onnx runtime

onnxruntime/onnxruntime-linux-x64-gpu-1.18.1/include/core/providers/cuda/cuda_context.h

@@ -0,0 +1,100 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+// This header is to expose a context for cuda custom ops.
+// By the context, a custom cuda operator could fetch existing resources,
+// such as cuda stream and cudnn handle, for reusing.
+
+// For concrete usage, pls find page here:
+// https://onnxruntime.ai/docs/reference/operators/add-custom-op.html#custom-ops-for-cuda-and-rocm
+
+#pragma once
+
+#define ORT_CUDA_CTX
+
+#include "cuda_resource.h"
+#include "core/providers/custom_op_context.h"
+#include <cuda.h>
+#include <cuda_runtime.h>
+#ifndef USE_CUDA_MINIMAL
+#include <cublas_v2.h>
+#include <cudnn.h>
+#endif
+namespace Ort {
+
+namespace Custom {
+
+struct CudaContext : public CustomOpContext {
+  cudaStream_t cuda_stream = {};
+  cudnnHandle_t cudnn_handle = {};
+  cublasHandle_t cublas_handle = {};
+  OrtAllocator* deferred_cpu_allocator = {};
+  // below are cuda ep options
+  int16_t device_id = 0;
+  int32_t arena_extend_strategy = 0;
+  int32_t cudnn_conv_algo_search = 0;
+  bool cudnn_conv_use_max_workspace = true;
+  bool cudnn_conv1d_pad_to_nc1d = false;
+  bool enable_skip_layer_norm_strict_mode = false;
+  bool prefer_nhwc = false;
+  bool use_tf32 = true;
+
+  void Init(const OrtKernelContext& kernel_ctx) {
+    cuda_stream = FetchResource<cudaStream_t>(kernel_ctx, CudaResource::cuda_stream_t);
+    cudnn_handle = FetchResource<cudnnHandle_t>(kernel_ctx, CudaResource::cudnn_handle_t);
+    cublas_handle = FetchResource<cublasHandle_t>(kernel_ctx, CudaResource::cublas_handle_t);
+    deferred_cpu_allocator = FetchResource<OrtAllocator*>(kernel_ctx, CudaResource::deferred_cpu_allocator_t);
+
+    device_id = FetchResource<int16_t>(kernel_ctx, CudaResource::device_id_t);
+    arena_extend_strategy = FetchResource<int32_t>(kernel_ctx, CudaResource::arena_extend_strategy_t);
+    cudnn_conv_algo_search = FetchResource<int32_t>(kernel_ctx, CudaResource::cudnn_conv_algo_search_t);
+    cudnn_conv_use_max_workspace = FetchResource<bool>(kernel_ctx, CudaResource::cudnn_conv_use_max_workspace_t);
+
+    cudnn_conv1d_pad_to_nc1d = FetchResource<bool>(kernel_ctx, CudaResource::cudnn_conv1d_pad_to_nc1d_t);
+    enable_skip_layer_norm_strict_mode = FetchResource<bool>(kernel_ctx, CudaResource::enable_skip_layer_norm_strict_mode_t);
+    prefer_nhwc = FetchResource<bool>(kernel_ctx, CudaResource::prefer_nhwc_t);
+    use_tf32 = FetchResource<bool>(kernel_ctx, CudaResource::use_tf32_t);
+  }
+
+  template <typename T>
+  T FetchResource(const OrtKernelContext& kernel_ctx, CudaResource resource_type) {
+    if constexpr (sizeof(T) > sizeof(void*)) {
+      ORT_CXX_API_THROW("void* is not large enough to hold resource type: " + std::to_string(resource_type), OrtErrorCode::ORT_INVALID_ARGUMENT);
+    }
+    const auto& ort_api = Ort::GetApi();
+    void* resource = {};
+    OrtStatus* status = ort_api.KernelContext_GetResource(&kernel_ctx, ORT_CUDA_RESOUCE_VERSION, resource_type, &resource);
+    if (status) {
+      ORT_CXX_API_THROW("Failed to fetch cuda ep resource, resouce type: " + std::to_string(resource_type), OrtErrorCode::ORT_RUNTIME_EXCEPTION);
+    }
+    T t = {};
+    memcpy(&t, &resource, sizeof(T));
+    return t;
+  }
+
+  void* AllocDeferredCpuMem(size_t size) const {
+    if (0 == size) {
+      return {};
+    }
+    const auto& ort_api = Ort::GetApi();
+    void* mem = {};
+    auto status = ort_api.AllocatorAlloc(deferred_cpu_allocator, size, &mem);
+    if (status) {
+      ORT_CXX_API_THROW("failed to allocate deferred cpu memory", OrtErrorCode::ORT_RUNTIME_EXCEPTION);
+    }
+    return mem;
+  }
+
+  void FreeDeferredCpuMem(void* mem) const {
+    if (mem) {
+      const auto& ort_api = Ort::GetApi();
+      auto status = ort_api.AllocatorFree(deferred_cpu_allocator, mem);
+      if (status) {
+        ORT_CXX_API_THROW("failed to free deferred cpu memory", OrtErrorCode::ORT_RUNTIME_EXCEPTION);
+      }
+    }
+  }
+};
+
+}  // namespace Custom
+}  // namespace Ort

onnxruntime/onnxruntime-linux-x64-gpu-1.18.1/include/core/providers/cuda/cuda_resource.h

@@ -0,0 +1,22 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+#include "core/providers/resource.h"
+
+#define ORT_CUDA_RESOUCE_VERSION 3
+
+enum CudaResource : int {
+  cuda_stream_t = cuda_resource_offset,  // 10000
+  cudnn_handle_t,
+  cublas_handle_t,
+  deferred_cpu_allocator_t,
+  // below are cuda ep options
+  device_id_t,  // 10004
+  arena_extend_strategy_t,
+  cudnn_conv_algo_search_t,
+  cudnn_conv_use_max_workspace_t,
+  cudnn_conv1d_pad_to_nc1d_t,
+  enable_skip_layer_norm_strict_mode_t,
+  prefer_nhwc_t,
+  use_tf32_t,
+};

onnxruntime/onnxruntime-linux-x64-gpu-1.18.1/include/core/providers/custom_op_context.h

@@ -0,0 +1,10 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+#pragma once
+
+// CustomOpContext defines an interface allowing a custom op to access ep-specific resources.
+struct CustomOpContext {
+  CustomOpContext() = default;
+  virtual ~CustomOpContext(){};
+};

onnxruntime/onnxruntime-linux-x64-gpu-1.18.1/include/core/providers/resource.h

@@ -0,0 +1,14 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+#pragma once
+
+enum ResourceOffset {
+  cpu_resource_offset = 0,
+  cuda_resource_offset = 10000,
+  dml_resource_offset = 20000,
+  rocm_resource_offset = 30000,
+  // offsets for other ort eps
+  custom_ep_resource_offset = 10000000,
+  // offsets for customized eps
+};