gher-uliege / DINCAE

DINCAE (Data-Interpolating Convolutional Auto-Encoder) is a neural network to reconstruct missing data in satellite observations.
GNU General Public License v3.0
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Failed to interpolate MODIS Chlorophyll-a Data #14

Closed hidayatmn378 closed 1 year ago

hidayatmn378 commented 1 year ago

Describe the bug

A description of what the bug is.

To Reproduce

Please provide a minimal code example which reproduces the behavior (bug, performance regression, ...).

Environment

Full output

In case of an error, please paste the full error message and stack trace. The file output attached record_modis_chl_3d.txt

Input file

Run the shell command ncdump -h myfile.nc and paste the output here. `netcdf input_file_python { dimensions: lon = 445 ; lat = 459 ; time = UNLIMITED ; // (3 currently) variables: float lon(lon) ; float lat(lat) ; float time(time) ; time:units = "days since 2021-01-01 00:00:00" ; float chl(time, lat, lon) ; chl:_FillValue = -9999.f ; int mask(lat, lon) ; mask:comment = "one means the data location is valid (e.g. sea for SST), zero the location is invalid (e.g. land for SST)" ;

// global attributes: :_NCProperties = "version=2,netcdf=4.8.1,hdf5=1.12.2" ; }`

jsihunh commented 1 year ago

Hello, your error was come from shortage of GPU capacity. i recommend to reduce your study area because your data dimension( lat(459 pixels) and lon(445 pixels)) was too large as input data in deep learning model.

hidayatmn378 commented 1 year ago

Thank you for your help. Now it works...