The following lines are the warning messages i get:
2023-06-09 16:07:46.235447: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found
2023-06-09 16:07:46.235565: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2023-06-09 16:07:48.274818: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2023-06-09 16:07:48.338426: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties:
pciBusID: 0000:29:00.0 name: NVIDIA GeForce GTX 1650 computeCapability: 7.5
coreClock: 1.59GHz coreCount: 14 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 178.84GiB/s
2023-06-09 16:07:48.339794: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found
2023-06-09 16:07:48.340883: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cublas64_10.dll'; dlerror: cublas64_10.dll not found
2023-06-09 16:07:48.341921: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cufft64_10.dll'; dlerror: cufft64_10.dll not found
2023-06-09 16:07:48.371945: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2023-06-09 16:07:48.373297: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cusolver64_10.dll'; dlerror: cusolver64_10.dll not found
2023-06-09 16:07:48.374450: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cusparse64_10.dll'; dlerror: cusparse64_10.dll not found
2023-06-09 16:07:48.375527: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cudnn64_7.dll'; dlerror: cudnn64_7.dll not found
2023-06-09 16:07:48.375619: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1598] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
2023-06-09 16:07:48.743390: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2023-06-09 16:07:48.749498: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x1a49acc68c0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2023-06-09 16:07:48.749616: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
2023-06-09 16:07:48.749766: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2023-06-09 16:07:48.749847: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108]
WARNING:tensorflow:No training configuration found in save file, so the model was not compiled. Compile it manually.
WARNING:tensorflow:No training configuration found in the save file, so the model was not compiled. Compile it manually.
2023-06-09 16:08:00.418291: W tensorflow/compiler/jit/mark_for_compilation_pass.cc:1631] (One-time warning): Not using XLA:CPU for cluster because envvar TF_XLA_FLAGS=--tf_xla_cpu_global_jit was not set. If you want XLA:CPU, either set that envvar, or use experimental_jit_scope to enable XLA:CPU. To confirm that XLA is active, pass --vmodule=xla_compilation_cache=1 (as a proper command-line flag, not via TF_XLA_FLAGS) or set the envvar XLA_FLAGS=--xla_hlo_profile.
The following lines are the warning messages i get:
2023-06-09 16:07:46.235447: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found
2023-06-09 16:07:46.235565: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2023-06-09 16:07:48.274818: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2023-06-09 16:07:48.338426: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties:
pciBusID: 0000:29:00.0 name: NVIDIA GeForce GTX 1650 computeCapability: 7.5
coreClock: 1.59GHz coreCount: 14 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 178.84GiB/s
2023-06-09 16:07:48.339794: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found
2023-06-09 16:07:48.340883: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cublas64_10.dll'; dlerror: cublas64_10.dll not found
2023-06-09 16:07:48.341921: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cufft64_10.dll'; dlerror: cufft64_10.dll not found
2023-06-09 16:07:48.371945: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2023-06-09 16:07:48.373297: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cusolver64_10.dll'; dlerror: cusolver64_10.dll not found
2023-06-09 16:07:48.374450: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cusparse64_10.dll'; dlerror: cusparse64_10.dll not found
2023-06-09 16:07:48.375527: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cudnn64_7.dll'; dlerror: cudnn64_7.dll not found
2023-06-09 16:07:48.375619: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1598] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
2023-06-09 16:07:48.743390: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2023-06-09 16:07:48.749498: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x1a49acc68c0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2023-06-09 16:07:48.749616: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
2023-06-09 16:07:48.749766: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2023-06-09 16:07:48.749847: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108]
WARNING:tensorflow:No training configuration found in save file, so the model was not compiled. Compile it manually.
WARNING:tensorflow:No training configuration found in the save file, so the model was not compiled. Compile it manually.
2023-06-09 16:08:00.418291: W tensorflow/compiler/jit/mark_for_compilation_pass.cc:1631] (One-time warning): Not using XLA:CPU for cluster because envvar TF_XLA_FLAGS=--tf_xla_cpu_global_jit was not set. If you want XLA:CPU, either set that envvar, or use experimental_jit_scope to enable XLA:CPU. To confirm that XLA is active, pass --vmodule=xla_compilation_cache=1 (as a proper command-line flag, not via TF_XLA_FLAGS) or set the envvar XLA_FLAGS=--xla_hlo_profile.