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nnlib
GPU-accelerated, C/C++ neural network library.
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| ▼CBackwardFunction | |
| ▼CFunction< sTensor, float > | |
| CMulConstant | |
| ▼CFunction< sTensor, sTensor > | |
| CAdd | |
| CAddBroadcast | |
| CDivide | |
| CHadamard | |
| CMatVecMul | |
| CMatmul | |
| CSubtract | |
| ▼CFunction< sTensor > | |
| CLog | |
| CReLU | |
| CSigmoid | |
| CSumReduce | |
| CTranspose | |
| CFunction< Types > | |
| CCache | |
| CEpochProgress | Structure to contain information about the current epoch |
| ▼Cstd::exception | |
| CDifferentDataLocationException | Exception to be thrown where operands are located in different places |
| CSizeMismatchException | Exception to be thrown where operands are different shapes |
| CUnexpectedCUDACallException | Exception to be thrown when a CUDA method was called despite no CUDA/GPU support |
| CUnsupportedOperationException | Exception to be thrown when an invalid operation is to be performed |
| CExtractType< i, tuple_element_t, wanted_element_t, wanted > | |
| CExtractType< i, tuple_element_t, wanted_element_t, true > | |
| CIsWantedType< wantedType, T > | |
| CIsWantedType< wantedType, std::tuple< Types... > > | |
| CLayer | Represents a single layer of a neural network |
| ▼CMetric | An abstract class to represent metrics |
| CBinaryAccuracy | The implementation of binary accuracy |
| CCategoricalAccuracy | The implementation of categorical accuracy |
| ▼CLoss | Abstract class representing a loss function |
| CBinaryCrossEntropy | Class representing the Binary Cross Entropy |
| CCategoricalCrossEntropy | Class representing the Categorical Cross Entropy |
| CMeanSquaredError | Class representing the Mean Squared Error |
| CNetwork | Represents a neural network |
| CRuntime | |
| CSession | Contains information about the current session |
| CTensor | Class to represent multidimensional arrays |
1.9.1
