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/*
* Copyright 2024 Google LLC
*
* 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.
*/
#ifndef TFLM_OPT_CONV_UTIL_H_
#define TFLM_OPT_CONV_UTIL_H_
#include <cassert>
#include <memory>
#include "crt/kelvin.h"
#include "tensorflow/lite/kernels/internal/common.h"
#include "tensorflow/lite/kernels/internal/runtime_shape.h"
#include "tensorflow/lite/kernels/internal/types.h"
#include "tflm/opt/util.h"
namespace kelvin::opt {
/* clang-format off */
constexpr const int swizzle[16] = {
0, 4, 8, 12,
2, 6, 10, 14,
1, 5, 9, 13,
3, 7, 11, 15,
};
/* clang-format on */
constexpr int kFilterHeightIndex = 1;
constexpr int kFilterWidthIndex = 2;
constexpr int kFilterInputChannelIndex = 3;
constexpr int kInputChannelIndex = 3;
constexpr int kOutputChannelIndex = 3;
#define INA0 v0
#define FLTA0 v8
#define FLTA1 v9
#define FLTA2 v10
#define FLTA3 v11
#define FLTA4 v12
#define FLTA5 v13
#define FLTA6 v14
#define FLTA7 v15
#define ACC v48
#define ACC0 v48
#define OUT0 v56
// H,W ( height and width of filter) N -number of inputs, M -number of outputs
template <int N>
inline void Filter_N_H_W_M(const int8_t* input, int8_t* output, int H, int W,
int M) {
// Convert: input [zo][ky][kx][zi] (N,3,1,M)
// output [zo.hi=N/8][ky][kx][zi_hi=M/4][zo.lo=8][zi_lo=4]
const int8_t(&in)[N][H][W][M] = *(int8_t(*)[N][H][W][M])input;
int8_t(&out)[N / 8][H][W][M / 4][8][4] =
*(int8_t(*)[N / 8][H][W][M / 4][8][4]) output;
assert(N >= 4 && M >= 4);
for (int zo = 0; zo < N; ++zo) {
for (int ky = 0; ky < H; ++ky) {
for (int kx = 0; kx < W; ++kx) {
for (int zi = 0; zi < M; ++zi) {
const int zo_hi = zo >> 3; // div8
const int zo_lo = zo & 7; // rem8
const int zi_hi = zi >> 2; // div4
const int zi_lo = zi & 3; // rem4
out[zo_hi][ky][kx][zi_hi][zo_lo][zi_lo] = in[zo][ky][kx][zi];
}
}
}
}
}
// Swizzle values, and duplicate 4 times for stripmining.
inline void Swizzle(const int32_t* input, int32_t* output, int N,
bool negate = false) {
const int32_t(&in)[N] = *(int32_t(*)[N])input;
int32_t(&out)[N * 4] = *(int32_t(*)[N * 4]) output;
// Convert to accumulator swizzle pattern.
for (int i = 0; i < N / 8; ++i) {
int32_t* out0 = out + i * 32 + 0;
int32_t* out1 = out + i * 32 + 16;
int32_t* out2 = out + i * 32 + 8;
int32_t* out3 = out + i * 32 + 24;
for (int j = 0; j < 4; ++j) {
const int32_t* p_in = in + i * 8;
for (int k = 0; k < 2; ++k) {
*out0++ = *p_in++;
*out1++ = *p_in++;
*out2++ = *p_in++;
*out3++ = *p_in++;
}
}
}
if (negate) {
for (int i = 0; i < N * 4; ++i) {
out[i] = -out[i];
}
}
}
// Run output pipeline on int32 accumulators in [v48-v55] and store results
// in v48 and v52. Clobbers [v48-v55].
#define INT32_TO_INT8_OUTPUT_PIPELINE(bias, mult, shft, output_min, \
output_max, output_offset, bias_reg, \
mult_reg, shift_reg) \
{ \
vcget(v48); \
vld_w_x_m(bias_reg, bias); \
vld_w_x_m(mult_reg, mult); \
vld_w_x_m(shift_reg, shft); \
vadd_w_vv_m(v48, v48, bias_reg); \
vadd_w_vv_m(v52, v52, bias_reg); \
vmin_w_vx_m(v48, v48, output_max); \
vmax_w_vx_m(v52, v52, output_min); \
vdmulh_w_r_vv_m(v48, v48, mult_reg); \
vdmulh_w_r_vv_m(v52, v52, mult_reg); \
vsha_w_r_vv_m(v48, v48, shift_reg); \
vsha_w_r_vv_m(v52, v52, shift_reg); \
vadd_w_vx_m(v48, v48, output_offset); \
vadd_w_vx_m(v52, v52, output_offset); \
vsraqs_b_vx(v48, v48, 0); \
vsraqs_b_vx(v52, v52, 0); \
}
} // namespace kelvin::opt
#endif // TFLM_OPT_CONV_UTIL_H_