instruction stringclasses 100
values | code stringlengths 78 193k | response stringlengths 259 170k | file stringlengths 59 203 |
|---|---|---|---|
Generate docstrings for exported functions | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
def quantize(arr, min_val, max_val, levels, dtype=np.int64):
if not (isinstance(levels, int) and levels > 1):
raise ValueError(
f'levels must be a positive integer, but got {levels}')
if min_val >= max_val:
raise Va... | --- +++ @@ -3,6 +3,18 @@
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): Maximum value to be clipped.
+ ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/arraymisc/quantization.py |
Write docstrings for algorithm functions | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
import torch.nn.functional as F
from annotator.mmpkg.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, nn... | --- +++ @@ -16,6 +16,17 @@ @ACTIVATION_LAYERS.register_module(name='Clip')
@ACTIVATION_LAYERS.register_module()
class Clamp(nn.Module):
+ """Clamp activation layer.
+
+ This activation function is to clamp the feature map value within
+ :math:`[min, max]`. More details can be found in ``torch.clamp()``.
+
+ ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/cnn/bricks/activation.py |
Fully document this Python code with docstrings | import sys
import re
import numpy as np
import cv2
import torch
def read_pfm(path):
with open(path, "rb") as file:
color = None
width = None
height = None
scale = None
endian = None
header = file.readline().rstrip()
if header.decode("ascii") == "PF":
... | --- +++ @@ -1,3 +1,4 @@+"""Utils for monoDepth."""
import sys
import re
import numpy as np
@@ -6,6 +7,14 @@
def read_pfm(path):
+ """Read pfm file.
+
+ Args:
+ path (str): path to file
+
+ Returns:
+ tuple: (data, scale)
+ """
with open(path, "rb") as file:
color = None
... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/midas/utils.py |
Replace inline comments with docstrings | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import warnings
import torch
import torch.nn as nn
from annotator.mmpkg.mmcv import ConfigDict, deprecated_api_warning
from annotator.mmpkg.mmcv.cnn import Linear, build_activation_layer, build_norm_layer
from annotator.mmpkg.mmcv.runner.base_module import B... | --- +++ @@ -31,27 +31,52 @@
def build_positional_encoding(cfg, default_args=None):
+ """Builder for Position Encoding."""
return build_from_cfg(cfg, POSITIONAL_ENCODING, default_args)
def build_attention(cfg, default_args=None):
+ """Builder for attention."""
return build_from_cfg(cfg, ATTENTIO... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/cnn/bricks/transformer.py |
Add docstrings following best practices | import torch.nn as nn
import torch.nn as NN
__all__ = ['ResNet', 'resnet18', 'resnet34', 'resnet50', 'resnet101',
'resnet152']
model_urls = {
'resnet18': 'https://download.pytorch.org/models/resnet18-5c106cde.pth',
'resnet34': 'https://download.pytorch.org/models/resnet34-333f7ec4.pth',
'resne... | --- +++ @@ -15,6 +15,7 @@
def conv3x3(in_planes, out_planes, stride=1):
+ """3x3 convolution with padding"""
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
padding=1, bias=False)
@@ -152,27 +153,47 @@
def resnet18(pretrained=True, **kwargs):
+ """Constru... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/leres/leres/Resnet.py |
Add docstrings to improve code quality | # 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.... | --- +++ @@ -11,6 +11,18 @@
@UPSAMPLE_LAYERS.register_module(name='pixel_shuffle')
class PixelShufflePack(nn.Module):
+ """Pixel Shuffle upsample layer.
+
+ This module packs `F.pixel_shuffle()` and a nn.Conv2d module together to
+ achieve a simple upsampling with pixel shuffle.
+
+ Args:
+ in_chan... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/cnn/bricks/upsample.py |
Add docstrings to meet PEP guidelines |
'''
M-LSD
Copyright 2021-present NAVER Corp.
Apache License v2.0
'''
import os
import numpy as np
import cv2
import torch
from torch.nn import functional as F
from modules import devices
def deccode_output_score_and_ptss(tpMap, topk_n = 200, ksize = 5):
b, c, h, w = tpMap.shape
assert b==1, 'only support... | --- +++ @@ -1,3 +1,7 @@+'''
+modified by lihaoweicv
+pytorch version
+'''
'''
M-LSD
@@ -14,6 +18,11 @@
def deccode_output_score_and_ptss(tpMap, topk_n = 200, ksize = 5):
+ '''
+ tpMap:
+ center: tpMap[1, 0, :, :]
+ displacement: tpMap[1, 1:5, :, :]
+ '''
b, c, h, w = tpMap.shape
assert... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mlsd/utils.py |
Add docstrings following best practices | # 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):
return nn.Conv2d(
in_planes,
out_planes,
kernel_size=3,
... | --- +++ @@ -8,6 +8,7 @@
def conv3x3(in_planes, out_planes, stride=1, dilation=1):
+ """3x3 convolution with padding."""
return nn.Conv2d(
in_planes,
out_planes,
@@ -71,6 +72,11 @@ downsample=None,
style='pytorch',
with_cp=False):
+ ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/cnn/resnet.py |
Generate consistent docstrings | # Copyright (c) OpenMMLab. All rights reserved.
import inspect
import os
import os.path as osp
import re
import tempfile
import warnings
from abc import ABCMeta, abstractmethod
from contextlib import contextmanager
from pathlib import Path
from typing import Iterable, Iterator, Optional, Tuple, Union
from urllib.reques... | --- +++ @@ -17,6 +17,12 @@
class BaseStorageBackend(metaclass=ABCMeta):
+ """Abstract class of storage backends.
+
+ All backends need to implement two apis: ``get()`` and ``get_text()``.
+ ``get()`` reads the file as a byte stream and ``get_text()`` reads the file
+ as texts.
+ """
# a flag t... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/fileio/file_client.py |
Replace inline comments with docstrings | import torch
import torch.nn as nn
from .base_model import BaseModel
from .blocks import FeatureFusionBlock, FeatureFusionBlock_custom, Interpolate, _make_encoder
class MidasNet_small(BaseModel):
def __init__(self, path=None, features=64, backbone="efficientnet_lite3", non_negative=True, exportable=True, channe... | --- +++ @@ -1,3 +1,7 @@+"""MidashNet: Network for monocular depth estimation trained by mixing several datasets.
+This file contains code that is adapted from
+https://github.com/thomasjpfan/pytorch_refinenet/blob/master/pytorch_refinenet/refinenet/refinenet_4cascade.py
+"""
import torch
import torch.nn as nn
@@ -6... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/midas/midas/midas_net_custom.py |
Write proper docstrings for these functions | # Copyright (c) OpenMMLab. All rights reserved.
from io import StringIO
from .file_client import FileClient
def list_from_file(filename,
prefix='',
offset=0,
max_num=0,
encoding='utf-8',
file_client_args=None):
cnt = ... | --- +++ @@ -11,6 +11,33 @@ max_num=0,
encoding='utf-8',
file_client_args=None):
+ """Load a text file and parse the content as a list of strings.
+
+ Note:
+ In v1.3.16 and later, ``list_from_file`` supports loading a text file
+ which can b... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/fileio/parse.py |
Add docstrings for utility scripts | # Copyright (c) OpenMMLab. All rights reserved.
import io
import os.path as osp
from pathlib import Path
import cv2
import numpy as np
from cv2 import (IMREAD_COLOR, IMREAD_GRAYSCALE, IMREAD_IGNORE_ORIENTATION,
IMREAD_UNCHANGED)
from annotator.mmpkg.mmcv.utils import check_file_exist, is_str, mkdir_o... | --- +++ @@ -41,6 +41,14 @@
def use_backend(backend):
+ """Select a backend for image decoding.
+
+ Args:
+ backend (str): The image decoding backend type. Options are `cv2`,
+ `pillow`, `turbojpeg` (see https://github.com/lilohuang/PyTurboJPEG)
+ and `tifffile`. `turbojpeg` is faster but ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/image/io.py |
Document classes and their methods | import torch
import torch.nn as nn
from .vit import (
_make_pretrained_vitb_rn50_384,
_make_pretrained_vitl16_384,
_make_pretrained_vitb16_384,
forward_vit,
)
def _make_encoder(backbone, features, use_pretrained, groups=1, expand=False, exportable=True, hooks=None, use_vit_only=False, use_readout="ign... | --- +++ @@ -118,8 +118,16 @@
class Interpolate(nn.Module):
+ """Interpolation module.
+ """
def __init__(self, scale_factor, mode, align_corners=False):
+ """Init.
+
+ Args:
+ scale_factor (float): scaling
+ mode (str): interpolation mode
+ """
super(... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/midas/midas/blocks.py |
Expand my code with proper documentation strings | # Copyright (c) OpenMMLab. All rights reserved.
import cv2
import numpy as np
def imconvert(img, src, dst):
code = getattr(cv2, f'COLOR_{src.upper()}2{dst.upper()}')
out_img = cv2.cvtColor(img, code)
return out_img
def bgr2gray(img, keepdim=False):
out_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
... | --- +++ @@ -4,12 +4,32 @@
def imconvert(img, src, dst):
+ """Convert an image from the src colorspace to dst colorspace.
+
+ Args:
+ img (ndarray): The input image.
+ src (str): The source colorspace, e.g., 'rgb', 'hsv'.
+ dst (str): The destination colorspace, e.g., 'rgb', 'hsv'.
+
+ ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/image/colorspace.py |
Fully document this Python code with docstrings | import numpy as np
import cv2
import math
def apply_min_size(sample, size, image_interpolation_method=cv2.INTER_AREA):
shape = list(sample["disparity"].shape)
if shape[0] >= size[0] and shape[1] >= size[1]:
return sample
scale = [0, 0]
scale[0] = size[0] / shape[0]
scale[1] = size[1] / s... | --- +++ @@ -4,6 +4,15 @@
def apply_min_size(sample, size, image_interpolation_method=cv2.INTER_AREA):
+ """Rezise the sample to ensure the given size. Keeps aspect ratio.
+
+ Args:
+ sample (dict): sample
+ size (tuple): image size
+
+ Returns:
+ tuple: new size
+ """
shape = l... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/midas/midas/transforms.py |
Document this code for team use | # Copyright (c) OpenMMLab. All rights reserved.
import cv2
import numpy as np
from ..utils import is_tuple_of
from .colorspace import bgr2gray, gray2bgr
def imnormalize(img, mean, std, to_rgb=True):
img = img.copy().astype(np.float32)
return imnormalize_(img, mean, std, to_rgb)
def imnormalize_(img, mean, ... | --- +++ @@ -7,11 +7,33 @@
def imnormalize(img, mean, std, to_rgb=True):
+ """Normalize an image with mean and std.
+
+ Args:
+ img (ndarray): Image to be normalized.
+ mean (ndarray): The mean to be used for normalize.
+ std (ndarray): The std to be used for normalize.
+ to_rgb (bo... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/image/photometric.py |
Add docstrings for better understanding | # Copyright (c) OpenMMLab. All rights reserved.
import numbers
import cv2
import numpy as np
from ..utils import to_2tuple
from .io import imread_backend
try:
from PIL import Image
except ImportError:
Image = None
def _scale_size(size, scale):
if isinstance(scale, (float, int)):
scale = (scale,... | --- +++ @@ -14,6 +14,15 @@
def _scale_size(size, scale):
+ """Rescale a size by a ratio.
+
+ Args:
+ size (tuple[int]): (w, h).
+ scale (float | tuple(float)): Scaling factor.
+
+ Returns:
+ tuple[int]: scaled size.
+ """
if isinstance(scale, (float, int)):
scale = (sc... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/image/geometric.py |
Add detailed documentation for each class | import torch
import torch.nn as nn
from .base_model import BaseModel
from .blocks import FeatureFusionBlock, Interpolate, _make_encoder
class MidasNet(BaseModel):
def __init__(self, path=None, features=256, non_negative=True):
print("Loading weights: ", path)
super(MidasNet, self).__init__()
... | --- +++ @@ -1,3 +1,7 @@+"""MidashNet: Network for monocular depth estimation trained by mixing several datasets.
+This file contains code that is adapted from
+https://github.com/thomasjpfan/pytorch_refinenet/blob/master/pytorch_refinenet/refinenet/refinenet_4cascade.py
+"""
import torch
import torch.nn as nn
@@ -6... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/midas/midas/midas_net.py |
Add docstrings with type hints explained | 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):
@staticmethod
def forward(ctx,
scores,
point_features,
... | --- +++ @@ -7,6 +7,23 @@
class AssignScoreWithK(Function):
+ r"""Perform weighted sum to generate output features according to scores.
+ Modified from `PAConv <https://github.com/CVMI-Lab/PAConv/tree/main/
+ scene_seg/lib/paconv_lib/src/gpu>`_.
+
+ This is a memory-efficient CUDA implementation of assig... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/assign_score_withk.py |
Fill in missing docstrings in my code | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from torch.autograd import Function
from ..utils import ext_loader
ext_module = ext_loader.load_ext('_ext', ['ball_query_forward'])
class BallQuery(Function):
@staticmethod
def forward(ctx, min_radius: float, max_radius: float, sample_num: int,
... | --- +++ @@ -8,10 +8,23 @@
class BallQuery(Function):
+ """Find nearby points in spherical space."""
@staticmethod
def forward(ctx, min_radius: float, max_radius: float, sample_num: int,
xyz: torch.Tensor, center_xyz: torch.Tensor) -> torch.Tensor:
+ """
+ Args:
+ ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/ball_query.py |
Turn comments into proper docstrings | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Function
from torch.nn.modules.module import Module
from ..cnn import UPSAMPLE_LAYERS, normal_init, xavier_init
from ..utils import ext_loader
ext_module = ext_loader.load_ext(... | --- +++ @@ -178,6 +178,18 @@
class CARAFE(Module):
+ """ CARAFE: Content-Aware ReAssembly of FEatures
+
+ Please refer to https://arxiv.org/abs/1905.02188 for more details.
+
+ Args:
+ kernel_size (int): reassemble kernel size
+ group_size (int): reassemble group size
+ scale_factor (i... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/carafe.py |
Add docstrings to improve code quality | # 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_... | --- +++ @@ -63,15 +63,47 @@
class BorderAlign(nn.Module):
+ r"""Border align pooling layer.
+
+ Applies border_align over the input feature based on predicted bboxes.
+ The details were described in the paper
+ `BorderDet: Border Feature for Dense Object Detection
+ <https://arxiv.org/abs/2007.11056>... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/border_align.py |
Document functions with detailed explanations | # 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):
def __init__(self,
... | --- +++ @@ -10,6 +10,27 @@
class _NonLocalNd(nn.Module, metaclass=ABCMeta):
+ """Basic Non-local module.
+
+ This module is proposed in
+ "Non-local Neural Networks"
+ Paper reference: https://arxiv.org/abs/1711.07971
+ Code reference: https://github.com/AlexHex7/Non-local_pytorch
+
+ Args:
+ ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/cnn/bricks/non_local.py |
Add docstrings to meet PEP guidelines | 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):
@staticmethod
def forward(ctx, points_xyz: torch.Tensor... | --- +++ @@ -10,10 +10,20 @@
class FurthestPointSampling(Function):
+ """Uses iterative furthest point sampling to select a set of features whose
+ corresponding points have the furthest distance."""
@staticmethod
def forward(ctx, points_xyz: torch.Tensor,
num_points: int) -> torch... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/furthest_point_sample.py |
Generate docstrings for this script | # modified from https://github.com/rosinality/stylegan2-pytorch/blob/master/op/fused_act.py # noqa:E501
# Copyright (c) 2021, NVIDIA Corporation. All rights reserved.
# NVIDIA Source Code License for StyleGAN2 with Adaptive Discriminator
# Augmentation (ADA)
# ==========================================================... | --- +++ @@ -106,6 +106,11 @@
class FusedBiasLeakyReLUFunctionBackward(Function):
+ """Calculate second order deviation.
+
+ This function is to compute the second order deviation for the fused leaky
+ relu operation.
+ """
@staticmethod
def forward(ctx, grad_output, out, negative_slope, scal... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/fused_bias_leakyrelu.py |
Generate consistent documentation across files | import torch
from torch.autograd import Function
from ..utils import ext_loader
ext_module = ext_loader.load_ext('_ext', ['knn_forward'])
class KNN(Function):
@staticmethod
def forward(ctx,
k: int,
xyz: torch.Tensor,
center_xyz: torch.Tensor = None,
... | --- +++ @@ -7,6 +7,12 @@
class KNN(Function):
+ r"""KNN (CUDA) based on heap data structure.
+ Modified from `PAConv <https://github.com/CVMI-Lab/PAConv/tree/main/
+ scene_seg/lib/pointops/src/knnquery_heap>`_.
+
+ Find k-nearest points.
+ """
@staticmethod
def forward(ctx,
@@ -14,6 +20,2... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/knn.py |
Add docstrings for internal functions | import torch
from torch.autograd import Function
from ..utils import ext_loader
ext_module = ext_loader.load_ext(
'_ext', ['gather_points_forward', 'gather_points_backward'])
class GatherPoints(Function):
@staticmethod
def forward(ctx, features: torch.Tensor,
indices: torch.Tensor) -> t... | --- +++ @@ -8,10 +8,19 @@
class GatherPoints(Function):
+ """Gather points with given index."""
@staticmethod
def forward(ctx, features: torch.Tensor,
indices: torch.Tensor) -> torch.Tensor:
+ """
+ Args:
+ features (Tensor): (B, C, N) features to gather.
+ ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/gather_points.py |
Generate documentation strings for clarity | # 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... | --- +++ @@ -14,6 +14,27 @@
class QueryAndGroup(nn.Module):
+ """Groups points with a ball query of radius.
+
+ Args:
+ max_radius (float): The maximum radius of the balls.
+ If None is given, we will use kNN sampling instead of ball query.
+ sample_num (int): Maximum number of feature... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/group_points.py |
Add docstrings for internal functions | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from annotator.mmpkg.mmcv import build_from_cfg
from .registry import DROPOUT_LAYERS
def drop_path(x, drop_prob=0., training=False):
if drop_prob == 0. or not training:
return x
keep_prob = 1 - drop_prob
# handle t... | --- +++ @@ -7,6 +7,12 @@
def drop_path(x, drop_prob=0., training=False):
+ """Drop paths (Stochastic Depth) per sample (when applied in main path of
+ residual blocks).
+
+ We follow the implementation
+ https://github.com/rwightman/pytorch-image-models/blob/a2727c1bf78ba0d7b5727f5f95e37fb7f8866b1f/timm... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/cnn/bricks/drop.py |
Write Python docstrings for this snippet | import os
import numpy as np
import torch
from annotator.mmpkg.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(torch... | --- +++ @@ -116,6 +116,38 @@
@deprecated_api_warning({'iou_thr': 'iou_threshold'})
def nms(boxes, scores, iou_threshold, offset=0, score_threshold=0, max_num=-1):
+ """Dispatch to either CPU or GPU NMS implementations.
+
+ The input can be either torch tensor or numpy array. GPU NMS will be used
+ if the in... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/nms.py |
Write proper docstrings for these functions | # Modified from https://github.com/facebookresearch/detectron2/tree/master/projects/PointRend # noqa
from os import path as osp
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.modules.utils import _pair
from torch.onnx.operators import shape_as_tensor
def bilinear_grid_sample(im, g... | --- +++ @@ -10,6 +10,21 @@
def bilinear_grid_sample(im, grid, align_corners=False):
+ """Given an input and a flow-field grid, computes the output using input
+ values and pixel locations from grid. Supported only bilinear interpolation
+ method to sample the input pixels.
+
+ Args:
+ im (torch.T... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/point_sample.py |
Generate consistent documentation across files | 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):
def camel2snack(word):
word = re.sub(r'([A-Z]+)([A-Z][a-z])', r'\1_\2', word)
word = re.sub(r'([a-z\d])([A-Z])', r'\1_\2'... | --- +++ @@ -10,8 +10,33 @@
def infer_abbr(class_type):
+ """Infer abbreviation from the class name.
+
+ This method will infer the abbreviation to map class types to
+ abbreviations.
+
+ Rule 1: If the class has the property "abbr", return the property.
+ Rule 2: Otherwise, the abbreviation falls bac... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/cnn/bricks/plugin.py |
Generate NumPy-style docstrings | # 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 deprecated_api_warning, ext_loader
ext_module = ext_loader.load_ext('_ext',
... | --- +++ @@ -131,6 +131,41 @@
class RoIAlign(nn.Module):
+ """RoI align pooling layer.
+
+ Args:
+ output_size (tuple): h, w
+ spatial_scale (float): scale the input boxes by this number
+ sampling_ratio (int): number of inputs samples to take for each
+ output sample. 0 to take... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/roi_align.py |
Create docstrings for reusable components | # Copyright (c) OpenMMLab. All rights reserved.
import inspect
import torch.nn as nn
from annotator.mmpkg.mmcv.utils import is_tuple_of
from annotator.mmpkg.mmcv.utils.parrots_wrapper import SyncBatchNorm, _BatchNorm, _InstanceNorm
from .registry import NORM_LAYERS
NORM_LAYERS.register_module('BN', module=nn.BatchNo... | --- +++ @@ -21,6 +21,27 @@
def infer_abbr(class_type):
+ """Infer abbreviation from the class name.
+
+ When we build a norm layer with `build_norm_layer()`, we want to preserve
+ the norm type in variable names, e.g, self.bn1, self.gn. This method will
+ infer the abbreviation to map class types to abb... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/cnn/bricks/norm.py |
Create docstrings for each class method | # Copyright (c) OpenMMLab. All rights reserved.
# Code reference from "Temporal Interlacing Network"
# https://github.com/deepcs233/TIN/blob/master/cuda_shift/rtc_wrap.py
# Hao Shao, Shengju Qian, Yu Liu
# shaoh19@mails.tsinghua.edu.cn, sjqian@cse.cuhk.edu.hk, yuliu@ee.cuhk.edu.hk
import torch
import torch.nn as nn
fr... | --- +++ @@ -46,6 +46,23 @@
class TINShift(nn.Module):
+ """Temporal Interlace Shift.
+
+ Temporal Interlace shift is a differentiable temporal-wise frame shifting
+ which is proposed in "Temporal Interlacing Network"
+
+ Please refer to https://arxiv.org/abs/2001.06499 for more details.
+ Code is mod... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/tin_shift.py |
Write docstrings that follow conventions | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from torch import nn as nn
from torch.autograd import Function
import annotator.mmpkg.mmcv as mmcv
from ..utils import ext_loader
ext_module = ext_loader.load_ext(
'_ext', ['roiaware_pool3d_forward', 'roiaware_pool3d_backward'])
class RoIAwarePool3d(n... | --- +++ @@ -11,6 +11,19 @@
class RoIAwarePool3d(nn.Module):
+ """Encode the geometry-specific features of each 3D proposal.
+
+ Please refer to `PartA2 <https://arxiv.org/pdf/1907.03670.pdf>`_ for more
+ details.
+
+ Args:
+ out_size (int or tuple): The size of output features. n or
+ ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/roiaware_pool3d.py |
Add standardized docstrings across the file | from torch import nn as nn
from torch.autograd import Function
from ..utils import ext_loader
ext_module = ext_loader.load_ext('_ext', ['roipoint_pool3d_forward'])
class RoIPointPool3d(nn.Module):
def __init__(self, num_sampled_points=512):
super().__init__()
self.num_sampled_points = num_sampl... | --- +++ @@ -7,12 +7,33 @@
class RoIPointPool3d(nn.Module):
+ """Encode the geometry-specific features of each 3D proposal.
+
+ Please refer to `Paper of PartA2 <https://arxiv.org/pdf/1907.03670.pdf>`_
+ for more details.
+
+ Args:
+ num_sampled_points (int, optional): Number of samples in each ro... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/roipoint_pool3d.py |
Fill in missing docstrings in my code | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from ..utils import ext_loader
ext_module = ext_loader.load_ext(
'_ext', ['dynamic_voxelize_forward', 'hard_voxelize_forward'])
class _Voxelization(Funct... | --- +++ @@ -19,6 +19,31 @@ coors_range,
max_points=35,
max_voxels=20000):
+ """Convert kitti points(N, >=3) to voxels.
+
+ Args:
+ points (torch.Tensor): [N, ndim]. Points[:, :3] contain xyz points
+ and points[:, 3:] contain othe... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/voxelize.py |
Improve my code by adding docstrings | # 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):
def __init__(self, *args, dim=0, **kwargs):
super(MMDataParallel, self).__init__(*args, dim=dim, **kwargs... | --- +++ @@ -7,12 +7,32 @@
class MMDataParallel(DataParallel):
+ """The DataParallel module that supports DataContainer.
+
+ MMDataParallel has two main differences with PyTorch DataParallel:
+
+ - It supports a custom type :class:`DataContainer` which allows more
+ flexible control of input data durin... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/parallel/data_parallel.py |
Add docstrings that explain purpose and usage | # 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.mmpkg.mmcv.utils import Registry, build_from_cfg, get_logger, print_log
INITIALIZERS = Registry('initializer')
def update_init_info(m... | --- +++ @@ -14,6 +14,15 @@
def update_init_info(module, init_info):
+ """Update the `_params_init_info` in the module if the value of parameters
+ are changed.
+
+ Args:
+ module (obj:`nn.Module`): The module of PyTorch with a user-defined
+ attribute `_params_init_info` which records the... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/cnn/utils/weight_init.py |
Write docstrings for algorithm functions | # 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.mmpkg.mmcv.runner.dist_utils import master_only
from annotator.mmpkg.mmcv.utils.logging import get_logger, logger... | --- +++ @@ -12,8 +12,26 @@
class BaseModule(nn.Module, metaclass=ABCMeta):
+ """Base module for all modules in openmmlab.
+
+ ``BaseModule`` is a wrapper of ``torch.nn.Module`` with additional
+ functionality of parameter initialization. Compared with
+ ``torch.nn.Module``, ``BaseModule`` mainly adds th... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/runner/base_module.py |
Generate docstrings for script automation | # 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.mmpkg.mmcv as mmcv
from ..parallel import is_module_wrapper
from .checkpoint import load_checkpoint
f... | --- +++ @@ -19,6 +19,34 @@
class BaseRunner(metaclass=ABCMeta):
+ """The base class of Runner, a training helper for PyTorch.
+
+ All subclasses should implement the following APIs:
+
+ - ``run()``
+ - ``train()``
+ - ``val()``
+ - ``save_checkpoint()``
+
+ Args:
+ model (:obj:`torch.nn.... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/runner/base_runner.py |
Add docstrings to improve readability | # 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... | --- +++ @@ -40,6 +40,47 @@ input_constructor=None,
flush=False,
ost=sys.stdout):
+ """Get complexity information of a model.
+
+ This method can calculate FLOPs and parameter counts of a model with
+ corresponding input... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/cnn/utils/flops_counter.py |
Write docstrings for utility functions | # 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... | --- +++ @@ -39,6 +39,21 @@
def load_state_dict(module, state_dict, strict=False, logger=None):
+ """Load state_dict to a module.
+
+ This method is modified from :meth:`torch.nn.Module.load_state_dict`.
+ Default value for ``strict`` is set to ``False`` and the message for
+ param mismatch will be shown... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/runner/checkpoint.py |
Generate helpful docstrings for debugging | # 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... | --- +++ @@ -41,6 +41,16 @@
def _init_dist_slurm(backend, port=None):
+ """Initialize slurm distributed training environment.
+
+ If argument ``port`` is not specified, then the master port will be system
+ environment variable ``MASTER_PORT``. If ``MASTER_PORT`` is not in system
+ environment variable, ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/runner/dist_utils.py |
Fill in missing docstrings in my code | import torch
import annotator.mmpkg.mmcv as mmcv
class _BatchNormXd(torch.nn.modules.batchnorm._BatchNorm):
def _check_input_dim(self, input):
return
def revert_sync_batchnorm(module):
module_output = module
module_checklist = [torch.nn.modules.batchnorm.SyncBatchNorm]
if hasattr(mmcv, 'op... | --- +++ @@ -4,12 +4,34 @@
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 between BatchNorm1d, Bat... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/cnn/utils/sync_bn.py |
Add docstrings to improve readability | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
def _fuse_conv_bn(conv, bn):
conv_w = conv.weight
conv_b = conv.bias if conv.bias is not None else torch.zeros_like(
bn.running_mean)
factor = bn.weight / torch.sqrt(bn.running_var + bn.eps)
conv.weight = nn.Pa... | --- +++ @@ -4,6 +4,15 @@
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 = conv.weight
conv_b = conv.bias if conv.bias... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/cnn/utils/fuse_conv_bn.py |
Improve documentation using docstrings | # 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.mmpkg.mmcv.fileio import FileClient
from annotator.mmpkg.mmcv.utils impor... | --- +++ @@ -14,6 +14,61 @@
class EvalHook(Hook):
+ """Non-Distributed evaluation hook.
+
+ This hook will regularly perform evaluation in a given interval when
+ performing in non-distributed environment.
+
+ Args:
+ dataloader (DataLoader): A PyTorch dataloader, whose dataset has
+ im... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/runner/hooks/evaluation.py |
Add docstrings for utility scripts | # Copyright (c) OpenMMLab. All rights reserved.
from ...parallel import is_module_wrapper
from ..hooks.hook import HOOKS, Hook
@HOOKS.register_module()
class EMAHook(Hook):
def __init__(self,
momentum=0.0002,
interval=1,
warm_up=100,
resume_from... | --- +++ @@ -5,6 +5,26 @@
@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 have a ema backup, which update by the formula
+ as below. EMAHook takes priority over EvalHook... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/runner/hooks/ema.py |
Write beginner-friendly docstrings | # Copyright (c) OpenMMLab. All rights reserved.
from io import BytesIO, StringIO
from pathlib import Path
from ..utils import is_list_of, is_str
from .file_client import FileClient
from .handlers import BaseFileHandler, JsonHandler, PickleHandler, YamlHandler
file_handlers = {
'json': JsonHandler(),
'yaml': Y... | --- +++ @@ -16,6 +16,33 @@
def load(file, file_format=None, file_client_args=None, **kwargs):
+ """Load data from json/yaml/pickle files.
+
+ This method provides a unified api for loading data from serialized files.
+
+ Note:
+ In v1.3.16 and later, ``load`` supports loading data from serialized
+ ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/fileio/io.py |
Generate consistent docstrings | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import warnings
from annotator.mmpkg.mmcv.fileio import FileClient
from ..dist_utils import allreduce_params, master_only
from .hook import HOOKS, Hook
@HOOKS.register_module()
class CheckpointHook(Hook):
def __init__(self,
i... | --- +++ @@ -9,6 +9,44 @@
@HOOKS.register_module()
class CheckpointHook(Hook):
+ """Save checkpoints periodically.
+
+ Args:
+ interval (int): The saving period. If ``by_epoch=True``, interval
+ indicates epochs, otherwise it indicates iterations.
+ Default: -1, which means "never".... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/runner/hooks/checkpoint.py |
Write docstrings for backend logic | # Copyright (c) OpenMMLab. All rights reserved.
import annotator.mmpkg.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,
... | --- +++ @@ -152,6 +152,18 @@
@HOOKS.register_module()
class StepMomentumUpdaterHook(MomentumUpdaterHook):
+ """Step momentum scheduler with min value clipping.
+
+ Args:
+ step (int | list[int]): Step to decay the momentum. If an int value is
+ given, regard it as the decay interval. If a lis... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/runner/hooks/momentum_updater.py |
Write docstrings for algorithm functions | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
import torch.nn.functional as F
from annotator.mmpkg.mmcv.cnn import PLUGIN_LAYERS, Scale
def NEG_INF_DIAG(n, device):
return torch.diag(torch.tensor(float('-inf')).to(device).repeat(n), 0)
@PLUGIN_LAYERS.register_module()
class... | --- +++ @@ -7,11 +7,39 @@
def NEG_INF_DIAG(n, device):
+ """Returns a diagonal matrix of size [n, n].
+
+ The diagonal are all "-inf". This is for avoiding calculating the
+ overlapped element in the Criss-Cross twice.
+ """
return torch.diag(torch.tensor(float('-inf')).to(device).repeat(n), 0)
... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/cc_attention.py |
Write docstrings for data processing functions | # 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... | --- +++ @@ -190,6 +190,38 @@
class DeformConv2d(nn.Module):
+ r"""Deformable 2D convolution.
+
+ Applies a deformable 2D convolution over an input signal composed of
+ several input planes. DeformConv2d was described in the paper
+ `Deformable Convolutional Networks
+ <https://arxiv.org/pdf/1703.0621... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/deform_conv.py |
Replace inline comments with docstrings | # Copyright (c) OpenMMLab. All rights reserved.
import numbers
from math import cos, pi
import annotator.mmpkg.mmcv as mmcv
from .hook import HOOKS, Hook
class LrUpdaterHook(Hook):
def __init__(self,
by_epoch=True,
warmup=None,
warmup_iters=0,
... | --- +++ @@ -7,6 +7,20 @@
class LrUpdaterHook(Hook):
+ """LR Scheduler in MMCV.
+
+ Args:
+ by_epoch (bool): LR changes epoch by epoch
+ warmup (string): Type of warmup used. It can be None(use no warmup),
+ 'constant', 'linear' or 'exp'
+ warmup_iters (int): The number of itera... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/runner/hooks/lr_updater.py |
Replace inline comments with docstrings | # 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.mmpkg.mmcv import deprecated_api_warning
from annotator.mmpkg.mmcv.cnn import constant_init, x... | --- +++ @@ -22,6 +22,26 @@ @staticmethod
def forward(ctx, value, value_spatial_shapes, value_level_start_index,
sampling_locations, attention_weights, im2col_step):
+ """GPU version of multi-scale deformable attention.
+
+ Args:
+ value (Tensor): The value has shape
+ ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/multi_scale_deform_attn.py |
Add verbose docstrings with examples | # 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',
['dynamic_point_to_voxel_forward', 'dynamic_point_to_voxel_backward'])
class _DynamicScatter(Function):
@staticm... | --- +++ @@ -14,6 +14,22 @@
@staticmethod
def forward(ctx, feats, coors, reduce_type='max'):
+ """convert kitti points(N, >=3) to voxels.
+
+ Args:
+ feats (torch.Tensor): [N, C]. Points features to be reduced
+ into voxels.
+ coors (torch.Tensor): [N, ndim].... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/scatter_points.py |
Add docstrings to clarify complex logic | 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):
assert points.shape[0] == boxes.shape[0], \
'Points and boxes should hav... | --- +++ @@ -9,6 +9,17 @@
def points_in_boxes_part(points, boxes):
+ """Find the box in which each point is (CUDA).
+
+ Args:
+ points (torch.Tensor): [B, M, 3], [x, y, z] in LiDAR/DEPTH coordinate
+ boxes (torch.Tensor): [B, T, 7],
+ num_valid_boxes <= T, [x, y, z, x_size, y_size, z_s... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/points_in_boxes.py |
Create docstrings for each class method | # Copyright (c) OpenMMLab. All rights reserved.
from enum import Enum
class Priority(Enum):
HIGHEST = 0
VERY_HIGH = 10
HIGH = 30
ABOVE_NORMAL = 40
NORMAL = 50
BELOW_NORMAL = 60
LOW = 70
VERY_LOW = 90
LOWEST = 100
def get_priority(priority):
if isinstance(priority, int):
... | --- +++ @@ -3,6 +3,30 @@
class Priority(Enum):
+ """Hook priority levels.
+
+ +--------------+------------+
+ | Level | Value |
+ +==============+============+
+ | HIGHEST | 0 |
+ +--------------+------------+
+ | VERY_HIGH | 10 |
+ +--------------+------... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/runner/priority.py |
Insert docstrings into my code | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import subprocess
import sys
from collections import defaultdict
import cv2
import torch
import annotator.mmpkg.mmcv as mmcv
from .parrots_wrapper import get_build_config
def collect_env():
env_info = {}
env_info['sys.platform'] = sys.pl... | --- +++ @@ -1,4 +1,5 @@ # Copyright (c) OpenMMLab. All rights reserved.
+"""This file holding some environment constant for sharing by other files."""
import os.path as osp
import subprocess
@@ -13,6 +14,27 @@
def collect_env():
+ """Collect the information of the running environments.
+
+ Returns:
+ ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/utils/env.py |
Write docstrings describing each step | # 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... | --- +++ @@ -37,6 +37,20 @@
def scandir(dir_path, suffix=None, recursive=False, case_sensitive=True):
+ """Scan a directory to find the interested files.
+
+ Args:
+ dir_path (str | obj:`Path`): Path of the directory.
+ suffix (str | tuple(str), optional): File suffix that we are
+ int... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/utils/path.py |
Generate docstrings for exported functions | # 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... | --- +++ @@ -68,6 +68,29 @@
class Config:
+ """A facility for config and config files.
+
+ It supports common file formats as configs: python/json/yaml. The interface
+ is the same as a dict object and also allows access config values as
+ attributes.
+
+ Example:
+ >>> cfg = Config(dict(a=1, b... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/utils/config.py |
Write beginner-friendly docstrings | # 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:
def __init__(self, start=True, print_tmpl=None):
self._is_running = False
... | --- +++ @@ -10,6 +10,30 @@
class Timer:
+ """A flexible Timer class.
+
+ :Example:
+
+ >>> import time
+ >>> import annotator.mmpkg.mmcv as mmcv
+ >>> with mmcv.Timer():
+ >>> # simulate a code block that will run for 1s
+ >>> time.sleep(1)
+ 1.000
+ >>> with mmcv.Timer(print_tmpl... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/utils/timer.py |
Create docstrings for API functions | 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):
@staticmethod
def forward(ctx, features: torch.Tensor, indic... | --- +++ @@ -10,10 +10,26 @@
class ThreeInterpolate(Function):
+ """Performs weighted linear interpolation on 3 features.
+
+ Please refer to `Paper of PointNet++ <https://arxiv.org/abs/1706.02413>`_
+ for more details.
+ """
@staticmethod
def forward(ctx, features: torch.Tensor, indices: tor... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/three_interpolate.py |
Document this script properly | # 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):
if not isinstance(cfg, dict):
raise TypeError(f'cfg must be a dict, but got {type(cfg)}')
if 'type' not in cfg... | --- +++ @@ -7,6 +7,16 @@
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".
+ registry (:obj:`Registry`): The registry to search the type from.
+ default_args (dict, op... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/utils/registry.py |
Write docstrings describing each step | # 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.mmpkg.mmcv as mmcv
from .base_runner import BaseRunner
from .builder import RUNNERS
from .checkpoint import save_checkpoint
fr... | --- +++ @@ -46,6 +46,10 @@
@RUNNERS.register_module()
class IterBasedRunner(BaseRunner):
+ """Iteration-based Runner.
+
+ This runner train models iteration by iteration.
+ """
def train(self, data_loader, **kwargs):
self.model.train()
@@ -81,6 +85,16 @@ self._inner_iter += 1
... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/runner/iter_based_runner.py |
Add docstrings for production code | # 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):
ans_iou = boxes_a.new_zeros(
torch.Size((b... | --- +++ @@ -10,6 +10,15 @@
def boxes_iou_bev(boxes_a, boxes_b):
+ """Calculate boxes IoU in the Bird's Eye View.
+
+ Args:
+ boxes_a (torch.Tensor): Input boxes a with shape (M, 5).
+ boxes_b (torch.Tensor): Input boxes b with shape (N, 5).
+
+ Returns:
+ ans_iou (torch.Tensor): IoU re... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/iou3d.py |
Generate missing documentation strings | # 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.mmpkg.mmcv.utils import TORCH_VERSION, digit_version
from .dist_utils import allreduce_grads as _allreduc... | --- +++ @@ -22,6 +22,16 @@
def cast_tensor_type(inputs, src_type, dst_type):
+ """Recursively convert Tensor in inputs from src_type to dst_type.
+
+ Args:
+ inputs: Inputs that to be casted.
+ src_type (torch.dtype): Source type..
+ dst_type (torch.dtype): Destination type.
+
+ Return... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/runner/fp16_utils.py |
Add docstrings explaining edge cases | # 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.mmpkg.mmcv as mmcv
def get_host_info():
host = ''
try:
host = f'{getuser()}@{geth... | --- +++ @@ -14,6 +14,11 @@
def get_host_info():
+ """Get hostname and username.
+
+ Return empty string if exception raised, e.g. ``getpass.getuser()`` will
+ lead to error in docker container
+ """
host = ''
try:
host = f'{getuser()}@{gethostname()}'
@@ -28,6 +33,22 @@
def obj_fr... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/runner/utils.py |
Document all public functions with docstrings | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
from collections import OrderedDict
import cv2
from cv2 import (CAP_PROP_FOURCC, CAP_PROP_FPS, CAP_PROP_FRAME_COUNT,
CAP_PROP_FRAME_HEIGHT, CAP_PROP_FRAME_WIDTH,
CAP_PROP_POS_FRAMES, VideoWriter_fourcc)
from annota... | --- +++ @@ -40,6 +40,26 @@
class VideoReader:
+ """Video class with similar usage to a list object.
+
+ This video warpper class provides convenient apis to access frames.
+ There exists an issue of OpenCV's VideoCapture class that jumping to a
+ certain frame may be inaccurate. It is fixed in this clas... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/video/io.py |
Please document this code using docstrings | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import platform
import shutil
import time
import warnings
import torch
import annotator.mmpkg.mmcv as mmcv
from .base_runner import BaseRunner
from .builder import RUNNERS
from .checkpoint import save_checkpoint
from .utils import get_host_info
@... | --- +++ @@ -16,6 +16,10 @@
@RUNNERS.register_module()
class EpochBasedRunner(BaseRunner):
+ """Epoch-based Runner.
+
+ This runner train models epoch by epoch.
+ """
def run_iter(self, data_batch, train_mode, **kwargs):
if self.batch_processor is not None:
@@ -66,6 +70,16 @@ self.cal... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/runner/epoch_based_runner.py |
Create documentation for each function signature | from typing import List
import torch
from torch import nn as nn
from annotator.mmpkg.mmcv.runner import force_fp32
from .furthest_point_sample import (furthest_point_sample,
furthest_point_sample_with_dist)
def calc_square_dist(point_feat_a, point_feat_b, norm=True):
num_chan... | --- +++ @@ -9,6 +9,17 @@
def calc_square_dist(point_feat_a, point_feat_b, norm=True):
+ """Calculating square distance between a and b.
+
+ Args:
+ point_feat_a (Tensor): (B, N, C) Feature vector of each point.
+ point_feat_b (Tensor): (B, M, C) Feature vector of each point.
+ norm (Bool,... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/points_sampler.py |
Create docstrings for all classes and functions | from typing import Tuple
import torch
from torch.autograd import Function
from ..utils import ext_loader
ext_module = ext_loader.load_ext('_ext', ['three_nn_forward'])
class ThreeNN(Function):
@staticmethod
def forward(ctx, target: torch.Tensor,
source: torch.Tensor) -> Tuple[torch.Tensor,... | --- +++ @@ -9,10 +9,26 @@
class ThreeNN(Function):
+ """Find the top-3 nearest neighbors of the target set from the source set.
+
+ Please refer to `Paper of PointNet++ <https://arxiv.org/abs/1706.02413>`_
+ for more details.
+ """
@staticmethod
def forward(ctx, target: torch.Tensor,
... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/ops/three_nn.py |
Add docstrings that explain inputs and outputs | # 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):
def scatter_map(obj):
if isinstance(obj, torch.Tensor):
... | --- +++ @@ -7,6 +7,11 @@
def scatter(inputs, target_gpus, dim=0):
+ """Scatter inputs to target gpus.
+
+ The only difference from original :func:`scatter` is to add support for
+ :type:`~mmcv.parallel.DataContainer`.
+ """
def scatter_map(obj):
if isinstance(obj, torch.Tensor):
@@ -42,6... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/parallel/scatter_gather.py |
Add docstrings with type hints explained | # Copyright (c) OpenMMLab. All rights reserved.
import os
import os.path as osp
import subprocess
import tempfile
from annotator.mmpkg.mmcv.utils import requires_executable
@requires_executable('ffmpeg')
def convert_video(in_file,
out_file,
print_cmd=False,
pre_o... | --- +++ @@ -13,6 +13,24 @@ print_cmd=False,
pre_options='',
**kwargs):
+ """Convert a video with ffmpeg.
+
+ This provides a general api to ffmpeg, the executed command is::
+
+ `ffmpeg -y <pre_options> -i <in_file> <options> <out_file>`
+
+ Option... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/video/processing.py |
Add verbose docstrings with examples | # Copyright (c) OpenMMLab. All rights reserved.
from enum import Enum
import numpy as np
from annotator.mmpkg.mmcv.utils import is_str
class Color(Enum):
red = (0, 0, 255)
green = (0, 255, 0)
blue = (255, 0, 0)
cyan = (255, 255, 0)
yellow = (0, 255, 255)
magenta = (255, 0, 255)
white = (... | --- +++ @@ -7,6 +7,10 @@
class Color(Enum):
+ """An enum that defines common colors.
+
+ Contains red, green, blue, cyan, yellow, magenta, white and black.
+ """
red = (0, 0, 255)
green = (0, 255, 0)
blue = (255, 0, 0)
@@ -18,6 +22,14 @@
def color_val(color):
+ """Convert various inpu... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/visualization/color.py |
Generate consistent docstrings | # Copyright (c) OpenMMLab. All rights reserved.
import cv2
import numpy as np
from annotator.mmpkg.mmcv.image import imread, imwrite
from .color import color_val
def imshow(img, win_name='', wait_time=0):
cv2.imshow(win_name, imread(img))
if wait_time == 0: # prevent from hanging if windows was closed
... | --- +++ @@ -7,6 +7,13 @@
def imshow(img, win_name='', wait_time=0):
+ """Show an image.
+
+ Args:
+ img (str or ndarray): The image to be displayed.
+ win_name (str): The window name.
+ wait_time (int): Value of waitKey param.
+ """
cv2.imshow(win_name, imread(img))
if wait_t... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/visualization/image.py |
Add docstrings to improve collaboration | import matplotlib.pyplot as plt
import annotator.mmpkg.mmcv as mmcv
import torch
from annotator.mmpkg.mmcv.parallel import collate, scatter
from annotator.mmpkg.mmcv.runner import load_checkpoint
from annotator.mmpkg.mmseg.datasets.pipelines import Compose
from annotator.mmpkg.mmseg.models import build_segmentor
from ... | --- +++ @@ -10,6 +10,18 @@
def init_segmentor(config, checkpoint=None, device=devices.get_device_for("controlnet")):
+ """Initialize a segmentor from config file.
+
+ Args:
+ config (str or :obj:`mmcv.Config`): Config file path or the config
+ object.
+ checkpoint (str, optional): Che... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/apis/inference.py |
Generate consistent documentation across files | import annotator.mmpkg.mmcv as mmcv
def cityscapes_classes():
return [
'road', 'sidewalk', 'building', 'wall', 'fence', 'pole',
'traffic light', 'traffic sign', 'vegetation', 'terrain', 'sky',
'person', 'rider', 'car', 'truck', 'bus', 'train', 'motorcycle',
'bicycle'
]
def ad... | --- +++ @@ -2,6 +2,7 @@
def cityscapes_classes():
+ """Cityscapes class names for external use."""
return [
'road', 'sidewalk', 'building', 'wall', 'fence', 'pole',
'traffic light', 'traffic sign', 'vegetation', 'terrain', 'sky',
@@ -11,6 +12,7 @@
def ade_classes():
+ """ADE20K clas... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/core/evaluation/class_names.py |
Document functions with detailed explanations | from collections import OrderedDict
import annotator.mmpkg.mmcv as mmcv
import numpy as np
import torch
def f_score(precision, recall, beta=1):
score = (1 + beta**2) * (precision * recall) / (
(beta**2 * precision) + recall)
return score
def intersect_and_union(pred_label,
l... | --- +++ @@ -6,6 +6,17 @@
def f_score(precision, recall, beta=1):
+ """calcuate the f-score value.
+
+ Args:
+ precision (float | torch.Tensor): The precision value.
+ recall (float | torch.Tensor): The recall value.
+ beta (int): Determines the weight of recall in the combined score.
+ ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/core/evaluation/metrics.py |
Generate documentation strings for clarity | import os.path as osp
from annotator.mmpkg.mmcv.runner import DistEvalHook as _DistEvalHook
from annotator.mmpkg.mmcv.runner import EvalHook as _EvalHook
class EvalHook(_EvalHook):
greater_keys = ['mIoU', 'mAcc', 'aAcc']
def __init__(self, *args, by_epoch=False, efficient_test=False, **kwargs):
sup... | --- +++ @@ -5,6 +5,17 @@
class EvalHook(_EvalHook):
+ """Single GPU EvalHook, with efficient test support.
+
+ Args:
+ by_epoch (bool): Determine perform evaluation by epoch or by iteration.
+ If set to True, it will perform by epoch. Otherwise, by iteration.
+ Default: False.
+ ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/core/evaluation/eval_hooks.py |
Add docstrings to improve collaboration | # Copyright (c) OpenMMLab. All rights reserved.
from __future__ import division
import numpy as np
from annotator.mmpkg.mmcv.image import rgb2bgr
from annotator.mmpkg.mmcv.video import flowread
from .image import imshow
def flowshow(flow, win_name='', wait_time=0):
flow = flowread(flow)
flow_img = flow2rgb(... | --- +++ @@ -9,12 +9,31 @@
def flowshow(flow, win_name='', wait_time=0):
+ """Show optical flow.
+
+ Args:
+ flow (ndarray or str): The optical flow to be displayed.
+ win_name (str): The window name.
+ wait_time (int): Value of waitKey param.
+ """
flow = flowread(flow)
flow_... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/visualization/optflow.py |
Add docstrings to improve code quality | import torch
import torch.nn.functional as F
from ..builder import PIXEL_SAMPLERS
from .base_pixel_sampler import BasePixelSampler
@PIXEL_SAMPLERS.register_module()
class OHEMPixelSampler(BasePixelSampler):
def __init__(self, context, thresh=None, min_kept=100000):
super(OHEMPixelSampler, self).__init__... | --- +++ @@ -7,6 +7,18 @@
@PIXEL_SAMPLERS.register_module()
class OHEMPixelSampler(BasePixelSampler):
+ """Online Hard Example Mining Sampler for segmentation.
+
+ Args:
+ context (nn.Module): The context of sampler, subclass of
+ :obj:`BaseDecodeHead`.
+ thresh (float, optional): The t... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/core/seg/sampler/ohem_pixel_sampler.py |
Add standardized docstrings across the file | import os.path as osp
import tempfile
import annotator.mmpkg.mmcv as mmcv
import numpy as np
from annotator.mmpkg.mmcv.utils import print_log
from PIL import Image
from .builder import DATASETS
from .custom import CustomDataset
@DATASETS.register_module()
class CityscapesDataset(CustomDataset):
CLASSES = ('roa... | --- +++ @@ -12,6 +12,11 @@
@DATASETS.register_module()
class CityscapesDataset(CustomDataset):
+ """Cityscapes dataset.
+
+ The ``img_suffix`` is fixed to '_leftImg8bit.png' and ``seg_map_suffix`` is
+ fixed to '_gtFine_labelTrainIds.png' for Cityscapes dataset.
+ """
CLASSES = ('road', 'sidewalk'... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/datasets/cityscapes.py |
Write docstrings for this repository | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from torch.nn.parallel.distributed import (DistributedDataParallel,
_find_tensors)
from annotator.mmpkg.mmcv import print_log
from annotator.mmpkg.mmcv.utils import TORCH_VERSION, digit_version
from .scatter_gather ... | --- +++ @@ -9,6 +9,14 @@
class MMDistributedDataParallel(DistributedDataParallel):
+ """The DDP module that supports DataContainer.
+
+ MMDDP has two main differences with PyTorch DDP:
+
+ - It supports a custom type :class:`DataContainer` which allows more
+ flexible control of input data.
+ - It ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/parallel/distributed.py |
Document this module using docstrings | import os
import os.path as osp
from collections import OrderedDict
from functools import reduce
import annotator.mmpkg.mmcv as mmcv
import numpy as np
from annotator.mmpkg.mmcv.utils import print_log
from torch.utils.data import Dataset
from annotator.mmpkg.mmseg.core import eval_metrics
from annotator.mmpkg.mmseg.u... | --- +++ @@ -16,6 +16,56 @@
@DATASETS.register_module()
class CustomDataset(Dataset):
+ """Custom dataset for semantic segmentation. An example of file structure
+ is as followed.
+
+ .. code-block:: none
+
+ ├── data
+ │ ├── my_dataset
+ │ │ ├── img_dir
+ │ │ │ ├── tr... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/datasets/custom.py |
Insert docstrings into my code | from torch.utils.data.dataset import ConcatDataset as _ConcatDataset
from .builder import DATASETS
@DATASETS.register_module()
class ConcatDataset(_ConcatDataset):
def __init__(self, datasets):
super(ConcatDataset, self).__init__(datasets)
self.CLASSES = datasets[0].CLASSES
self.PALETTE ... | --- +++ @@ -5,6 +5,14 @@
@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 ratio.
+
+ Args:
+ datasets (list[:obj:`Dataset`]): A list of da... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/datasets/dataset_wrappers.py |
Generate documentation strings for clarity | import collections
from annotator.mmpkg.mmcv.utils import build_from_cfg
from ..builder import PIPELINES
@PIPELINES.register_module()
class Compose(object):
def __init__(self, transforms):
assert isinstance(transforms, collections.abc.Sequence)
self.transforms = []
for transform in tran... | --- +++ @@ -7,6 +7,12 @@
@PIPELINES.register_module()
class Compose(object):
+ """Compose multiple transforms sequentially.
+
+ Args:
+ transforms (Sequence[dict | callable]): Sequence of transform object or
+ config dict to be composed.
+ """
def __init__(self, transforms):
... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/datasets/pipelines/compose.py |
Add professional docstrings to my codebase | import os.path as osp
import annotator.mmpkg.mmcv as mmcv
import numpy as np
from ..builder import PIPELINES
@PIPELINES.register_module()
class LoadImageFromFile(object):
def __init__(self,
to_float32=False,
color_type='color',
file_client_args=dict(backend='d... | --- +++ @@ -8,6 +8,25 @@
@PIPELINES.register_module()
class LoadImageFromFile(object):
+ """Load an image from file.
+
+ Required keys are "img_prefix" and "img_info" (a dict that must contain the
+ key "filename"). Added or updated keys are "filename", "img", "img_shape",
+ "ori_shape" (same as `img_sha... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/datasets/pipelines/loading.py |
Add concise docstrings to each method | import os.path as osp
from .builder import DATASETS
from .custom import CustomDataset
@DATASETS.register_module()
class PascalContextDataset(CustomDataset):
CLASSES = ('background', 'aeroplane', 'bag', 'bed', 'bedclothes', 'bench',
'bicycle', 'bird', 'boat', 'book', 'bottle', 'building', 'bus',
... | --- +++ @@ -6,6 +6,16 @@
@DATASETS.register_module()
class PascalContextDataset(CustomDataset):
+ """PascalContext dataset.
+
+ In segmentation map annotation for PascalContext, 0 stands for background,
+ which is included in 60 categories. ``reduce_zero_label`` is fixed to
+ False. The ``img_suffix`` is... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/datasets/pascal_context.py |
Write docstrings for backend logic | from collections.abc import Sequence
import annotator.mmpkg.mmcv as mmcv
import numpy as np
import torch
from annotator.mmpkg.mmcv.parallel import DataContainer as DC
from ..builder import PIPELINES
def to_tensor(data):
if isinstance(data, torch.Tensor):
return data
elif isinstance(data, np.ndarray... | --- +++ @@ -9,6 +9,15 @@
def to_tensor(data):
+ """Convert objects of various python types to :obj:`torch.Tensor`.
+
+ Supported types are: :class:`numpy.ndarray`, :class:`torch.Tensor`,
+ :class:`Sequence`, :class:`int` and :class:`float`.
+
+ Args:
+ data (torch.Tensor | numpy.ndarray | Sequenc... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/datasets/pipelines/formating.py |
Add docstrings to improve code quality | import annotator.mmpkg.mmcv as mmcv
import numpy as np
from annotator.mmpkg.mmcv.utils import deprecated_api_warning, is_tuple_of
from numpy import random
from ..builder import PIPELINES
@PIPELINES.register_module()
class Resize(object):
def __init__(self,
img_scale=None,
multi... | --- +++ @@ -8,6 +8,35 @@
@PIPELINES.register_module()
class Resize(object):
+ """Resize images & seg.
+
+ This transform resizes the input image to some scale. If the input dict
+ contains the key "scale", then the scale in the input dict is used,
+ otherwise the specified scale in the init method is use... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/datasets/pipelines/transforms.py |
Document this module using docstrings | import torch
import torch.nn as nn
from annotator.mmpkg.mmcv.cnn import (ConvModule, DepthwiseSeparableConvModule, constant_init,
kaiming_init)
from torch.nn.modules.batchnorm import _BatchNorm
from annotator.mmpkg.mmseg.models.decode_heads.psp_head import PPM
from annotator.mmpkg.mmseg.ops impor... | --- +++ @@ -11,6 +11,20 @@
class LearningToDownsample(nn.Module):
+ """Learning to downsample module.
+
+ Args:
+ in_channels (int): Number of input channels.
+ dw_channels (tuple[int]): Number of output channels of the first and
+ the second depthwise conv (dwconv) layers.
+ o... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/backbones/fast_scnn.py |
Add docstrings including usage examples | import torch
import torch.nn as nn
import torch.utils.checkpoint as cp
from annotator.mmpkg.mmcv.cnn import (ConvModule, build_conv_layer, build_norm_layer,
constant_init, kaiming_init)
from annotator.mmpkg.mmcv.runner import load_checkpoint
from annotator.mmpkg.mmcv.utils.parrots_wrapper import _... | --- +++ @@ -11,6 +11,17 @@
class GlobalContextExtractor(nn.Module):
+ """Global Context Extractor for CGNet.
+
+ This class is employed to refine the joint feature of both local feature
+ and surrounding context.
+
+ Args:
+ channel (int): Number of input feature channels.
+ reduction (int... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/backbones/cgnet.py |
Replace inline comments with docstrings | import math
from annotator.mmpkg.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):
def __init__(self,
inplanes,
... | --- +++ @@ -9,6 +9,11 @@
class Bottleneck(_Bottleneck):
+ """Bottleneck block for ResNeXt.
+
+ If style is "pytorch", the stride-two layer is the 3x3 conv layer, if it is
+ "caffe", the stride-two layer is the first 1x1 conv layer.
+ """
def __init__(self,
inplanes,
@@ -80,6 +85... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/backbones/resnext.py |
Add docstrings to meet PEP guidelines | # 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):
__metaclass__ = ABCMeta
def __init__(self,
interval=10,
ignore_last=True,
... | --- +++ @@ -9,6 +9,15 @@
class LoggerHook(Hook):
+ """Base class for logger hooks.
+
+ Args:
+ interval (int): Logging interval (every k iterations).
+ ignore_last (bool): Ignore the log of last iterations in each epoch
+ if less than `interval`.
+ reset_flag (bool): Whether to... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/runner/hooks/logger/base.py |
Write proper docstrings for these functions | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint as cp
from annotator.mmpkg.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 ResN... | --- +++ @@ -13,6 +13,12 @@
class RSoftmax(nn.Module):
+ """Radix Softmax module in ``SplitAttentionConv2d``.
+
+ Args:
+ radix (int): Radix of input.
+ groups (int): Groups of input.
+ """
def __init__(self, radix, groups):
super().__init__()
@@ -31,6 +37,23 @@
class Split... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/backbones/resnest.py |
Add docstrings to clarify complex logic |
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint as cp
from annotator.mmpkg.mmcv.cnn import (Conv2d, Linear, build_activation_layer, build_norm_layer,
constant_init, kaiming_init, normal_init)
from annotator.mmpkg.mmcv.runner import _lo... | --- +++ @@ -1,3 +1,5 @@+"""Modified from https://github.com/rwightman/pytorch-image-
+models/blob/master/timm/models/vision_transformer.py."""
import math
@@ -16,6 +18,20 @@
class Mlp(nn.Module):
+ """MLP layer for Encoder block.
+
+ Args:
+ in_features(int): Input dimension for the first fully
+ ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/backbones/vit.py |
Write beginner-friendly docstrings | import logging
import torch.nn as nn
from annotator.mmpkg.mmcv.cnn import ConvModule, constant_init, kaiming_init
from annotator.mmpkg.mmcv.runner import load_checkpoint
from torch.nn.modules.batchnorm import _BatchNorm
from ..builder import BACKBONES
from ..utils import InvertedResidual, make_divisible
@BACKBONES.... | --- +++ @@ -11,6 +11,31 @@
@BACKBONES.register_module()
class MobileNetV2(nn.Module):
+ """MobileNetV2 backbone.
+
+ Args:
+ widen_factor (float): Width multiplier, multiply number of
+ channels in each layer by this amount. Default: 1.0.
+ strides (Sequence[int], optional): Strides of... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/backbones/mobilenet_v2.py |
Please document this code using docstrings | import math
import torch
import torch.distributed as dist
import torch.nn as nn
import torch.nn.functional as F
from annotator.mmpkg.mmcv.cnn import ConvModule
from ..builder import HEADS
from .decode_head import BaseDecodeHead
def reduce_mean(tensor):
if not (dist.is_available() and dist.is_initialized()):
... | --- +++ @@ -11,6 +11,7 @@
def reduce_mean(tensor):
+ """Reduce mean when distributed training."""
if not (dist.is_available() and dist.is_initialized()):
return tensor
tensor = tensor.clone()
@@ -19,6 +20,13 @@
class EMAModule(nn.Module):
+ """Expectation Maximization Attention Module u... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/decode_heads/ema_head.py |
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