Args: img_size (int, tuple): input image size in_chans (int): number of input channels patch_size (int):

Creates an EfficientNet-V2 base model Ref impl: https://github.com/google/automl/tree/master/efficientnetv2 Paper: `EfficientNetV2: Smaller

Creates an EfficientNet-V2 Large model Ref impl: https://github.com/google/automl/tree/master/efficientnetv2 Paper: `EfficientNetV2: Smaller

Creates an EfficientNet-V2 Medium model Ref impl: https://github.com/google/automl/tree/master/efficientnetv2 Paper: `EfficientNetV2: Smalle

Creates a mnasnet-a1 model. Ref impl: https://github.com/tensorflow/tpu/tree/master/models/official/mnasnet Paper: https://arxiv.org/pdf/1807

Creates a mnasnet-b1 model. Ref impl: https://github.com/tensorflow/tpu/tree/master/models/official/mnasnet Paper: https://arxiv.org/pdf/1807

Generate MobileNet-V2 network Ref impl: https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet/mobilenet_v2.py Paper:

input: grad_out: (b, c, m, nsample) output: (b, c, n), None

Expand lst to length N by randomly sampling from original elements (with replacement).

return info dicts for specified keys (or all if None) at specified indices (or out_indices if None)

Insert CLS token.

Load a CLIP model Parameters ---------- name : str A model name listed by `clip.available_models()`, or the path to a model check

将车辆 yaw（弧度制）转换为前/后/左/右朝向描述

将车辆 yaw（弧度制）转换为前/后/左/右朝向描述

Performs a single optimization step. Arguments: closure (callable, optional): A closure that reevaluates the model

VovNet (v2)

Constructs a GhostNet model

Creates an EfficientNet-V2 Xtra-Large model Ref impl: https://github.com/google/automl/tree/master/efficientnetv2 Paper: `EfficientNetV2: Sm

FBNetV3 Paper: `FBNetV3: Joint Architecture-Recipe Search using Predictor Pretraining` - https://arxiv.org/abs/2006.02049 FIXME untes

Compute gradient of the Lovasz extension w.r.t sorted errors See Alg. 1 in paper

Gets all parameters in all param_groups with gradients

Nan-mean compatible with generators.

See http://www.codinghorror.com/blog/archives/001018.html

Override model level attn/self-attn/block kwargs w/ block level NOTE: kwargs are NOT merged across levels, block_kwargs will fully replace model

Key: text_quantity_l1 Using The Training and Combination. Exmaple : NUM_THRESHOLD = 2 No cars. O