activation.h¶
Activation functions.
Functions
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void nvte_gelu(const NVTETensor input, NVTETensor output, cudaStream_t stream)¶
- Compute GELU activation of the input. - Parameters
- input – [in] Input tensor for GELU activation. 
- output – [inout] Output tensor. 
- stream – [in] CUDA stream used for the operation. 
 
 
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void nvte_dgelu(const NVTETensor grad, const NVTETensor input, NVTETensor output, cudaStream_t stream)¶
- Compute GELU activation gradient. - Parameters
- grad – [in] Incoming gradient. 
- input – [in] Input tensor for GELU activation. 
- output – [inout] Output tensor. 
- stream – [in] CUDA stream used for the operation. 
 
 
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void nvte_geglu(const NVTETensor input, NVTETensor output, cudaStream_t stream)¶
- Compute GeGLU of the input. - Parameters
- input – [in] Input tensor of shape [N, H * 2]. 
- output – [inout] Output tensor of shape [N, H]. It computes GELU(input[N, :H]) x input[N, H:] 
- stream – [in] CUDA stream used for the operation. 
 
 
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void nvte_dgeglu(const NVTETensor grad, const NVTETensor input, NVTETensor output, cudaStream_t stream)¶
- Compute GeGLU gradient. - Parameters
- grad – [in] Incoming gradient of shape [N, H]. 
- input – [in] Forward input tensor of shape [N, H * 2]. 
- output – [inout] Outgoing gradient of shape [N, H * 2]. 
- stream – [in] CUDA stream used for the operation. 
 
 
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void nvte_relu(const NVTETensor input, NVTETensor output, cudaStream_t stream)¶
- Compute RELU activation of the input. - Parameters
- input – [in] Input tensor for RELU activation. 
- output – [inout] Output tensor. 
- stream – [in] CUDA stream used for the operation. 
 
 
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void nvte_drelu(const NVTETensor grad, const NVTETensor input, NVTETensor output, cudaStream_t stream)¶
- Compute RELU activation gradient. - Parameters
- grad – [in] Incoming gradient. 
- input – [in] Input tensor for RELU activation. 
- output – [inout] Output tensor. 
- stream – [in] CUDA stream used for the operation. 
 
 
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void nvte_swiglu(const NVTETensor input, NVTETensor output, cudaStream_t stream)¶
- Compute SwiGLU activation of the input. - Parameters
- input – [in] Input tensor of shape [N, H * 2]. 
- output – [inout] Output tensor of shape [N, H]. It computes Swish(input[N, :H]) x input[N, H:] 
- stream – [in] CUDA stream used for the operation. 
 
 
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void nvte_dswiglu(const NVTETensor grad, const NVTETensor input, NVTETensor output, cudaStream_t stream)¶
- Compute SwiGLU gradient. - Parameters
- grad – [in] Incoming gradient of shape [N, H]. 
- input – [in] Forward input tensor of shape [N, H * 2]. 
- output – [inout] Outgoing gradient of shape [N, H * 2]. 
- stream – [in] CUDA stream used for the operation. 
 
 
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void nvte_reglu(const NVTETensor input, NVTETensor output, cudaStream_t stream)¶
- Compute ReGLU activation of the input. - Parameters
- input – [in] Input tensor of shape [N, H * 2]. 
- output – [inout] Output tensor of shape [N, H]. It computes ReLU(input[N, :H]) x input[N, H:] 
- stream – [in] CUDA stream used for the operation. 
 
 
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void nvte_dreglu(const NVTETensor grad, const NVTETensor input, NVTETensor output, cudaStream_t stream)¶
- Compute ReGLU gradient. - Parameters
- grad – [in] Incoming gradient of shape [N, H]. 
- input – [in] Forward input tensor of shape [N, H * 2]. 
- output – [inout] Outgoing gradient of shape [N, H * 2]. 
- stream – [in] CUDA stream used for the operation.