search

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
47 stars 19 forks source link

Running examples input_file_python.nc #13

Closed hidayatmn378 closed 1 year ago

hidayatmn378 commented 1 year ago

Describe the bug

Error when running the original examples

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. ` 2023-02-04 11:40:35.989971: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: SSE4.1 SSE4.2 AVX AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2023-02-04 11:40:37.278685: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: SSE4.1 SSE4.2 AVX AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2023-02-04 11:40:37.279681: I tensorflow/core/common_runtime/process_util.cc:146] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance. 2023-02-04 11:40:37.280860: I tensorflow/core/common_runtime/process_util.cc:146] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance

varname SST (3, 3) data shape: (3, 3, 3) data range: 0.0 0.0 sz (3, 3, 3) sz (3, 3, 3) Number of input variables: 10 regularization_L2_beta 0 enc_nfilter_internal [16, 24, 36, 54] nvar 10 nepoch_keep_missing 0

Traceback (most recent call last): File "/home/ocean/DINCAE-master/run_DINCAE.py", line 10, in DINCAE.reconstruct_gridded_nc(filename,varname,outdir) File "/home/ocean/DINCAE-master/DINCAE/init.py", line 733, in reconstruct_gridded_nc reconstruct( File "/home/ocean/DINCAE-master/DINCAE/init.py", line 404, in reconstruct train_iterator_handle = sess.run(train_iterator.string_handle()) AttributeError: 'OwnedIterator' object has no attribute 'string_handle' ` Input file

Run the shell command ncdump -h myfile.nc and paste the output here. ` ocean@ocean-HP-EliteDesk-800-G1-TWR:~/DINCAE-master/examples$ ncdump -h input_file_python.nc netcdf input_file_python { dimensions: lon = 3 ; lat = 3 ; time = UNLIMITED ; // (3 currently) variables: float lon(lon) ; float lat(lat) ; float time(time) ; time:units = "days since 1900-01-01 00:00:00" ; float SST(time, lat, lon) ; SST:_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=1.10.6" ; } `

hidayatmn378 commented 1 year ago

Never mind. It works after I create the new env and install the libraries based on the README.md version.