Remove new lines and multiple spaces and adjust end of sentence dot.

Retrieves a single item from the dataset with the option to only return a portion of the item. get(idx) is the same as [idx] but get

Main training program. This function will run the followings in the order provided: 1) initialize Megatron. 2) setup model, optim

If distributed is initialized, print only on last rank.

Save a model checkpoint.

Build language model and return along with the key to save.

Parse the package dependencies listed in a requirements file but strips specific versioning information. Args: fname (str): path

Note that this call will sync across all ranks.

Make sure the input variable is not None.

Track the rng state.

Fork the cuda rng state, perform operations, and exit with the original state.

Instantiate a PreTrainedBertModel from a pre-trained model file. Download and cache the pre-trained model file if needed.

A unified checkpoint name.

Tracker file rescords the latest chckpoint during training to restart from.

Load a model checkpoint and return the iteration. strict (bool): whether to strictly enforce that the keys in :attr:`state_dict` of the ch

Load the state dicts of each of the models

Runs Non-Maximum Suppression (NMS) on inference results Returns: list of detections, on (n,6) tensor per image [xyxy, conf, cls]

pre_pred:已经得到的前一个预测结果 这里要将原始已经得到的预测结果逐个加入原始测试集

VGG 19-layer model (configuration "E") model pre-trained on ImageNet

Sets the random number generator state of the current GPU. Argumentss: new_state (torch.ByteTensor): The desired state This function

Backward step through passed-in output tensor. If last stage, output_tensor_grad is None, otherwise gradient of loss with respect to stage's

Build universial encoder representations models. The combinations of different embedding, encoder, and target layers yield pretrained mo

Initialize tokenizer.

Ensure that numerator is divisible by the denominator and return the division value.

Helper function to evaluate and dump results on screen.

Compute exp_t for `u'.

Forward step for passed-in model. If first stage, input tensor is obtained from data_iterator, otherwise passed-in input_tensor is used.

Get cuda rng tracker.

Build the model.

Get a list that maps a sample index to a starting sentence index, end sentence index, and length

Initialize torch.distributed.

Set global variables, initialize distributed, and set autoresume and random seeds. `allow_no_cuda` should not be set unless using megatron for

Load the state dicts of each of the models