Qiao Zhongzheng

Hi, I tried to modify the original codes to fit the case you mentioned: ``` class SwitchNorm1d(nn.Module): def __init__(self, num_features, eps=1e-5, momentum=0.997, using_moving_average=True): super(SwitchNorm1d, self).__init__() self.eps = eps self.momentum =...

Hi @yaoyao-liu Thanks for your kind and prompt reply. I will check that project for BOP implementation. There are some other issues that I am confused about: 1. The `prototypes`...

Hello @yaoyao-liu, Thank you so much for your kind and comprehensive explanations. Now I have a thorough understanding of the codes and the pipeline. Indeed, the stored historical training data...

Hi, it should be `math.ceil(prediction_length / patch_size)` since the prediction range has been padded.

Let's say if prediction length is 96 and patch size is 64, the prediction range will be padded to 128 to make sure there are multiple patches. So, the last...

Thanks for your reply. Following your suggestions, I normalized the data for fine-tuning, built the data in 'wide_multivariate' and removed the SampleDimension transformation. However, when I ran the experiment, an...

Hi. I haven't resolved this issue, but I have tracked the reason. This issue can happen when a flatten patchfied sequence exceeds the `max_length=512` of Moirai. I think this could...

FYI, you can reproduce this issue by running your example codes of finetuning. Just build the Etth1 dataset with `wide_multivariate`, and set context_length=5000, prediction_length=96, and patch_size=64.

@wyhzunzun123123 Hi, I haven't solved this issue for ETTh1. Since the config for reproduction uses mode='M' in ETTh1, I think one may need to finetune it with dataset built in...

Thanks. Can you briefly explain the role of `SampleDimension` feature? Does it sample as many dimensions/variates as possible from an MTS with a given limit of `max_seq_len`?