Restructure include paths

2025-12-23 06:44:24 +00:00 · 2025-11-23 20:57:08 +01:00
parent 4161caf3e1
commit 38cb0c9ac0
13 changed files with 15 additions and 15 deletions
--- a/include/backend/cuda/cuda.cuh
+++ b/include/backend/cuda/cuda.cuh
@@ -0,0 +1,118 @@
+#pragma once
+
+#include <cstdio>
+
+#include "backend.hpp"
+#include "tensor.hpp"
+
+#ifndef BLOCK_SIZE
+#define BLOCK_SIZE 128
+#endif // BLOCK_SIZE
+
+/**
+ * @brief CUDA error checking macro
+ * 
+ */
+#define CUDA_CHECK(call) \
+do { \
+    cudaError_t result = call; \
+    if (result != cudaSuccess) { \
+        fprintf(stderr, "CUDA error at %s:%d code=%d(%s) \"%s\" \n", \
+                __FILE__, __LINE__, static_cast<unsigned int>(result), \
+                cudaGetErrorString(result), #call); \
+        exit(EXIT_FAILURE); \
+    } \
+} while (0)
+
+namespace CUDANet::Backends {
+
+class CUDA : public Backend {
+  public:
+    // Memory management
+    void* allocate(size_t bytes) override;
+    void  deallocate(void* ptr) override;
+
+    // Tensor ops
+    void print(const CUDANet::Tensor& input) override;
+    void zero(CUDANet::Tensor& input) override;
+    void fill(CUDANet::Tensor &input, int value) override;
+    void
+    copy_to_device(CUDANet::Tensor& tensor, void* data, size_t size) override;
+    void sum(const CUDANet::Tensor& input, CUDANet::Tensor& sum) override;
+    void max(const CUDANet::Tensor& input, CUDANet::Tensor& max) override;
+
+    // Layer ops
+    void relu(CUDANet::Tensor& tensor) override;
+    void sigmoid(CUDANet::Tensor& tensor) override;
+    void softmax(
+        CUDANet::Tensor& tensor,
+        CUDANet::Tensor& temp_max,
+        CUDANet::Tensor& temp_sum
+    ) override;
+
+    CUDANet::Tensor& dense(
+        const CUDANet::Tensor& weights,
+        const CUDANet::Tensor& biases,
+        const CUDANet::Tensor& input,
+        CUDANet::Tensor& output,
+        const size_t           input_size,
+        const size_t           output_size
+    ) override;
+
+    CUDANet::Tensor& conv2d(
+        const CUDANet::Tensor& weights,
+        const CUDANet::Tensor& biases,
+        const CUDANet::Tensor& input,
+        CUDANet::Tensor& output,
+        const CUDANet::Shape in_shape,
+        const CUDANet::Shape padding_shape,
+        const CUDANet::Shape kernel_shape,
+        const CUDANet::Shape stride_shape,
+        const CUDANet::Shape out_shape
+    ) override;
+
+    CUDANet::Tensor& max_pool2d(
+        const CUDANet::Tensor& input,
+        CUDANet::Tensor& output,
+        CUDANet::Shape input_shape,
+        CUDANet::Shape pool_shape,
+        CUDANet::Shape stride_shape,
+        CUDANet::Shape padding_shape,
+        CUDANet::Shape output_shape
+    ) override;
+
+    CUDANet::Tensor& avg_pool2d(
+        const CUDANet::Tensor& input,
+        CUDANet::Tensor& output,
+        CUDANet::Shape input_shape,
+        CUDANet::Shape pool_shape,
+        CUDANet::Shape stride_shape,
+        CUDANet::Shape padding_shape,
+        CUDANet::Shape output_shape
+    ) override;
+
+    CUDANet::Tensor& batch_norm(
+        const CUDANet::Tensor& input,
+        CUDANet::Tensor& output,
+        CUDANet::Shape input_shape,
+        CUDANet::Tensor& weights,
+        CUDANet::Tensor& biases,
+        CUDANet::Tensor& running_mean,
+        CUDANet::Tensor& running_var,
+        CUDANet::Tensor& epsilon
+    ) override;
+
+    CUDANet::Tensor& concat(
+        CUDANet::Tensor& input_a,
+        CUDANet::Tensor& input_b,
+        CUDANet::Tensor& output
+    ) override;
+
+    CUDANet::Tensor& add(
+        CUDANet::Tensor& input_a,
+        CUDANet::Tensor& input_b,
+        CUDANet::Tensor& output
+    ) override;
+};
+
+}  // namespace CUDANet::Backend