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@@ -0,0 +1,99 @@
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+//
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+// MIT license
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+// Copyright (C) 2024 Intel Corporation
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+// SPDX-License-Identifier: MIT
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+//
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+
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+//
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+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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+// See https://llvm.org/LICENSE.txt for license information.
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+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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+//
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+
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+#include "conv.hpp"
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+
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+static void conv_transpose_1d_kernel(
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+ const int s0, const int output_size,
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+ const int src0_ne0, const int src0_ne1, const int src0_ne2,
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+ const int src1_ne0, const int dst_ne0,
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+ const float * src0, const float * src1, float * dst,
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+ const sycl::nd_item<3> &item_ct1) {
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+ int global_index = item_ct1.get_local_id(2) +
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+ item_ct1.get_group(2) * item_ct1.get_local_range(2);
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+ if (global_index >= output_size) {
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+ return;
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+ }
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+
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+ int out_index = global_index / dst_ne0;
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+
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+ float accumulator = 0;
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+
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+ for (int c = 0; c < src0_ne2; c++) {
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+ int idx = global_index % dst_ne0;
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+
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+ int kernel_offset = (src0_ne0 * src0_ne1 * c) + (out_index * src0_ne0);
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+ int input_offset = src1_ne0 * c;
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+
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+ for (int i = 0; i < src1_ne0; i++) {
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+ if (!(idx >= i*s0 && idx < i*s0 + src0_ne0)) {
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+ continue;
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+ }
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+ int weight_idx = idx - i*s0;
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+
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+ float kernel_weight = src0[kernel_offset + weight_idx];
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+ float input_value = src1[input_offset+i];
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+
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+ accumulator += kernel_weight * input_value;
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+ }
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+ }
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+ dst[global_index] = accumulator;
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+}
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+
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+static void conv_transpose_1d_f32_f32_sycl(
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+ const int s0, const int output_size,
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+ const int src0_ne0, const int src0_ne1, const int src0_ne2,
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+ const int src1_ne0, const int dst_ne0,
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+ const float *src0, const float *src1, float *dst,
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+ const queue_ptr& stream) {
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+
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+ const int num_blocks = (output_size + SYCL_CONV_TRANPOSE_1D_BLOCK_SIZE - 1) / SYCL_CONV_TRANPOSE_1D_BLOCK_SIZE;
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+ const sycl::range<3> block_dims(1, 1, SYCL_CONV_TRANPOSE_1D_BLOCK_SIZE);
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+ const sycl::range<3> block_nums(1, 1, num_blocks);
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+ stream->parallel_for(
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+ sycl::nd_range<3>(
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+ block_nums * block_dims, block_dims),
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+ [=](sycl::nd_item<3> item_ct1) {
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+ conv_transpose_1d_kernel(
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+ s0, output_size,
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+ src0_ne0, src0_ne1, src0_ne2,
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+ src1_ne0, dst_ne0,
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+ src0, src1, dst, item_ct1);
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+ });
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+}
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+
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+void ggml_sycl_op_conv_transpose_1d(ggml_backend_sycl_context & ctx, const ggml_tensor *src0,
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+ const ggml_tensor *src1, ggml_tensor *dst) {
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+ const float * src0_d = (const float *)src0->data;
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+ const float * src1_d = (const float *)src1->data;
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+
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+ float * dst_d = (float *)dst->data;
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+ dpct::queue_ptr stream = ctx.stream();
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+
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+ GGML_ASSERT(src0->type == GGML_TYPE_F32);
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+ GGML_ASSERT( dst->type == GGML_TYPE_F32);
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+
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+ GGML_ASSERT(ggml_is_contiguous(src0));
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+ GGML_ASSERT(ggml_is_contiguous(src1));
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+
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+ const int32_t * opts = (const int32_t *)dst->op_params;
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+
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+ const int s0 = opts[0];
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+
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+ const int64_t output_size = ggml_nelements(dst);
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+
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+ conv_transpose_1d_f32_f32_sycl(s0, output_size,
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+ src0->ne[0], src0->ne[1], src0->ne[2],
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+ src1->ne[0], dst->ne[0],
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+ src0_d, src1_d, dst_d, stream);
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+}
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+
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