30 | 651 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/transformer.py | .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... | 596 | 24,639 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/norm.py | .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... | 145 | 5,154 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/swish.py | .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:
... | 26 | 485 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/non_local.py | .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 ... | 307 | 11,012 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/upsample.py | .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.... | 85 | 2,880 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/__init__.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from .activation import build_activation_layer
from .context_block import ContextBlock
from .conv import build_conv_layer
from .conv2d_adaptive_padding import Conv2dAdaptivePadding
from .conv_module import ConvModule
from .conv_ws import ConvAWS2d, ConvWS2d, conv_ws_2d
fr... | 36 | 1,732 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/generalized_attention.py | .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... | 413 | 15,999 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/activation.py | .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... | 93 | 2,508 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/conv2d_adaptive_padding.py | .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... | 63 | 2,514 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/conv_module.py | .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... | 207 | 8,760 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/registry.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from annotator.uniformer.mmcv.utils import Registry
CONV_LAYERS = Registry('conv layer')
NORM_LAYERS = Registry('norm layer')
ACTIVATION_LAYERS = Registry('activation layer')
PADDING_LAYERS = Registry('padding layer')
UPSAMPLE_LAYERS = Registry('upsample layer')
PLUGIN_L... | 17 | 658 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/conv.py | .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... | 45 | 1,446 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/wrappers.py | .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... | 181 | 6,961 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/context_block.py | .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... | 126 | 4,681 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/drop.py | .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... | 66 | 2,172 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/padding.py | .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... | 37 | 1,127 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/conv_ws.py | .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... | 149 | 5,417 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/depthwise_separable_conv_module.py | .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... | 97 | 4,142 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/hsigmoid.py | .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... | 35 | 1,097 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/plugin.py | .py | import inspect
import platform
from .registry import PLUGIN_LAYERS
if platform.system() == 'Windows':
import regex as re
else:
import re
def infer_abbr(class_type):
"""Infer abbreviation from the class name.
This method will infer the abbreviation to map class types to
abbreviations.
Rule ... | 89 | 2,487 |
ControlNet | annotator/uniformer/mmcv/cnn/bricks/scale.py | .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): ... | 22 | 577 |
ControlNet | annotator/uniformer/mmcv/arraymisc/__init__.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from .quantization import dequantize, quantize
__all__ = ['quantize', 'dequantize']
| 5 | 133 |
ControlNet | annotator/uniformer/mmcv/arraymisc/quantization.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
def quantize(arr, min_val, max_val, levels, dtype=np.int64):
"""Quantize an array of (-inf, inf) to [0, levels-1].
Args:
arr (ndarray): Input array.
min_val (scalar): Minimum value to be clipped.
max_val (scalar): Maxi... | 56 | 1,824 |
ControlNet | annotator/uniformer/mmcv/ops/modulated_deform_conv.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import math
import torch
import torch.nn as nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair, _single
from annotator.uniformer.mmcv.utils import deprecated_api_warning
from ..cnn impo... | 283 | 10,574 |
ControlNet | annotator/uniformer/mmcv/ops/bbox.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from ..utils import ext_loader
ext_module = ext_loader.load_ext('_ext', ['bbox_overlaps'])
def bbox_overlaps(bboxes1, bboxes2, mode='iou', aligned=False, offset=0):
"""Calculate overlap between two set of bboxes.
If ``aligned`` is ``False``, then calculate the... | 73 | 2,508 |
ControlNet | annotator/uniformer/mmcv/ops/deform_roi_pool.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from torch import nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
from ..utils import ext_loader
ext_module = ext_loader.load_ext(
'_ext', ['deform_roi_pool_forward', 'deform_roi... | 205 | 7,410 |
ControlNet | annotator/uniformer/mmcv/ops/cc_attention.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
import torch.nn.functional as F
from annotator.uniformer.mmcv.cnn import PLUGIN_LAYERS, Scale
def NEG_INF_DIAG(n, device):
"""Returns a diagonal matrix of size [n, n].
The diagonal are all "-inf". This is for avoiding calcula... | 84 | 3,041 |
ControlNet | annotator/uniformer/mmcv/ops/roiaware_pool3d.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from torch import nn as nn
from torch.autograd import Function
import annotator.uniformer.mmcv as mmcv
from ..utils import ext_loader
ext_module = ext_loader.load_ext(
'_ext', ['roiaware_pool3d_forward', 'roiaware_pool3d_backward'])
class RoIAwarePool... | 115 | 4,256 |
ControlNet | annotator/uniformer/mmcv/ops/border_align.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
# modified from
# https://github.com/Megvii-BaseDetection/cvpods/blob/master/cvpods/layers/border_align.py
import torch
import torch.nn as nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from ..utils import ext_loader
ext_... | 110 | 3,725 |
ControlNet | annotator/uniformer/mmcv/ops/deform_conv.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Tuple, Union
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch import Tensor
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair, _single
from... | 406 | 15,603 |
ControlNet | annotator/uniformer/mmcv/ops/pixel_group.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from ..utils import ext_loader
ext_module = ext_loader.load_ext('_ext', ['pixel_group'])
def pixel_group(score, mask, embedding, kernel_label, kernel_contour,
kernel_region_num, distance_threshold):
"""Group pixels i... | 76 | 3,113 |
ControlNet | annotator/uniformer/mmcv/ops/roi_align_rotated.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from torch.autograd import Function
from ..utils import ext_loader
ext_module = ext_loader.load_ext(
'_ext', ['roi_align_rotated_forward', 'roi_align_rotated_backward'])
class RoIAlignRotatedFunction(Function):
@staticmethod
def symb... | 178 | 6,434 |
ControlNet | annotator/uniformer/mmcv/ops/group_points.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Tuple
import torch
from torch import nn as nn
from torch.autograd import Function
from ..utils import ext_loader
from .ball_query import ball_query
from .knn import knn
ext_module = ext_loader.load_ext(
'_ext', ['group_points_forward', 'group_poi... | 225 | 8,135 |
ControlNet | annotator/uniformer/mmcv/ops/info.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import glob
import os
import torch
if torch.__version__ == 'parrots':
import parrots
def get_compiler_version():
return 'GCC ' + parrots.version.compiler
def get_compiling_cuda_version():
return parrots.version.cuda
else:
from ..utils i... | 37 | 887 |
ControlNet | annotator/uniformer/mmcv/ops/nms.py | .py | import os
import numpy as np
import torch
from annotator.uniformer.mmcv.utils import deprecated_api_warning
from ..utils import ext_loader
ext_module = ext_loader.load_ext(
'_ext', ['nms', 'softnms', 'nms_match', 'nms_rotated'])
# This function is modified from: https://github.com/pytorch/vision/
class NMSop(t... | 418 | 16,237 |
ControlNet | annotator/uniformer/mmcv/ops/__init__.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from .assign_score_withk import assign_score_withk
from .ball_query import ball_query
from .bbox import bbox_overlaps
from .border_align import BorderAlign, border_align
from .box_iou_rotated import box_iou_rotated
from .carafe import CARAFE, CARAFENaive, CARAFEPack, cara... | 82 | 4,506 |
ControlNet | annotator/uniformer/mmcv/ops/iou3d.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from ..utils import ext_loader
ext_module = ext_loader.load_ext('_ext', [
'iou3d_boxes_iou_bev_forward', 'iou3d_nms_forward',
'iou3d_nms_normal_forward'
])
def boxes_iou_bev(boxes_a, boxes_b):
"""Calculate boxes IoU in the Bird's Eye View.
... | 86 | 2,988 |
ControlNet | annotator/uniformer/mmcv/ops/three_interpolate.py | .py | from typing import Tuple
import torch
from torch.autograd import Function
from ..utils import ext_loader
ext_module = ext_loader.load_ext(
'_ext', ['three_interpolate_forward', 'three_interpolate_backward'])
class ThreeInterpolate(Function):
"""Performs weighted linear interpolation on 3 features.
Ple... | 69 | 2,147 |
ControlNet | annotator/uniformer/mmcv/ops/merge_cells.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from abc import abstractmethod
import torch
import torch.nn as nn
import torch.nn.functional as F
from ..cnn import ConvModule
class BaseMergeCell(nn.Module):
"""The basic class for cells used in NAS-FPN and NAS-FCOS.
BaseMergeCell takes 2 inputs. After apply... | 150 | 5,403 |
ControlNet | annotator/uniformer/mmcv/ops/points_in_boxes.py | .py | import torch
from ..utils import ext_loader
ext_module = ext_loader.load_ext('_ext', [
'points_in_boxes_part_forward', 'points_in_boxes_cpu_forward',
'points_in_boxes_all_forward'
])
def points_in_boxes_part(points, boxes):
"""Find the box in which each point is (CUDA).
Args:
points (torch.... | 134 | 5,241 |
ControlNet | annotator/uniformer/mmcv/ops/roi_pool.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
from ..utils import ext_loader
ext_module = ext_loader.load_ext('_ext',
... | 87 | 2,517 |
ControlNet | annotator/uniformer/mmcv/ops/furthest_point_sample.py | .py | import torch
from torch.autograd import Function
from ..utils import ext_loader
ext_module = ext_loader.load_ext('_ext', [
'furthest_point_sampling_forward',
'furthest_point_sampling_with_dist_forward'
])
class FurthestPointSampling(Function):
"""Uses iterative furthest point sampling to select a set of... | 84 | 2,550 |
ControlNet | annotator/uniformer/mmcv/ops/sync_bn.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.distributed as dist
import torch.nn.functional as F
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.module import Module
from torch.nn.parameter import Parameter
from annotator.un... | 280 | 11,267 |
ControlNet | annotator/uniformer/mmcv/ops/box_iou_rotated.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
from ..utils import ext_loader
ext_module = ext_loader.load_ext('_ext', ['box_iou_rotated'])
def box_iou_rotated(bboxes1, bboxes2, mode='iou', aligned=False):
"""Return intersection-over-union (Jaccard index) of boxes.
Both sets of boxes are expected to be in
... | 46 | 1,609 |
ControlNet | annotator/uniformer/mmcv/ops/corner_pool.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from torch import nn
from torch.autograd import Function
from ..utils import ext_loader
ext_module = ext_loader.load_ext('_ext', [
'top_pool_forward', 'top_pool_backward', 'bottom_pool_forward',
'bottom_pool_backward', 'left_pool_forward', 'left_poo... | 162 | 4,697 |
ControlNet | annotator/uniformer/mmcv/ops/assign_score_withk.py | .py | from torch.autograd import Function
from ..utils import ext_loader
ext_module = ext_loader.load_ext(
'_ext', ['assign_score_withk_forward', 'assign_score_withk_backward'])
class AssignScoreWithK(Function):
r"""Perform weighted sum to generate output features according to scores.
Modified from `PAConv <h... | 124 | 4,344 |
ControlNet | annotator/uniformer/mmcv/ops/multi_scale_deform_attn.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import math
import warnings
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd.function import Function, once_differentiable
from annotator.uniformer.mmcv import deprecated_api_warning
from annotator.uniformer.mmcv.cnn import constant... | 359 | 15,175 |
ControlNet | annotator/uniformer/mmcv/ops/contour_expand.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from ..utils import ext_loader
ext_module = ext_loader.load_ext('_ext', ['contour_expand'])
def contour_expand(kernel_mask, internal_kernel_label, min_kernel_area,
kernel_num):
"""Expand kernel contours so that fo... | 50 | 1,795 |
ControlNet | annotator/uniformer/mmcv/ops/deprecated_wrappers.py | .py | # Copyright (c) OpenMMLab. All rights reserved.
# This file is for backward compatibility.
# Module wrappers for empty tensor have been moved to mmcv.cnn.bricks.
import warnings
from ..cnn.bricks.wrappers import Conv2d, ConvTranspose2d, Linear, MaxPool2d
class Conv2d_deprecated(Conv2d):
def __init__(self, *args... | 44 | 1,467 |
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