Return set of symbol pairs in a word. Word is represented as tuple of symbols (symbols being variable-length strings).

Return set of symbol pairs in a word. Word is represented as tuple of symbols (symbols being variable-length strings).

Check if params contain overflow.

Check whether it is a list of some type. A partial method of :func:`is_seq_of`.

Check if a method of base class is overridden in derived class. Args: method (str): the method name to check. base_class (type):

Cast elements of an iterable object into some type. Args: inputs (Iterable): The input object. dst_type (type): Destination type.

Concatenate all file paths. Args: filepath (str or Path): Path to be concatenated. Returns: str: The result

Load from a finetuned checkpoint. This should expect no mismatch in the model keys and the checkpoint keys.

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 ``F

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

Binary Lovasz hinge loss. Args: logits (torch.Tensor): [P], logits at each prediction (between -infty and +infty). la

Multi-class Lovasz-Softmax loss. Args: probs (torch.Tensor): [P, C], class probabilities at each prediction (between 0 and 1)

Test model with multiple gpus. This method tests model with multiple gpus and collects the results under two different modes: gpu and cpu mod

nn.Module: normalization layer after the first convolution layer

Convert parameter number into a string. Args: num_params (float): Parameter number to be converted. units (str | None): Converted

PARAMETERS

Prepare results dict for pipeline.

Write data to a given ``filepath`` with 'wb' mode. Note: ``put`` should create a directory if the directory of ``filepath``

Write data to a given ``filepath`` with 'w' mode. Note: ``put_text`` should create a directory if the directory of ``

Randomly sample an img_scale when ``multiscale_mode=='range'``. Args: img_scales (list[tuple]): Images scale range for sampling.

Randomly sample an img_scale when ``ratio_range`` is specified. A ratio will be randomly sampled from the range specified by ``ratio_

Convert roi based relative point coordinates to image based absolute point coordinates. Args: rois (Tensor): RoIs or BBoxes, shape (N

Calculate the new size to be rescaled to. Args: old_size (tuple[int]): The old size (w, h) of image. scale (float | tuple[int]):

Resize pos_embed weights. Resize pos_embed using bicubic interpolate method. Args: pos_embed (torch.Tensor): pos_embed we

Rotates half the hidden dims of the input.

Save checkpoint to file. The checkpoint will have 3 fields: ``meta``, ``state_dict`` and ``optimizer``. By default ``meta`` will contain vers

Scan a directory to find the interested files. Args: dir_path (str | obj:`Path`): Path of the directory. suffix (str | tuple(str)

Scatter inputs to target gpus. The only difference from original :func:`scatter` is to add support for :type:`~mmcv.parallel.DataContainer`.

Scatters tensor across multiple GPUs.

Draw `result` over `img`. Args: img (str or Tensor): The image to be displayed. result (Tensor): The semantic segment

Time since the last checking. Either :func:`since_start` or :func:`since_last_check` is a checking operation. Returns (float

Test with single GPU. Args: model (nn.Module): Model to be tested. data_loader (utils.data.Dataloader): Pytorch data loader.

Start the timer.

Track the progress of tasks execution with a progress bar. Tasks are done with a simple for-loop. Args: func (callable): The functio

update the current loss scale value when overflow happens.

Wrap the FP32 model to FP16. If you are using PyTorch >= 1.6, torch.cuda.amp is used as the backend, otherwise, original mmcv implementation

Returns a diagonal matrix of size [n, n]. The diagonal are all "-inf". This is for avoiding calculating the overlapped element in the Criss-C