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Rolling v10.6.1

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jomjol
2022-07-24 18:53:25 +02:00
parent 189093d548
commit 0e7c600cf7
209 changed files with 1791 additions and 12917 deletions
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4
code/components/esp-nn/CMakeLists.txt
View File

@@ -5,9 +5,7 @@ set(c_srcs
"src/basic_math/esp_nn_add_ansi.c"
"src/basic_math/esp_nn_mul_ansi.c"
"src/convolution/esp_nn_conv_ansi.c"
"src/convolution/esp_nn_conv_opt.c"
"src/convolution/esp_nn_depthwise_conv_ansi.c"
"src/convolution/esp_nn_depthwise_conv_opt.c"
"src/fully_connected/esp_nn_fully_connected_ansi.c"
"src/softmax/esp_nn_softmax_ansi.c"
"src/softmax/esp_nn_softmax_opt.c"
@@ -25,7 +23,7 @@ if(CONFIG_IDF_TARGET_ESP32S3)
"src/convolution/esp_nn_conv_esp32s3.c"
"src/convolution/esp_nn_depthwise_conv_s8_esp32s3.c"
"src/convolution/esp_nn_conv_s16_mult8_esp32s3.S"
"src/convolution/esp_nn_conv_s8_mult8_1x1_esp32s3.S"
"src/convolution/esp_nn_conv_s16_mult8_1x1_esp32s3.S"
"src/convolution/esp_nn_conv_s16_mult4_1x1_esp32s3.S"
"src/convolution/esp_nn_depthwise_conv_s8_mult1_3x3_padded_esp32s3.S"
"src/convolution/esp_nn_depthwise_conv_s16_mult1_esp32s3.S"

8
code/components/esp-nn/Kconfig.projbuild
View File

@@ -6,8 +6,8 @@ choice NN_OPTIMIZATIONS
help
Use ANSI-C versions for verification and debug purpose.
Optimisations are automatically picked up for a chipset.
For ESP32-S3, assembly optimisations are selected.
For other platforms(viz., ESP32, ESP32-C3), generic optimisations are used.
For ESP32-S3, assembly Optimisations are selected.
For ESP32, just the ANSI C versions are selected for now.
config NN_ANSI_C
bool "ANSI C"
@@ -17,8 +17,8 @@ config NN_OPTIMIZED
bool "Optimized versions"
help
Optimisations are automatically picked up for a chipset.
For ESP32-S3, assembly optimisations are selected.
For other platforms(viz., ESP32, ESP32-C3), generic optimisations are used.
For ESP32-S3, assembly Optimisations are selected.
For ESP32, just the ANSI C versions are selected for now.
endchoice
config NN_OPTIMIZATIONS

7
code/components/esp-nn/README.md
View File

@@ -7,8 +7,7 @@ The library contains optimised NN (Neural Network) functions for various Espress
* Supported ESP chipsets include:
* ESP32-S3 (Assembly versions optimised to benefit from vector instructions of ESP32-S3)
* ESP32 (Generic optimisations)
* ESP32-C3 (Generic optimisations)
* ESP32 (ANSI C versions)
## Performance
@@ -40,8 +39,8 @@ The library contains optimised NN (Neural Network) functions for various Espress
* Optimized versions
* ANSI C
* Default selection is for `Optimized versions`. For ESP32-S3, assembly versions are automatically selected, whereas for other chipsets (viz., ESP32, ESP32-C3), generic optimisations are selected.
* For debugging purposes, you may want to select `ANSI C` reference versions.
* Default selection is for `Optimized versions`. For ESP32-S3, assembly versions are automatically selected, whereas for ESP32, ANSI-C versions are selected by default.
* For debugging purposes, you may want to select `ANSI C`
## Contributing

10
code/components/esp-nn/include/esp_nn.h
View File

@@ -15,7 +15,6 @@
#pragma once
#if defined(CONFIG_NN_OPTIMIZED)
// select apt optimisations
#ifdef CONFIG_IDF_TARGET_ESP32S3
#define ARCH_ESP32_S3 1
#endif
@@ -32,11 +31,12 @@ extern "C" {
#include "esp_nn_ansi_headers.h"
#if defined(CONFIG_NN_OPTIMIZED)
#if defined(ARCH_ESP32_S3)
#ifdef ARCH_ESP32_S3
#include "esp_nn_esp32s3.h"
#else // for other platforms use generic optimisations
#include "esp_nn_generic_opt.h"
#endif // #if defined(ARCH_ESP32_S3)
#endif
#ifdef ARCH_ESP32
#include "esp_nn_esp32.h"
#endif
#else
#include "esp_nn_ansi_c.h"
#endif

1
code/components/esp-nn/include/esp_nn_ansi_c.h
View File

@@ -19,7 +19,6 @@
#pragma once
#include "esp_nn_defs.h"
#include "esp_nn_ansi_headers.h"
#define esp_nn_add_elementwise_s8 esp_nn_add_elementwise_s8_ansi

136
code/components/esp-nn/include/esp_nn_ansi_headers.h
View File

@@ -18,7 +18,8 @@
* @file Header definitions to include for esp_nn reference functions
*/
#include "esp_nn_defs.h"
#include <stdint.h>
/************************** Basic math functions ****************************/
/**
@@ -80,15 +81,28 @@ void esp_nn_mul_elementwise_s8_ansi(const int8_t *input1_data,
* optimization notes: Though input_offset is int32 type,
* offset values are contained in 8 bits [-128, 127]
*/
void esp_nn_depthwise_conv_s8_ansi(const data_dims_t *input_dims,
const int8_t *input_data,
const data_dims_t *filter_dims,
void esp_nn_depthwise_conv_s8_ansi(const int8_t *input_data,
const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t channels,
const int32_t input_offset,
const uint16_t pad_wd,
const uint16_t pad_ht,
const uint16_t stride_wd,
const uint16_t stride_ht,
const uint16_t ch_mult,
const int8_t *filter_data,
const uint16_t filter_wd,
const uint16_t filter_ht,
const int32_t *bias,
const data_dims_t *output_dims,
int8_t *out_data,
const dw_conv_params_t *conv_params,
const quant_data_t *quant_data);
const uint16_t out_wd,
const uint16_t out_ht,
const int32_t out_offset,
const int32_t *out_shift,
const int32_t *out_mult,
const int32_t activation_min,
const int32_t activation_max);
/**
* @brief 2d-convolution channelwise
@@ -98,26 +112,43 @@ void esp_nn_depthwise_conv_s8_ansi(const data_dims_t *input_dims,
* inputs type: int8_t, output: int8_t
* input offsets: although int32_t, they are contained in 8 bits [-128, 127]
*/
void esp_nn_conv_s8_ansi(const data_dims_t *input_dims,
const int8_t *input_data,
const data_dims_t *filter_dims,
void esp_nn_conv_s8_ansi(const int8_t *input_data,
const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t in_channels,
const int32_t input_offset,
const uint16_t pad_wd,
const uint16_t pad_ht,
const uint16_t stride_wd,
const uint16_t stride_ht,
const int8_t *filter_data,
const uint16_t filter_wd,
const uint16_t filter_ht,
const int32_t *bias,
const data_dims_t *output_dims,
int8_t *out_data,
const conv_params_t *conv_params,
const quant_data_t *quant_data);
const uint16_t out_wd,
const uint16_t out_ht,
const uint16_t out_channels,
const int32_t out_offset,
const int32_t *out_shift,
const int32_t *out_mult,
const int32_t activation_min,
const int32_t activation_max);
int esp_nn_get_conv_scratch_size_ansi(const data_dims_t *input_dims,
const data_dims_t *filter_dims,
const data_dims_t *output_dims,
const conv_params_t *conv_params);
int esp_nn_get_conv_scratch_size_ansi(const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t in_ch,
const uint16_t out_ch,
const uint16_t filter_wd,
const uint16_t filter_ht);
void esp_nn_set_conv_scratch_buf_ansi(const void *buf);
int esp_nn_get_depthwise_conv_scratch_size_ansi(const data_dims_t *input_dims,
const data_dims_t *filter_dims,
const data_dims_t *output_dims,
const dw_conv_params_t *conv_params);
int esp_nn_get_depthwise_conv_scratch_size_ansi(const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t channels,
const uint16_t ch_mult,
const uint16_t filter_wd,
const uint16_t filter_ht);
void esp_nn_set_depthwise_conv_scratch_buf_ansi(const void *buf);
/************************** Activation functions *****************************/
@@ -221,6 +252,9 @@ int32_t esp_nn_get_softmax_scratch_size_opt(const int32_t width, const int32_t h
*/
void esp_nn_set_softmax_scratch_buf_ansi(void *buffer);
/* ANSI C function to be hooked up when optimised version needed */
void esp_nn_set_softmax_scratch_buf_opt(void *buffer);
/**
* @brief reference softmax function
*
@@ -234,66 +268,6 @@ void esp_nn_softmax_s8_ansi(const int8_t *input_data,
const int32_t diff_min,
int8_t *output_data);
//////////////////////////// Generic optimisations /////////////////////////////
/************************** Convolution functions *****************************/
/**
* @brief 2d-convolution channelwise optimized version
*
* @note operation: result += (input + offset) * filter
*
* inputs type: int8_t, output: int8_t
* input offsets: although int32_t, they are contained in 8 bits [-128, 127]
*/
void esp_nn_conv_s8_opt(const data_dims_t *input_dims,
const int8_t *input_data,
const data_dims_t *filter_dims,
const int8_t *filter_data,
const int32_t *bias,
const data_dims_t *output_dims,
int8_t *out_data,
const conv_params_t *conv_params,
const quant_data_t *quant_data);
/**
* @brief depthwise convolution per channel optimized version
*
* @note inputs type: int8_t, output: int8_t
* Version used in tflite is per channel.
* This version follows the same footsprints.
* Meaning, it has per out_channel shift and multiplier for
* requantization
*
* optimization notes: Though input_offset is int32 type,
* offset values are contained in 8 bits [-128, 127]
*/
void esp_nn_depthwise_conv_s8_opt(const data_dims_t *input_dims,
const int8_t *input_data,
const data_dims_t *filter_dims,
const int8_t *filter_data,
const int32_t *bias,
const data_dims_t *output_dims,
int8_t *out_data,
const dw_conv_params_t *conv_params,
const quant_data_t *quant_data);
int esp_nn_get_conv_scratch_size_opt(const data_dims_t *input_dims,
const data_dims_t *filter_dims,
const data_dims_t *output_dims,
const conv_params_t *conv_params);
void esp_nn_set_conv_scratch_buf_opt(const void *buf);
int esp_nn_get_depthwise_conv_scratch_size_opt(const data_dims_t *input_dims,
const data_dims_t *filter_dims,
const data_dims_t *output_dims,
const dw_conv_params_t *conv_params);
void esp_nn_set_depthwise_conv_scratch_buf_opt(const void *buf);
/* ANSI C function to be hooked up when optimised version needed */
void esp_nn_set_softmax_scratch_buf_opt(void *buffer);
/**
* @brief optimised version of softmax function
*

83
code/components/esp-nn/include/esp_nn_defs.h
View File

@@ -1,83 +0,0 @@
// Copyright 2022 Espressif Systems (Shanghai) PTE LTD
//
// 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.
#pragma once
#include <stdint.h>
/**
* @brief structure to club data dims
* this structure can be used for input, output and filter
*/
typedef struct data_dims {
int32_t width;
int32_t height;
int32_t channels;
int32_t extra; // can be used as batch or any other param
} data_dims_t;
/**
* @brief 2d data structure (width, height)
*
*/
typedef struct data_2d {
int32_t width;
int32_t height;
} data_2d_t;
/**
* @brief min/max activation
*/
typedef struct act_params {
int32_t min;
int32_t max;
} act_params_t;
/**
* @brief per channel quant data
*
* @note number of shift and mult elements are equal to output channels
*/
typedef struct quant_data {
int32_t *shift;
int32_t *mult;
} quant_data_t;
/**
* @brief params specific to convolution 2d
*
*/
typedef struct conv_params {
int32_t in_offset;
int32_t out_offset;
data_2d_t stride;
data_2d_t padding;
data_2d_t dilation;
act_params_t activation;
} conv_params_t;
/**
* @brief params specific to depthwise convolution 2d
*
*/
typedef struct dw_conv_params {
int32_t in_offset;
int32_t out_offset;
int32_t ch_mult; // channel multiplier. (in_ch * ch_mult = out_ch)
data_2d_t stride;
data_2d_t padding;
data_2d_t dilation;
act_params_t activation;
} dw_conv_params_t;

19
code/components/esp-nn/include/esp_nn_generic_opt.h → code/components/esp-nn/include/esp_nn_esp32.h
View File

@@ -13,27 +13,28 @@
// limitations under the License.
/**
* @file Header definitions to include for esp_nn generic optimisations
* For functions which not having optimisations, _ansi versions are picked.
* @file Header definitions to include for esp_nn optimized functions for
* the ESP32 platform.
* We are hooking up just the C versions for now.
* The file hence is exactly same as `esp_nn_ansi_c.h`
*/
#pragma once
#include "esp_nn_defs.h"
#include "esp_nn_ansi_headers.h"
#define esp_nn_add_elementwise_s8 esp_nn_add_elementwise_s8_ansi
#define esp_nn_mul_elementwise_s8 esp_nn_mul_elementwise_s8_ansi
#define esp_nn_depthwise_conv_s8 esp_nn_depthwise_conv_s8_opt
#define esp_nn_depthwise_conv_s8 esp_nn_depthwise_conv_s8_ansi
#define esp_nn_conv_s8 esp_nn_conv_s8_opt
#define esp_nn_conv_s8 esp_nn_conv_s8_ansi
#define esp_nn_get_conv_scratch_size esp_nn_get_conv_scratch_size_opt
#define esp_nn_set_conv_scratch_buf esp_nn_set_conv_scratch_buf_opt
#define esp_nn_get_conv_scratch_size esp_nn_get_conv_scratch_size_ansi
#define esp_nn_set_conv_scratch_buf esp_nn_set_conv_scratch_buf_ansi
#define esp_nn_get_depthwise_conv_scratch_size esp_nn_get_depthwise_conv_scratch_size_opt
#define esp_nn_set_depthwise_conv_scratch_buf esp_nn_set_depthwise_conv_scratch_buf_opt
#define esp_nn_get_depthwise_conv_scratch_size esp_nn_get_depthwise_conv_scratch_size_ansi
#define esp_nn_set_depthwise_conv_scratch_buf esp_nn_set_depthwise_conv_scratch_buf_ansi
#define esp_nn_relu6_s8 esp_nn_relu6_s8_ansi

76
code/components/esp-nn/include/esp_nn_esp32s3.h
View File

@@ -19,7 +19,7 @@
#pragma once
#include "esp_nn_defs.h"
#include <stdint.h>
#include "esp_nn_ansi_headers.h"
/************************** Basic math functions *****************************/
@@ -85,15 +85,28 @@ void esp_nn_mul_elementwise_s8_esp32s3(const int8_t *input1_data,
* optimization notes: Though input_offset is int32 type,
* offset values are contained in 8 bits [-128, 127]
*/
void esp_nn_depthwise_conv_s8_esp32s3(const data_dims_t *input_dims,
const int8_t *input_data,
const data_dims_t *filter_dims,
void esp_nn_depthwise_conv_s8_esp32s3(const int8_t *input_data,
const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t channels,
const int32_t input_offset,
const uint16_t pad_wd,
const uint16_t pad_ht,
const uint16_t stride_wd,
const uint16_t stride_ht,
const uint16_t ch_mult,
const int8_t *filter_data,
const uint16_t filter_wd,
const uint16_t filter_ht,
const int32_t *bias,
const data_dims_t *output_dims,
int8_t *output_data,
const dw_conv_params_t *conv_params,
const quant_data_t *quant_data);
int8_t *out_data,
const uint16_t out_wd,
const uint16_t out_ht,
const int32_t out_offset,
const int32_t *out_shift,
const int32_t *out_mult,
const int32_t activation_min,
const int32_t activation_max);
/**
* @brief 2d - convolution channelwise
@@ -103,26 +116,43 @@ void esp_nn_depthwise_conv_s8_esp32s3(const data_dims_t *input_dims,
* inputs type: int8_t, output: int8_t
* input offsets: although int32_t, they are contained in 8 bits [-128, 127]
*/
void esp_nn_conv_s8_esp32s3(const data_dims_t *input_dims,
const int8_t *input_data,
const data_dims_t *filter_dims,
void esp_nn_conv_s8_esp32s3(const int8_t *input_data,
const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t in_channels,
const int32_t input_offset,
const uint16_t pad_wd,
const uint16_t pad_ht,
const uint16_t stride_wd,
const uint16_t stride_ht,
const int8_t *filter_data,
const uint16_t filter_wd,
const uint16_t filter_ht,
const int32_t *bias,
const data_dims_t *output_dims,
int8_t *output_data,
const conv_params_t *conv_params,
const quant_data_t *quant_data);
int8_t *out_data,
const uint16_t out_wd,
const uint16_t out_ht,
const uint16_t out_channels,
const int32_t out_offset,
const int32_t *out_shift,
const int32_t *out_mult,
const int32_t activation_min,
const int32_t activation_max);
int esp_nn_get_conv_scratch_size_esp32s3(const data_dims_t *input_dims,
const data_dims_t *filter_dims,
const data_dims_t *output_dims,
const conv_params_t *conv_params);
int esp_nn_get_conv_scratch_size_esp32s3(const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t in_ch,
const uint16_t out_ch,
const uint16_t filter_wd,
const uint16_t filter_ht);
void esp_nn_set_conv_scratch_buf_esp32s3(const void *buf);
int esp_nn_get_depthwise_conv_scratch_size_esp32s3(const data_dims_t *input_dims,
const data_dims_t *filter_dims,
const data_dims_t *output_dims,
const dw_conv_params_t *conv_params);
int esp_nn_get_depthwise_conv_scratch_size_esp32s3(const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t channels,
const uint16_t ch_mult,
const uint16_t filter_wd,
const uint16_t filter_ht);
void esp_nn_set_depthwise_conv_scratch_buf_esp32s3(const void *buf);
/************************** Pooling functions *****************************/

67
code/components/esp-nn/src/common/common_functions.h
View File

@@ -41,52 +41,8 @@
__NN_FORCE_INLINE__ int32_t esp_nn_clz32(uint32_t in)
{
#if CONFIG_IDF_TARGET_ARCH_XTENSA
__asm__ volatile("nsau %0, %0" : "+r" (in));
return in;
#elif defined(__GNUC__)
return __builtin_clz(in);
#else
int32_t count = 32;
uint32_t x = in, y = in >> 16;
if (y != 0) {
count -= 16;
x = y;
}
y = x >> 8;
if (y != 0) {
count -= 8;
x = y;
}
y = x >> 4;
if (y != 0) {
count -= 4;
x = y;
}
y = x >> 2;
if (y != 0) {
count -= 2;
x = y;
}
y = x >> 1;
if (y != 0) {
return count - 2;
}
return count - x;
#endif
}
/**
* Signed saturate a 32 bit value to 8 bits keeping output in 32 bit variable.
*/
__NN_FORCE_INLINE__ int32_t esp_nn_saturate8(int32_t in)
{
#if CONFIG_IDF_TARGET_ARCH_XTENSA
__asm__ volatile("clamps %0, %0, 7" : "+a"(in));
return in;
#else
return max(INT8_MIN, min(in, INT8_MAX));
#endif
}
__NN_FORCE_INLINE__ int32_t esp_nn_pick_sat_high32_of64(int64_t val64)
@@ -96,6 +52,15 @@ __NN_FORCE_INLINE__ int32_t esp_nn_pick_sat_high32_of64(int64_t val64)
return (int32_t) ((int64_t) (val64 + to_add) >> 31);
}
/**
* Signed saturate a 32 bit value to 8 bits keeping output in 32 bit variable.
*/
__NN_FORCE_INLINE__ int32_t esp_nn_saturate8(int32_t in)
{
__asm__ volatile("clamps %0, %0, 7" : "+a"(in));
return in;
}
__NN_FORCE_INLINE__ int32_t esp_nn_sat_round_doubling_high_mul(int32_t in0, int32_t in1)
{
int32_t result;
@@ -179,7 +144,7 @@ static void esp_nn_aligned_s8_pad_with_value(const int8_t *src, int8_t *dst,
const uint16_t pad_ht)
{
/* memset with pad_val */
memset(dst, pad_val, ((input_wd + 2 * pad_wd) * (input_ht + 2 * pad_ht)) * channels);
memset(dst, pad_val, ((input_wd + 2 * pad_wd) * (input_ht + 2 * pad_ht)) * channels * 2);
dst += (pad_wd + input_wd + pad_wd) * channels;
for (int i = 0; i < input_ht; i++) {
@@ -191,6 +156,7 @@ static void esp_nn_aligned_s8_pad_with_value(const int8_t *src, int8_t *dst,
}
}
#if 0
static void esp_nn_aligned_s8_pad_end_with_value(const int8_t *src, int8_t *dst,
const uint16_t input_wd,
const uint16_t input_ht,
@@ -203,16 +169,13 @@ static void esp_nn_aligned_s8_pad_end_with_value(const int8_t *src, int8_t *dst,
for (int j = 0; j < input_wd * channels; j++) {
*dst++ = *src++;
}
if (pad_wd) {
memset(dst, pad_val, pad_wd * channels);
dst += pad_wd * channels;
}
memset(dst, pad_val, pad_wd * channels);
dst += pad_wd * channels;
}
/* pad end `pad_ht` lines at end */
if (pad_ht) {
memset(dst, pad_val, (input_wd + pad_wd) * pad_ht * channels);
}
memset(dst, pad_val, (input_wd + pad_wd) * pad_ht * channels);
}
#endif
/**
* @brief convert 8 bit input data to 16 bit

56
code/components/esp-nn/src/convolution/esp_nn_conv_ansi.c
View File

@@ -12,14 +12,16 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include <esp_nn_defs.h>
#include <stdint.h>
#include <common_functions.h>
int esp_nn_get_conv_scratch_size_ansi(const data_dims_t *input_dims,
const data_dims_t *filter_dims,
const data_dims_t *output_dims,
const conv_params_t *conv_params)
int esp_nn_get_conv_scratch_size_ansi(const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t in_ch,
const uint16_t out_ch,
const uint16_t filter_wd,
const uint16_t filter_ht)
{
return 0;
}
@@ -106,35 +108,29 @@ void esp_nn_conv_u8_ansi(const uint8_t *input_data,
* Assumption 2: Pointers are valid
* Assumption 3: dialation width = 1
*/
void esp_nn_conv_s8_ansi(const data_dims_t *input_dims,
const int8_t *input_data,
const data_dims_t *filter_dims,
void esp_nn_conv_s8_ansi(const int8_t *input_data,
const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t in_channels,
const int32_t input_offset,
const uint16_t pad_wd,
const uint16_t pad_ht,
const uint16_t stride_wd,
const uint16_t stride_ht,
const int8_t *filter_data,
const uint16_t filter_wd,
const uint16_t filter_ht,
const int32_t *bias,
const data_dims_t *output_dims,
int8_t *out_data,
const conv_params_t *conv_params,
const quant_data_t *quant_data)
const uint16_t out_wd,
const uint16_t out_ht,
const uint16_t out_channels,
const int32_t out_offset,
const int32_t *out_shift,
const int32_t *out_mult,
const int32_t activation_min,
const int32_t activation_max)
{
const uint16_t input_wd = input_dims->width;
const uint16_t input_ht = input_dims->height;
const uint16_t in_channels = input_dims->channels;
const int32_t input_offset = conv_params->in_offset;
const int32_t out_offset = conv_params->out_offset;
const uint16_t pad_wd = conv_params->padding.width;
const uint16_t pad_ht = conv_params->padding.height;
const uint16_t stride_wd = conv_params->stride.width;
const uint16_t stride_ht = conv_params->stride.height;
const uint16_t filter_wd = filter_dims->width;
const uint16_t filter_ht = filter_dims->height;
const uint16_t out_wd = output_dims->width;
const uint16_t out_ht = output_dims->height;
const uint16_t out_channels = output_dims->channels;
const int32_t *out_shift = quant_data->shift;
const int32_t *out_mult = quant_data->mult;
const int32_t activation_min = conv_params->activation.min;
const int32_t activation_max = conv_params->activation.max;
int32_t out_ch_idx, out_y, out_x, in_ch_idx, filter_y_idx, filter_x_idx;
for (out_y = 0; out_y < out_ht; out_y++) {

185
code/components/esp-nn/src/convolution/esp_nn_conv_esp32s3.c
View File

@@ -12,30 +12,30 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include <stdint.h>
#include <stdio.h>
#include <esp_nn_defs.h>
#include <common_functions.h>
static int16_t *scratch_buffer = NULL;
extern void esp_nn_conv_s8_mult8_1x1_esp32s3(const int8_t *input_data,
const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t in_channels,
const int32_t input_offset,
const int8_t *filter_aligned,
const int32_t *bias,
int8_t *out_data,
const uint16_t out_wd,
const uint16_t out_ht,
const uint16_t out_channels,
const int32_t out_offset,
const int32_t *out_shift,
const int32_t *out_mult,
const int32_t activation_min,
const int32_t activation_max,
void *buffer /* scratch buffer */);
extern void esp_nn_conv_s16_mult8_1x1_esp32s3(const int8_t *input_data,
const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t in_channels,
const int32_t input_offset,
const int16_t *filter_data,
const int32_t *bias,
int8_t *out_data,
const uint16_t out_wd,
const uint16_t out_ht,
const uint16_t out_channels,
const int32_t out_offset,
const int32_t *out_shift,
const int32_t *out_mult,
const int32_t activation_min,
const int32_t activation_max,
void *buffer /* scratch buffer */);
extern void esp_nn_conv_s16_mult4_1x1_esp32s3(const int16_t *input_data,
const uint16_t input_wd,
@@ -81,40 +81,34 @@ extern void esp_nn_aligned_s8_to_s16_with_offset_esp32s3(const int8_t *src, int1
extern void esp_nn_s8_to_s16_esp32s3(const int8_t *src, int16_t *dst, const int size);
static void esp_nn_conv_s8_unrolled(const data_dims_t *input_dims,
const int8_t *input_data,
const data_dims_t *filter_dims,
static void esp_nn_conv_s8_unrolled(const int8_t *input_data,
const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t in_channels,
const int32_t input_offset,
const uint16_t pad_wd,
const uint16_t pad_ht,
const uint16_t stride_wd,
const uint16_t stride_ht,
const int8_t *filter_data,
const uint16_t filter_wd,
const uint16_t filter_ht,
const int32_t *bias,
const data_dims_t *output_dims,
int8_t *out_data,
const conv_params_t *conv_params,
const quant_data_t *quant_data)
const uint16_t out_wd,
const uint16_t out_ht,
const uint16_t out_channels,
const int32_t out_offset,
const int32_t *out_shift,
const int32_t *out_mult,
const int32_t activation_min,
const int32_t activation_max)
{
const uint16_t input_wd = input_dims->width;
const uint16_t input_ht = input_dims->height;
const uint16_t in_ch = input_dims->channels;
const int32_t input_offset = conv_params->in_offset;
const int32_t out_offset = conv_params->out_offset;
const uint16_t pad_wd = conv_params->padding.width;
const uint16_t pad_ht = conv_params->padding.height;
const uint16_t stride_wd = conv_params->stride.width;
const uint16_t stride_ht = conv_params->stride.height;
const uint16_t filter_wd = filter_dims->width;
const uint16_t filter_ht = filter_dims->height;
const uint16_t out_wd = output_dims->width;
const uint16_t out_ht = output_dims->height;
const uint16_t out_ch = output_dims->channels;
const int32_t *out_shift = quant_data->shift;
const int32_t *out_mult = quant_data->mult;
const int32_t activation_min = conv_params->activation.min;
const int32_t activation_max = conv_params->activation.max;
int32_t out_ch_idx, out_y, out_x, in_ch_idx, filter_y_idx, filter_x_idx;
for (out_y = 0; out_y < out_ht; out_y++) {
for (out_x = 0; out_x < out_wd; out_x++) {
for (out_ch_idx = 0; out_ch_idx < out_ch; out_ch_idx++) {
for (out_ch_idx = 0; out_ch_idx < out_channels; out_ch_idx++) {
int32_t conv_out = 0;
const int32_t base_y = stride_ht * out_y - pad_ht;
@@ -130,10 +124,10 @@ static void esp_nn_conv_s8_unrolled(const data_dims_t *input_dims,
for (filter_x_idx = filter_x_start; filter_x_idx < filter_x_end; filter_x_idx++) {
const int32_t in_row = base_y + filter_y_idx;
const int32_t in_col = base_x + filter_x_idx;
int32_t input_base_offset = (in_row * input_wd + in_col) * in_ch;
int32_t filter_base_offset = out_ch_idx * in_ch * filter_ht * filter_wd +
(filter_y_idx * filter_wd + filter_x_idx) * in_ch;
for (in_ch_idx = 0; in_ch_idx < in_ch; in_ch_idx++) {
int32_t input_base_offset = (in_row * input_wd + in_col) * in_channels;
int32_t filter_base_offset = out_ch_idx * in_channels * filter_ht * filter_wd +
(filter_y_idx * filter_wd + filter_x_idx) * in_channels;
for (in_ch_idx = 0; in_ch_idx < in_channels; in_ch_idx++) {
conv_out +=
(input_data[input_base_offset + in_ch_idx] + input_offset) *
filter_data[filter_base_offset + in_ch_idx];
@@ -338,35 +332,18 @@ static void esp_nn_conv_s8_pad_valid_ch3_3x3(const int8_t *input_data,
}
}
int esp_nn_get_conv_scratch_size_esp32s3(const data_dims_t *input_dims,
const data_dims_t *filter_dims,
const data_dims_t *output_dims,
const conv_params_t *conv_params)
int esp_nn_get_conv_scratch_size_esp32s3(const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t in_ch,
const uint16_t out_ch,
const uint16_t filter_wd,
const uint16_t filter_ht)
{
const uint16_t input_wd = input_dims->width;
const uint16_t input_ht = input_dims->height;
const uint16_t in_ch = input_dims->channels;
const uint16_t filter_wd = filter_dims->width;
const uint16_t filter_ht = filter_dims->height;
const uint16_t out_ch = output_dims->channels;
const uint16_t pad_wd = conv_params->padding.width;
const uint16_t pad_ht = conv_params->padding.height;
const uint16_t stride_wd = conv_params->stride.width;
const uint16_t stride_ht = conv_params->stride.height;
int filter_size = filter_wd * filter_ht * in_ch * out_ch;
int input_size = input_wd * input_ht * in_ch;
int transpose_buf_size = 2 * (8 * in_ch); /* to store intermediate data */
if (input_wd * input_ht < 8) {
transpose_buf_size = 0; // not using this for leftover
}
int transpose_buf_size = 8 * in_ch; /* to store intermediate data */
int align_buf_size = 32; /* extra buffer for alignment */
if (in_ch % 8 == 0 && filter_wd == 1 && filter_ht == 1 &&
pad_wd == 0 && pad_ht == 0 && stride_wd == 1 && stride_ht == 1) {
return filter_size + transpose_buf_size + align_buf_size;
}
return 2 * (filter_size + input_size) + transpose_buf_size + align_buf_size;
return 2 * (filter_size + input_size + transpose_buf_size) + align_buf_size;
}
void esp_nn_set_conv_scratch_buf_esp32s3(void *buf)
@@ -374,35 +351,29 @@ void esp_nn_set_conv_scratch_buf_esp32s3(void *buf)
scratch_buffer = (int16_t *) buf;
}
void esp_nn_conv_s8_esp32s3(const data_dims_t *input_dims,
const int8_t *input,
const data_dims_t *filter_dims,
void esp_nn_conv_s8_esp32s3(const int8_t *input,
const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t channels,
const int32_t input_offset,
const uint16_t pad_wd,
const uint16_t pad_ht,
const uint16_t stride_wd,
const uint16_t stride_ht,
const int8_t *filter_data,
const uint16_t filter_wd,
const uint16_t filter_ht,
const int32_t *bias,
const data_dims_t *output_dims,
int8_t *out_data,
const conv_params_t *conv_params,
const quant_data_t *quant_data)
const uint16_t out_wd,
const uint16_t out_ht,
const uint16_t out_channels,
const int32_t out_offset,
const int32_t *out_shift,
const int32_t *out_mult,
const int32_t activation_min,
const int32_t activation_max)
{
const uint16_t input_wd = input_dims->width;
const uint16_t input_ht = input_dims->height;
const uint16_t channels = input_dims->channels;
const int32_t input_offset = conv_params->in_offset;
const int32_t out_offset = conv_params->out_offset;
const uint16_t pad_wd = conv_params->padding.width;
const uint16_t pad_ht = conv_params->padding.height;
const uint16_t stride_wd = conv_params->stride.width;
const uint16_t stride_ht = conv_params->stride.height;
const uint16_t filter_wd = filter_dims->width;
const uint16_t filter_ht = filter_dims->height;
const uint16_t out_wd = output_dims->width;
const uint16_t out_ht = output_dims->height;
const uint16_t out_channels = output_dims->channels;
const int32_t *out_shift = quant_data->shift;
const int32_t *out_mult = quant_data->mult;
const int32_t activation_min = conv_params->activation.min;
const int32_t activation_max = conv_params->activation.max;
int filter_size = filter_wd * filter_ht * channels * out_channels;
int input_size = input_wd * input_ht * channels;
int align_len = 16 - (filter_size & 15);
@@ -416,16 +387,15 @@ void esp_nn_conv_s8_esp32s3(const data_dims_t *input_dims,
if (channels % 8 == 0 && filter_wd == 1 && filter_ht == 1 &&
pad_wd == 0 && pad_ht == 0 && stride_wd == 1 && stride_ht == 1) {
int8_t *filter_aligned = (int8_t *) scratch_buffer;
int scratch_offset = (int) (filter_aligned + filter_size);
int scratch_offset = (int) (filter_data16 + filter_size);
void *scratch_buf = (void *) (scratch_offset + 16 - (scratch_offset & 15));
memcpy(filter_aligned, filter_data, filter_size); // copy to aligned address
esp_nn_conv_s8_mult8_1x1_esp32s3(
input, input_wd, input_ht, channels, input_offset, filter_aligned,
esp_nn_s8_to_s16_esp32s3(filter_data, filter_data16, filter_size);
esp_nn_conv_s16_mult8_1x1_esp32s3(
input, input_wd, input_ht, channels, input_offset, filter_data16,
bias, out_data, out_wd, out_ht, out_channels, out_offset,
out_shift, out_mult, activation_min, activation_max, scratch_buf);
} else if (channels % 4 == 0 && filter_wd == 1 && filter_ht == 1 &&
(input_wd * input_ht) % 4 == 0 && /* TODO: remove this check */
(input_wd * input_ht) % 16 == 0 && /* TODO: remove this check */
pad_wd == 0 && pad_ht == 0 && stride_wd == 1 && stride_ht == 1) {
int scratch_offset = (int) (input_data16 + input_size);
void *scratch_buf = (void *) (scratch_offset + 16 - (scratch_offset & 15));
@@ -457,7 +427,10 @@ void esp_nn_conv_s8_esp32s3(const data_dims_t *input_dims,
}
} else {
/* Basic unrolled version */
esp_nn_conv_s8_unrolled(input_dims, input, filter_dims, filter_data,
bias, output_dims, out_data, conv_params, quant_data);
esp_nn_conv_s8_unrolled(input, input_wd, input_ht, channels, input_offset,
pad_wd, pad_ht, stride_wd, stride_ht,
filter_data, filter_wd, filter_ht, bias,
out_data, out_wd, out_ht, out_channels, out_offset, out_shift,
out_mult, activation_min, activation_max);
}
}

179
code/components/esp-nn/src/convolution/esp_nn_conv_opt.c
View File

@@ -1,179 +0,0 @@
// Copyright 2020-2021 Espressif Systems (Shanghai) PTE LTD
//
// 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 <esp_nn_defs.h>
#include <common_functions.h>
int esp_nn_get_conv_scratch_size_opt(const data_dims_t *input_dims,
const data_dims_t *filter_dims,
const data_dims_t *output_dims,
const conv_params_t *conv_params)
{
return 0;
}
void esp_nn_set_conv_scratch_buf_opt(const void *buf)
{
}
__attribute__ ((noinline))
static void esp_nn_conv_s8_1x1(const data_dims_t *input_dims,
const int8_t *input_data,
const int8_t *filter_data,
const int32_t *bias,
const data_dims_t *output_dims,
int8_t *out_data,
const conv_params_t *conv_params,
const quant_data_t *quant_data)
{
const uint16_t input_wd = input_dims->width;
const uint16_t in_channels = input_dims->channels;
const int32_t input_offset = conv_params->in_offset;
const int32_t out_offset = conv_params->out_offset;
const uint16_t stride_wd = conv_params->stride.width;
const uint16_t stride_ht = conv_params->stride.height;
const uint16_t out_wd = output_dims->width;
const uint16_t out_ht = output_dims->height;
const uint16_t out_channels = output_dims->channels;
const int32_t activation_min = conv_params->activation.min;
const int32_t activation_max = conv_params->activation.max;
for (int32_t in_row = 0; in_row < out_ht * stride_ht; in_row += stride_ht) {
for (int32_t in_col = 0; in_col < out_wd * stride_wd; in_col += stride_wd) {
const int32_t *out_mult = quant_data->mult;
const int32_t *out_shift = quant_data->shift;
const int8_t *filter_ptr = filter_data;
const int8_t *input_base_ptr = input_data + (in_row * input_wd + in_col) * in_channels;
int32_t out_ch_idx = 0;
for (; out_ch_idx < out_channels; out_ch_idx++) {
int32_t conv_out = 0;
const int8_t *input_ptr = input_base_ptr;
int32_t in_ch_idx = 0;
for (; in_ch_idx < in_channels - 3; in_ch_idx += 4) {
conv_out += (*input_ptr++ + input_offset) * *filter_ptr++;
conv_out += (*input_ptr++ + input_offset) * *filter_ptr++;
conv_out += (*input_ptr++ + input_offset) * *filter_ptr++;
conv_out += (*input_ptr++ + input_offset) * *filter_ptr++;
}
for (; in_ch_idx < in_channels; in_ch_idx ++) {
conv_out += (*input_ptr++ + input_offset) * *filter_ptr++;
}
if (bias) {
conv_out += bias[out_ch_idx];
}
conv_out = esp_nn_multiply_by_quantized_mult_fast(conv_out, *out_mult++, *out_shift++);
conv_out += out_offset;
conv_out = max(conv_out, activation_min);
conv_out = min(conv_out, activation_max);
*out_data++ = (int8_t) conv_out;
}
}
}
}
/**
* Assumption 1: i/p channels == o/p channels
* Assumption 2: Pointers are valid
* Assumption 3: dialation width = 1
*/
void esp_nn_conv_s8_opt(const data_dims_t *input_dims,
const int8_t *input_data,
const data_dims_t *filter_dims,
const int8_t *filter_data,
const int32_t *bias,
const data_dims_t *output_dims,
int8_t *out_data,
const conv_params_t *conv_params,
const quant_data_t *quant_data)
{
const uint16_t filter_wd = filter_dims->width;
const uint16_t filter_ht = filter_dims->height;
if (filter_wd == 1 && filter_ht == 1) {
esp_nn_conv_s8_1x1(input_dims, input_data, filter_data, bias,
output_dims, out_data, conv_params, quant_data);
return;
}
const uint16_t input_wd = input_dims->width;
const uint16_t input_ht = input_dims->height;
const uint16_t in_channels = input_dims->channels;
const int32_t input_offset = conv_params->in_offset;
const int32_t out_offset = conv_params->out_offset;
const uint16_t pad_wd = conv_params->padding.width;
const uint16_t pad_ht = conv_params->padding.height;
const uint16_t stride_wd = conv_params->stride.width;
const uint16_t stride_ht = conv_params->stride.height;
const uint16_t out_wd = output_dims->width;
const uint16_t out_ht = output_dims->height;
const uint16_t out_channels = output_dims->channels;
const int32_t activation_min = conv_params->activation.min;
const int32_t activation_max = conv_params->activation.max;
int32_t out_ch_idx, out_y, out_x, filter_y_idx, filter_x_idx;
for (out_y = 0; out_y < out_ht; out_y++) {
for (out_x = 0; out_x < out_wd; out_x++) {
const int32_t *out_shift = quant_data->shift;
const int32_t *out_mult = quant_data->mult;
for (out_ch_idx = 0; out_ch_idx < out_channels; out_ch_idx++) {
int32_t conv_out = 0;
const int32_t base_y = stride_ht * out_y - pad_ht;
const int32_t base_x = stride_wd * out_x - pad_wd;
const int32_t filter_y_start = max(0, -base_y);
const int32_t filter_x_start = max(0, -base_x);
const int32_t filter_y_end = min(filter_ht, input_ht - base_y);
const int32_t filter_x_end = min(filter_wd, input_wd - base_x);
for (filter_y_idx = filter_y_start; filter_y_idx < filter_y_end; filter_y_idx++) {
for (filter_x_idx = filter_x_start; filter_x_idx < filter_x_end; filter_x_idx++) {
const int32_t in_row = base_y + filter_y_idx;
const int32_t in_col = base_x + filter_x_idx;
const int8_t *input_ptr = input_data +
(in_row * input_wd + in_col) * in_channels;
const int8_t *filter_ptr = filter_data +
out_ch_idx * in_channels * filter_ht * filter_wd +
(filter_y_idx * filter_wd + filter_x_idx) * in_channels;
int32_t in_ch_idx = 0;
for (; in_ch_idx < in_channels - 3; in_ch_idx += 4) {
conv_out += (*input_ptr++ + input_offset) * *filter_ptr++;
conv_out += (*input_ptr++ + input_offset) * *filter_ptr++;
conv_out += (*input_ptr++ + input_offset) * *filter_ptr++;
conv_out += (*input_ptr++ + input_offset) * *filter_ptr++;
}
for (; in_ch_idx < in_channels; in_ch_idx ++) {
conv_out += (*input_ptr++ + input_offset) * *filter_ptr++;
}
}
}
if (bias) {
conv_out += bias[out_ch_idx];
}
conv_out = esp_nn_multiply_by_quantized_mult_fast(conv_out, *out_mult++, *out_shift++);
conv_out += out_offset;
conv_out = max(conv_out, activation_min);
conv_out = min(conv_out, activation_max);
*out_data++ = (int8_t) conv_out;
}
}
}
}

57
code/components/esp-nn/src/convolution/esp_nn_depthwise_conv_ansi.c
View File

@@ -12,13 +12,16 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include <esp_nn_defs.h>
#include <stdint.h>
#include <common_functions.h>
int esp_nn_get_depthwise_conv_scratch_size_ansi(const data_dims_t *input_dims,
const data_dims_t *filter_dims,
const data_dims_t *output_dims,
const dw_conv_params_t *conv_params)
int esp_nn_get_depthwise_conv_scratch_size_ansi(const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t channels,
const uint16_t ch_mult,
const uint16_t filter_wd,
const uint16_t filter_ht)
{
return 0;
}
@@ -28,35 +31,29 @@ void esp_nn_set_depthwise_conv_scratch_buf_ansi(const void *buf)
}
void esp_nn_depthwise_conv_s8_ansi(const data_dims_t *input_dims,
const int8_t *input_data,
const data_dims_t *filter_dims,
void esp_nn_depthwise_conv_s8_ansi(const int8_t *input_data,
const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t channels,
const int32_t input_offset,
const uint16_t pad_wd,
const uint16_t pad_ht,
const uint16_t stride_wd,
const uint16_t stride_ht,
const uint16_t ch_mult,
const int8_t *filter_data,
const uint16_t filter_wd,
const uint16_t filter_ht,
const int32_t *bias,
const data_dims_t *output_dims,
int8_t *out_data,
const dw_conv_params_t *conv_params,
const quant_data_t *quant_data)
const uint16_t out_wd,
const uint16_t out_ht,
const int32_t out_offset,
const int32_t *out_shift,
const int32_t *out_mult,
const int32_t activation_min,
const int32_t activation_max)
{
const uint16_t input_wd = input_dims->width;
const uint16_t input_ht = input_dims->height;
const uint16_t channels = input_dims->channels;
const int32_t input_offset = conv_params->in_offset;
const int32_t out_offset = conv_params->out_offset;
const uint16_t pad_wd = conv_params->padding.width;
const uint16_t pad_ht = conv_params->padding.height;
const uint16_t stride_wd = conv_params->stride.width;
const uint16_t stride_ht = conv_params->stride.height;
const uint16_t filter_wd = filter_dims->width;
const uint16_t filter_ht = filter_dims->height;
const uint16_t out_wd = output_dims->width;
const uint16_t out_ht = output_dims->height;
const int32_t *out_shift = quant_data->shift;
const int32_t *out_mult = quant_data->mult;
const int32_t activation_min = conv_params->activation.min;
const int32_t activation_max = conv_params->activation.max;
const uint16_t ch_mult = conv_params->ch_mult;
int out_idx = 0;
for (int out_y = 0; out_y < out_ht; out_y++) { //height loop
const int16_t base_y = (out_y * stride_ht) - pad_ht;

291
code/components/esp-nn/src/convolution/esp_nn_depthwise_conv_opt.c
View File

@@ -1,291 +0,0 @@
// Copyright 2020-2021 Espressif Systems (Shanghai) PTE LTD
//
// 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 <esp_nn_defs.h>
#include <common_functions.h>
int esp_nn_get_depthwise_conv_scratch_size_opt(const data_dims_t *input_dims,
const data_dims_t *filter_dims,
const data_dims_t *output_dims,
const dw_conv_params_t *conv_params)
{
return 0;
}
void esp_nn_set_depthwise_conv_scratch_buf_opt(const void *buf)
{
}
/* common channel multiplier == 1 case */
__attribute__ ((noinline))
static void esp_nn_depthwise_conv_s8_ch_mult_1(const data_dims_t *input_dims,
const int8_t *input_data,
const data_dims_t *filter_dims,
const int8_t *filter_data,
const int32_t *bias,
const data_dims_t *output_dims,
int8_t *out_data,
const dw_conv_params_t *conv_params,
const quant_data_t *quant_data)
{
const uint16_t input_wd = input_dims->width;
const uint16_t input_ht = input_dims->height;
const uint16_t channels = input_dims->channels;
const int32_t input_offset = conv_params->in_offset;
const int32_t out_offset = conv_params->out_offset;
const uint16_t pad_wd = conv_params->padding.width;
const uint16_t pad_ht = conv_params->padding.height;
const uint16_t stride_wd = conv_params->stride.width;
const uint16_t stride_ht = conv_params->stride.height;
const uint16_t filter_wd = filter_dims->width;
const uint16_t filter_ht = filter_dims->height;
const uint16_t out_wd = output_dims->width;
const uint16_t out_ht = output_dims->height;
const int32_t activation_min = conv_params->activation.min;
const int32_t activation_max = conv_params->activation.max;
int out_idx = 0;
for (int out_y = 0; out_y < out_ht; out_y++) { //height loop
const int16_t base_y = (out_y * stride_ht) - pad_ht;
for (int out_x = 0; out_x < out_wd; out_x++) { //width_loop
const int16_t base_x = (out_x * stride_wd) - pad_wd;
const int32_t *out_shift = quant_data->shift;
const int32_t *out_mult = quant_data->mult;
/* Select filter so as the point doesn't lie outside block */
int filter_y_start = max(0, -base_y);
int filter_x_start = max(0, -base_x);
int filter_y_end = min(filter_ht, input_ht - base_y);
int filter_x_end = min(filter_wd, input_wd - base_x);
int ch_idx = 0;
for (; ch_idx < channels - 3; ch_idx += 4) {//channel_loop
int32_t result0 = 0;
int32_t result1 = 0;
int32_t result2 = 0;
int32_t result3 = 0;
for (int filter_y_idx = filter_y_start; filter_y_idx < filter_y_end; filter_y_idx++) {
const int32_t idx_y = base_y + filter_y_idx;
for (int filter_x_idx = filter_x_start; filter_x_idx < filter_x_end; filter_x_idx++) {
const int32_t idx_x = base_x + filter_x_idx;
int32_t input_index = (idx_y * input_wd + idx_x) * channels + ch_idx;
int32_t filter_index = (filter_y_idx * filter_wd + filter_x_idx) * (channels) + ch_idx;
int32_t input_val0 = input_data[input_index + 0] + input_offset;
int32_t input_val1 = input_data[input_index + 1] + input_offset;
int32_t input_val2 = input_data[input_index + 2] + input_offset;
int32_t input_val3 = input_data[input_index + 3] + input_offset;
int32_t filter_val0 = filter_data[filter_index + 0];
int32_t filter_val1 = filter_data[filter_index + 1];
int32_t filter_val2 = filter_data[filter_index + 2];
int32_t filter_val3 = filter_data[filter_index + 3];
result0 += input_val0 * filter_val0;
result1 += input_val1 * filter_val1;
result2 += input_val2 * filter_val2;
result3 += input_val3 * filter_val3;
}
}
if (bias) {
result0 += bias[ch_idx + 0];
result1 += bias[ch_idx + 1];
result2 += bias[ch_idx + 2];
result3 += bias[ch_idx + 3];
}
result0 = esp_nn_multiply_by_quantized_mult_fast(result0, *out_mult++, *out_shift++);
result1 = esp_nn_multiply_by_quantized_mult_fast(result1, *out_mult++, *out_shift++);
result2 = esp_nn_multiply_by_quantized_mult_fast(result2, *out_mult++, *out_shift++);
result3 = esp_nn_multiply_by_quantized_mult_fast(result3, *out_mult++, *out_shift++);
result0 += out_offset;
result1 += out_offset;
result2 += out_offset;
result3 += out_offset;
result0 = max(result0, activation_min);
result1 = max(result1, activation_min);
result2 = max(result2, activation_min);
result3 = max(result3, activation_min);
result0 = min(result0, activation_max);
result1 = min(result1, activation_max);
result2 = min(result2, activation_max);
result3 = min(result3, activation_max);
out_data[out_idx++] = result0;
out_data[out_idx++] = result1;
out_data[out_idx++] = result2;
out_data[out_idx++] = result3;
}
for (; ch_idx < channels; ch_idx++) {//channel_loop
int32_t result = 0;
for (int filter_y_idx = filter_y_start; filter_y_idx < filter_y_end; filter_y_idx++) {
const int32_t idx_y = base_y + filter_y_idx;
for (int filter_x_idx = filter_x_start; filter_x_idx < filter_x_end; filter_x_idx++) {
const int32_t idx_x = base_x + filter_x_idx;
int32_t input_index = (idx_y * input_wd + idx_x) * channels + ch_idx;
int32_t filter_index = (filter_y_idx * filter_wd + filter_x_idx) * (channels) + ch_idx;
int32_t input_val = input_data[input_index] + input_offset;
int32_t filter_val = filter_data[filter_index];
result += input_val * filter_val;
}
}
if (bias) {
result += bias[ch_idx];
}
result = esp_nn_multiply_by_quantized_mult_fast(result, *out_mult++, *out_shift++);
result += out_offset;
result = max(result, activation_min);
result = min(result, activation_max);
out_data[out_idx++] = result;
}
}
}
}
void esp_nn_depthwise_conv_s8_opt(const data_dims_t *input_dims,
const int8_t *input_data,
const data_dims_t *filter_dims,
const int8_t *filter_data,
const int32_t *bias,
const data_dims_t *output_dims,
int8_t *out_data,
const dw_conv_params_t *conv_params,
const quant_data_t *quant_data)
{
const uint16_t ch_mult = conv_params->ch_mult;
if (ch_mult == 1) {
esp_nn_depthwise_conv_s8_ch_mult_1(input_dims, input_data, filter_dims, filter_data,
bias, output_dims, out_data, conv_params, quant_data);
return;
}
const uint16_t input_wd = input_dims->width;
const uint16_t input_ht = input_dims->height;
const uint16_t channels = input_dims->channels;
const int32_t input_offset = conv_params->in_offset;
const int32_t out_offset = conv_params->out_offset;
const uint16_t pad_wd = conv_params->padding.width;
const uint16_t pad_ht = conv_params->padding.height;
const uint16_t stride_wd = conv_params->stride.width;
const uint16_t stride_ht = conv_params->stride.height;
const uint16_t filter_wd = filter_dims->width;
const uint16_t filter_ht = filter_dims->height;
const uint16_t out_wd = output_dims->width;
const uint16_t out_ht = output_dims->height;
const int32_t activation_min = conv_params->activation.min;
const int32_t activation_max = conv_params->activation.max;
int out_idx = 0;
for (int out_y = 0; out_y < out_ht; out_y++) { //height loop
const int16_t base_y = (out_y * stride_ht) - pad_ht;
for (int out_x = 0; out_x < out_wd; out_x++) { //width_loop
const int16_t base_x = (out_x * stride_wd) - pad_wd;
const int32_t *out_shift = quant_data->shift;
const int32_t *out_mult = quant_data->mult;
/* Select filter so as the point doesn't lie outside block */
int filter_y_start = max(0, -base_y);
int filter_x_start = max(0, -base_x);
int filter_y_end = min(filter_ht, input_ht - base_y);
int filter_x_end = min(filter_wd, input_wd - base_x);
for (int ch_idx = 0; ch_idx < channels; ch_idx++) {//channel_loop
int ch_mult_idx = 0;
for (; ch_mult_idx < ch_mult - 3; ch_mult_idx += 4) {
int32_t result0 = 0;
int32_t result1 = 0;
int32_t result2 = 0;
int32_t result3 = 0;
const int out_ch_idx = ch_idx * ch_mult + ch_mult_idx;
for (int filter_y_idx = filter_y_start; filter_y_idx < filter_y_end; filter_y_idx++) {
const int32_t idx_y = base_y + filter_y_idx;
for (int filter_x_idx = filter_x_start; filter_x_idx < filter_x_end; filter_x_idx++) {
const int32_t idx_x = base_x + filter_x_idx;
int32_t input_index = (idx_y * input_wd + idx_x) * channels + ch_idx;
int32_t filter_index = (filter_y_idx * filter_wd + filter_x_idx) * (channels * ch_mult) + out_ch_idx;
int32_t input_val = input_data[input_index] + input_offset;
int32_t filter_val0 = filter_data[filter_index + 0];
int32_t filter_val1 = filter_data[filter_index + 1];
int32_t filter_val2 = filter_data[filter_index + 2];
int32_t filter_val3 = filter_data[filter_index + 3];
result0 += input_val * filter_val0;
result1 += input_val * filter_val1;
result2 += input_val * filter_val2;
result3 += input_val * filter_val3;
}
}
if (bias) {
result0 += bias[out_ch_idx + 0];
result1 += bias[out_ch_idx + 1];
result2 += bias[out_ch_idx + 2];
result3 += bias[out_ch_idx + 3];
}
result0 = esp_nn_multiply_by_quantized_mult_fast(result0, *out_mult++, *out_shift++);
result1 = esp_nn_multiply_by_quantized_mult_fast(result1, *out_mult++, *out_shift++);
result2 = esp_nn_multiply_by_quantized_mult_fast(result2, *out_mult++, *out_shift++);
result3 = esp_nn_multiply_by_quantized_mult_fast(result3, *out_mult++, *out_shift++);
result0 += out_offset;
result1 += out_offset;
result2 += out_offset;
result3 += out_offset;
result0 = max(result0, activation_min);
result1 = max(result1, activation_min);
result2 = max(result2, activation_min);
result3 = max(result3, activation_min);
result0 = min(result0, activation_max);
result1 = min(result1, activation_max);
result2 = min(result2, activation_max);
result3 = min(result3, activation_max);
out_data[out_idx++] = result0;
out_data[out_idx++] = result1;
out_data[out_idx++] = result2;
out_data[out_idx++] = result3;
}
for (; ch_mult_idx < ch_mult; ch_mult_idx++) {
int32_t result = 0;
const int out_ch_idx = ch_idx * ch_mult + ch_mult_idx;
for (int filter_y_idx = filter_y_start; filter_y_idx < filter_y_end; filter_y_idx++) {
const int32_t idx_y = base_y + filter_y_idx;
for (int filter_x_idx = filter_x_start; filter_x_idx < filter_x_end; filter_x_idx++) {
const int32_t idx_x = base_x + filter_x_idx;
int32_t input_index = (idx_y * input_wd + idx_x) * channels + ch_idx;
int32_t filter_index = (filter_y_idx * filter_wd + filter_x_idx) * (channels * ch_mult) + out_ch_idx;
int32_t input_val = input_data[input_index] + input_offset;
int32_t filter_val = filter_data[filter_index];
result += input_val * filter_val;
}
}
if (bias) {
result += bias[out_ch_idx];
}
result = esp_nn_multiply_by_quantized_mult_fast(result, *out_mult++, *out_shift++);
result += out_offset;
result = max(result, activation_min);
result = min(result, activation_max);
out_data[out_idx++] = result;
}
}
}
}
}

134
code/components/esp-nn/src/convolution/esp_nn_depthwise_conv_s8_esp32s3.c
View File

@@ -12,8 +12,8 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include <stdint.h>
#include <stdio.h>
#include <esp_nn_defs.h>
#include <common_functions.h>
@@ -353,59 +353,17 @@ void esp_nn_depthwise_conv_s8_ch_mult1(const int8_t *input_data,
}
}
int esp_nn_get_depthwise_conv_scratch_size_esp32s3(const data_dims_t *input_dims,
const data_dims_t *filter_dims,
const data_dims_t *output_dims,
const dw_conv_params_t *conv_params)
int esp_nn_get_depthwise_conv_scratch_size_esp32s3(const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t channels,
const uint16_t ch_mult,
const uint16_t filter_wd,
const uint16_t filter_ht)
{
const uint16_t input_wd = input_dims->width;
const uint16_t input_ht = input_dims->height;
const uint16_t channels = input_dims->channels;
const uint16_t filter_wd = filter_dims->width;
const uint16_t filter_ht = filter_dims->height;
const uint16_t ch_mult = conv_params->ch_mult;
const uint16_t out_wd = output_dims->width;
const uint16_t out_ht = output_dims->height;
const uint16_t pad_wd = conv_params->padding.width;
const uint16_t pad_ht = conv_params->padding.height;
const uint16_t stride_wd = conv_params->stride.width;
const uint16_t stride_ht = conv_params->stride.height;
int filter_size = filter_wd * filter_ht * channels * ch_mult;
int pad_width = 0, pad_height = 0;
if ((ch_mult == 1) && (channels % 8 == 0) && (filter_wd == 3) && (filter_ht == 3)) {
if (channels % 16 == 0) {
if (pad_wd || pad_ht) {
pad_width = pad_wd * 2;
pad_height = pad_ht * 2;
} else {
// check if we need to pad additionally
pad_width = (out_wd * stride_wd + filter_wd - 1) - input_wd;
pad_height = (out_ht * stride_ht + filter_ht - 1) - input_ht;
// printf("in(%d %d %d), out(%d %d), filter (%d %d) stride (%d %d), pad (%d %d)",
// input_wd, input_ht, channels, out_wd, out_ht, filter_wd, filter_ht,
// stride_wd, stride_ht, pad_wd, pad_ht);
}
if (pad_width || pad_height) {
int input_size = (input_wd + pad_width) * (input_ht + pad_height) * channels;
// printf("ask1 %d\n", filter_size + input_size + 16);
return filter_size + input_size + 16; // 16 for alignment
} else {
// printf("ask2 %d\n", filter_size + 16);
return filter_size + 16; // 16 for alignment
}
} else {
int input_size = input_wd * input_ht * channels;
// printf("ask3 %d\n", 2 * (filter_size + input_size) + 16);
return 2 * (filter_size + input_size) + 16; // 16 for alignment
}
} else if (ch_mult % 4 == 0) {
int input_size = input_wd * input_ht * channels;
// printf("ask4 %d\n", 2 * (filter_size + input_size) + 16);
return 2 * (filter_size + input_size) + 16; // 16 for alignment
}
return 32; // just few bytes
int padding_used = ((filter_wd == 3) && (filter_ht == 3)) * 2;
int input_size = (input_wd + padding_used) * (input_ht + padding_used) * channels;
return 2 * (filter_size + input_size) + 16; //16 for alignment
}
void esp_nn_set_depthwise_conv_scratch_buf_esp32s3(void *buf)
@@ -418,38 +376,29 @@ void esp_nn_set_depthwise_conv_scratch_buf_esp32s3(void *buf)
* Assumption 2: Pointers are valid
* Assumption 3: dialation width = 1
*/
void esp_nn_depthwise_conv_s8_esp32s3(const data_dims_t *input_dims,
const int8_t *input_data,
const data_dims_t *filter_dims,
void esp_nn_depthwise_conv_s8_esp32s3(const int8_t *input_data,
const uint16_t input_wd,
const uint16_t input_ht,
const uint16_t channels,
const int32_t input_offset,
const uint16_t pad_wd,
const uint16_t pad_ht,
const uint16_t stride_wd,
const uint16_t stride_ht,
const uint16_t ch_mult,
const int8_t *filter_data,
const uint16_t filter_wd,
const uint16_t filter_ht,
const int32_t *bias,
const data_dims_t *output_dims,
int8_t *out_data,
const dw_conv_params_t *conv_params,
const quant_data_t *quant_data)
const uint16_t out_wd,
const uint16_t out_ht,
const int32_t out_offset,
const int32_t *out_shift,
const int32_t *out_mult,
const int32_t activation_min,
const int32_t activation_max)
{
const uint16_t input_wd = input_dims->width;
const uint16_t input_ht = input_dims->height;
const uint16_t channels = input_dims->channels;
const int32_t input_offset = conv_params->in_offset;
const int32_t out_offset = conv_params->out_offset;
const uint16_t pad_wd = conv_params->padding.width;
const uint16_t pad_ht = conv_params->padding.height;
const uint16_t stride_wd = conv_params->stride.width;
const uint16_t stride_ht = conv_params->stride.height;
const uint16_t filter_wd = filter_dims->width;
const uint16_t filter_ht = filter_dims->height;
const uint16_t out_wd = output_dims->width;
const uint16_t out_ht = output_dims->height;
const int32_t *out_shift = quant_data->shift;
const int32_t *out_mult = quant_data->mult;
const int32_t activation_min = conv_params->activation.min;
const int32_t activation_max = conv_params->activation.max;
const uint16_t ch_mult = conv_params->ch_mult;
int filter_size = filter_wd * filter_ht * channels * ch_mult;
int align_len = 16 - (filter_size & 15);
int input_size = input_wd * input_ht * channels;
@@ -474,27 +423,18 @@ void esp_nn_depthwise_conv_s8_esp32s3(const data_dims_t *input_dims,
stride_wd, stride_ht, filter_aligned, bias,
out_data, out_wd, out_ht, out_offset, out_shift,
out_mult, activation_min, activation_max);
} else if ((channels % 16 == 0) && (pad_wd == 0) && (pad_ht == 0)) {
} else if ((pad_wd == 0) && (pad_ht == 0) &&
// because this does not handle padding offset cases yet, run just for stride (1, 1).
// end padding of input with `-input_offset` should solve this
(stride_wd == 1) && (stride_ht == 1)) {
/* process in 8 bits */
int8_t *filter_aligned = (int8_t *) scratch_buffer;
int8_t *input_padded = (int8_t *) scratch_buffer + filter_size + align_len;
// check if we need to pad additionally
int pad_right = (out_wd * stride_wd + filter_wd - 1) - input_wd;
int pad_bottom = (out_ht * stride_ht + filter_ht - 1) - input_ht;
if (pad_right || pad_bottom) { // pad right and bottom
esp_nn_aligned_s8_pad_end_with_value(input_data, input_padded, input_wd, input_ht,
channels, -input_offset, pad_right, pad_bottom);
} else {
input_padded = (int8_t *) input_data;
}
memcpy(filter_aligned, filter_data, filter_size);
esp_nn_depthwise_conv_s8_mult1_3x3_padded_esp32s3(input_padded, input_wd + pad_right,
input_ht + pad_bottom, channels, input_offset,
stride_wd, stride_ht, filter_aligned, bias,
out_data, out_wd, out_ht, out_offset, out_shift,
esp_nn_depthwise_conv_s8_mult1_3x3_padded_esp32s3(input_data, input_wd, input_ht, channels, input_offset,
stride_wd, stride_ht, filter_aligned,
bias, out_data, out_wd, out_ht, out_offset, out_shift,
out_mult, activation_min, activation_max);
} else { /* (channels % 8) == 0 */
} else { /* (channels % 8) == 0 && pad_wd == 1 && pad_ht == 1 */
esp_nn_s8_to_s16_esp32s3(filter_data, filter_data16, filter_size);
esp_nn_aligned_s8_to_s16_with_offset_esp32s3(input_data, input_data16, input_size, input_offset);
esp_nn_depthwise_conv_s16_mult1_3x3_esp32s3(input_data16, input_wd, input_ht, channels,

8
code/components/esp-nn/test_app/sdkconfig.defaults.esp32s3
View File

@@ -1,8 +0,0 @@
# Default configurations for ESP32-S3
CONFIG_ESP32S3_DEFAULT_CPU_FREQ_240=y
CONFIG_ESP32S3_SPIRAM_SUPPORT=y
CONFIG_ESP32S3_DATA_CACHE_64KB=y
CONFIG_ESP32S3_DATA_CACHE_8WAYS=y
CONFIG_ESP32S3_DATA_CACHE_LINE_64B=y

20
code/components/esp-nn/tests/src/basic_math_test.c
View File

@@ -23,9 +23,7 @@
#include "test_utils.h"
#if CONFIG_IDF_CMAKE
#if (CONFIG_SPIRAM_SUPPORT && (CONFIG_SPIRAM_USE_CAPS_ALLOC || CONFIG_SPIRAM_USE_MALLOC))
#define IDF_HEAP_CAPS 1
#endif
#if IDF_HEAP_CAPS
#include "esp_heap_caps.h"
@@ -140,11 +138,6 @@ void esp_nn_add_elementwise_s8_test()
out_c_orig = out_data_c;
out_opt_orig = out_data_opt;
#endif
if (input1_orig == NULL || input2_orig == NULL || out_c_orig == NULL ||
out_opt_orig == NULL) {
printf(ANSI_COLOR_RED"%s error allocating buffers\n"ANSI_COLOR_RESET, __FUNCTION__);
goto elementwise_add_test_cleanup;
}
for (int i = 0; i < size; ++i) {
input1[i] = rand() % 256 - 128;
@@ -201,10 +194,10 @@ elementwise_add_test_cleanup:
if (input2_orig) {
free(input2_orig);
}
if (out_c_orig) {
if (out_data_c) {
free(out_c_orig);
}
if (out_opt_orig) {
if (out_data_opt) {
free(out_opt_orig);
}
}
@@ -289,11 +282,6 @@ void esp_nn_mul_elementwise_s8_test()
out_c_orig = out_data_c;
out_opt_orig = out_data_opt;
#endif
if (input1_orig == NULL || input2_orig == NULL || out_c_orig == NULL ||
out_opt_orig == NULL) {
printf(ANSI_COLOR_RED"%s error allocating buffers\n"ANSI_COLOR_RESET, __FUNCTION__);
goto elementwise_mult_test_cleanup;
}
for (int i = 0; i < size; ++i) {
input1[i] = rand() % 256 - 128;
@@ -345,10 +333,10 @@ elementwise_mult_test_cleanup:
if (input2_orig) {
free(input2_orig);
}
if (out_c_orig) {
if (out_data_c) {
free(out_c_orig);
}
if (out_opt_orig) {
if (out_data_opt) {
free(out_opt_orig);
}
}

106
code/components/esp-nn/tests/src/convolution_test.c
View File

@@ -22,9 +22,8 @@
#include "test_utils.h"
#if CONFIG_IDF_CMAKE
#if (CONFIG_SPIRAM_SUPPORT && (CONFIG_SPIRAM_USE_CAPS_ALLOC || CONFIG_SPIRAM_USE_MALLOC))
#define IDF_HEAP_CAPS 1
#endif
#if IDF_HEAP_CAPS
#include "esp_heap_caps.h"
#endif
@@ -45,8 +44,8 @@ void esp_nn_depthwise_conv_s8_test()
uint16_t filter_ht, filter_wd, ch_mult;
uint16_t pad_wd, pad_ht, stride_wd, stride_ht;
// run for 15 iterations
for (int itr = 0; itr < 15; itr++) {
// run for 10 iterations
for (int itr = 0; itr < 10; itr++) {
/* prepare data */
switch (itr) {
case 0: // (ch_mult 1, (channels % 16) = 0), filter (3,3), pad (0,0)
@@ -145,52 +144,22 @@ void esp_nn_depthwise_conv_s8_test()
stride_wd = 2;
stride_ht = 2;
break;
case 8: // same as case 7, with large parameters
input_wd = 58;
input_ht = 58;
filter_ht = 3;
filter_wd = 3;
ch_mult = 1;
channels = 128;
pad_wd = 0;
pad_ht = 0;
stride_wd = 2;
stride_ht = 2;
break;
case 9: // (ch_mult 1, (channels % 16) = 0), filter (3,3), pad (0,0) stride (2,2)
input_wd = 6;
input_ht = 6;
filter_ht = 3;
filter_wd = 3;
ch_mult = 1;
channels = 16;
pad_wd = 0;
pad_ht = 0;
stride_wd = 2;
stride_ht = 2;
break;
default:
input_wd = 6;
input_ht = 6;
input_wd = 4;
input_ht = 4;
filter_ht = 3;
filter_wd = 3;
ch_mult = 1;
channels = 16;
stride_wd = rand() % 2 + 1;
stride_ht = stride_wd;
pad_wd = stride_wd == 1 ? 0 : rand() % 2;
pad_ht = pad_wd;
printf("stride(%d), pad (%d)\t", stride_wd, pad_wd);
ch_mult = 4;
channels = 4;
pad_wd = 1;
pad_ht = 1;
stride_wd = 1;
stride_ht = 1;
break;
}
uint16_t out_wd = (input_wd - filter_wd + 1) / stride_wd;
uint16_t out_ht = (input_ht - filter_ht + 1) / stride_ht;
if (itr == 9) {
// expect the function to handle this gracefully
out_wd += 1;
out_ht += 1;
}
int in_size = input_wd * input_ht * channels;
int out_size = out_wd * out_ht * channels * ch_mult;
int filter_size = filter_wd * filter_ht * channels * ch_mult + 4;
@@ -241,16 +210,9 @@ void esp_nn_depthwise_conv_s8_test()
out_mult[i] = 0x7eb0e200 + rand() % 50;
}
data_dims_t input_dims = {.width = input_wd, .height = input_ht, .channels = channels, 1};
data_dims_t output_dims = {.width = out_wd, .height = out_ht, .channels = channels * ch_mult, 1};
data_dims_t filter_dims = {.width = filter_wd, .height = filter_ht, 0, 0};
dw_conv_params_t conv_params = {.in_offset = input_offset, .out_offset = out_offset, .ch_mult = ch_mult,
.stride = {stride_wd, stride_ht}, .padding = {pad_wd, pad_ht},
.dilation = {0, 0}, .activation = {activation_min, activation_max}};
quant_data_t quant_data = {.shift = out_shift, .mult = out_mult};
int scratch_buf_size = esp_nn_get_depthwise_conv_scratch_size(&input_dims, &filter_dims,
&output_dims, &conv_params);
int scratch_buf_size = esp_nn_get_depthwise_conv_scratch_size(input_wd, input_ht,
channels, ch_mult,
filter_wd, filter_ht);
if (scratch_buf_size > 0) {
#if IDF_HEAP_CAPS
scratch_buf = heap_caps_malloc(scratch_buf_size + 32, MALLOC_CAP_SPIRAM | MALLOC_CAP_8BIT);
@@ -272,8 +234,11 @@ void esp_nn_depthwise_conv_s8_test()
}
/* C function */
esp_nn_depthwise_conv_s8_ansi(&input_dims, input, &filter_dims, filter_data + 4,
bias + 1, &output_dims, out_data_c, &conv_params, &quant_data);
esp_nn_depthwise_conv_s8_ansi(input, input_wd, input_ht, channels, input_offset,
pad_wd, pad_ht, stride_wd, stride_ht, ch_mult,
filter_data + 4, filter_wd, filter_ht,
bias + 1, out_data_c, out_wd, out_ht, out_offset, out_shift,
out_mult, activation_min, activation_max);
if (itr == 0) {
profile_c_end();
@@ -281,8 +246,11 @@ void esp_nn_depthwise_conv_s8_test()
}
/* Optimized function */
esp_nn_depthwise_conv_s8(&input_dims, input, &filter_dims, filter_data + 4,
bias + 1, &output_dims, out_data_opt, &conv_params, &quant_data);
esp_nn_depthwise_conv_s8(input, input_wd, input_ht, channels, input_offset,
pad_wd, pad_ht, stride_wd, stride_ht, ch_mult,
filter_data + 4, filter_wd, filter_ht,
bias + 1, out_data_opt, out_wd, out_ht, out_offset, out_shift,
out_mult, activation_min, activation_max);
if (itr == 0) {
/* disable profiler */
@@ -511,16 +479,8 @@ void esp_nn_conv_s8_test()
out_mult[i] = 0x7f67f4f8 + rand() % 50;
}
data_dims_t input_dims = {.width = in_wd, .height = in_ht, .channels = in_channels, 1};
data_dims_t output_dims = {.width = out_wd, .height = out_ht, .channels = out_channels, 1};
data_dims_t filter_dims = {.width = filter_wd, .height = filter_ht, 0, 0};
conv_params_t conv_params = {.in_offset = input_offset, .out_offset = out_offset,
.stride = {stride_wd, stride_ht}, .padding = {pad_wd, pad_ht},
.dilation = {0, 0}, .activation = {activation_min, activation_max}};
quant_data_t quant_data = {.shift = out_shift, .mult = out_mult};
int scratch_buf_size = esp_nn_get_conv_scratch_size(&input_dims, &filter_dims,
&output_dims, &conv_params);
int scratch_buf_size = esp_nn_get_conv_scratch_size(in_wd, in_ht, in_channels,
out_channels, filter_wd, filter_ht);
if (scratch_buf_size > 0) {
#if IDF_HEAP_CAPS
void *scratch_buf = heap_caps_malloc(scratch_buf_size + 32, MALLOC_CAP_SPIRAM | MALLOC_CAP_8BIT);
@@ -542,8 +502,11 @@ void esp_nn_conv_s8_test()
}
/* C function */
esp_nn_conv_s8_ansi(&input_dims, input, &filter_dims, filter_data + 2,
bias, &output_dims, out_data_c, &conv_params, &quant_data);
esp_nn_conv_s8_ansi(input, in_wd, in_ht, in_channels, input_offset,
pad_wd, pad_ht, stride_wd, stride_ht,
filter_data + 2, filter_wd, filter_ht, bias,
out_data_c, out_wd, out_ht, out_channels, out_offset, out_shift,
out_mult, activation_min, activation_max);
if (itr == 0) {
profile_c_end();
@@ -551,8 +514,11 @@ void esp_nn_conv_s8_test()
}
/* Optimized function */
esp_nn_conv_s8(&input_dims, input, &filter_dims, filter_data + 2,
bias, &output_dims, out_data_opt, &conv_params, &quant_data);
esp_nn_conv_s8(input, in_wd, in_ht, in_channels, input_offset,
pad_wd, pad_ht, stride_wd, stride_ht,
filter_data + 2, filter_wd, filter_ht, bias,
out_data_opt, out_wd, out_ht, out_channels, out_offset, out_shift,
out_mult, activation_min, activation_max);
if (itr == 0) {
/* disable profiler */