Load cats with the specified ids. :param ids (int array) : integer ids specifying cats :return: cats (object array) : l

Load anns with the specified ids. :param ids (int array) : integer ids specifying img :return: imgs (object array) : lo

Convert result data from a numpy array [Nx7] where each row contains {imageID,x1,y1,w,h,score,class} :param data (numpy.ndarray)

Calculate reward for object detection task with length penalty. Args: content (str): Model's predicted answer containing boundin

Calculate reward for object detection task with length penalty. Args: content (str): Model's predicted answer containing boundin

Starts prefetching the next layer cache

Starts prefetching the next layer cache

Starts prefetching the next layer cache

Starts prefetching the next layer cache

Pushes the model to branch on a Hub repo.

Sampling x0 & t based on shape of x1 (if needed) Args: x1 - data point; [batch, *dim]

Create sinusoidal timestep embeddings. :param t: a 1-D Tensor of N indices, one per batch element. These ma

Create sinusoidal timestep embeddings. :param t: a 1-D Tensor of N indices, one per batch element. These ma

Loss for training torche score model Args: - model: backbone model; could be score, noise, or velocity - x1: datapoint - model_kwargs:

r""" Function invoked when calling the pipeline for generation. Args: prompt (`str` or `List[str]`): The p

r""" Function invoked when calling the pipeline for generation. Args: prompt (`str` or `List[str]`): The

Gets the cache for this layer to the device. Prefetches the next and evicts the previous layer.

Gets the cache for this layer to the device. Prefetches the next and evicts the previous layer.

Constructor of Microsoft COCO helper class for reading and visualizing annotations. :param annotation_file (str): location of annotat

Initialize CocoEval using coco APIs for gt and dt :param cocoGt: coco object with ground truth annotations :param cocoDt: coc

Phi3RMSNorm is equivalent to T5LayerNorm