Wrapper for bucket initialization, with specified key, secret, endpoint, and bucket name. See more: https://pypi.org/project/oss2/. A

Determine if a checkpoint should be saved on current epoch. Args: cfg (Config): the global config object. cur_epoch (int): cu

Determine if the model should be evaluated at the current epoch. Args: cfg (Config): the global config object. cur_epoch (int

Determines if the current process is the master process.

Returns: bool: whether the timer is currently paused

Start to record time.

Stop to record time.

Calculates number of correctly predicted samples for each top-k value respectively for separate verb/noun, and joint action predictions.

Loading checkpoint logic for testing.

Loading checkpoint logic for training.

Log the stats of the current epoch. Args: cur_epoch (int): the number of current epoch.

Log the stats. Args: cur_iter (int): the current iteration of testing.

Log the stats. Args: cur_iter (int): the current iteration of testing.

log the stats of the current iteration. Args: cur_epoch (int): the number of current epoch. cur_iter (int): t

Logs json stats. Args: stats (dict): a dictionary of statistical information to log.

Log info, includes number of parameters, gpu usage, gflops and activation count. The model info is computed when the model is in validati

Retrieve the learning rate to specified values at specified epoch with the cosine learning rate schedule. Details can be found in: Ilya L

Retrieve the learning rate to specified values at specified epoch with the cosine learning rate schedule. Details can be found in: Ilya L

Retrieve the learning rate to specified values at specified epoch with the steps with relative learning rate schedule. Args: cfg

Creates the checkpoint directory (if not present already). Args: path_to_job (string): the path to the folder of the current job.

Parse epic proposals by BMN map Args: cfg (Config): the global config object. results_dict (dict): Maps output by BMN. re

Plot the input tensor with the optional bounding box and save it to disk. Args: tensor (tensor): a tensor with shape of `NxCxHxW`.

Wrapper for putting data to the specified bucket. See more: https://pypi.org/project/oss2/. Args: bucket (oss2.Bucket):

Wrapper for reading data to the hard drive of local machine, from the specified bucket. See more: https://pypi.org/project/oss2/. Ar

Wrapper for reading data directly to the memory of the local machine, from the specified bucket. See more: https://pypi.org/project/oss2/.

Wrapper function for registering a module.

Reset the deque.

Reset the Meter.

Resume the timer.

Runs a function from a child process. Args: local_rank (int): rank of the current process on the current machine. func (funct

Save a checkpoint. Args: model (model): model to save the weight to the checkpoint. optimizer (optim): optimizer to save the

Save a video proposals for epic-kitchen. Args: cfg (Config): the global config object. bucket (Oss bucket): ignore it if you

Sets the optimizer lr to the specified value. Args: optimizer (optim): the optimizer using to optimize the current network. n

Sets up the logging for multiple processes. Only enable the logging for the master process, and suppress logging for the non-master processes

Performs multi-view test on the submission set, and save the prediction results. Currently only support EPIC-KITCHENS submission set. Arg

Helper function to synchronize (barrier) among all processes when using distributed training

Put Tensor in iterable data into gpu. Args: data :(tensor or list or dict)

Perform multi-view testing on the pretrained video model. Args: cfg (Config): The global config object.

Perform sliding windows testing on the pretrained video model. Args: cfg (CfgNode): Gobal configs.

Computes the top-k accuracy for each k. Args: preds (array): array of predictions. Dimension is N. labels (array): array of l

Computes the top-k error for each k. Args: preds (array): array of predictions. Dimension is N. labels (array): array of labe

Train a video model for many epochs on train set and evaluate it on val set. Args: cfg (Config): The global config object.

Update stats using custom keys. Args: stats (dict): additional stats to be updated.

Collect the predictions from the current batch and perform on-the-flight summation as ensemble. Args: preds (tens

Update the current stats. Args: top1_err (float): top1 error rate. top5_err (float): top5 error rate.

Collect the predictions from the current batch and perform on-the-flight summation as ensemble, for joint verb and noun training.

Collect the predictions from the current batch and perform on-the-flight summation as ensemble, for separate verb and noun training.

Visualizes and saves the normalized output features for the module.