--- /dev/null
+//
+// MIT license
+// Copyright (C) 2024 Intel Corporation
+// SPDX-License-Identifier: MIT
+//
+
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+
+#include "conv.hpp"
+
+static void conv_transpose_1d_kernel(
+ const int s0, const int output_size,
+ const int src0_ne0, const int src0_ne1, const int src0_ne2,
+ const int src1_ne0, const int dst_ne0,
+ const float * src0, const float * src1, float * dst,
+ const sycl::nd_item<3> &item_ct1) {
+ int global_index = item_ct1.get_local_id(2) +
+ item_ct1.get_group(2) * item_ct1.get_local_range(2);
+ if (global_index >= output_size) {
+ return;
+ }
+
+ int out_index = global_index / dst_ne0;
+
+ float accumulator = 0;
+
+ for (int c = 0; c < src0_ne2; c++) {
+ int idx = global_index % dst_ne0;
+
+ int kernel_offset = (src0_ne0 * src0_ne1 * c) + (out_index * src0_ne0);
+ int input_offset = src1_ne0 * c;
+
+ for (int i = 0; i < src1_ne0; i++) {
+ if (!(idx >= i*s0 && idx < i*s0 + src0_ne0)) {
+ continue;
+ }
+ int weight_idx = idx - i*s0;
+
+ float kernel_weight = src0[kernel_offset + weight_idx];
+ float input_value = src1[input_offset+i];
+
+ accumulator += kernel_weight * input_value;
+ }
+ }
+ dst[global_index] = accumulator;
+}
+
+static void conv_transpose_1d_f32_f32_sycl(
+ const int s0, const int output_size,
+ const int src0_ne0, const int src0_ne1, const int src0_ne2,
+ const int src1_ne0, const int dst_ne0,
+ const float *src0, const float *src1, float *dst,
+ const queue_ptr& stream) {
+
+ const int num_blocks = (output_size + SYCL_CONV_TRANPOSE_1D_BLOCK_SIZE - 1) / SYCL_CONV_TRANPOSE_1D_BLOCK_SIZE;
+ const sycl::range<3> block_dims(1, 1, SYCL_CONV_TRANPOSE_1D_BLOCK_SIZE);
+ const sycl::range<3> block_nums(1, 1, num_blocks);
+ stream->parallel_for(
+ sycl::nd_range<3>(
+ block_nums * block_dims, block_dims),
+ [=](sycl::nd_item<3> item_ct1) {
+ conv_transpose_1d_kernel(
+ s0, output_size,
+ src0_ne0, src0_ne1, src0_ne2,
+ src1_ne0, dst_ne0,
+ src0, src1, dst, item_ct1);
+ });
+}
+
+void ggml_sycl_op_conv_transpose_1d(ggml_backend_sycl_context & ctx, const ggml_tensor *src0,
+ const ggml_tensor *src1, ggml_tensor *dst) {
+ const float * src0_d = (const float *)src0->data;
+ const float * src1_d = (const float *)src1->data;
+
+ float * dst_d = (float *)dst->data;
+ dpct::queue_ptr stream = ctx.stream();
+
+ GGML_ASSERT(src0->type == GGML_TYPE_F32);
+ GGML_ASSERT( dst->type == GGML_TYPE_F32);
+
+ GGML_ASSERT(ggml_is_contiguous(src0));
+ GGML_ASSERT(ggml_is_contiguous(src1));
+
+ const int32_t * opts = (const int32_t *)dst->op_params;
+
+ const int s0 = opts[0];
+
+ const int64_t output_size = ggml_nelements(dst);
+
+ conv_transpose_1d_f32_f32_sycl(s0, output_size,
+ src0->ne[0], src0->ne[1], src0->ne[2],
+ src1->ne[0], dst->ne[0],
+ src0_d, src1_d, dst_d, stream);
+}
+