Some dimensions, such as batch size or sequence length, may vary. e.g.: adaptive batching will execute inference requests with varying batch sizes depending on how many re quests it received within its batching window. 可能是对每个batch,选择max seq length,把其他值用pad填补到那么长 Some ...
The evaluation process of Seq2seq PyTorch is to check the model output. Each pair of Sequence to sequence models will be feed into the model and generate the predicted words. After that you will look the highest value at each output to find the correct index. And in the end, you will ...
Reformer comes with a slight drawback that the sequence must be neatly divisible by the bucket size * 2. I have provided a small helper tool that can help you auto-round the sequence length to the next best multiple. import torch from reformer_pytorch import ReformerLM, Autopadder model =...
nn.utils.rnn import pad_sequence from torch.utils.data import DataLoader import torch.nn.functional as F import random # Tokenizer for English and German tokenizer_en = get_tokenizer('spacy', language='en_core_web_sm') tokenizer_de = get_tokenizer('spacy', language='de_core_news_sm') ...
batch_sizes_npu = sequence.batch_sizes.to(sequence.data.device) padded_output, lengths = torch._VF._pad_packed_sequence( sequence.data, batch_sizes_npu, batch_first, padding_value, max_seq_length) else: padded_output, lengths = torch._VF._pad_packed_sequence( sequence.data, sequen...
Fixed experiment version and log-dir divergence in DDP when using multiple Trainer instances in sequence (7403) Enabled manual optimization for TPUs (#8458) Fixed accumulate_grad_batches not been recomputed during model reload (#5334) Fixed a TypeError when wrapping optimizers in the HorovodPlugin...
对于PyTorch 1.x版本用户,通过在重置梯度时使用set_to_none=True选项(PyTorch 2.0中的默认行为)可以显著降低峰值内存占用。在训练循环中,调用loss.backward()和optimizer.step()后,可以使用optimizer.zero_grad(set_to_none=True)或model.zero_grad(set_to_none=True),将梯度张量重置为None而非填充零值,这不仅节省...
nest.pack_sequence_as 49: nn 1: nn.all_candidate_sampler 2: nn.approx_max_k 3: nn.approx_min_k 4: nn.atrous_conv2d 5: nn.atrous_conv2d_transpose 6: nn.avg_pool 7: nn.avg_pool1d 8: nn.avg_pool2d 9: nn.avg_pool3d 10: nn.batch_norm_with_global_normalization 11: nn.batch...
weight (Tensor)– The embedding matrix with number of rows equal to the maximum possible index + 1, and number of columns equal to the embedding size offsets (LongTensor, optional)– Only used when input is 1D. offsets determines the starting index position of each bag (sequence) in input...
and segmentation. It leverages our FLD-5B dataset, containing 5.4 billion annotations across 126 million images, to master multi-task learning. The model's sequence-to-sequence architecture enables it to excel in both zero-shot and fine-tuned settings, proving to be a competitive vision foundation...