diff --git a/UNet/Sim_logs/UNet_32_V9_V10_J.log b/UNet/Sim_logs/UNet_32_V9_V10_J.log
new file mode 100644
index 0000000000000000000000000000000000000000..c5e6f0cd9f906edd3713c3477a04bfdfb9d153bc
--- /dev/null
+++ b/UNet/Sim_logs/UNet_32_V9_V10_J.log
@@ -0,0 +1,70 @@
+(OK) Loading cuda 10.2.89
+(OK) Loading python 3.7.11
+(!!) The SciPy Stack is available: http://www.scipy.org/stackspec.html
+ Built with GCC compilers.
+Collecting torch==1.10.1
+ Using cached torch-1.10.1-cp37-cp37m-manylinux1_x86_64.whl (881.9 MB)
+Collecting typing-extensions
+ Using cached typing_extensions-4.1.1-py3-none-any.whl (26 kB)
+Installing collected packages: typing-extensions, torch
+ WARNING: The scripts convert-caffe2-to-onnx, convert-onnx-to-caffe2 and torchrun are installed in '/home/yk138599/.local/bin' which is not on PATH.
+ Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
+Successfully installed torch-1.10.1 typing-extensions-4.1.1
+WARNING: You are using pip version 21.2.4; however, version 22.0.3 is available.
+You should consider upgrading via the '/usr/local_rwth/sw/python/3.7.11/x86_64/bin/python3.7 -m pip install --upgrade pip' command.
+number auf epochs: 500
+batchsize: 32
+learning rate: 1e-05
+kernel size is: 5
+ seed is: 373686838
+Traceback (most recent call last):
+ File "./UNet_V9_1.py", line 247, in <module>
+ normalization = np.load(f'{path_to_rep}/UNet/Trainingsdata/Norm_min_max_32_angles.npy')
+ File "/rwthfs/rz/SW/UTIL.common/Python/3.7.11/x86_64/lib/python3.7/site-packages/numpy/lib/npyio.py", line 441, in load
+ pickle_kwargs=pickle_kwargs)
+ File "/rwthfs/rz/SW/UTIL.common/Python/3.7.11/x86_64/lib/python3.7/site-packages/numpy/lib/format.py", line 743, in read_array
+ raise ValueError("Object arrays cannot be loaded when "
+ValueError: Object arrays cannot be loaded when allow_pickle=False
+python3 ./UNet_V9_1.py 0.86s user 1.37s system 63% cpu 3.518 total
+number auf epochs: 500
+batchsize: 32
+learning rate: 1e-05
+kernel size is: 7
+ seed is: 373686838
+Traceback (most recent call last):
+ File "./UNet_V9_2.py", line 247, in <module>
+ normalization = np.load(f'{path_to_rep}/UNet/Trainingsdata/Norm_min_max_32_angles.npy')
+ File "/rwthfs/rz/SW/UTIL.common/Python/3.7.11/x86_64/lib/python3.7/site-packages/numpy/lib/npyio.py", line 441, in load
+ pickle_kwargs=pickle_kwargs)
+ File "/rwthfs/rz/SW/UTIL.common/Python/3.7.11/x86_64/lib/python3.7/site-packages/numpy/lib/format.py", line 743, in read_array
+ raise ValueError("Object arrays cannot be loaded when "
+ValueError: Object arrays cannot be loaded when allow_pickle=False
+python3 ./UNet_V9_2.py 0.87s user 1.33s system 79% cpu 2.786 total
+number auf epochs: 500
+batchsize: 32
+learning rate: 1e-05
+kernel size is: 3
+ seed is: 373686838
+Traceback (most recent call last):
+ File "./UNet_V9_3.py", line 247, in <module>
+ normalization = np.load(f'{path_to_rep}/UNet/Trainingsdata/Norm_min_max_32_angles.npy')
+ File "/rwthfs/rz/SW/UTIL.common/Python/3.7.11/x86_64/lib/python3.7/site-packages/numpy/lib/npyio.py", line 441, in load
+ pickle_kwargs=pickle_kwargs)
+ File "/rwthfs/rz/SW/UTIL.common/Python/3.7.11/x86_64/lib/python3.7/site-packages/numpy/lib/format.py", line 743, in read_array
+ raise ValueError("Object arrays cannot be loaded when "
+ValueError: Object arrays cannot be loaded when allow_pickle=False
+python3 ./UNet_V9_3.py 0.85s user 1.39s system 82% cpu 2.716 total
+number auf epochs: 500
+batchsize: 32
+learning rate: 1e-05
+kernel size is: 5
+ seed is: 2193910023
+Traceback (most recent call last):
+ File "./UNet_V10.py", line 243, in <module>
+ normalization = np.load(f'{path_to_rep}/UNet/Trainingsdata/Norm_min_max_32_angles.npy')
+ File "/rwthfs/rz/SW/UTIL.common/Python/3.7.11/x86_64/lib/python3.7/site-packages/numpy/lib/npyio.py", line 441, in load
+ pickle_kwargs=pickle_kwargs)
+ File "/rwthfs/rz/SW/UTIL.common/Python/3.7.11/x86_64/lib/python3.7/site-packages/numpy/lib/format.py", line 743, in read_array
+ raise ValueError("Object arrays cannot be loaded when "
+ValueError: Object arrays cannot be loaded when allow_pickle=False
+python3 ./UNet_V10.py 0.86s user 1.38s system 79% cpu 2.806 total
diff --git a/UNet/Sim_logs/UNet_V9_32_25584245.log b/UNet/Sim_logs/UNet_V9_32_25584245.log
new file mode 100644
index 0000000000000000000000000000000000000000..b7bd00424b0b120a1ac35fe1a96f78f2c96ebd62
--- /dev/null
+++ b/UNet/Sim_logs/UNet_V9_32_25584245.log
@@ -0,0 +1,62 @@
+(OK) Loading cuda 10.2.89
+(OK) Loading python 3.7.11
+(!!) The SciPy Stack is available: http://www.scipy.org/stackspec.html
+ Built with GCC compilers.
+Collecting torch==1.10.1
+ Using cached torch-1.10.1-cp37-cp37m-manylinux1_x86_64.whl (881.9 MB)
+Collecting typing-extensions
+ Using cached typing_extensions-4.1.1-py3-none-any.whl (26 kB)
+Installing collected packages: typing-extensions, torch
+ WARNING: The scripts convert-caffe2-to-onnx, convert-onnx-to-caffe2 and torchrun are installed in '/home/yk138599/.local/bin' which is not on PATH.
+ Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
+Successfully installed torch-1.10.1 typing-extensions-4.1.1
+WARNING: You are using pip version 21.2.4; however, version 22.0.3 is available.
+You should consider upgrading via the '/usr/local_rwth/sw/python/3.7.11/x86_64/bin/python3.7 -m pip install --upgrade pip' command.
+number auf epochs: 500
+batchsize: 32
+learning rate: 1e-05
+kernel size is: 5
+ seed is: 373686838
+Traceback (most recent call last):
+ File "./UNet_V9_1.py", line 247, in <module>
+ normalization = np.load(f'{path_to_rep}/UNet/Trainingsdata/Norm_min_max_32_angles.npy')
+ File "/rwthfs/rz/SW/UTIL.common/Python/3.7.11/x86_64/lib/python3.7/site-packages/numpy/lib/npyio.py", line 417, in load
+ fid = stack.enter_context(open(os_fspath(file), "rb"))
+FileNotFoundError: [Errno 2] No such file or directory: 'home/yk138599/Hiwi/UNet/Trainingsdata/Norm_min_max_32_angles.npy'
+python3 ./UNet_V9_1.py 0.84s user 1.49s system 45% cpu 5.157 total
+number auf epochs: 500
+batchsize: 32
+learning rate: 1e-05
+kernel size is: 7
+ seed is: 373686838
+Traceback (most recent call last):
+ File "./UNet_V9_2.py", line 247, in <module>
+ normalization = np.load(f'{path_to_rep}/UNet/Trainingsdata/Norm_min_max_32_angles.npy')
+ File "/rwthfs/rz/SW/UTIL.common/Python/3.7.11/x86_64/lib/python3.7/site-packages/numpy/lib/npyio.py", line 417, in load
+ fid = stack.enter_context(open(os_fspath(file), "rb"))
+FileNotFoundError: [Errno 2] No such file or directory: 'home/yk138599/Hiwi/UNet/Trainingsdata/Norm_min_max_32_angles.npy'
+python3 ./UNet_V9_2.py 0.86s user 1.41s system 76% cpu 2.953 total
+number auf epochs: 500
+batchsize: 32
+learning rate: 1e-05
+kernel size is: 3
+ seed is: 373686838
+Traceback (most recent call last):
+ File "./UNet_V9_3.py", line 247, in <module>
+ normalization = np.load(f'{path_to_rep}/UNet/Trainingsdata/Norm_min_max_32_angles.npy')
+ File "/rwthfs/rz/SW/UTIL.common/Python/3.7.11/x86_64/lib/python3.7/site-packages/numpy/lib/npyio.py", line 417, in load
+ fid = stack.enter_context(open(os_fspath(file), "rb"))
+FileNotFoundError: [Errno 2] No such file or directory: 'home/yk138599/Hiwi/UNet/Trainingsdata/Norm_min_max_32_angles.npy'
+python3 ./UNet_V9_3.py 0.89s user 1.33s system 75% cpu 2.963 total
+number auf epochs: 500
+batchsize: 32
+learning rate: 1e-05
+kernel size is: 5
+ seed is: 2193910023
+Traceback (most recent call last):
+ File "./UNet_V10.py", line 243, in <module>
+ normalization = np.load(f'{path_to_rep}/UNet/Trainingsdata/Norm_min_max_32_angles.npy')
+ File "/rwthfs/rz/SW/UTIL.common/Python/3.7.11/x86_64/lib/python3.7/site-packages/numpy/lib/npyio.py", line 417, in load
+ fid = stack.enter_context(open(os_fspath(file), "rb"))
+FileNotFoundError: [Errno 2] No such file or directory: 'home/yk138599/Hiwi/UNet/Trainingsdata/Norm_min_max_32_angles.npy'
+python3 ./UNet_V10.py 0.89s user 1.41s system 69% cpu 3.295 total
diff --git a/UNet/Train_model.sh b/UNet/Train_model.sh
index 04db9528c80a33d7bef53bf147074d422d32934e..c9969a09599aa13ae9ab0c32bfa74966a80beb7b 100644
--- a/UNet/Train_model.sh
+++ b/UNet/Train_model.sh
@@ -6,16 +6,19 @@
#SBATCH --partition=c18g
#SBATCH -J training_model
-#SBATCH -o Sim_logs/UNet_V9_32_%J.log
+#SBATCH -o Sim_logs/UNet_32_V9_V10_J.log
#SBATCH --gres=gpu:1
-#SBATCH --time=50:00:00
+#SBATCH --time=90:00:00
### Request memory you need for your job in MB
#SBATCH --mem-per-cpu=10000
#SBATCH --mem-per-gpu=16000
module load cuda
module load python/3.7.11
pip3 install --user -Iv -q torch==1.10.1
-time python3 ./UNet_V9.py
+time python3 ./UNet_V9_1.py
+time python3 ./UNet_V9_2.py
+time python3 ./UNet_V9_3.py
+time python3 ./UNet_V10.py
#print GPU Information
#$CUDA_ROOT/extras/demo_suite/deviceQuery -noprompt
diff --git a/UNet/UNet_V10.py b/UNet/UNet_V10.py
index 5efc2f75d0d3e1feaf208d306a42e6d369268a97..9f16b123be0a8f93a75178dc61d0d23273a6dbfa 100644
--- a/UNet/UNet_V10.py
+++ b/UNet/UNet_V10.py
@@ -224,7 +224,7 @@ if __name__ == '__main__':
path_to_rep = '/home/yk138599/Hiwi/damask3'
use_seeds = True
seed = 2193910023
- num_epochs = 1300
+ num_epochs = 500
b_size = 32
opt_func = torch.optim.Adam
lr = 0.00001
@@ -240,8 +240,8 @@ if __name__ == '__main__':
random.seed(seed)
np.random.seed(seed)
device = get_default_device()
- normalization = np.load(f'{path_to_rep}/UNet/Trainingsdata/Norm_min_max_32_angles.npy')
- train_dl, valid_dl = Create_Dataloader(f'{path_to_rep}/UNet/Trainingsdata/Training_Dataset_normalized_32_V2.pt', batch_size= b_size )
+ normalization = np.load(f'{path_to_rep}/UNet/Trainingsdata/Norm_min_max_32_angles.npy', allow_pickle = True)
+ train_dl, valid_dl = Create_Dataloader(f'{path_to_rep}/UNet/Trainingsdata/TD_norm_32_phase_only.pt', batch_size= b_size )
train_dl = DeviceDataLoader(train_dl, device)
valid_dl = DeviceDataLoader(valid_dl, device)
diff --git a/UNet/UNet_V9_1.py b/UNet/UNet_V9_1.py
index 67edfbcdb7440ef6cbe86c974746ccfb49fe932a..9d0a6421475873e2e5eee12ced18dd07b79bc22e 100644
--- a/UNet/UNet_V9_1.py
+++ b/UNet/UNet_V9_1.py
@@ -228,7 +228,7 @@ if __name__ == '__main__':
path_to_rep = '/home/yk138599/Hiwi/damask3'
use_seeds = True
seed = 373686838
- num_epochs = 1300
+ num_epochs = 500
b_size = 32
opt_func = torch.optim.Adam
lr = 0.00001
@@ -244,8 +244,8 @@ if __name__ == '__main__':
random.seed(seed)
np.random.seed(seed)
device = get_default_device()
- normalization = np.load(f'{path_to_rep}/UNet/Trainingsdata/Norm_min_max_32_angles.npy')
- train_dl, valid_dl = Create_Dataloader(f'{path_to_rep}/UNet/Trainingsdata/Training_Dataset_normalized_32_V2.pt', batch_size= b_size )
+ normalization = np.load(f'{path_to_rep}/UNet/Trainingsdata/Norm_min_max_32_phase_only.npy', allow_pickle = True)
+ train_dl, valid_dl = Create_Dataloader(f'{path_to_rep}/UNet/Trainingsdata/TD_norm_32_phase_only.pt', batch_size= b_size )
train_dl = DeviceDataLoader(train_dl, device)
valid_dl = DeviceDataLoader(valid_dl, device)
diff --git a/UNet/UNet_V9_2.py b/UNet/UNet_V9_2.py
index 7337baa0bf57519d089d9edffc07139c2a2e0a1e..886846e464e23278dbde1bd5df84be223152bacd 100644
--- a/UNet/UNet_V9_2.py
+++ b/UNet/UNet_V9_2.py
@@ -228,7 +228,7 @@ if __name__ == '__main__':
path_to_rep = '/home/yk138599/Hiwi/damask3'
use_seeds = True
seed = 373686838
- num_epochs = 1300
+ num_epochs = 500
b_size = 32
opt_func = torch.optim.Adam
lr = 0.00001
@@ -244,8 +244,8 @@ if __name__ == '__main__':
random.seed(seed)
np.random.seed(seed)
device = get_default_device()
- normalization = np.load(f'{path_to_rep}/UNet/Trainingsdata/Norm_min_max_32_angles.npy')
- train_dl, valid_dl = Create_Dataloader(f'{path_to_rep}/UNet/Trainingsdata/Training_Dataset_normalized_32_V2.pt', batch_size= b_size )
+ normalization = np.load(f'{path_to_rep}/UNet/Trainingsdata/Norm_min_max_32_angles.npy', allow_pickle = True)
+ train_dl, valid_dl = Create_Dataloader(f'{path_to_rep}/UNet/Trainingsdata/TD_norm_32_phase_only.pt', batch_size= b_size )
train_dl = DeviceDataLoader(train_dl, device)
valid_dl = DeviceDataLoader(valid_dl, device)
diff --git a/UNet/UNet_V9_3.py b/UNet/UNet_V9_3.py
index 997dcfec17c601400f5116467ba2563f18cfed06..8453bc792f10eb753a017f1f514e110bc0a4d7e3 100644
--- a/UNet/UNet_V9_3.py
+++ b/UNet/UNet_V9_3.py
@@ -228,7 +228,7 @@ if __name__ == '__main__':
path_to_rep = '/home/yk138599/Hiwi/damask3'
use_seeds = True
seed = 373686838
- num_epochs = 1300
+ num_epochs = 500
b_size = 32
opt_func = torch.optim.Adam
lr = 0.00001
@@ -244,8 +244,8 @@ if __name__ == '__main__':
random.seed(seed)
np.random.seed(seed)
device = get_default_device()
- normalization = np.load(f'{path_to_rep}/UNet/Trainingsdata/Norm_min_max_32_angles.npy')
- train_dl, valid_dl = Create_Dataloader(f'{path_to_rep}/UNet/Trainingsdata/Training_Dataset_normalized_32_V2.pt', batch_size= b_size )
+ normalization = np.load(f'{path_to_rep}/UNet/Trainingsdata/Norm_min_max_32_angles.npy', allow_pickle = True)
+ train_dl, valid_dl = Create_Dataloader(f'{path_to_rep}/UNet/Trainingsdata/TD_norm_32_phase_only.pt', batch_size= b_size )
train_dl = DeviceDataLoader(train_dl, device)
valid_dl = DeviceDataLoader(valid_dl, device)