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- BinaryAccuracy
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- Recall
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- SparseTopKCategoricalAccuracy
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- SpecificityAtSensitivity
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		Accelerator
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		Constant
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		Generator
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		Full Train Step
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		Eval Step
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		Train Step
Get GPU platform
Description
Check if your computer is GPU ready. First check if CUDA is installed, if yes display device informations according to deviceID and check if CuDNN is also installed. If both are installed, it’s GPU ready.
 
			Input parameters
 Model in : model architecture.
 Model in : model architecture. deviceID : integer, ID of GPU device.
 deviceID : integer, ID of GPU device.
Output parameters
 Model out : model architecture.
 Model out : model architecture.
 Platform : cluster
 Platform : cluster
 Devices : cluster
 Devices : cluster
 GPU : boolean, true if computer is GPU ready.
 GPU : boolean, true if computer is GPU ready.
 Installed : cluster
 Installed : cluster
 CUDA : boolean, true if CUDA is installed.
 CUDA : boolean, true if CUDA is installed. CUDNN : boolean, true if CUDNN is installed.
 CUDNN : boolean, true if CUDNN is installed.
 Device Informations : cluster
 Device Informations : cluster
 Name : string, returns an identifier string for the device.
 Name : string, returns an identifier string for the device. Total Global Memory (Bytes) : integer, returns the total amount of memory on the device.
 Total Global Memory (Bytes) : integer, returns the total amount of memory on the device. Shared Memory / Block (Bytes) : integer, maximum shared memory available per block in bytes.
 Shared Memory / Block (Bytes) : integer, maximum shared memory available per block in bytes. Registers / Block : integer, maximum number of 32-bit registers available per block.
 Registers / Block : integer, maximum number of 32-bit registers available per block. Warp Size : integer, warp size in threads.
 Warp Size : integer, warp size in threads. Memory Pitch (Bytes) : integer, maximum pitch in bytes allowed by memory copies.
 Memory Pitch (Bytes) : integer, maximum pitch in bytes allowed by memory copies. Max Threads / Block : integer, maximum number of threads per block.
 Max Threads / Block : integer, maximum number of threads per block. Max Threads DimΒ : array, maximum block dimensions X, Y, and Z.
 Max Threads DimΒ : array, maximum block dimensions X, Y, and Z. Max Grid Size : array, maximum grid dimension X, Y and Z.
 Max Grid Size : array, maximum grid dimension X, Y and Z. Total Constant Memory : integer, memory available on device for __constant__ variables in a CUDA C kernel in bytes.
 Total Constant Memory : integer, memory available on device for __constant__ variables in a CUDA C kernel in bytes. Version (Compute Capability) : cluster
 Version (Compute Capability) : cluster
 Major : integer, major revision number.
 Major : integer, major revision number. Minor : integer, minor revision number.
 Minor : integer, minor revision number.
 Clock Rate (Hz) : integer, typical clock frequency in kilohertz.
 Clock Rate (Hz) : integer, typical clock frequency in kilohertz. Texture Alignment (Bytes) : integer, alignment requirement for textures.
 Texture Alignment (Bytes) : integer, alignment requirement for textures.
 Informations : cluster
 Informations : cluster
 CUDADriverVersion : string, returns the latest CUDA version supported by driver.
 CUDADriverVersion : string, returns the latest CUDA version supported by driver. CUDARuntimeVersion : string, returns the CUDA Runtime version.
 CUDARuntimeVersion : string, returns the CUDA Runtime version. Number of CUDA Devives : integer, returns the number of compute-capable devices.
 Number of CUDA Devives : integer, returns the number of compute-capable devices.
 
			Example
All these exemples are snippets PNG, you can drop these Snippet onto the block diagram and get the depicted code added to your VI (Do not forget to install Deep Learning library to run it).
