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3bcd40b3c5
* rwkv6: rename to wkv6 * rwkv6: support avx2 avx512 armv8 armv9 * rwkv6: update cuda file name * rwkv6: rename params * wkv on sycl * sycl: add some ops * sycl: Enhance OP support judgment * wkv6: drop armv9 and tranfer to GGML style ggml-ci * sync : ggml * update the function to use appropriate types * fix define error * Update ggml/src/ggml-cpu.c * add appropriate asserts * move element-wise functions outside * put the declaration outside the loop * rewrite to be more inline with the common pattern for distributing threads * use recommended way GGML_TENSOR_LOCALS --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: Diego Devesa <slarengh@gmail.com> Co-authored-by: Plamen Minev <pacominev@gmail.com> Co-authored-by: Yuri Khrustalev <ykhrustalev@users.noreply.github.com> Co-authored-by: Meng, Hengyu <airdldl@163.com>
77 lines
3.5 KiB
C++
77 lines
3.5 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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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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void ggml_sycl_sqrt(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_sin(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_cos(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_acc(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_gelu(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_silu(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_gelu_quick(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_tanh(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_relu(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_sigmoid(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_hardsigmoid(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_hardswish(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_exp(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_log(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_neg(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_step(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_leaky_relu(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_sqr(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_upscale(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_pad(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_add(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_sub(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_mul(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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void ggml_sycl_div(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
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#endif // GGML_SYCL_ELEMENTWISE_HPP
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