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command = [ 'python', '-u', 'run.py', '--is_training', '1', '--root_path', './dataset/ETT-small/', '--data_path', 'ETTh1.csv', '--model_id', 'ETTh1_96_96', '--model', model_name, '--data', 'ETTh1', '--features', 'MS', '--seq_len', '96', '--pred_len', '96', '--e_layers', '2', '--enc_in', '7', '--dec_in', '7', '--c_out', '7', '--des', 'Exp', '--d_model', '256', '--d_ff', '256', '--itr', '1' ] Traceback (most recent call last): File "run.py", line 135, in exp.test(setting) File "C:\Users\ZRCC\Desktop\kk\iTransformer-main\iTransformer-main\experiments\exp_long_term_forecasting.py", line 235, in test outputs = test_data.inverse_transform(outputs.squeeze(0)).reshape(shape) File "C:\Users\ZRCC\Desktop\kk\iTransformer-main\iTransformer-main\data_provider\data_loader.py", line 98, in inverse_transform return self.scaler.inverse_transform(data) File "F:\shuoAPP\anaconda\envs\itr\lib\site-packages\sklearn\preprocessing_data.py", line 1052, in inverse_transform X *= self.scale_ ValueError: non-broadcastable output operand with shape (96,1) doesn't match the broadcast shape (96,7)
The text was updated successfully, but these errors were encountered:
楼上解决了吗我也遇到了
Sorry, something went wrong.
逆标准化失败了而已,你输出维度为96,1自然不可能直接使用96,7的scaler进行恢复,自己做个转换吧
用这个来做逆标准化吧 def inverse_result(self, data): mean_last = self.scaler.mean_[-1] std_last = self.scaler.scale_[-1] return data * std_last + mean_last
楼上解决这个问题了吗?我也遇到了逆归一化没法完成,不清楚如何改?能不能指点一下,具体在哪块代码下面怎么修改
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command = [
'python', '-u', 'run.py',
'--is_training', '1',
'--root_path', './dataset/ETT-small/',
'--data_path', 'ETTh1.csv',
'--model_id', 'ETTh1_96_96',
'--model', model_name,
'--data', 'ETTh1',
'--features', 'MS',
'--seq_len', '96',
'--pred_len', '96',
'--e_layers', '2',
'--enc_in', '7',
'--dec_in', '7',
'--c_out', '7',
'--des', 'Exp',
'--d_model', '256',
'--d_ff', '256',
'--itr', '1'
]
Traceback (most recent call last):
File "run.py", line 135, in
exp.test(setting)
File "C:\Users\ZRCC\Desktop\kk\iTransformer-main\iTransformer-main\experiments\exp_long_term_forecasting.py", line 235, in test
outputs = test_data.inverse_transform(outputs.squeeze(0)).reshape(shape)
File "C:\Users\ZRCC\Desktop\kk\iTransformer-main\iTransformer-main\data_provider\data_loader.py", line 98, in inverse_transform
return self.scaler.inverse_transform(data)
File "F:\shuoAPP\anaconda\envs\itr\lib\site-packages\sklearn\preprocessing_data.py", line 1052, in inverse_transform
X *= self.scale_
ValueError: non-broadcastable output operand with shape (96,1) doesn't match the broadcast shape (96,7)
The text was updated successfully, but these errors were encountered: