instruction stringclasses 100
values | code stringlengths 78 193k | response stringlengths 259 170k | file stringlengths 59 203 |
|---|---|---|---|
Help me write clear docstrings | import torch
import torch.nn.functional as F
from annotator.mmpkg.mmcv.cnn import ConvModule, Scale
from torch import nn
from annotator.mmpkg.mmseg.core import add_prefix
from ..builder import HEADS
from ..utils import SelfAttentionBlock as _SelfAttentionBlock
from .decode_head import BaseDecodeHead
class PAM(_SelfA... | --- +++ @@ -10,6 +10,12 @@
class PAM(_SelfAttentionBlock):
+ """Position Attention Module (PAM)
+
+ Args:
+ in_channels (int): Input channels of key/query feature.
+ channels (int): Output channels of key/query transform.
+ """
def __init__(self, in_channels, channels):
super(... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/decode_heads/da_head.py |
Add return value explanations in docstrings | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import torch
from torch.nn import GroupNorm, LayerNorm
from annotator.mmpkg.mmcv.utils import _BatchNorm, _InstanceNorm, build_from_cfg, is_list_of
from annotator.mmpkg.mmcv.utils.ext_loader import check_ops_exist
from .builder import OPTIMIZER_BUILDERS,... | --- +++ @@ -11,6 +11,86 @@
@OPTIMIZER_BUILDERS.register_module()
class DefaultOptimizerConstructor:
+ """Default constructor for optimizers.
+
+ By default each parameter share the same optimizer settings, and we
+ provide an argument ``paramwise_cfg`` to specify parameter-wise settings.
+ It is a dict a... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/runner/optimizer/default_constructor.py |
Improve documentation using docstrings | # 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.mmpkg.mmcv.utils import TORCH_VERSION, _BatchNorm, digit_version
from ..dist_utils import allreduce_grads
from ..fp16_utils import LossScaler,... | --- +++ @@ -44,6 +44,22 @@
@HOOKS.register_module()
class GradientCumulativeOptimizerHook(OptimizerHook):
+ """Optimizer Hook implements multi-iters gradient cumulating.
+
+ Args:
+ cumulative_iters (int, optional): Num of gradient cumulative iters.
+ The optimizer will step every `cumulative... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/runner/hooks/optimizer.py |
Add missing documentation to my Python functions | # Modified from https://github.com/facebookresearch/detectron2/tree/master/projects/PointRend/point_head/point_head.py # noqa
import torch
import torch.nn as nn
try:
from mmcv.cnn import ConvModule, normal_init
from mmcv.ops import point_sample
except ImportError:
from annotator.mmpkg.mmcv.cnn import Co... | --- +++ @@ -17,12 +17,50 @@
def calculate_uncertainty(seg_logits):
+ """Estimate uncertainty based on seg logits.
+
+ For each location of the prediction ``seg_logits`` we estimate
+ uncertainty as the difference between top first and top second
+ predicted logits.
+
+ Args:
+ seg_logits (Tens... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/decode_heads/point_head.py |
Generate docstrings for script automation | from abc import ABCMeta, abstractmethod
from .decode_head import BaseDecodeHead
class BaseCascadeDecodeHead(BaseDecodeHead, metaclass=ABCMeta):
def __init__(self, *args, **kwargs):
super(BaseCascadeDecodeHead, self).__init__(*args, **kwargs)
@abstractmethod
def forward(self, inputs, prev_output... | --- +++ @@ -4,20 +4,54 @@
class BaseCascadeDecodeHead(BaseDecodeHead, metaclass=ABCMeta):
+ """Base class for cascade decode head used in
+ :class:`CascadeEncoderDecoder."""
def __init__(self, *args, **kwargs):
super(BaseCascadeDecodeHead, self).__init__(*args, **kwargs)
@abstractmethod... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/decode_heads/cascade_decode_head.py |
Add docstrings that explain inputs and outputs | import torch
import torch.nn as nn
from annotator.mmpkg.mmcv.cnn import ConvModule
from annotator.mmpkg.mmseg.ops import resize
from ..builder import HEADS
from .decode_head import BaseDecodeHead
class ASPPModule(nn.ModuleList):
def __init__(self, dilations, in_channels, channels, conv_cfg, norm_cfg,
... | --- +++ @@ -8,6 +8,16 @@
class ASPPModule(nn.ModuleList):
+ """Atrous Spatial Pyramid Pooling (ASPP) Module.
+
+ Args:
+ dilations (tuple[int]): Dilation rate of each layer.
+ in_channels (int): Input channels.
+ channels (int): Channels after modules, before conv_seg.
+ conv_cfg (... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/decode_heads/aspp_head.py |
Add docstrings to my Python code | import torch
import torch.nn as nn
import torch.nn.functional as F
from annotator.mmpkg.mmcv.cnn import ConvModule, build_norm_layer
from annotator.mmpkg.mmseg.ops import Encoding, resize
from ..builder import HEADS, build_loss
from .decode_head import BaseDecodeHead
class EncModule(nn.Module):
def __init__(sel... | --- +++ @@ -9,6 +9,15 @@
class EncModule(nn.Module):
+ """Encoding Module used in EncNet.
+
+ Args:
+ in_channels (int): Input channels.
+ num_codes (int): Number of code words.
+ conv_cfg (dict|None): Config of conv layers.
+ norm_cfg (dict|None): Config of norm layers.
+ a... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/decode_heads/enc_head.py |
Add clean documentation to messy code | import torch
import torch.nn as nn
import torch.nn.functional as F
from annotator.mmpkg.mmcv.cnn import ConvModule
from annotator.mmpkg.mmseg.ops import resize
from ..builder import HEADS
from ..utils import SelfAttentionBlock as _SelfAttentionBlock
from .cascade_decode_head import BaseCascadeDecodeHead
class Spatia... | --- +++ @@ -10,12 +10,18 @@
class SpatialGatherModule(nn.Module):
+ """Aggregate the context features according to the initial predicted
+ probability distribution.
+
+ Employ the soft-weighted method to aggregate the context.
+ """
def __init__(self, scale):
super(SpatialGatherModule, s... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/decode_heads/ocr_head.py |
Add documentation for all methods | import torch.nn as nn
import torch.utils.checkpoint as cp
from annotator.mmpkg.mmcv.cnn import (UPSAMPLE_LAYERS, ConvModule, build_activation_layer,
build_norm_layer, constant_init, kaiming_init)
from annotator.mmpkg.mmcv.runner import load_checkpoint
from annotator.mmpkg.mmcv.utils.parrots_wrappe... | --- +++ @@ -11,6 +11,34 @@
class BasicConvBlock(nn.Module):
+ """Basic convolutional block for UNet.
+
+ This module consists of several plain convolutional layers.
+
+ Args:
+ in_channels (int): Number of input channels.
+ out_channels (int): Number of output channels.
+ num_convs (in... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/backbones/unet.py |
Generate docstrings for this script |
import annotator.mmpkg.mmcv as mmcv
import torch
import torch.nn as nn
import torch.nn.functional as F
from ..builder import LOSSES
from .utils import get_class_weight, weight_reduce_loss
def lovasz_grad(gt_sorted):
p = len(gt_sorted)
gts = gt_sorted.sum()
intersection = gts - gt_sorted.float().cumsum(0... | --- +++ @@ -1,3 +1,6 @@+"""Modified from https://github.com/bermanmaxim/LovaszSoftmax/blob/master/pytor
+ch/lovasz_losses.py Lovasz-Softmax and Jaccard hinge loss in PyTorch Maxim
+Berman 2018 ESAT-PSI KU Leuven (MIT License)"""
import annotator.mmpkg.mmcv as mmcv
import torch
@@ -9,6 +12,10 @@
def lovasz_grad(... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/losses/lovasz_loss.py |
Document this module using docstrings | import torch
import torch.nn as nn
from annotator.mmpkg.mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from annotator.mmpkg.mmseg.ops import resize
from ..builder import HEADS
from .aspp_head import ASPPHead, ASPPModule
class DepthwiseSeparableASPPModule(ASPPModule):
def __init__(self, **kwargs):
... | --- +++ @@ -8,6 +8,8 @@
class DepthwiseSeparableASPPModule(ASPPModule):
+ """Atrous Spatial Pyramid Pooling (ASPP) Module with depthwise separable
+ conv."""
def __init__(self, **kwargs):
super(DepthwiseSeparableASPPModule, self).__init__(**kwargs)
@@ -25,6 +27,17 @@
@HEADS.register_module()... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/decode_heads/sep_aspp_head.py |
Generate consistent docstrings | import torch
import torch.nn as nn
from annotator.mmpkg.mmcv.cnn import ConvModule
from annotator.mmpkg.mmseg.ops import resize
from ..builder import HEADS
from .decode_head import BaseDecodeHead
from .psp_head import PPM
@HEADS.register_module()
class UPerHead(BaseDecodeHead):
def __init__(self, pool_scales=(1... | --- +++ @@ -10,6 +10,15 @@
@HEADS.register_module()
class UPerHead(BaseDecodeHead):
+ """Unified Perceptual Parsing for Scene Understanding.
+
+ This head is the implementation of `UPerNet
+ <https://arxiv.org/abs/1807.10221>`_.
+
+ Args:
+ pool_scales (tuple[int]): Pooling scales used in Pooling ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/decode_heads/uper_head.py |
Write reusable docstrings | import torch
import torch.nn as nn
import torch.nn.functional as F
from ..builder import LOSSES
from .utils import get_class_weight, weight_reduce_loss
def cross_entropy(pred,
label,
weight=None,
class_weight=None,
reduction='mean',
... | --- +++ @@ -13,6 +13,7 @@ reduction='mean',
avg_factor=None,
ignore_index=-100):
+ """The wrapper function for :func:`F.cross_entropy`"""
# class_weight is a manual rescaling weight given to each class.
# If given, has to be a Tensor of size C element... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/losses/cross_entropy_loss.py |
Write beginner-friendly docstrings | import functools
import annotator.mmpkg.mmcv as mmcv
import numpy as np
import torch.nn.functional as F
def get_class_weight(class_weight):
if isinstance(class_weight, str):
# take it as a file path
if class_weight.endswith('.npy'):
class_weight = np.load(class_weight)
else:
... | --- +++ @@ -6,6 +6,12 @@
def get_class_weight(class_weight):
+ """Get class weight for loss function.
+
+ Args:
+ class_weight (list[float] | str | None): If class_weight is a str,
+ take it as a file name and read from it.
+ """
if isinstance(class_weight, str):
# take it a... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/losses/utils.py |
Create documentation for each function signature | import torch
import torch.nn as nn
import torch.nn.functional as F
from ..builder import LOSSES
from .utils import get_class_weight, weighted_loss
@weighted_loss
def dice_loss(pred,
target,
valid_mask,
smooth=1,
exponent=2,
class_weight=None,
... | --- +++ @@ -1,3 +1,5 @@+"""Modified from https://github.com/LikeLy-Journey/SegmenTron/blob/master/
+segmentron/solver/loss.py (Apache-2.0 License)"""
import torch
import torch.nn as nn
import torch.nn.functional as F
@@ -46,6 +48,26 @@
@LOSSES.register_module()
class DiceLoss(nn.Module):
+ """DiceLoss.
+
+ ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/losses/dice_loss.py |
Write docstrings for algorithm functions | # Copyright (c) OpenMMLab. All rights reserved.
from ..dist_utils import allreduce_params
from .hook import HOOKS, Hook
@HOOKS.register_module()
class SyncBuffersHook(Hook):
def __init__(self, distributed=True):
self.distributed = distributed
def after_epoch(self, runner):
if self.distribute... | --- +++ @@ -5,10 +5,18 @@
@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): Whether distributed training is used. It is
+ effective only for distributed t... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/runner/hooks/sync_buffer.py |
Help me comply with documentation standards | import torch
import torch.nn as nn
from annotator.mmpkg.mmcv.cnn import ConvModule
from annotator.mmpkg.mmseg.ops import resize
from ..builder import HEADS
from .decode_head import BaseDecodeHead
class PPM(nn.ModuleList):
def __init__(self, pool_scales, in_channels, channels, conv_cfg, norm_cfg,
... | --- +++ @@ -8,6 +8,18 @@
class PPM(nn.ModuleList):
+ """Pooling Pyramid Module used in PSPNet.
+
+ Args:
+ pool_scales (tuple[int]): Pooling scales used in Pooling Pyramid
+ Module.
+ in_channels (int): Input channels.
+ channels (int): Channels after modules, before conv_seg.
... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/decode_heads/psp_head.py |
Document this module using docstrings | import logging
import warnings
from abc import ABCMeta, abstractmethod
from collections import OrderedDict
import annotator.mmpkg.mmcv as mmcv
import numpy as np
import torch
import torch.distributed as dist
import torch.nn as nn
from annotator.mmpkg.mmcv.runner import auto_fp16
class BaseSegmentor(nn.Module):
... | --- +++ @@ -12,6 +12,7 @@
class BaseSegmentor(nn.Module):
+ """Base class for segmentors."""
__metaclass__ = ABCMeta
@@ -21,43 +22,67 @@
@property
def with_neck(self):
+ """bool: whether the segmentor has neck"""
return hasattr(self, 'neck') and self.neck is not None
@p... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/segmentors/base.py |
Add docstrings to existing functions | from torch import nn
from annotator.mmpkg.mmseg.core import add_prefix
from annotator.mmpkg.mmseg.ops import resize
from .. import builder
from ..builder import SEGMENTORS
from .encoder_decoder import EncoderDecoder
@SEGMENTORS.register_module()
class CascadeEncoderDecoder(EncoderDecoder):
def __init__(self,
... | --- +++ @@ -9,6 +9,12 @@
@SEGMENTORS.register_module()
class CascadeEncoderDecoder(EncoderDecoder):
+ """Cascade Encoder Decoder segmentors.
+
+ CascadeEncoderDecoder almost the same as EncoderDecoder, while decoders of
+ CascadeEncoderDecoder are cascaded. The output of previous decoder_head
+ will be t... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/segmentors/cascade_encoder_decoder.py |
Write documentation strings for class attributes | from annotator.mmpkg.mmcv.cnn import ConvModule
from torch import nn
from torch.utils import checkpoint as cp
from .se_layer import SELayer
class InvertedResidual(nn.Module):
def __init__(self,
in_channels,
out_channels,
stride,
expand_ratio,
... | --- +++ @@ -6,6 +6,27 @@
class InvertedResidual(nn.Module):
+ """InvertedResidual block for MobileNetV2.
+
+ Args:
+ in_channels (int): The input channels of the InvertedResidual block.
+ out_channels (int): The output channels of the InvertedResidual block.
+ stride (int): Stride of the ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/utils/inverted_residual.py |
Generate descriptive docstrings automatically |
import torch
from torch import nn
class DropPath(nn.Module):
def __init__(self, drop_prob=0.):
super(DropPath, self).__init__()
self.drop_prob = drop_prob
self.keep_prob = 1 - drop_prob
def forward(self, x):
if self.drop_prob == 0. or not self.training:
return x
... | --- +++ @@ -1,9 +1,18 @@+"""Modified from https://github.com/rwightman/pytorch-image-
+models/blob/master/timm/models/layers/drop.py."""
import torch
from torch import nn
class DropPath(nn.Module):
+ """Drop paths (Stochastic Depth) per sample (when applied in main path of
+ residual blocks).
+
+ Arg... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/utils/drop.py |
Generate missing documentation strings | # 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... | --- +++ @@ -29,10 +29,32 @@
def is_str(x):
+ """Whether the input is an string instance.
+
+ Note: This method is deprecated since python 2 is no longer supported.
+ """
return isinstance(x, str)
def import_modules_from_strings(imports, allow_failed_imports=False):
+ """Import modules from the... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/utils/misc.py |
Help me add docstrings to my project | import torch
import torch.nn as nn
import torch.nn.functional as F
from annotator.mmpkg.mmseg.core import add_prefix
from annotator.mmpkg.mmseg.ops import resize
from .. import builder
from ..builder import SEGMENTORS
from .base import BaseSegmentor
@SEGMENTORS.register_module()
class EncoderDecoder(BaseSegmentor):
... | --- +++ @@ -11,6 +11,12 @@
@SEGMENTORS.register_module()
class EncoderDecoder(BaseSegmentor):
+ """Encoder Decoder segmentors.
+
+ EncoderDecoder typically consists of backbone, decode_head, auxiliary_head.
+ Note that auxiliary_head is only used for deep supervision during training,
+ which could be dum... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/segmentors/encoder_decoder.py |
Write docstrings for backend logic | # 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:
def __init__(self, task_num=0, bar_width=50, start=True, file=sys.stdout):
self.task_num = tas... | --- +++ @@ -8,6 +8,7 @@
class ProgressBar:
+ """A progress bar which can print the progress."""
def __init__(self, task_num=0, bar_width=50, start=True, file=sys.stdout):
self.task_num = task_num
@@ -61,6 +62,19 @@
def track_progress(func, tasks, bar_width=50, file=sys.stdout, **kwargs):
+ ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/utils/progressbar.py |
Generate helpful docstrings for debugging | import torch
from annotator.mmpkg.mmcv.cnn import ConvModule, constant_init
from torch import nn as nn
from torch.nn import functional as F
class SelfAttentionBlock(nn.Module):
def __init__(self, key_in_channels, query_in_channels, channels,
out_channels, share_key_query, query_downsample,
... | --- +++ @@ -5,6 +5,29 @@
class SelfAttentionBlock(nn.Module):
+ """General self-attention block/non-local block.
+
+ Please refer to https://arxiv.org/abs/1706.03762 for details about key,
+ query and value.
+
+ Args:
+ key_in_channels (int): Input channels of key feature.
+ query_in_chann... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/utils/self_attention_block.py |
Generate NumPy-style docstrings | # 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'):
logger = logging.getLogger(name)
if name in logger_initialized:
return logger
# handle hierarchical ... | --- +++ @@ -7,6 +7,27 @@
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
+ logger by adding one or two handlers, otherwise the initialized logger will
+ be di... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/utils/logging.py |
Generate documentation strings for clarity |
import math
import warnings
import torch
def _no_grad_trunc_normal_(tensor, mean, std, a, b):
def norm_cdf(x):
# Computes standard normal cumulative distribution function
return (1. + math.erf(x / math.sqrt(2.))) / 2.
if (mean < a - 2 * std) or (mean > b + 2 * std):
warnings.warn(
... | --- +++ @@ -1,3 +1,5 @@+"""Modified from https://github.com/rwightman/pytorch-image-
+models/blob/master/timm/models/layers/drop.py."""
import math
import warnings
@@ -6,6 +8,8 @@
def _no_grad_trunc_normal_(tensor, mean, std, a, b):
+ """Reference: https://people.sc.fsu.edu/~jburkardt/presentations
+ /tru... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/utils/weight_init.py |
Add docstrings including usage examples | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import cv2
import numpy as np
from annotator.mmpkg.mmcv.arraymisc import dequantize, quantize
from annotator.mmpkg.mmcv.image import imread, imwrite
from annotator.mmpkg.mmcv.utils import is_str
def flowread(flow_or_path, quantize=False, concat_axis=0,... | --- +++ @@ -10,6 +10,18 @@
def flowread(flow_or_path, quantize=False, concat_axis=0, *args, **kwargs):
+ """Read an optical flow map.
+
+ Args:
+ flow_or_path (ndarray or str): A flow map or filepath.
+ quantize (bool): whether to read quantized pair, if set to True,
+ remaining args ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/video/optflow.py |
Auto-generate documentation strings for this file | from torch import nn as nn
from torch.nn import functional as F
def swish(x, inplace: bool = False):
return x.mul_(x.sigmoid()) if inplace else x.mul(x.sigmoid())
class Swish(nn.Module):
def __init__(self, inplace: bool = False):
super(Swish, self).__init__()
self.inplace = inplace
def ... | --- +++ @@ -1,87 +1,102 @@-from torch import nn as nn
-from torch.nn import functional as F
-
-
-def swish(x, inplace: bool = False):
- return x.mul_(x.sigmoid()) if inplace else x.mul(x.sigmoid())
-
-
-class Swish(nn.Module):
- def __init__(self, inplace: bool = False):
- super(Swish, self).__init__()
- ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/normalbae/models/submodules/efficientnet_repo/geffnet/activations/activations.py |
Improve my code by adding docstrings |
import torch
from torch import nn as nn
from torch.nn import functional as F
__all__ = ['swish_jit', 'SwishJit', 'mish_jit', 'MishJit',
'hard_sigmoid_jit', 'HardSigmoidJit', 'hard_swish_jit', 'HardSwishJit']
@torch.jit.script
def swish_jit(x, inplace: bool = False):
return x.mul(x.sigmoid())
@torch... | --- +++ @@ -1,61 +1,79 @@-
-import torch
-from torch import nn as nn
-from torch.nn import functional as F
-
-__all__ = ['swish_jit', 'SwishJit', 'mish_jit', 'MishJit',
- 'hard_sigmoid_jit', 'HardSigmoidJit', 'hard_swish_jit', 'HardSwishJit']
-
-
-@torch.jit.script
-def swish_jit(x, inplace: bool = False):
- ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/normalbae/models/submodules/efficientnet_repo/geffnet/activations/activations_jit.py |
Write docstrings for data processing functions | from geffnet import config
from geffnet.activations.activations_me import *
from geffnet.activations.activations_jit import *
from geffnet.activations.activations import *
import torch
_has_silu = 'silu' in dir(torch.nn.functional)
_ACT_FN_DEFAULT = dict(
silu=F.silu if _has_silu else swish,
swish=F.silu if _... | --- +++ @@ -1,128 +1,137 @@-from geffnet import config
-from geffnet.activations.activations_me import *
-from geffnet.activations.activations_jit import *
-from geffnet.activations.activations import *
-import torch
-
-_has_silu = 'silu' in dir(torch.nn.functional)
-
-_ACT_FN_DEFAULT = dict(
- silu=F.silu if _has_s... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/normalbae/models/submodules/efficientnet_repo/geffnet/activations/__init__.py |
Document functions with detailed explanations | import torch.nn as nn
import torch.utils.checkpoint as cp
from annotator.mmpkg.mmcv.cnn import (build_conv_layer, build_norm_layer, build_plugin_layer,
constant_init, kaiming_init)
from annotator.mmpkg.mmcv.runner import load_checkpoint
from annotator.mmpkg.mmcv.utils.parrots_wrapper import _Batch... | --- +++ @@ -11,6 +11,7 @@
class BasicBlock(nn.Module):
+ """Basic block for ResNet."""
expansion = 1
@@ -55,13 +56,16 @@
@property
def norm1(self):
+ """nn.Module: normalization layer after the first convolution layer"""
return getattr(self, self.norm1_name)
@property
... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/backbones/resnet.py |
Add docstrings to improve collaboration | import torch.nn as nn
from annotator.mmpkg.mmcv.cnn import (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 _BatchNorm
from annotator.mmpkg.mmseg.ops import Upsample, re... | --- +++ @@ -11,6 +11,11 @@
class HRModule(nn.Module):
+ """High-Resolution Module for HRNet.
+
+ In this module, every branch has 4 BasicBlocks/Bottlenecks. Fusion/Exchange
+ is in this module.
+ """
def __init__(self,
num_branches,
@@ -40,6 +45,7 @@
def _check_branches(se... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/backbones/hrnet.py |
Write reusable docstrings | from typing import Any, Optional
__all__ = [
'is_exportable', 'is_scriptable', 'is_no_jit', 'layer_config_kwargs',
'set_exportable', 'set_scriptable', 'set_no_jit', 'set_layer_config'
]
# Set to True if prefer to have layers with no jit optimization (includes activations)
_NO_JIT = False
# Set to True if pre... | --- +++ @@ -1,117 +1,123 @@-from typing import Any, Optional
-
-__all__ = [
- 'is_exportable', 'is_scriptable', 'is_no_jit', 'layer_config_kwargs',
- 'set_exportable', 'set_scriptable', 'set_no_jit', 'set_layer_config'
-]
-
-# Set to True if prefer to have layers with no jit optimization (includes activations)
-_... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/normalbae/models/submodules/efficientnet_repo/geffnet/config.py |
Write docstrings for this repository | import os
class AverageMeter:
def __init__(self):
self.reset()
def reset(self):
self.val = 0
self.avg = 0
self.sum = 0
self.count = 0
def update(self, val, n=1):
self.val = val
self.sum += val * n
self.count += n
self.avg = self.sum... | --- +++ @@ -1,49 +1,52 @@-import os
-
-
-class AverageMeter:
- def __init__(self):
- self.reset()
-
- def reset(self):
- self.val = 0
- self.avg = 0
- self.sum = 0
- self.count = 0
-
- def update(self, val, n=1):
- self.val = val
- self.sum += val * n
- s... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/normalbae/models/submodules/efficientnet_repo/utils.py |
Write docstrings describing functionality | import copy
import platform
import random
from functools import partial
import numpy as np
from annotator.mmpkg.mmcv.parallel import collate
from annotator.mmpkg.mmcv.runner import get_dist_info
from annotator.mmpkg.mmcv.utils import Registry, build_from_cfg
from annotator.mmpkg.mmcv.utils.parrots_wrapper import DataL... | --- +++ @@ -23,6 +23,7 @@
def _concat_dataset(cfg, default_args=None):
+ """Build :obj:`ConcatDataset by."""
from .dataset_wrappers import ConcatDataset
img_dir = cfg['img_dir']
ann_dir = cfg.get('ann_dir', None)
@@ -58,6 +59,7 @@
def build_dataset(cfg, default_args=None):
+ """Build datase... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/datasets/builder.py |
Please document this code using docstrings | # 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):
assert 'parrots' not in version_str
version = parse(version_str)
assert version.release, f'failed to parse version {version... | --- +++ @@ -7,6 +7,18 @@
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
+ versions: alpha < beta < rc.
+
+ Args:
+ version_str (str): The version string.
+ ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmcv/utils/version_utils.py |
Generate NumPy-style docstrings | import torch
from annotator.mmpkg.mmcv.cnn import NonLocal2d
from torch import nn
from ..builder import HEADS
from .fcn_head import FCNHead
class DisentangledNonLocal2d(NonLocal2d):
def __init__(self, *arg, temperature, **kwargs):
super().__init__(*arg, **kwargs)
self.temperature = temperature
... | --- +++ @@ -7,6 +7,11 @@
class DisentangledNonLocal2d(NonLocal2d):
+ """Disentangled Non-Local Blocks.
+
+ Args:
+ temperature (float): Temperature to adjust attention. Default: 0.05
+ """
def __init__(self, *arg, temperature, **kwargs):
super().__init__(*arg, **kwargs)
@@ -14,6 +19,... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/decode_heads/dnl_head.py |
Generate descriptive docstrings automatically |
import torch
from torch import nn as nn
from torch.nn import functional as F
__all__ = ['swish_me', 'SwishMe', 'mish_me', 'MishMe',
'hard_sigmoid_me', 'HardSigmoidMe', 'hard_swish_me', 'HardSwishMe']
@torch.jit.script
def swish_jit_fwd(x):
return x.mul(torch.sigmoid(x))
@torch.jit.script
def swish... | --- +++ @@ -1,151 +1,174 @@-
-import torch
-from torch import nn as nn
-from torch.nn import functional as F
-
-
-__all__ = ['swish_me', 'SwishMe', 'mish_me', 'MishMe',
- 'hard_sigmoid_me', 'HardSigmoidMe', 'hard_swish_me', 'HardSwishMe']
-
-
-@torch.jit.script
-def swish_jit_fwd(x):
- return x.mul(torch.s... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/normalbae/models/submodules/efficientnet_repo/geffnet/activations/activations_me.py |
Write docstrings describing functionality | # Copyright (c) Facebook, Inc. and its affiliates.
import copy
import logging
import re
from typing import Dict, List
import torch
from tabulate import tabulate
def convert_basic_c2_names(original_keys):
layer_keys = copy.deepcopy(original_keys)
layer_keys = [
{"pred_b": "linear_b", "pred_w": "linear_... | --- +++ @@ -1,348 +1,412 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import copy
-import logging
-import re
-from typing import Dict, List
-import torch
-from tabulate import tabulate
-
-
-def convert_basic_c2_names(original_keys):
- layer_keys = copy.deepcopy(original_keys)
- layer_keys = [
- {... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/checkpoint/c2_model_loading.py |
Generate documentation strings for clarity | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import functools
import inspect
import logging
from fvcore.common.config import CfgNode as _CfgNode
from annotator.oneformer.detectron2.utils.file_io import PathManager
class CfgNode(_CfgNode):
@classmethod
def _open_cfg(cls, filena... | --- +++ @@ -1,168 +1,265 @@-# -*- coding: utf-8 -*-
-# Copyright (c) Facebook, Inc. and its affiliates.
-
-import functools
-import inspect
-import logging
-from fvcore.common.config import CfgNode as _CfgNode
-
-from annotator.oneformer.detectron2.utils.file_io import PathManager
-
-
-class CfgNode(_CfgNode):
-
- @... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/config/config.py |
Document my Python code with docstrings | # Copyright (c) Facebook, Inc. and its affiliates.
import ast
import builtins
import collections.abc as abc
import importlib
import inspect
import logging
import os
import uuid
from contextlib import contextmanager
from copy import deepcopy
from dataclasses import is_dataclass
from typing import List, Tuple, Union
imp... | --- +++ @@ -1,368 +1,435 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-
-import ast
-import builtins
-import collections.abc as abc
-import importlib
-import inspect
-import logging
-import os
-import uuid
-from contextlib import contextmanager
-from copy import deepcopy
-from dataclasses import is_dataclass
-... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/config/lazy.py |
Add return value explanations in docstrings | # Copyright (c) Facebook, Inc. and its affiliates.
import itertools
import logging
import numpy as np
import operator
import pickle
from typing import Any, Callable, Dict, List, Optional, Union
import torch
import torch.utils.data as torchdata
from tabulate import tabulate
from termcolor import colored
from annotator.... | --- +++ @@ -1,407 +1,556 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import itertools
-import logging
-import numpy as np
-import operator
-import pickle
-from typing import Any, Callable, Dict, List, Optional, Union
-import torch
-import torch.utils.data as torchdata
-from tabulate import tabulate
-from ter... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/data/build.py |
Add detailed docstrings explaining each function | # Copyright (c) Facebook, Inc. and its affiliates.
import copy
import logging
import types
from collections import UserDict
from typing import List
from annotator.oneformer.detectron2.utils.logger import log_first_n
__all__ = ["DatasetCatalog", "MetadataCatalog", "Metadata"]
class _DatasetCatalog(UserDict):
de... | --- +++ @@ -1,147 +1,236 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import copy
-import logging
-import types
-from collections import UserDict
-from typing import List
-
-from annotator.oneformer.detectron2.utils.logger import log_first_n
-
-__all__ = ["DatasetCatalog", "MetadataCatalog", "Metadata"]
-
-
-... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/data/catalog.py |
Add professional docstrings to my codebase | from abc import ABCMeta, abstractmethod
import torch
import torch.nn as nn
from annotator.mmpkg.mmcv.cnn import normal_init
from annotator.mmpkg.mmcv.runner import auto_fp16, force_fp32
from annotator.mmpkg.mmseg.core import build_pixel_sampler
from annotator.mmpkg.mmseg.ops import resize
from ..builder import build_... | --- +++ @@ -12,6 +12,36 @@
class BaseDecodeHead(nn.Module, metaclass=ABCMeta):
+ """Base class for BaseDecodeHead.
+
+ Args:
+ in_channels (int|Sequence[int]): Input channels.
+ channels (int): Channels after modules, before conv_seg.
+ num_classes (int): Number of classes.
+ dropo... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/decode_heads/decode_head.py |
Create docstrings for each class method | # Copyright (c) Facebook, Inc. and its affiliates.
import contextlib
import copy
import itertools
import logging
import numpy as np
import pickle
import random
from typing import Callable, Union
import torch
import torch.utils.data as data
from torch.utils.data.sampler import Sampler
from annotator.oneformer.detectron... | --- +++ @@ -1,216 +1,301 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import contextlib
-import copy
-import itertools
-import logging
-import numpy as np
-import pickle
-import random
-from typing import Callable, Union
-import torch
-import torch.utils.data as data
-from torch.utils.data.sampler import Samp... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/data/common.py |
Write reusable docstrings | # Copyright (c) Facebook, Inc. and its affiliates.
import collections.abc as abc
import dataclasses
import logging
from typing import Any
from annotator.oneformer.detectron2.utils.registry import _convert_target_to_string, locate
__all__ = ["dump_dataclass", "instantiate"]
def dump_dataclass(obj: Any):
assert ... | --- +++ @@ -1,68 +1,88 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-
-import collections.abc as abc
-import dataclasses
-import logging
-from typing import Any
-
-from annotator.oneformer.detectron2.utils.registry import _convert_target_to_string, locate
-
-__all__ = ["dump_dataclass", "instantiate"]
-
-
-def... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/config/instantiate.py |
Write docstrings that follow conventions | # Copyright (c) Facebook, Inc. and its affiliates.
import logging
import numpy as np
from itertools import count
from typing import List, Tuple
import torch
import tqdm
from fvcore.common.timer import Timer
from annotator.oneformer.detectron2.utils import comm
from .build import build_batch_data_loader
from .common i... | --- +++ @@ -1,180 +1,225 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import logging
-import numpy as np
-from itertools import count
-from typing import List, Tuple
-import torch
-import tqdm
-from fvcore.common.timer import Timer
-
-from annotator.oneformer.detectron2.utils import comm
-
-from .build import... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/data/benchmark.py |
Write clean docstrings for readability | import torch
import torch.nn as nn
import torch.nn.functional as F
from annotator.mmpkg.mmcv.cnn import ConvModule
from annotator.mmpkg.mmseg.ops import resize
from ..builder import HEADS
from .decode_head import BaseDecodeHead
class ACM(nn.Module):
def __init__(self, pool_scale, fusion, in_channels, channels, ... | --- +++ @@ -9,6 +9,18 @@
class ACM(nn.Module):
+ """Adaptive Context Module used in APCNet.
+
+ Args:
+ pool_scale (int): Pooling scale used in Adaptive Context
+ Module to extract region features.
+ fusion (bool): Add one conv to fuse residual feature.
+ in_channels (int): Inp... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/decode_heads/apc_head.py |
Generate consistent docstrings | # Copyright (c) Facebook, Inc. and its affiliates.
import copy
import logging
import numpy as np
from typing import List, Optional, Union
import torch
from annotator.oneformer.detectron2.config import configurable
from . import detection_utils as utils
from . import transforms as T
"""
This file contains the default... | --- +++ @@ -1,152 +1,191 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import copy
-import logging
-import numpy as np
-from typing import List, Optional, Union
-import torch
-
-from annotator.oneformer.detectron2.config import configurable
-
-from . import detection_utils as utils
-from . import transforms as... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/data/dataset_mapper.py |
Annotate my code with docstrings | # Copyright (c) Facebook, Inc. and its affiliates.
import functools
import json
import logging
import multiprocessing as mp
import numpy as np
import os
from itertools import chain
import annotator.oneformer.pycocotools.mask as mask_util
from PIL import Image
from annotator.oneformer.detectron2.structures import BoxMo... | --- +++ @@ -1,296 +1,329 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import functools
-import json
-import logging
-import multiprocessing as mp
-import numpy as np
-import os
-from itertools import chain
-import annotator.oneformer.pycocotools.mask as mask_util
-from PIL import Image
-
-from annotator.onefo... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/data/datasets/cityscapes.py |
Add minimal docstrings for each function | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import logging
import numpy as np
from typing import List, Union
import annotator.oneformer.pycocotools.mask as mask_util
import torch
from PIL import Image
from annotator.oneformer.detectron2.structures import (
BitMasks,
Boxes,
B... | --- +++ @@ -1,451 +1,659 @@-# -*- coding: utf-8 -*-
-# Copyright (c) Facebook, Inc. and its affiliates.
-
-import logging
-import numpy as np
-from typing import List, Union
-import annotator.oneformer.pycocotools.mask as mask_util
-import torch
-from PIL import Image
-
-from annotator.oneformer.detectron2.structures i... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/data/detection_utils.py |
Add docstrings for internal functions | import torch
import torch.nn as nn
from annotator.mmpkg.mmcv.cnn import ConvModule
from ..builder import HEADS
from ..utils import SelfAttentionBlock as _SelfAttentionBlock
from .decode_head import BaseDecodeHead
class PPMConcat(nn.ModuleList):
def __init__(self, pool_scales=(1, 3, 6, 8)):
super(PPMConc... | --- +++ @@ -8,12 +8,19 @@
class PPMConcat(nn.ModuleList):
+ """Pyramid Pooling Module that only concat the features of each layer.
+
+ Args:
+ pool_scales (tuple[int]): Pooling scales used in Pooling Pyramid
+ Module.
+ """
def __init__(self, pool_scales=(1, 3, 6, 8)):
sup... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/decode_heads/ann_head.py |
Generate missing documentation strings | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
import torch
import torch.nn.functional as F
from fvcore.transforms.transform import (
CropTransform,
HFlipTransform,
NoOpTransform,
Transform,
TransformList,
)
from PIL import Image
try:
import cv2 ... | --- +++ @@ -1,258 +1,351 @@-# -*- coding: utf-8 -*-
-# Copyright (c) Facebook, Inc. and its affiliates.
-
-
-import numpy as np
-import torch
-import torch.nn.functional as F
-from fvcore.transforms.transform import (
- CropTransform,
- HFlipTransform,
- NoOpTransform,
- Transform,
- TransformList,
-)
-f... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/data/transforms/transform.py |
Write documentation strings for class attributes | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import datetime
import itertools
import logging
import math
import operator
import os
import tempfile
import time
import warnings
from collections import Counter
import torch
from fvcore.common.checkpoint import Checkpointer
from fvcore.common.... | --- +++ @@ -1,517 +1,690 @@-# -*- coding: utf-8 -*-
-# Copyright (c) Facebook, Inc. and its affiliates.
-
-import datetime
-import itertools
-import logging
-import math
-import operator
-import os
-import tempfile
-import time
-import warnings
-from collections import Counter
-import torch
-from fvcore.common.checkpoi... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/engine/hooks.py |
Add docstrings for internal functions | # Copyright (c) Facebook, Inc. and its affiliates.
import datetime
import logging
import time
from collections import OrderedDict, abc
from contextlib import ExitStack, contextmanager
from typing import List, Union
import torch
from torch import nn
from annotator.oneformer.detectron2.utils.comm import get_world_size, ... | --- +++ @@ -1,148 +1,224 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import datetime
-import logging
-import time
-from collections import OrderedDict, abc
-from contextlib import ExitStack, contextmanager
-from typing import List, Union
-import torch
-from torch import nn
-
-from annotator.oneformer.detectr... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/evaluation/evaluator.py |
Help me comply with documentation standards | # Copyright (c) Facebook, Inc. and its affiliates.
import logging
import os
from fvcore.common.timer import Timer
from annotator.oneformer.detectron2.data import DatasetCatalog, MetadataCatalog
from annotator.oneformer.detectron2.structures import BoxMode
from annotator.oneformer.detectron2.utils.file_io import PathMa... | --- +++ @@ -1,202 +1,241 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import logging
-import os
-from fvcore.common.timer import Timer
-
-from annotator.oneformer.detectron2.data import DatasetCatalog, MetadataCatalog
-from annotator.oneformer.detectron2.structures import BoxMode
-from annotator.oneformer.det... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/data/datasets/lvis.py |
Provide docstrings following PEP 257 | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
import sys
from numpy import random
from typing import Tuple
import torch
from fvcore.transforms.transform import (
BlendTransform,
CropTransform,
HFlipTransform,
NoOpTransform,
PadTransform,
Transform,... | --- +++ @@ -1,507 +1,736 @@-# -*- coding: utf-8 -*-
-# Copyright (c) Facebook, Inc. and its affiliates.
-import numpy as np
-import sys
-from numpy import random
-from typing import Tuple
-import torch
-from fvcore.transforms.transform import (
- BlendTransform,
- CropTransform,
- HFlipTransform,
- NoOpTran... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/data/transforms/augmentation_impl.py |
Add docstrings to improve code quality | # Copyright (c) Facebook, Inc. and its affiliates.
import contextlib
import io
import itertools
import json
import logging
import numpy as np
import os
import tempfile
from collections import OrderedDict
from typing import Optional
from PIL import Image
from tabulate import tabulate
from annotator.oneformer.detectron2... | --- +++ @@ -1,188 +1,199 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import contextlib
-import io
-import itertools
-import json
-import logging
-import numpy as np
-import os
-import tempfile
-from collections import OrderedDict
-from typing import Optional
-from PIL import Image
-from tabulate import tabul... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/evaluation/panoptic_evaluation.py |
Add detailed documentation for each class | # Copyright (c) Facebook, Inc. and its affiliates.
import glob
import logging
import numpy as np
import os
import tempfile
from collections import OrderedDict
import torch
from PIL import Image
from annotator.oneformer.detectron2.data import MetadataCatalog
from annotator.oneformer.detectron2.utils import comm
from an... | --- +++ @@ -1,168 +1,197 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import glob
-import logging
-import numpy as np
-import os
-import tempfile
-from collections import OrderedDict
-import torch
-from PIL import Image
-
-from annotator.oneformer.detectron2.data import MetadataCatalog
-from annotator.oneform... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/evaluation/cityscapes_evaluation.py |
Generate docstrings for each module | # Copyright (c) Facebook, Inc. and its affiliates.
import itertools
import logging
import math
from collections import defaultdict
from typing import Optional
import torch
from torch.utils.data.sampler import Sampler
from annotator.oneformer.detectron2.utils import comm
logger = logging.getLogger(__name__)
class Tr... | --- +++ @@ -1,182 +1,278 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import itertools
-import logging
-import math
-from collections import defaultdict
-from typing import Optional
-import torch
-from torch.utils.data.sampler import Sampler
-
-from annotator.oneformer.detectron2.utils import comm
-
-logger =... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/data/samplers/distributed_sampler.py |
Add docstrings with type hints explained | # Copyright (c) Facebook, Inc. and its affiliates.
import copy
import itertools
import json
import logging
import os
import pickle
from collections import OrderedDict
import torch
import annotator.oneformer.detectron2.utils.comm as comm
from annotator.oneformer.detectron2.config import CfgNode
from annotator.oneformer... | --- +++ @@ -1,328 +1,380 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import copy
-import itertools
-import json
-import logging
-import os
-import pickle
-from collections import OrderedDict
-import torch
-
-import annotator.oneformer.detectron2.utils.comm as comm
-from annotator.oneformer.detectron2.config ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/evaluation/lvis_evaluation.py |
Add docstrings to improve code quality | # Copyright (c) Facebook, Inc. and its affiliates.
import copy
import logging
import numpy as np
import time
from annotator.oneformer.pycocotools.cocoeval import COCOeval
from annotator.oneformer.detectron2 import _C
logger = logging.getLogger(__name__)
class COCOeval_opt(COCOeval):
def evaluate(self):
... | --- +++ @@ -1,106 +1,121 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import copy
-import logging
-import numpy as np
-import time
-from annotator.oneformer.pycocotools.cocoeval import COCOeval
-
-from annotator.oneformer.detectron2 import _C
-
-logger = logging.getLogger(__name__)
-
-
-class COCOeval_opt(COC... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/evaluation/fast_eval_api.py |
Add standardized docstrings across the file | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import logging
import numpy as np
import time
import weakref
from typing import List, Mapping, Optional
import torch
from torch.nn.parallel import DataParallel, DistributedDataParallel
import annotator.oneformer.detectron2.utils.comm as comm
f... | --- +++ @@ -1,340 +1,469 @@-# -*- coding: utf-8 -*-
-# Copyright (c) Facebook, Inc. and its affiliates.
-
-import logging
-import numpy as np
-import time
-import weakref
-from typing import List, Mapping, Optional
-import torch
-from torch.nn.parallel import DataParallel, DistributedDataParallel
-
-import annotator.on... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/engine/train_loop.py |
Create structured documentation for my script | import torch
import torch.nn as nn
import torch.nn.functional as F
from annotator.mmpkg.mmcv.cnn import ConvModule, build_activation_layer, build_norm_layer
from ..builder import HEADS
from .decode_head import BaseDecodeHead
class DCM(nn.Module):
def __init__(self, filter_size, fusion, in_channels, channels, co... | --- +++ @@ -8,6 +8,18 @@
class DCM(nn.Module):
+ """Dynamic Convolutional Module used in DMNet.
+
+ Args:
+ filter_size (int): The filter size of generated convolution kernel
+ used in Dynamic Convolutional Module.
+ fusion (bool): Add one conv to fuse DCM output feature.
+ in_... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/decode_heads/dm_head.py |
Generate consistent documentation across files | # Copyright (c) Facebook, Inc. and its affiliates.
import contextlib
import copy
import io
import itertools
import json
import logging
import numpy as np
import os
import pickle
from collections import OrderedDict
import annotator.oneformer.pycocotools.mask as mask_util
import torch
from annotator.oneformer.pycocotools... | --- +++ @@ -1,613 +1,722 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import contextlib
-import copy
-import io
-import itertools
-import json
-import logging
-import numpy as np
-import os
-import pickle
-from collections import OrderedDict
-import annotator.oneformer.pycocotools.mask as mask_util
-import to... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/evaluation/coco_evaluation.py |
Fully document this Python code with docstrings | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import logging
import numpy as np
import os
import tempfile
import xml.etree.ElementTree as ET
from collections import OrderedDict, defaultdict
from functools import lru_cache
import torch
from annotator.oneformer.detectron2.data import Metada... | --- +++ @@ -1,260 +1,300 @@-# -*- coding: utf-8 -*-
-# Copyright (c) Facebook, Inc. and its affiliates.
-
-import logging
-import numpy as np
-import os
-import tempfile
-import xml.etree.ElementTree as ET
-from collections import OrderedDict, defaultdict
-from functools import lru_cache
-import torch
-
-from annotator... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/evaluation/pascal_voc_evaluation.py |
Create simple docstrings for beginners | # Copyright (c) Facebook, Inc. and its affiliates.
import itertools
import json
import numpy as np
import os
import torch
from annotator.oneformer.pycocotools.cocoeval import COCOeval, maskUtils
from annotator.oneformer.detectron2.structures import BoxMode, RotatedBoxes, pairwise_iou_rotated
from annotator.oneformer.d... | --- +++ @@ -1,187 +1,207 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import itertools
-import json
-import numpy as np
-import os
-import torch
-from annotator.oneformer.pycocotools.cocoeval import COCOeval, maskUtils
-
-from annotator.oneformer.detectron2.structures import BoxMode, RotatedBoxes, pairwise_io... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/evaluation/rotated_coco_evaluation.py |
Provide docstrings following PEP 257 | # Copyright (c) Facebook, Inc. and its affiliates.
import collections
import copy
import functools
import logging
import numpy as np
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
from unittest import mock
import caffe2.python.utils as putils
import torch
import torch.nn.functional as F... | --- +++ @@ -1,937 +1,1039 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-
-import collections
-import copy
-import functools
-import logging
-import numpy as np
-import os
-from typing import Any, Callable, Dict, List, Optional, Tuple, Union
-from unittest import mock
-import caffe2.python.utils as putils
-impo... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/export/shared.py |
Auto-generate documentation strings for this file | # Copyright (c) Facebook, Inc. and its affiliates.
import math
from typing import Dict
import torch
import torch.nn.functional as F
from annotator.oneformer.detectron2.layers import ShapeSpec, cat
from annotator.oneformer.detectron2.layers.roi_align_rotated import ROIAlignRotated
from annotator.oneformer.detectron2.m... | --- +++ @@ -1,533 +1,557 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-
-import math
-from typing import Dict
-import torch
-import torch.nn.functional as F
-
-from annotator.oneformer.detectron2.layers import ShapeSpec, cat
-from annotator.oneformer.detectron2.layers.roi_align_rotated import ROIAlignRotated
-... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/export/c10.py |
Improve documentation using docstrings | # Copyright (c) Facebook, Inc. and its affiliates.
import copy
import logging
import os
import torch
from caffe2.proto import caffe2_pb2
from torch import nn
from annotator.oneformer.detectron2.config import CfgNode
from annotator.oneformer.detectron2.utils.file_io import PathManager
from .caffe2_inference import Pro... | --- +++ @@ -1,113 +1,230 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import copy
-import logging
-import os
-import torch
-from caffe2.proto import caffe2_pb2
-from torch import nn
-
-from annotator.oneformer.detectron2.config import CfgNode
-from annotator.oneformer.detectron2.utils.file_io import PathManag... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/export/api.py |
Create Google-style docstrings for my code | # Copyright (c) Facebook, Inc. and its affiliates.
import os
import torch
from annotator.oneformer.detectron2.utils.file_io import PathManager
from .torchscript_patch import freeze_training_mode, patch_instances
__all__ = ["scripting_with_instances", "dump_torchscript_IR"]
def scripting_with_instances(model, fiel... | --- +++ @@ -1,88 +1,132 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-
-import os
-import torch
-
-from annotator.oneformer.detectron2.utils.file_io import PathManager
-
-from .torchscript_patch import freeze_training_mode, patch_instances
-
-__all__ = ["scripting_with_instances", "dump_torchscript_IR"]
-
-
-d... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/export/torchscript.py |
Add docstrings that explain purpose and usage | # Copyright (c) Facebook, Inc. and its affiliates.
import itertools
import json
import logging
import numpy as np
import os
from collections import OrderedDict
from typing import Optional, Union
import annotator.oneformer.pycocotools.mask as mask_util
import torch
from PIL import Image
from annotator.oneformer.detectr... | --- +++ @@ -1,231 +1,265 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import itertools
-import json
-import logging
-import numpy as np
-import os
-from collections import OrderedDict
-from typing import Optional, Union
-import annotator.oneformer.pycocotools.mask as mask_util
-import torch
-from PIL import I... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/evaluation/sem_seg_evaluation.py |
Can you add docstrings to this Python file? | # Copyright (c) Facebook, Inc. and its affiliates.
import functools
import io
import struct
import types
import torch
from annotator.oneformer.detectron2.modeling import meta_arch
from annotator.oneformer.detectron2.modeling.box_regression import Box2BoxTransform
from annotator.oneformer.detectron2.modeling.roi_heads... | --- +++ @@ -1,332 +1,419 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-
-import functools
-import io
-import struct
-import types
-import torch
-
-from annotator.oneformer.detectron2.modeling import meta_arch
-from annotator.oneformer.detectron2.modeling.box_regression import Box2BoxTransform
-from annotator.o... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/export/caffe2_modeling.py |
Add structured docstrings to improve clarity | # Copyright (c) Facebook, Inc. and its affiliates.
import os
import sys
import tempfile
from contextlib import ExitStack, contextmanager
from copy import deepcopy
from unittest import mock
import torch
from torch import nn
# need some explicit imports due to https://github.com/pytorch/pytorch/issues/38964
import anno... | --- +++ @@ -1,373 +1,406 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-
-import os
-import sys
-import tempfile
-from contextlib import ExitStack, contextmanager
-from copy import deepcopy
-from unittest import mock
-import torch
-from torch import nn
-
-# need some explicit imports due to https://github.com/p... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/export/torchscript_patch.py |
Generate descriptive docstrings automatically | # Copyright (c) Facebook, Inc. and its affiliates.
import collections
from dataclasses import dataclass
from typing import Callable, List, Optional, Tuple
import torch
from torch import nn
from annotator.oneformer.detectron2.structures import Boxes, Instances, ROIMasks
from annotator.oneformer.detectron2.utils.registr... | --- +++ @@ -1,257 +1,330 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import collections
-from dataclasses import dataclass
-from typing import Callable, List, Optional, Tuple
-import torch
-from torch import nn
-
-from annotator.oneformer.detectron2.structures import Boxes, Instances, ROIMasks
-from annotato... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/export/flatten.py |
Add docstrings to make code maintainable | # Copyright (c) Facebook, Inc. and its affiliates.
import contextlib
from unittest import mock
import torch
from annotator.oneformer.detectron2.modeling import poolers
from annotator.oneformer.detectron2.modeling.proposal_generator import rpn
from annotator.oneformer.detectron2.modeling.roi_heads import keypoint_head... | --- +++ @@ -1,136 +1,152 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-
-import contextlib
-from unittest import mock
-import torch
-
-from annotator.oneformer.detectron2.modeling import poolers
-from annotator.oneformer.detectron2.modeling.proposal_generator import rpn
-from annotator.oneformer.detectron2.mod... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/export/caffe2_patch.py |
Write docstrings that follow conventions | # Copyright (c) Facebook, Inc. and its affiliates.
import torch
import torch.distributed as dist
from fvcore.nn.distributed import differentiable_all_reduce
from torch import nn
from torch.nn import functional as F
from annotator.oneformer.detectron2.utils import comm, env
from .wrappers import BatchNorm2d
class Fr... | --- +++ @@ -1,208 +1,300 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import torch
-import torch.distributed as dist
-from fvcore.nn.distributed import differentiable_all_reduce
-from torch import nn
-from torch.nn import functional as F
-
-from annotator.oneformer.detectron2.utils import comm, env
-
-from .w... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/layers/batch_norm.py |
Can you add docstrings to this Python file? | # Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
from typing import Tuple
import torch
from PIL import Image
from torch.nn import functional as F
__all__ = ["paste_masks_in_image"]
BYTES_PER_FLOAT = 4
# TODO: This memory limit may be too much or too little. It would be better to
# determine it b... | --- +++ @@ -1,195 +1,275 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import numpy as np
-from typing import Tuple
-import torch
-from PIL import Image
-from torch.nn import functional as F
-
-__all__ = ["paste_masks_in_image"]
-
-
-BYTES_PER_FLOAT = 4
-# TODO: This memory limit may be too much or too little.... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/layers/mask_ops.py |
Create Google-style docstrings for my code | # Copyright (c) Facebook, Inc. and its affiliates.
import math
from functools import lru_cache
import torch
from torch import nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
from torchvision.ops import deform_conv2d
from annotator.... | --- +++ @@ -1,485 +1,514 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import math
-from functools import lru_cache
-import torch
-from torch import nn
-from torch.autograd import Function
-from torch.autograd.function import once_differentiable
-from torch.nn.modules.utils import _pair
-from torchvision.ops i... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/layers/deform_conv.py |
Add docstrings to make code maintainable | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import torch
from torchvision.ops import boxes as box_ops
from torchvision.ops import nms # noqa . for compatibility
def batched_nms(
boxes: torch.Tensor, scores: torch.Tensor, idxs: torch.Tensor, iou_threshold: float
):
assert boxes... | --- +++ @@ -1,58 +1,144 @@-# -*- coding: utf-8 -*-
-# Copyright (c) Facebook, Inc. and its affiliates.
-
-import torch
-from torchvision.ops import boxes as box_ops
-from torchvision.ops import nms # noqa . for compatibility
-
-
-def batched_nms(
- boxes: torch.Tensor, scores: torch.Tensor, idxs: torch.Tensor, iou_... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/layers/nms.py |
Add docstrings to improve code quality | # Copyright (c) Facebook, Inc. and its affiliates.
import torch
from torch import nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
class _ROIAlignRotated(Function):
@staticmethod
def forward(ctx, input, roi, output_size, sp... | --- +++ @@ -1,80 +1,100 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import torch
-from torch import nn
-from torch.autograd import Function
-from torch.autograd.function import once_differentiable
-from torch.nn.modules.utils import _pair
-
-
-class _ROIAlignRotated(Function):
- @staticmethod
- def for... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/layers/roi_align_rotated.py |
Document helper functions with docstrings | # Copyright (c) Facebook, Inc. and its affiliates.
from abc import ABCMeta, abstractmethod
from typing import Dict
import torch.nn as nn
from annotator.oneformer.detectron2.layers import ShapeSpec
__all__ = ["Backbone"]
class Backbone(nn.Module, metaclass=ABCMeta):
def __init__(self):
super().__init__(... | --- +++ @@ -1,35 +1,74 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-from abc import ABCMeta, abstractmethod
-from typing import Dict
-import torch.nn as nn
-
-from annotator.oneformer.detectron2.layers import ShapeSpec
-
-__all__ = ["Backbone"]
-
-
-class Backbone(nn.Module, metaclass=ABCMeta):
-
- def __i... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/modeling/backbone/backbone.py |
Create docstrings for each class method | import torch.nn as nn
def accuracy(pred, target, topk=1, thresh=None):
assert isinstance(topk, (int, tuple))
if isinstance(topk, int):
topk = (topk, )
return_single = True
else:
return_single = False
maxk = max(topk)
if pred.size(0) == 0:
accu = [pred.new_tensor(0.... | --- +++ @@ -2,6 +2,24 @@
def accuracy(pred, target, topk=1, thresh=None):
+ """Calculate accuracy according to the prediction and target.
+
+ Args:
+ pred (torch.Tensor): The model prediction, shape (N, num_class, ...)
+ target (torch.Tensor): The target of each prediction, shape (N, , ...)
+ ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/mmpkg/mmseg/models/losses/accuracy.py |
Add docstrings to incomplete code | # Copyright (c) Facebook, Inc. and its affiliates.
import os
from typing import Optional
import pkg_resources
import torch
from annotator.oneformer.detectron2.checkpoint import DetectionCheckpointer
from annotator.oneformer.detectron2.config import CfgNode, LazyConfig, get_cfg, instantiate
from annotator.oneformer.det... | --- +++ @@ -1,155 +1,213 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import os
-from typing import Optional
-import pkg_resources
-import torch
-
-from annotator.oneformer.detectron2.checkpoint import DetectionCheckpointer
-from annotator.oneformer.detectron2.config import CfgNode, LazyConfig, get_cfg, insta... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/model_zoo/model_zoo.py |
Generate missing documentation strings | # Copyright (c) Facebook, Inc. and its affiliates.
import collections
import math
from typing import List
import torch
from torch import nn
from annotator.oneformer.detectron2.config import configurable
from annotator.oneformer.detectron2.layers import ShapeSpec, move_device_like
from annotator.oneformer.detectron2.st... | --- +++ @@ -1,245 +1,386 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import collections
-import math
-from typing import List
-import torch
-from torch import nn
-
-from annotator.oneformer.detectron2.config import configurable
-from annotator.oneformer.detectron2.layers import ShapeSpec, move_device_like
-f... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/modeling/anchor_generator.py |
Write docstrings that follow conventions | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint as checkpoint
from annotator.oneformer.detectron2.modeling.backbone.backbone import Backbone
_to_2tuple = nn.modules.utils._ntuple... | --- +++ @@ -1,561 +1,695 @@-# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
-
-import numpy as np
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-import torch.utils.checkpoint as checkpoint
-
-from annotator.oneformer.detectron2.modeling.backbone.backbone import Backbone
-
... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/modeling/backbone/swin.py |
Document classes and their methods | # Copyright (c) Facebook, Inc. and its affiliates.
import logging
from typing import List, Optional, Tuple
import torch
from fvcore.nn import sigmoid_focal_loss_jit
from torch import nn
from torch.nn import functional as F
from annotator.oneformer.detectron2.layers import ShapeSpec, batched_nms
from annotator.oneform... | --- +++ @@ -1,288 +1,328 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-
-import logging
-from typing import List, Optional, Tuple
-import torch
-from fvcore.nn import sigmoid_focal_loss_jit
-from torch import nn
-from torch.nn import functional as F
-
-from annotator.oneformer.detectron2.layers import ShapeSpe... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/modeling/meta_arch/fcos.py |
Document my Python code with docstrings | # Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
import fvcore.nn.weight_init as weight_init
import torch
import torch.nn.functional as F
from torch import nn
from annotator.oneformer.detectron2.layers import (
CNNBlockBase,
Conv2d,
DeformConv,
ModulatedDeformConv,
ShapeSpec,
... | --- +++ @@ -1,555 +1,694 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import numpy as np
-import fvcore.nn.weight_init as weight_init
-import torch
-import torch.nn.functional as F
-from torch import nn
-
-from annotator.oneformer.detectron2.layers import (
- CNNBlockBase,
- Conv2d,
- DeformConv,
- ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/modeling/backbone/resnet.py |
Add missing documentation to my Python functions | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import numpy as np
from torch import nn
from annotator.oneformer.detectron2.layers import CNNBlockBase, ShapeSpec, get_norm
from .backbone import Backbone
__all__ = [
"AnyNet",
"RegNet",
"ResStem",
"SimpleStem",
"VanillaBlock... | --- +++ @@ -1,359 +1,452 @@-# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
-
-import numpy as np
-from torch import nn
-
-from annotator.oneformer.detectron2.layers import CNNBlockBase, ShapeSpec, get_norm
-
-from .backbone import Backbone
-
-__all__ = [
- "AnyNet",
- "RegNet",
- "ResSt... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/modeling/backbone/regnet.py |
Document all endpoints with docstrings | import collections.abc
import math
from functools import partial
from itertools import repeat
from typing import Tuple, Optional
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from .config import *
# From PyTorch internals
def _ntuple(n):
def parse(x):
if isinstanc... | --- +++ @@ -1,280 +1,304 @@-import collections.abc
-import math
-from functools import partial
-from itertools import repeat
-from typing import Tuple, Optional
-
-import numpy as np
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-
-from .config import *
-
-
-# From PyTorch internals
-def _ntuple... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/normalbae/models/submodules/efficientnet_repo/geffnet/conv2d_layers.py |
Generate docstrings with examples | # Copyright (c) Facebook, Inc. and its affiliates.
import logging
import math
from typing import List, Tuple
import torch
from fvcore.nn import sigmoid_focal_loss_jit
from torch import Tensor, nn
from torch.nn import functional as F
from annotator.oneformer.detectron2.config import configurable
from annotator.oneforme... | --- +++ @@ -1,324 +1,439 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import logging
-import math
-from typing import List, Tuple
-import torch
-from fvcore.nn import sigmoid_focal_loss_jit
-from torch import Tensor, nn
-from torch.nn import functional as F
-
-from annotator.oneformer.detectron2.config import... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/modeling/meta_arch/retinanet.py |
Generate docstrings for exported functions | # Copyright (c) Facebook, Inc. and its affiliates.
import math
from typing import List, Optional
import torch
from torch import nn
from torchvision.ops import RoIPool
from annotator.oneformer.detectron2.layers import ROIAlign, ROIAlignRotated, cat, nonzero_tuple, shapes_to_tensor
from annotator.oneformer.detectron2.st... | --- +++ @@ -1,176 +1,263 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import math
-from typing import List, Optional
-import torch
-from torch import nn
-from torchvision.ops import RoIPool
-
-from annotator.oneformer.detectron2.layers import ROIAlign, ROIAlignRotated, cat, nonzero_tuple, shapes_to_tensor
-fr... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/modeling/poolers.py |
Add structured docstrings to improve clarity | # Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
from typing import Callable, Dict, Optional, Tuple, Union
import fvcore.nn.weight_init as weight_init
import torch
from torch import nn
from torch.nn import functional as F
from annotator.oneformer.detectron2.config import configurable
from annotato... | --- +++ @@ -1,207 +1,267 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import numpy as np
-from typing import Callable, Dict, Optional, Tuple, Union
-import fvcore.nn.weight_init as weight_init
-import torch
-from torch import nn
-from torch.nn import functional as F
-
-from annotator.oneformer.detectron2.conf... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/modeling/meta_arch/semantic_seg.py |
Add documentation for all methods | # Copyright (c) Facebook, Inc. and its affiliates.
import itertools
import logging
import numpy as np
from collections import OrderedDict
from collections.abc import Mapping
from typing import Dict, List, Optional, Tuple, Union
import torch
from omegaconf import DictConfig, OmegaConf
from torch import Tensor, nn
from ... | --- +++ @@ -1,236 +1,273 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import itertools
-import logging
-import numpy as np
-from collections import OrderedDict
-from collections.abc import Mapping
-from typing import Dict, List, Optional, Tuple, Union
-import torch
-from omegaconf import DictConfig, OmegaConf... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/modeling/mmdet_wrapper.py |
Document all public functions with docstrings | import re
from copy import deepcopy
from .conv2d_layers import *
from geffnet.activations import *
__all__ = ['get_bn_args_tf', 'resolve_bn_args', 'resolve_se_args', 'resolve_act_layer', 'make_divisible',
'round_channels', 'drop_connect', 'SqueezeExcite', 'ConvBnAct', 'DepthwiseSeparableConv',
'... | --- +++ @@ -1,625 +1,683 @@-import re
-from copy import deepcopy
-
-from .conv2d_layers import *
-from geffnet.activations import *
-
-__all__ = ['get_bn_args_tf', 'resolve_bn_args', 'resolve_se_args', 'resolve_act_layer', 'make_divisible',
- 'round_channels', 'drop_connect', 'SqueezeExcite', 'ConvBnAct', 'De... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/normalbae/models/submodules/efficientnet_repo/geffnet/efficientnet_builder.py |
Generate helpful docstrings for debugging | import numpy as np
from typing import Dict, List, Optional, Tuple
import torch
from torch import Tensor, nn
from annotator.oneformer.detectron2.data.detection_utils import convert_image_to_rgb
from annotator.oneformer.detectron2.layers import move_device_like
from annotator.oneformer.detectron2.modeling import Backbon... | --- +++ @@ -1,193 +1,294 @@-import numpy as np
-from typing import Dict, List, Optional, Tuple
-import torch
-from torch import Tensor, nn
-
-from annotator.oneformer.detectron2.data.detection_utils import convert_image_to_rgb
-from annotator.oneformer.detectron2.layers import move_device_like
-from annotator.oneformer... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/modeling/meta_arch/dense_detector.py |
Generate consistent docstrings | # Copyright (c) Facebook, Inc. and its affiliates.
from typing import Dict, List, Optional, Tuple, Union
import torch
import torch.nn.functional as F
from torch import nn
from annotator.oneformer.detectron2.config import configurable
from annotator.oneformer.detectron2.layers import Conv2d, ShapeSpec, cat
from annotat... | --- +++ @@ -1,388 +1,533 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-from typing import Dict, List, Optional, Tuple, Union
-import torch
-import torch.nn.functional as F
-from torch import nn
-
-from annotator.oneformer.detectron2.config import configurable
-from annotator.oneformer.detectron2.layers import ... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/modeling/proposal_generator/rpn.py |
Add well-formatted docstrings | # Copyright (c) Facebook, Inc. and its affiliates.
import itertools
import logging
from typing import Dict, List
import torch
from annotator.oneformer.detectron2.config import configurable
from annotator.oneformer.detectron2.layers import ShapeSpec, batched_nms_rotated, cat
from annotator.oneformer.detectron2.structur... | --- +++ @@ -1,162 +1,209 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import itertools
-import logging
-from typing import Dict, List
-import torch
-
-from annotator.oneformer.detectron2.config import configurable
-from annotator.oneformer.detectron2.layers import ShapeSpec, batched_nms_rotated, cat
-from ann... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/modeling/proposal_generator/rrpn.py |
Add docstrings to clarify complex logic | # Copyright (c) Facebook, Inc. and its affiliates.
import torch
from torch.nn import functional as F
from annotator.oneformer.detectron2.structures import Instances, ROIMasks
# perhaps should rename to "resize_instance"
def detector_postprocess(
results: Instances, output_height: int, output_width: int, mask_thr... | --- +++ @@ -1,65 +1,100 @@-# Copyright (c) Facebook, Inc. and its affiliates.
-import torch
-from torch.nn import functional as F
-
-from annotator.oneformer.detectron2.structures import Instances, ROIMasks
-
-
-# perhaps should rename to "resize_instance"
-def detector_postprocess(
- results: Instances, output_heig... | https://raw.githubusercontent.com/Mikubill/sd-webui-controlnet/HEAD/annotator/oneformer/detectron2/modeling/postprocessing.py |
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