#include "ggml-cuda/wkv.cuh"
#include "ggml-cuda/gla.cuh"
#include "ggml-cuda/set-rows.cuh"
+#include "ggml-cuda/pad_reflect_1d.cuh"
#include "ggml.h"
#include <algorithm>
case GGML_OP_PAD:
ggml_cuda_op_pad(ctx, dst);
break;
+ case GGML_OP_PAD_REFLECT_1D:
+ ggml_cuda_op_pad_reflect_1d(ctx, dst);
+ break;
case GGML_OP_ARANGE:
ggml_cuda_op_arange(ctx, dst);
break;
return ggml_is_contiguous(op->src[0]);
case GGML_OP_UPSCALE:
case GGML_OP_PAD:
+ case GGML_OP_PAD_REFLECT_1D:
case GGML_OP_ARANGE:
case GGML_OP_TIMESTEP_EMBEDDING:
case GGML_OP_LEAKY_RELU:
--- /dev/null
+#include "pad_reflect_1d.cuh"
+
+static __global__ void pad_reflect_1d_kernel_f32(
+ const void * __restrict__ src0,
+ void * __restrict__ dst,
+ const int64_t ne0,
+ const int64_t ne00,
+ const int64_t ne01,
+ const int64_t ne02,
+ const int64_t ne03,
+ const int64_t nb00,
+ const int64_t nb01,
+ const int64_t nb02,
+ const int64_t nb03,
+ const int64_t nb0,
+ const int64_t nb1,
+ const int64_t nb2,
+ const int64_t nb3,
+ const int p0,
+ const int p1) {
+
+ const int64_t i3 = blockIdx.z;
+ const int64_t i2 = blockIdx.y;
+ const int64_t i1 = blockIdx.x;
+
+ if (i1 >= ne01 || i2 >= ne02 || i3 >= ne03) {
+ return;
+ }
+
+ const char * src0_ptr = (const char *)src0 + i3*nb03 + i2*nb02 + i1*nb01;
+ char * dst_ptr = (char *)dst + i3*nb3 + i2*nb2 + i1*nb1;
+
+ for (int64_t i0 = threadIdx.x; i0 < ne0; i0 += blockDim.x) {
+ float value;
+
+ if (i0 < p0) {
+ // Left padding - reflect
+ value = *(const float *)(src0_ptr + (p0 - i0) * nb00);
+ } else if (i0 < ne0 - p1) {
+ // Middle - copy
+ value = *(const float *)(src0_ptr + (i0 - p0) * nb00);
+ } else {
+ // Right padding - reflect
+ int64_t src_idx = (ne0 - p1 - p0) - (p1 + 1 - (ne0 - i0)) - 1;
+ value = *(const float *)(src0_ptr + src_idx * nb00);
+ }
+
+ *(float *)(dst_ptr + i0 * nb0) = value;
+ }
+}
+
+void ggml_cuda_op_pad_reflect_1d(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
+ const ggml_tensor * src0 = dst->src[0];
+ cudaStream_t stream = ctx.stream();
+
+ GGML_ASSERT(src0->type == GGML_TYPE_F32);
+ GGML_ASSERT(dst->type == GGML_TYPE_F32);
+
+ const int32_t * opts = (const int32_t *) dst->op_params;
+ const int p0 = opts[0];
+ const int p1 = opts[1];
+
+ const int64_t ne00 = src0->ne[0];
+ const int64_t ne01 = src0->ne[1];
+ const int64_t ne02 = src0->ne[2];
+ const int64_t ne03 = src0->ne[3];
+
+ const int64_t ne0 = dst->ne[0];
+
+ GGML_ASSERT(ne0 == ne00 + p0 + p1);
+
+ const dim3 block_dims(CUDA_PAD_REFLECT_1D_BLOCK_SIZE, 1, 1);
+ const dim3 grid_dims(ne01, ne02, ne03);
+
+ pad_reflect_1d_kernel_f32<<<grid_dims, block_dims, 0, stream>>>(
+ src0->data, dst->data,
+ ne0, ne00, ne01, ne02, ne03,
+ src0->nb[0], src0->nb[1], src0->nb[2], src0->nb[3],
+ dst->nb[0], dst->nb[1], dst->nb[2], dst->nb[3],
+ p0, p1
+ );
+}