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| */ | |
| /** | |
| * @file cudnn_subquadratic_ops.h | |
| * @brief cuDNN subquadratic / linear-complexity operations (causal conv1d, etc.). | |
| * | |
| * Provides direct function-call APIs for specialized kernels originating from | |
| * the SubquadraticOps library, without requiring the graph API or engine | |
| * infrastructure. | |
| * | |
| * @note Not supported on Windows. | |
| * | |
| * @since cuDNN 9.22.0 | |
| */ | |
| extern "C" { | |
| /** | |
| * @brief Activation mode for causal conv1d operations. | |
| * | |
| * @since cuDNN 9.22.0 | |
| */ | |
| typedef enum { | |
| CUDNN_CAUSAL_CONV1D_ACTIVATION_IDENTITY = 0, /**< Identity (no activation). */ | |
| CUDNN_CAUSAL_CONV1D_ACTIVATION_SILU = 1, /**< SiLU (Sigmoid Linear Unit) activation. */ | |
| } cudnnCausalConv1dActivation_t; | |
| /** | |
| * @brief Check the version of the cuDNN SubquadraticOps library. | |
| * | |
| * Verifies that the SubquadraticOps sub-library version matches the core cuDNN version. | |
| * | |
| * @return cudnnStatus_t indicating success or version mismatch. | |
| * | |
| * @since cuDNN 9.22.0 | |
| */ | |
| cudnnStatus_t CUDNNWINAPI | |
| cudnnSubquadraticOpsVersionCheck(void); | |
| /** | |
| * @brief Compute a causal (left-padded) depthwise 1D convolution with optional SiLU activation. | |
| * | |
| * Computes: y = Act( conv1d_causal(x, weight) + bias ) | |
| * | |
| * Causal padding inserts (kernel_size - 1) zeros on the left and 0 on the right. | |
| * The convolution is depthwise: each channel is convolved independently with its | |
| * own 1D filter. | |
| * | |
| * @param[in] stream CUDA stream for kernel launch. | |
| * @param[in] x Input tensor in device memory, layout (batch, dim, seq_len), contiguous. | |
| * @param[in] weight Filter tensor in device memory, layout (dim, kernel_size), contiguous. | |
| * @param[in] bias Bias tensor in device memory, layout (dim,), contiguous. Must be non-NULL. | |
| * @param[out] y Output tensor in device memory, layout (batch, dim, seq_len), contiguous. | |
| * @param[in] batch Batch size. | |
| * @param[in] dim Number of channels (feature dimension). | |
| * @param[in] seqLen Sequence length. | |
| * @param[in] kernelSize Convolution kernel width. Supported: 2-8, 16, 32, 64, 128, 256. | |
| * @param[in] dataType Element type for x, weight, bias, y. Supported: FLOAT, HALF, BFLOAT16. | |
| * @param[in] activation Activation to apply after convolution + bias. | |
| * | |
| * @note Not supported on Windows. | |
| * | |
| * @return cudnnStatus_t indicating success or failure. | |
| * | |
| * @since cuDNN 9.22.0 | |
| */ | |
| cudnnStatus_t CUDNNWINAPI | |
| cudnnCausalConv1dForward(cudaStream_t stream, | |
| const void *x, | |
| const void *weight, | |
| const void *bias, | |
| void *y, | |
| int batch, | |
| int dim, | |
| int seqLen, | |
| int kernelSize, | |
| cudnnDataType_t dataType, | |
| cudnnCausalConv1dActivation_t activation); | |
| /** | |
| * @brief Compute gradients for causal depthwise 1D convolution. | |
| * | |
| * Computes: | |
| * - dx = dL/dx (batch, dim, seq_len) | |
| * - dweight = dL/dweight (dim, kernel_size) — accumulated via atomicAdd | |
| * - dbias = dL/dbias (dim,) — accumulated via atomicAdd | |
| * | |
| * The caller must zero-initialize dweight and dbias before calling this function | |
| * if accumulation across multiple calls is not desired. | |
| * | |
| * @param[in] stream CUDA stream for kernel launch. | |
| * @param[in] x Original input tensor (needed for activation backward), device memory. | |
| * @param[in] weight Original filter tensor in device memory. | |
| * @param[in] bias Original bias tensor in device memory. Must be non-NULL. | |
| * @param[in] dy Output gradient tensor in device memory, layout (batch, dim, seq_len). | |
| * @param[out] dx Input gradient tensor in device memory, layout (batch, dim, seq_len). | |
| * @param[in,out] dweight Filter gradient tensor (accumulated) in device memory, layout (dim, kernel_size). | |
| * @param[in,out] dbias Bias gradient tensor (accumulated) in device memory, layout (dim,). Must be non-NULL. | |
| * @param[in] batch Batch size. | |
| * @param[in] dim Number of channels. | |
| * @param[in] seqLen Sequence length. | |
| * @param[in] kernelSize Convolution kernel width. | |
| * @param[in] dataType Element type for x, weight, bias, dy, dx. Supported: FLOAT, HALF, BFLOAT16. | |
| * @param[in] dwDataType Element type for dweight, dbias. Currently only FLOAT is supported. | |
| * @param[in] activation Activation that was applied in forward (needed for backward recompute). | |
| * | |
| * @note Not supported on Windows. | |
| * | |
| * @return cudnnStatus_t indicating success or failure. | |
| * | |
| * @since cuDNN 9.22.0 | |
| */ | |
| cudnnStatus_t CUDNNWINAPI | |
| cudnnCausalConv1dBackward(cudaStream_t stream, | |
| const void *x, | |
| const void *weight, | |
| const void *bias, | |
| const void *dy, | |
| void *dx, | |
| void *dweight, | |
| void *dbias, | |
| int batch, | |
| int dim, | |
| int seqLen, | |
| int kernelSize, | |
| cudnnDataType_t dataType, | |
| cudnnDataType_t dwDataType, | |
| cudnnCausalConv1dActivation_t activation); | |
| } | |