在短期预测读取m4数据 about timemixer HOT 8 CLOSED

在短期预测读取m4数据 training_values = np.array([v for v in dataset.values[dataset.groups == self.seasonal_patterns]],dtype=np.float32)报错

ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (23000,) + inhomogeneous part. 想问一下怎么解决呀

你好，请问你执行的哪个脚本，我这边并没有这个问题，我尝试执行了M4其中一个预测，是正常执行的，日志如下：
##########start training : short_term_forecast_m4_Monthly_TimeMixer_m4_ftM_sl36_ll18_pl18_dm32_nh8_el4_dl1_df32_fc3_ebtimeF_dtTrue_'Exp'_0#########################
train 48000
val 48000
iters: 100, epoch: 1 | loss: 7.8308382
speed: 0.2817s/iter; left time: 5253.2988s
iters: 200, epoch: 1 | loss: 8.6521778
speed: 0.0946s/iter; left time: 1754.8944s
iters: 300, epoch: 1 | loss: 7.9615688
speed: 0.0943s/iter; left time: 1740.0839s
Epoch: 1 cost time: 104.02890491485596
Epoch: 1, Steps: 375 | Train Loss: 8.4553798 Vali Loss: 13.4481628 Test Loss: 13.4481628
Validation loss decreased (inf --> 13.448163). Saving model ...
Updating learning rate to 0.01
iters: 100, epoch: 2 | loss: 6.9544621
speed: 0.9484s/iter; left time: 17332.5653s
iters: 200, epoch: 2 | loss: 7.8785143
speed: 0.0935s/iter; left time: 1699.4366s
iters: 300, epoch: 2 | loss: 8.8131914
speed: 0.0929s/iter; left time: 1680.1044s
Epoch: 2 cost time: 105.14443969726562
Epoch: 2, Steps: 375 | Train Loss: 8.1038713 Vali Loss: 13.2876223 Test Loss: 13.2876223

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@kwuking

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请问你执行的是哪一个脚本，是怎么执行的？这段代码我测试了没有问题

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@kwuking

您好，我也遇到了同样的问题，执行的脚本是scripts/short_term_forecast/M4/TimeMixer.sh脚本，环境按照requirements.txt配置。在上述代码位置添加dtype=object后，会产生新的报错：
File "run.py", line 139, in
exp.train(setting)
File "/home/srwang/nlp/TimeMixer/exp/exp_short_term_forecasting.py", line 99, in train
loss_value = criterion(batch_x, self.args.frequency_map, outputs, batch_y, batch_y_mark)
File "/home/srwang/anaconda3/envs/timemixer/lib/python3.8/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/srwang/nlp/TimeMixer/utils/losses.py", line 67, in forward
return 200 * t.mean(divide_no_nan(t.abs(forecast - target),
RuntimeError: The size of tensor a (18) must match the size of tensor b (36) at non-singleton dimension 1

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@kwuking

您好，我也遇到了同样的问题，执行的脚本是scripts/short_term_forecast/M4/TimeMixer.sh脚本，环境按照requirements.txt配置。在上述代码位置添加dtype=object后，会产生新的报错： File "run.py", line 139, in exp.train(setting) File "/home/srwang/nlp/TimeMixer/exp/exp_short_term_forecasting.py", line 99, in train loss_value = criterion(batch_x, self.args.frequency_map, outputs, batch_y, batch_y_mark) File "/home/srwang/anaconda3/envs/timemixer/lib/python3.8/site-packages/torch/nn/modules/module.py", line 727, in _call_impl result = self.forward(*input, **kwargs) File "/home/srwang/nlp/TimeMixer/utils/losses.py", line 67, in forward return 200 * t.mean(divide_no_nan(t.abs(forecast - target), RuntimeError: The size of tensor a (18) must match the size of tensor b (36) at non-singleton dimension 1

看起来是tensor不匹配，您执行的参数脚本可以发一下嘛，是否和提供的脚本中参数一致呢？

from timemixer.

执行的参数脚本是scripts/short_term_forecast/M4/TimeMixer.sh，和提供的脚本完全一致，具体参数为：
model_name=TimeMixer

e_layers=4
down_sampling_layers=1
down_sampling_window=2
learning_rate=0.01
d_model=32
d_ff=32
batch_size=16

python -u run.py
--task_name short_term_forecast
--is_training 1
--root_path ./dataset/m4
--seasonal_patterns 'Monthly'
--model_id m4_Monthly
--model $model_name
--data m4
--features M
--e_layers $e_layers
--d_layers 1
--factor 3
--enc_in 1
--dec_in 1
--c_out 1
--batch_size 128
--d_model $d_model
--d_ff 32
--des 'Exp'
--itr 1
--learning_rate $learning_rate
--train_epochs 50
--patience 20
--down_sampling_layers $down_sampling_layers
--down_sampling_method avg
--down_sampling_window $down_sampling_window
--loss 'SMAPE'

如果不修改training_values，报错与提问者相同：ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (48000,) + inhomogeneous part.

from timemixer.

你好 我更新了M4短程预测的代码以便于更加便利运行，您可以在尝试一下是否可以运行呢

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感谢您的耐心回答，使用更新后的代码M4可以正常运行了~

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