| #ifndef NEUROFLOW_TENSOR_OPS_HPP
|
| #define NEUROFLOW_TENSOR_OPS_HPP
|
|
|
|
|
| namespace neuroflow {
|
|
|
| class TensorOps {
|
| public:
|
| static void gemm(const Tensor& A, const Tensor& B, Tensor& C,
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| bool transA = false, bool transB = false,
|
| float alpha = 1.0f, float beta = 0.0f);
|
|
|
| static void quantized_gemm(const Tensor& A, const Tensor& B, Tensor& C);
|
|
|
| static void layer_norm(Tensor& x, Tensor& weight, Tensor& bias, float eps = 1e-5f);
|
|
|
| static void gelu(Tensor& x);
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|
|
| static void softmax(Tensor& x, int axis = -1);
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|
|
| static void dropout(Tensor& x, float rate, bool training = true);
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|
|
| static void quantize_int8(const Tensor& src, Tensor& dst, Tensor& scale);
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|
|
| static void dequantize_int8(const Tensor& src, Tensor& dst, const Tensor& scale);
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|
|
| static void add(Tensor& a, const Tensor& b);
|
|
|
| static void mul(Tensor& a, float scalar);
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|
|
| static void parallel_gemm(const Tensor& A, const Tensor& B, Tensor& C,
|
| bool transA = false, bool transB = false,
|
| float alpha = 1.0f, float beta = 0.0f,
|
| size_t num_threads = 4);
|
|
|
| static Tensor matmul(const Tensor& A, const Tensor& B);
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|
|
| static Tensor elementwise_add(const Tensor& A, const Tensor& B);
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| static Tensor elementwise_sub(const Tensor& A, const Tensor& B);
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| static Tensor elementwise_mul(const Tensor& A, const Tensor& B);
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| static Tensor scalar_mul(const Tensor& A, float s);
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| static Tensor broadcast_add(const Tensor& A, const Tensor& B);
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|
|
| static Tensor transpose2d(const Tensor& A);
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|
|
| static void fill(Tensor& A, float value);
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| static void copy_data(Tensor& dst, const Tensor& src);
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|
|
| static float dot(const Tensor& A, const Tensor& B);
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| static float norm2(const Tensor& A);
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|
|
| static Tensor reduce_sum(const Tensor& A, int axis = -1);
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|
|
| static Tensor slice(const Tensor& A, size_t dim, size_t start, size_t end);
|
| static Tensor pad1d(const Tensor& A, size_t left, size_t right, float value = 0.0f);
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|
|
| static void apply_inplace(Tensor& A, std::function<float(float)> fn);
|
| static Tensor apply(const Tensor& A, std::function<float(float)> fn);
|
|
|
| static Tensor relu(const Tensor& A);
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| static Tensor sigmoid(const Tensor& A);
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| static Tensor tanh_act(const Tensor& A);
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| static Tensor log(const Tensor& A);
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| static Tensor exp(const Tensor& A);
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| static void clip_inplace(Tensor& A, float min_val, float max_val);
|
|
|
| static Tensor concat(const std::vector<Tensor>& tensors, size_t axis = 0);
|
|
|
| private:
|
| static void gemm_scalar(const float* a, const float* b, float* c,
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| size_t M, size_t K, size_t N,
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| bool transA, bool transB,
|
| float alpha, float beta);
|
|
|
| #ifdef HAS_AVX2
|
| static void gemm_avx2(const float* a, const float* b, float* c,
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| size_t M, size_t K, size_t N,
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| bool transA, bool transB,
|
| float alpha, float beta);
|
| #endif
|
|
|
| #ifdef HAS_NEON
|
| static void gemm_neon(const float* a, const float* b, float* c,
|
| size_t M, size_t K, size_t N,
|
| bool transA, bool transB,
|
| float alpha, float beta);
|
| #endif
|
| };
|
|
|
| }
|
|
|
| #endif |
