Akarshan Biswas
fccf9cae83
* SYCL: Add fp16 support to some elementwise OP kernels * remove comment ggml-ci * Use static_cast directly * remove not needed cast from tanh * Use static cast and remove unneeded castings * Adjust device_support_op for unary OPs * Use cast_data and typed_data struct to deduplicate casting code
101 lines
2.8 KiB
C++
101 lines
2.8 KiB
C++
#ifndef GGML_SYCL_ELEMENTWISE_HPP
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#define GGML_SYCL_ELEMENTWISE_HPP
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#include "common.hpp"
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#include "ggml.h"
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#include <limits.h>
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template <typename T>
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T neg_infinity() {
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return -std::numeric_limits<T>::infinity();
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}
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static __dpct_inline__ float op_repeat(const float a, const float b) {
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return b;
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GGML_UNUSED(a);
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}
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static __dpct_inline__ float op_add(const float a, const float b) {
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return a + b;
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}
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static __dpct_inline__ float op_sub(const float a, const float b) {
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return a - b;
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}
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static __dpct_inline__ float op_mul(const float a, const float b) {
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return a * b;
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}
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static __dpct_inline__ float op_div(const float a, const float b) {
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return a / b;
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}
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template<typename T>
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struct typed_data {
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const T * src;
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T * dst;
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};
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template<typename T>
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typed_data<T> cast_data(ggml_tensor * dst) {
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return {
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/* .src = */ static_cast<const T *>(dst->src[0]->data),
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/* .dst = */ static_cast<T *>(dst->data)
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};
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}
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void ggml_sycl_sqrt(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_sin(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_cos(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_acc(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_gelu(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_silu(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_gelu_quick(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_tanh(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_relu(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_sigmoid(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_hardsigmoid(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_hardswish(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_exp(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_log(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_neg(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_step(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_leaky_relu(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_sqr(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_upscale(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_pad(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_clamp(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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// ---------
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void ggml_sycl_add(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_sub(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_mul(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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void ggml_sycl_div(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
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#endif // GGML_SYCL_ELEMENTWISE_HPP
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