Build normalization layer. Args: cfg (dict): The norm layer config, which should contain: - type (str): Layer type.

Build convolution layer. Args: cfg (None or dict): The conv layer config, which should contain: - type (str): Layer type.

Convert a version string into a tuple of integers. This method is usually used for comparing two versions. For pre-release versions: alpha <

Load model from file. Args: path (str): file path

Register a module. A record will be added to `self._module_dict`, whose key is the class name or the specified name, and value is the

Transform inputs for decoder. Args: inputs (list[Tensor]): List of multi-level img features. Returns: Tensor

Classify each pixel with fc.

Call all hooks. Args: fn_name (str): The function name in each hook to be called, such as "before_train_epoch".

Read the next frame. If the next frame have been decoded before and in the cache, then return it directly, otherwise decode, cache an

Build a module from config dict. Args: cfg (dict): Config dict. It should at least contain the key "type". registry (:obj:`Regist

Check whether a file path exists. Args: filepath (str or Path): Path to be checked whether exists. Returns:

Print a log message. Args: msg (str): The message to be logged. logger (logging.Logger | str | None): The logger to be used.

Remove a file. Args: filepath (str, Path): Path to be removed.

Check whether a file path is a file. Args: filepath (str or Path): Path to be checked whether it is a file. Returns:

Load checkpoint from a file or URI. Args: model (Module): Module to load checkpoint. filename (str): Accept local filepath, URL,

Whether the input is an string instance. Note: This method is deprecated since python 2 is no longer supported.

Returns the state of the scaler as a :class:`dict`.

Convert a ``filepath`` to standard format of petrel oss. If the ``filepath`` is concatenated by ``os.path.join``, in a Windows enviro

Map ``filepath`` to a string path whose prefix will be replaced by :attr:`self.path_mapping`. Args: filepath (str): Path

Get the current training iteration step.

Loads the loss_scaler state dict. Args: state_dict (dict): scaler state.

Register a hook into the hook list. The hook will be inserted into a priority queue, with the specified priority (See :class:`Priorit

Recursively convert Tensor in inputs from src_type to dst_type. Args: inputs: Inputs that to be casted. src_type (torch.dtype): S

Infer a suitable file client based on the URI and arguments. Args: file_client_args (dict, optional): Arguments to instantiate a

Check if a module is a module wrapper. The following 3 modules in MMCV (and their subclasses) are regarded as module wrappers: DataParallel,

Add prefix for dict. Args: inputs (dict): The input dict with str keys. prefix (str): The prefix to add. Returns: d

Get the root logger. The logger will be initialized if it has not been initialized. By default a StreamHandler will be added. If `log_file` i

Update the `_params_init_info` in the module if the value of parameters are changed. Args: module (obj:`nn.Module`): The module of Py

Multiple with alpha and add beat with clip.

Concatenate all file paths. Join one or more filepath components intelligently. The return value is the concatenation of filepath and

Forward function for plugins.

Check whether the object has a method. Args: method (str): The method name to check. obj (object): The object to check. Retu

Check whether a file path is a directory. Args: filepath (str or Path): Path to be checked whether it is a direct

nn.Module: the normalization layer named "norm1"

nn.Module: the normalization layer named "norm2"

A wrapper around :func:`grid_sample` to support 3D point_coords tensors Unlike :func:`torch.nn.functional.grid_sample` it assumes point_coords to

Calculate annealing cos learning rate. Cosine anneal from `weight * start + (1 - weight) * end` to `end` as percentage goes from 0.0 to 1.0.

Build activation layer. Args: cfg (dict): The activation layer config, which should contain: - type (str): Layer type.

Args: imgs (List[Tensor]): the outer list indicates test-time augmentations and inner Tensor should have a shape

Read data from a given ``filepath`` with 'rb' mode. Note: There are two types of return values for ``get``, one is ``bytes``

Check whether it is a sequence of some type. Args: seq (Sequence): The sequence to be checked. expected_type (type): Expected typ

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

In distributed setting, this function only download checkpoint at local rank 0.

Apply element-wise weight and reduce loss. Args: loss (Tensor): Element-wise loss. weight (Tensor): Element-wise weights.

Initialize BaseModule, inherited from `torch.nn.Module`

Init. Args: scale_factor (float): scaling mode (str): interpolation mode

Convert the type and range of the input image. It converts the input image to np.float32 type and range of [0, 1]. It is mainly used for pre-

Convert the type and range of the image according to dst_type. It converts the image to desired type and range. If `dst_type` is np.uint8, im