Performs all_gather operation on the provided tensors. *** Warning ***: torch.distributed.all_gather has no gradient.

Undo batch shuffle. *** Only support DistributedDataParallel (DDP) model. ***

Computes the accuracy over the k top predictions for the specified values of k

1x1 convolution

3x3 convolution with padding

Args: anchor: (x0, y0, x1, y1) The coordinates of anchors in image q loc_q: (x0, y0, x1, y1) The cropped region of im

Initialize `module.weight` using the "XavierFill" implemented in Caffe2. Also initializes `module.bias` to 0. Args: module (torch

Batch shuffle, for making use of BatchNorm. *** Only support DistributedDataParallel (DDP) model. ***

Momentum update of the key encoder

Decay the learning rate based on schedule

Get parameters for ``crop`` for a random sized crop. Args: img (PIL Image): Image to be cropped. scale (tuple): range

Args: img (PIL Image): Image to be cropped and resized. Returns: PIL Image: Randomly cropped and resized imag

Args: img (PIL Image): Image to be flipped. Returns: PIL Image: Randomly flipped image.

Args: index (int): Index Returns: tuple: (sample, target) where target is class_index of the target class.

dim: feature dimension (default: 128) K: queue size; number of negative keys (default: 65536) m: moco momentum of updating ke

Input: im_q: a batch of query images im_k: a batch of key images Output: logits, targets

r"""ResNet-101 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ Args: pretrained (b

r"""ResNet-152 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ Args: pretrained (b

r"""ResNet-18 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ Args: pretrained (bo

r"""ResNet-34 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ Args: pretrained (bo

r"""ResNet-50 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ Args: pretrained (bo

r"""ResNeXt-101 32x8d model from `"Aggregated Residual Transformation for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ Args:

r"""ResNeXt-50 32x4d model from `"Aggregated Residual Transformation for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ Args:

r"""Wide ResNet-101-2 model from `"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_ The model is the same as ResNet except for

r"""Wide ResNet-50-2 model from `"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_ The model is the same as ResNet except for