Dear @vchung ,
Thanks for the challenge. Would you mind providing the error reason in Submission ID 9760505 container logs for us to troubleshoot the issue?
My memory in the environment: 125 GB
Thanks!
Best regards,
Robin, on behalf on Metformin-121
Created by Chih-Han Huang Chih-Han Thanks a lot! The information is quite helpful. Our team could make successful submission now Hi @Chih-Han ,
For subID 9760505, memory is no longer an issue! However, here was the error that was received:
```
start
Load input data
Load feature preprocessor
Build feature matrix (shape = (542673, 3))
Traceback (most recent call last)
/home/user/run_model.py:102 in main
99 print('Build feature matrix (shape = {})'.format(X.shape))
100
101 # ---- Apply preprocessing ----
102 X_imp = imputer.transform(X)
103 X_scaled = scaler.transform(X_imp)
104 print('Apply preprocessing')
105
locals
adata = AnnData object with n_obs n_vars = 542673 36601
backed at '/input/data.h5ad'
obs: 'library_prep', 'Donor ID', 'Method',
'Sex', 'Age at Death', 'Race (choice=White)', 'Race
(choice=Black/ African American)', 'Race
(choice=Asian)', 'Race (choice=American Indian/
Alaska Native)', 'Race (choice=Native Hawaiian or
Pacific Islander)', 'Race (choice=Unknown or
unreported)', 'Race (choice=Other)',
'Hispanic/Latino', 'Years of education', 'PMI',
'APOE Genotype', 'Class', 'Subclass', 'Supertype'
var: 'gene_ids', 'feature_types', 'genome'
uns: 'log1p'
layers: 'UMIs'
adata_path = '/input/data.h5ad'
feat_names = [
'Age at Death',
'Years of education',
'PMI',
'percent 6e10 positive area',
'percent AT8 positive area',
'percent NeuN positive area',
'percent GFAP positive area',
'percent aSyn positive area',
'percent pTDP43 positive area'
]
imputer = SimpleImputer(strategy='median')
input_dir = '/input'
obs_feats = ['Age at Death', 'Years of education', 'PMI']
output_dir = '/output'
parts = [
array([[96. , 14. , 10.3],
[96. , 14. , 10.3],
[96. , 14. , 10.3],
...,
[97. , 14. , 4.8],
[97. , 14. , 4.8],
[97. , 14. , 4.8]], shape=(542673, 3))
]
preproc = {
'imputer': SimpleImputer(strategy='median'),
'scaler': StandardScaler(),
'feat_names': [
'Age at Death',
'Years of education',
'PMI',
'percent 6e10 positive area',
'percent AT8 positive area',
'percent NeuN positive area',
'percent GFAP positive area',
'percent aSyn positive area',
'percent pTDP43 positive area'
]
}
... [truncated]
ValueError: X has 3 features, but SimpleImputer is expecting 9 features as
input.
```
This error was also received with subID 9760510 (https://www.synapse.org/Synapse:syn66496696/discussion/threadId=12475)
-Verena