TensorFlow detects the 68 RT cores on my 2080 Ti, but not the CUDA cores

CUDA 10.1
2080 Ti
latest geforce drivers
I use a program called Starnet++ which normally uses AVX to remove stars from astrophotography images. Someone made a tensorflow.dll that tells the program to use the GPU instead of the CPU. When I run the program, i get this output:
PS E:\Astro\StarNet_Win> .\rgb_starnet++.exe ‘E:\Scope\Targets\Andromeda Galaxy M31\60mm\Andromeda_2.tif’
2020-09-08 21:13:44.886688: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudart64_101.dll
Reading input image… TIFFReadDirectory: Warning, Unknown field with tag 37724 (0x935c) encountered.
Done!
Bits per sample: 16
Samples per pixel: 3
Height: 4500
Width: 4896
Restoring neural network checkpoint… Done!
2020-09-08 21:13:52.020545: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations: AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2020-09-08 21:13:52.053077: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x272b78a5320 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-09-08 21:13:52.053163: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
2020-09-08 21:13:52.058242: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library nvcuda.dll
2020-09-08 21:13:52.080903: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 2080 Ti computeCapability: 7.5
coreClock: 1.62GHz coreCount: 68 deviceMemorySize: 11.00GiB deviceMemoryBandwidth: 573.69GiB/s
2020-09-08 21:13:52.081000: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudart64_101.dll
2020-09-08 21:13:52.085975: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cublas64_10.dll
2020-09-08 21:13:52.089461: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cufft64_10.dll
2020-09-08 21:13:52.091125: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library curand64_10.dll
2020-09-08 21:13:52.095350: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cusolver64_10.dll
2020-09-08 21:13:52.097962: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cusparse64_10.dll
2020-09-08 21:13:52.111342: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudnn64_7.dll
2020-09-08 21:13:52.112290: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1858] Adding visible gpu devices: 0
2020-09-08 21:13:53.511078: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1257] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-09-08 21:13:53.511147: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1263] 0
2020-09-08 21:13:53.512067: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1276] 0: N
2020-09-08 21:13:53.513030: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:39] Overriding allow_growth setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.
2020-09-08 21:13:53.513103: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1402] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9419 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2080 Ti, pci bus id: 0000:01:00.0, compute capability: 7.5)
2020-09-08 21:13:53.519145: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x27285e3e810 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2020-09-08 21:13:53.519199: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): GeForce RTX 2080 Ti, Compute Capability 7.5
Total number of tiles: 5467
2020-09-08 21:13:56.732740: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudnn64_7.dll
2020-09-08 21:13:57.524116: W tensorflow/stream_executor/gpu/redzone_allocator.cc:314] Internal: Invoking GPU asm compilation is supported on Cuda non-Windows platforms only
Relying on driver to perform ptx compilation.
Modify $PATH to customize ptxas location.
This message will be only logged once.
2020-09-08 21:13:57.535013: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cublas64_10.dll
100% finished

Done!

I am new to CUDA on the dev side and was just wondering why wouldn’t the program see the CUDA cores of my gpu?

The number 68 refers to the number of SMs in a GeForce 2080 Ti. Each SM comprises a plurality of “CUDA cores” and tensor cores.