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Diffstat (limited to 'compute/ARMComputeEx/src/core/CL/cl_kernels/hashtable_lookup.cl')
| -rw-r--r-- | compute/ARMComputeEx/src/core/CL/cl_kernels/hashtable_lookup.cl | 117 |
1 files changed, 117 insertions, 0 deletions
diff --git a/compute/ARMComputeEx/src/core/CL/cl_kernels/hashtable_lookup.cl b/compute/ARMComputeEx/src/core/CL/cl_kernels/hashtable_lookup.cl new file mode 100644 index 000000000..73f29e3e5 --- /dev/null +++ b/compute/ARMComputeEx/src/core/CL/cl_kernels/hashtable_lookup.cl @@ -0,0 +1,117 @@ +/* + * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved + * Copyright (c) 2017 ARM Limited. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +#include "helpers.h" + +#ifndef VEC_SIZE +#define VEC_SIZE 1 +#endif + +#if defined(DATA_TYPE) && defined(DEPTH_OUT) && defined(NUM_DIMS) +/** Perform hashtable_lookup of input tensor + * + * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. + * -DDATA_TYPE=short + * @attention Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. + * -DVEC_SIZE=16 + * @attention Output tensor depth should be given as a preprocessor argument using + * -DDEPTH_OUT=depth. e.g. -DDEPTH_OUT=16 + * @attention Number of input dimensions are passed as a preprocessor argument using + * -DNUM_DIMS=size, e.g. -DNUM_DIMS=4 + * + * @param[in] input_ptr Pointer to the source tensor. Supported data + * types: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32 + * @param[in] input_stride_x Stride of the source tensor in X dimension (in + * bytes) + * @param[in] input_step_x input_stride_x * number of elements along X + * processed per workitem(in bytes) + * @param[in] input_stride_y Stride of the source tensor in Y dimension (in + * bytes) + * @param[in] input_step_y input_stride_y * number of elements along Y + * processed per workitem(in bytes) + * @param[in] input_stride_z Stride of the source tensor in Z dimension (in + * bytes) + * @param[in] input_step_z input_stride_z * number of elements along Z + * processed per workitem(in bytes) + * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source + * tensor + * @param[in] input_stride_w Stride of the source tensor in W dimension (in + * bytes) + * @param[in] input_step_w output_stride_w * number of elements along W + * processed per workitem(in bytes) + * @param[out] output_ptr Pointer to the destination tensor. Supported + * data types: same as @p input_ptr + * @param[in] output_stride_x Stride of the destination tensor in X dimension + * (in bytes) + * @param[in] output_step_x output_stride_x * number of elements along X + * processed per workitem(in bytes) + * @param[in] output_stride_y Stride of the destination tensor in Y dimension + * (in bytes) + * @param[in] output_step_y output_stride_y * number of elements along Y + * processed per workitem(in bytes) + * @param[in] output_stride_z Stride of the source tensor in Z dimension (in + * bytes) + * @param[in] output_step_z output_stride_z * number of elements along Z + * processed per workitem(in bytes) + * @param[in] output_stride_w Stride of the source tensor in W dimension (in + * bytes) + * @param[in] output_step_w output_stride_w * number of elements along W + * processed per workitem(in bytes) + * @param[in] output_offset_first_element_in_bytes The offset of the first element in the + * destination tensor + * @param[in] lookups_ptr Pointer to the lookups vector. Supported data + * types: S32 + * @param[in] lookups_stride_x Stride of the lookups vector in X dimension (in + * bytes) + * @param[in] lookups_step_x lookups_stride_x * number of elements along X + * processed per workitem(in bytes) + * @param[in] lookups_offset_first_element_in_bytes The offset of the first element in the lookups + * vector + */ +__kernel void hashtable_lookup(TENSOR4D_DECLARATION(input), TENSOR4D_DECLARATION(output), + VECTOR_DECLARATION(lookups)) +{ + Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT(output, DEPTH_OUT); + Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(input, DEPTH_OUT); + + Vector lups = CONVERT_TO_VECTOR_STRUCT_NO_STEP(lookups); + + int lup_id[4] = {0}; + + lup_id[0] = (NUM_DIMS == 1) ? *((__global int *)vector_offset(&lups, get_global_id(0))) + : get_global_id(0); + lup_id[1] = (NUM_DIMS == 2) ? *((__global int *)vector_offset(&lups, get_global_id(1))) + : get_global_id(1); + lup_id[2] = (NUM_DIMS == 3) ? *((__global int *)vector_offset(&lups, get_global_id(2))) + : get_global_id(2) % DEPTH_OUT; + lup_id[3] = (NUM_DIMS == 4) + ? *((__global int *)vector_offset(&lups, get_global_id(2) / DEPTH_OUT)) + : get_global_id(2) / DEPTH_OUT; + + if (lup_id[NUM_DIMS - 1] < 0) + { + VSTORE(VEC_SIZE)((VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))0, 0, (__global DATA_TYPE *)out.ptr); + return; + } + + in.ptr += input_offset_first_element_in_bytes + lup_id[0] * input_step_x + + lup_id[1] * input_step_y + lup_id[2] * input_step_z + lup_id[3] * input_step_w; + + VSTORE(VEC_SIZE) + (CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in.ptr), VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)), 0, + (__global DATA_TYPE *)out.ptr); +} +#endif // defined(DATA_TYPE) && defined(DEPTH_OUT) && defined(NUM_DIMS) |