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commit 570102c5018c6b4010227a044dde894b0b16feec
Author: xinhaiteng <xinhait...@xiaomi.com>
AuthorDate: Thu Apr 25 11:31:10 2024 +0800
delete the neon conv2D
The complete implementation is placed separately in
mLearning/tflite-micro/operators/neon, delete this part.
Signed-off-by: xinhaiteng <xinhait...@xiaomi.com>
---
mlearning/tflite-micro/tflite-micro.patch | 114 +++++-------------------------
1 file changed, 19 insertions(+), 95 deletions(-)
diff --git a/mlearning/tflite-micro/tflite-micro.patch
b/mlearning/tflite-micro/tflite-micro.patch
index d39038d5a..7c39ee527 100644
--- a/mlearning/tflite-micro/tflite-micro.patch
+++ b/mlearning/tflite-micro/tflite-micro.patch
@@ -1,5 +1,20 @@
+From e6049c8ddd7e36db4993e3c6d8b4e5a7114db2c5 Mon Sep 17 00:00:00 2001
+From: renzhiyuan1 <renzhiyu...@xiaomi.com>
+Date: Mon, 4 Dec 2023 12:30:20 +0800
+Subject: [PATCH] Patch files in tflite-micro
+
+VELAPLATFO-20049
+
+Patch files in tflite-micro
+
+Change-Id: Ic683fe4f12221d214ca77515c7b9487bb76a923f
+Signed-off-by: renzhiyuan1 <renzhiyu...@xiaomi.com>
+---
+ signal/src/circular_buffer.cc | 2 ++
+ 1 file changed, 2 insertions(+)
+
diff --git a/signal/src/circular_buffer.cc b/signal/src/circular_buffer.cc
-index 7638d912..3261be56 100644
+index 7638d912e..3261be56c 100644
--- a/signal/src/circular_buffer.cc
+++ b/signal/src/circular_buffer.cc
@@ -19,7 +19,9 @@ limitations under the License.
@@ -12,97 +27,6 @@ index 7638d912..3261be56 100644
namespace tflite {
namespace tflm_signal {
-diff --git a/tensorflow/lite/kernels/internal/reference/integer_ops/conv.h
b/tensorflow/lite/kernels/internal/reference/integer_ops/conv.h
-index eac00576..abfdea8c 100644
---- a/tensorflow/lite/kernels/internal/reference/integer_ops/conv.h
-+++ b/tensorflow/lite/kernels/internal/reference/integer_ops/conv.h
-@@ -18,6 +18,9 @@ limitations under the License.
- #include <algorithm>
-
- #include "tensorflow/lite/kernels/internal/common.h"
-+#ifdef USE_NEON
-+#include <arm_neon.h>
-+#endif
-
- namespace tflite {
- namespace reference_integer_ops {
-@@ -133,6 +136,79 @@ inline void ConvPerChannel(
- }
- }
- }
-+#ifdef USE_NEON
-+ for (int batch = 0; batch < batches; ++batch) {
-+ for (int out_y = 0; out_y < output_height; ++out_y) {
-+ int in_y_origin = (out_y * stride_height) - pad_height;
-+ for (int out_x = 0; out_x < output_width; ++out_x) {
-+ int in_x_origin = (out_x * stride_width) - pad_width;
-+ int filter_start_offset = 0;
-+ for (int out_channel = 0; out_channel < output_depth; ++out_channel) {
-+ auto group = out_channel / filters_per_group;
-+ int32_t acc = 0;
-+ int8x8_t input_v = vdup_n_s8(0);
-+ int8x8_t filter_v = vdup_n_s8(0);
-+ int16x8_t mid_mul = vdupq_n_s16(0);
-+ int32x4_t res_v = vdupq_n_s32(0);
-+ int32x4_t filter_offset_v = vdupq_n_s32(0);
-+ int input_offset_temp = 0;
-+ for (int filter_y = 0; filter_y < filter_height; ++filter_y) {
-+ int in_y = in_y_origin + dilation_height_factor * filter_y;
-+ for (int filter_x = 0; filter_x < filter_width; ++filter_x) {
-+ int in_x = in_x_origin + dilation_width_factor * filter_x;
-+ const bool is_point_inside_image = (in_x >= 0) && (in_x <
input_width) && (in_y >= 0) && (in_y < input_height);
-+ if (!is_point_inside_image)
-+ continue;
-+ int input_start_offset = ((batch * input_height + in_y) *
input_width + in_x) * input_depth + group * filter_input_depth;
-+ int in_channel = 0;
-+ for (; in_channel < (filter_input_depth & -8); in_channel += 8)
{
-+ input_v = vld1_s8(input_data + input_start_offset);
-+ input_start_offset += 8;
-+ filter_v = vld1_s8(filter_data + filter_start_offset);
-+ filter_start_offset += 8;
-+
-+ mid_mul = vmovl_s8(filter_v);
-+ filter_offset_v = vaddw_s16(filter_offset_v,
vget_low_s16(mid_mul));
-+ filter_offset_v = vaddw_s16(filter_offset_v,
vget_high_s16(mid_mul));
-+ mid_mul = vmull_s8(input_v, filter_v);
-+ res_v = vaddw_s16(res_v, vget_low_s16(mid_mul));
-+ res_v = vaddw_s16(res_v, vget_high_s16(mid_mul));
-+
-+ }
-+
-+ for (; in_channel < filter_input_depth; ++in_channel) {
-+ acc += (input_data[input_start_offset] + input_offset) *
filter_data[filter_start_offset];
-+ ++input_start_offset;
-+ ++filter_start_offset;
-+ }
-+ }
-+ }
-+ acc += vgetq_lane_s32(res_v, 0);
-+ acc += vgetq_lane_s32(res_v, 1);
-+ acc += vgetq_lane_s32(res_v, 2);
-+ acc += vgetq_lane_s32(res_v, 3);
-+ input_offset_temp += vgetq_lane_s32(filter_offset_v, 0);
-+ input_offset_temp += vgetq_lane_s32(filter_offset_v, 1);
-+ input_offset_temp += vgetq_lane_s32(filter_offset_v, 2);
-+ input_offset_temp += vgetq_lane_s32(filter_offset_v, 3);
-+ acc += input_offset_temp * input_offset;
-+
-+ if (bias_data)
-+ {
-+ acc += bias_data[out_channel];
-+ }
-+ acc = MultiplyByQuantizedMultiplier(
-+ acc, output_multiplier[out_channel], output_shift[out_channel]);
-+ acc += output_offset;
-+ acc = std::max(acc, output_activation_min);
-+ acc = std::min(acc, output_activation_max);
-+ output_data[Offset(output_shape, batch, out_y, out_x, out_channel)]
=
-+ static_cast<int8_t>(acc);
-+ }
-+ }
-+ }
-+ }
-+#endif
- }
-
-
+--
+2.25.1
+
