chore: import upstream snapshot with attribution

2026-07-13 13:36:55 +08:00
commit c8a779b1bb
1887 changed files with 3245738 additions and 0 deletions
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+/*
+ * SPDX-FileCopyrightText: Copyright (c) 1993-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef TRT_PLUGIN_CUDNN_WRAPPER_H
+#define TRT_PLUGIN_CUDNN_WRAPPER_H
+
+#include "NvInferPlugin.h"
+#include <functional>
+#include <string>
+
+extern "C"
+{
+    //! Forward declaration of cudnnTensorStruct to use in other interfaces.
+    struct cudnnTensorStruct;
+}
+
+namespace nvinfer1
+{
+namespace pluginInternal
+{
+/*
+ * Copy of the CUDNN return codes
+ */
+enum CudnnStatus
+{
+    CUDNN_STATUS_SUCCESS = 0,
+    CUDNN_STATUS_NOT_INITIALIZED = 1,
+    CUDNN_STATUS_ALLOC_FAILED = 2,
+    CUDNN_STATUS_BAD_PARAM = 3,
+    CUDNN_STATUS_INTERNAL_ERROR = 4,
+    CUDNN_STATUS_INVALID_VALUE = 5,
+    CUDNN_STATUS_ARCH_MISMATCH = 6,
+    CUDNN_STATUS_MAPPING_ERROR = 7,
+    CUDNN_STATUS_EXECUTION_FAILED = 8,
+    CUDNN_STATUS_NOT_SUPPORTED = 9,
+    CUDNN_STATUS_LICENSE_ERROR = 10,
+    CUDNN_STATUS_RUNTIME_PREREQUISITE_MISSING = 11,
+    CUDNN_STATUS_RUNTIME_IN_PROGRESS = 12,
+    CUDNN_STATUS_RUNTIME_FP_OVERFLOW = 13,
+    CUDNN_STATUS_VERSION_MISMATCH = 14,
+};
+
+/*
+ * Copy of the CUDNN cudnnBatchNormMode_t
+ */
+enum cudnnBatchNormMode
+{
+    CUDNN_BATCHNORM_PER_ACTIVATION = 0,
+    CUDNN_BATCHNORM_SPATIAL = 1,
+    CUDNN_BATCHNORM_SPATIAL_PERSISTENT = 2,
+};
+
+/*
+ * Copy of the CUDNN cudnnTensorFormat_t
+ */
+enum cudnnTensorFormat
+{
+    CUDNN_TENSOR_NCHW = 0,
+    CUDNN_TENSOR_NHWC = 1,
+    CUDNN_TENSOR_NCHW_VECT_C = 2,
+};
+
+/*
+ * Copy of CUDNN data type
+ */
+enum cudnnDataType
+{
+    CUDNN_DATA_FLOAT = 0,
+    CUDNN_DATA_DOUBLE = 1,
+    CUDNN_DATA_HALF = 2,
+    CUDNN_DATA_INT8 = 3,
+    CUDNN_DATA_INT32 = 4,
+    CUDNN_DATA_INT8x4 = 5,
+    CUDNN_DATA_UINT8 = 6,
+    CUDNN_DATA_UINT8x4 = 7,
+    CUDNN_DATA_INT8x32 = 8,
+    CUDNN_DATA_BFLOAT16 = 9,
+    CUDNN_DATA_INT64 = 10,
+    CUDNN_DATA_BOOLEAN = 11,
+    CUDNN_DATA_FP8_E4M3 = 12,
+    CUDNN_DATA_FP8_E5M2 = 13,
+    CUDNN_DATA_FAST_FLOAT_FOR_FP8 = 14,
+};
+
+using cudnnStatus_t = CudnnStatus;
+using cudnnBatchNormMode_t = cudnnBatchNormMode;
+using cudnnTensorFormat_t = cudnnTensorFormat;
+using cudnnDataType_t = cudnnDataType;
+
+using cudnnHandle_t = struct cudnnContext*;
+using cudnnTensorDescriptor_t = struct cudnnTensorStruct*;
+
+class CudnnWrapper
+{
+public:
+    explicit CudnnWrapper(bool initHandle = false, char const* callerPluginName = nullptr);
+    ~CudnnWrapper();
+
+    cudnnContext* getCudnnHandle();
+    bool isValid() const;
+
+    /*
+     * Copy of the CUDNN APIs
+     */
+    cudnnStatus_t cudnnCreate(cudnnContext** handle);
+    cudnnStatus_t cudnnDestroy(cudnnContext* handle);
+    cudnnStatus_t cudnnCreateTensorDescriptor(cudnnTensorDescriptor_t* tensorDesc);
+    cudnnStatus_t cudnnDestroyTensorDescriptor(cudnnTensorDescriptor_t tensorDesc);
+    cudnnStatus_t cudnnSetStream(cudnnHandle_t handle, cudaStream_t streamId);
+    cudnnStatus_t cudnnBatchNormalizationForwardTraining(cudnnHandle_t handle, cudnnBatchNormMode_t mode,
+        void const* alpha, void const* beta, cudnnTensorStruct const* xDesc, void const* x,
+        cudnnTensorStruct const* yDesc, void* y, cudnnTensorStruct const* bnScaleBiasMeanVarDesc, void const* bnScale,
+        void const* bnBias, double exponentialAverageFactor, void* resultRunningMean, void* resultRunningVariance,
+        double epsilon, void* resultSaveMean, void* resultSaveInvVariance);
+    cudnnStatus_t cudnnSetTensor4dDescriptor(cudnnTensorDescriptor_t tensorDesc, cudnnTensorFormat_t format,
+        cudnnDataType_t dataType, int n, int c, int h, int w);
+    cudnnStatus_t cudnnSetTensorNdDescriptor(cudnnTensorDescriptor_t tensorDesc, cudnnDataType_t dataType, int nbDims,
+        int const dimA[], int const strideA[]);
+    cudnnStatus_t cudnnSetTensorNdDescriptorEx(cudnnTensorDescriptor_t tensorDesc, cudnnTensorFormat_t format,
+        cudnnDataType_t dataType, int nbDims, int const dimA[]);
+    cudnnStatus_t cudnnDeriveBNTensorDescriptor(
+        cudnnTensorDescriptor_t derivedBnDesc, cudnnTensorStruct const* xDesc, cudnnBatchNormMode_t mode);
+    char const* cudnnGetErrorString(cudnnStatus_t status);
+
+private:
+    void* mLibrary{nullptr};
+    cudnnContext* mHandle{nullptr};
+    void* tryLoadingCudnn(char const*);
+
+    cudnnStatus_t (*_cudnnCreate)(cudnnContext**);
+    cudnnStatus_t (*_cudnnDestroy)(cudnnContext*);
+    cudnnStatus_t (*_cudnnCreateTensorDescriptor)(cudnnTensorDescriptor_t*);
+    cudnnStatus_t (*_cudnnDestroyTensorDescriptor)(cudnnTensorDescriptor_t);
+    cudnnStatus_t (*_cudnnSetStream)(cudnnHandle_t, cudaStream_t);
+    cudnnStatus_t (*_cudnnBatchNormalizationForwardTraining)(cudnnHandle_t, cudnnBatchNormMode_t, void const*,
+        void const*, cudnnTensorStruct const*, void const*, cudnnTensorStruct const*, void*, cudnnTensorStruct const*,
+        void const*, void const*, double, void*, void*, double, void*, void*);
+    cudnnStatus_t (*_cudnnSetTensor4dDescriptor)(
+        cudnnTensorDescriptor_t, cudnnTensorFormat_t, cudnnDataType_t, int, int, int, int);
+    cudnnStatus_t (*_cudnnSetTensorNdDescriptor)(cudnnTensorDescriptor_t tensorDesc, cudnnDataType_t dataType,
+        int nbDims, int const dimA[], int const strideA[]);
+    cudnnStatus_t (*_cudnnSetTensorNdDescriptorEx)(cudnnTensorDescriptor_t tensorDesc, cudnnTensorFormat_t format,
+        cudnnDataType_t dataType, int nbDims, int const dimA[]);
+    cudnnStatus_t (*_cudnnDeriveBNTensorDescriptor)(
+        cudnnTensorDescriptor_t, cudnnTensorStruct const*, cudnnBatchNormMode_t);
+    char const* (*_cudnnGetErrorString)(cudnnStatus_t status);
+};
+
+CudnnWrapper& getCudnnWrapper(char const* callerPluginName);
+
+} // namespace pluginInternal
+} // namespace nvinfer1
+
+#endif // TRT_PLUGIN_CUDNN_WRAPPER_H