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IDF release/v3.3 (#3672)

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ESP-IDF release/v3.3: 66d3783c8
esp-face: 420fc7e
esp32-camera: 0107093
This commit is contained in:
Me No Dev
2020-11-03 21:20:00 +02:00
committed by GitHub
parent 6e5be78838
commit 22b427df0f
256 changed files with 6074 additions and 1011 deletions
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211
tools/sdk/include/esp-face/dl_lib_matrix3d.h
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@ -7,10 +7,14 @@
#include <math.h>
#include <assert.h>
#if CONFIG_SPIRAM_SUPPORT
#if CONFIG_SPIRAM_SUPPORT || CONFIG_ESP32_SPIRAM_SUPPORT
#include "freertos/FreeRTOS.h"
#define DL_SPIRAM_SUPPORT 1
#else
#define DL_SPIRAM_SUPPORT 0
#endif
#ifndef max
#define max(x, y) (((x) < (y)) ? (y) : (x))
#endif
@ -30,17 +34,17 @@ typedef enum
typedef enum
{
PADDING_VALID = 0,
PADDING_SAME = 1,
PADDING_SAME_DONT_FREE_INPUT = 2,
PADDING_SAME_MXNET = 3,
PADDING_VALID = 0, /*!< Valid padding */
PADDING_SAME = 1, /*!< Same padding, from right to left, free input */
PADDING_SAME_DONT_FREE_INPUT = 2, /*!< Same padding, from right to left, do not free input */
PADDING_SAME_MXNET = 3, /*!< Same padding, from left to right */
} dl_padding_type;
typedef enum
{
DL_POOLING_MAX = 0,
DL_POOLING_AVG = 1,
} dl_pooling_type;
DL_POOLING_MAX = 0, /*!< Max pooling */
DL_POOLING_AVG = 1, /*!< Average pooling */
} dl_pooling_type;
/*
* Matrix for 3d
* @Warning: the sequence of variables is fixed, cannot be modified, otherwise there will be errors in esp_dsp_dot_float
@ -65,11 +69,17 @@ typedef struct
uc_t *item; /*!< Data */
} dl_matrix3du_t;
typedef enum
{
UPSAMPLE_NEAREST_NEIGHBOR = 0, /*!< Use nearest neighbor interpolation as the upsample method*/
UPSAMPLE_BILINEAR = 1, /*!< Use nearest bilinear interpolation as the upsample method*/
} dl_upsample_type;
typedef struct
{
int stride_x;
int stride_y;
dl_padding_type padding;
int stride_x; /*!< Strides of width */
int stride_y; /*!< Strides of height */
dl_padding_type padding; /*!< Padding type */
} dl_matrix3d_mobilenet_config_t;
/*
@ -80,20 +90,20 @@ typedef struct
* @param align Align of memory. If not required, set 0.
* @return Pointer of allocated memory. Null for failed.
*/
static inline void *dl_lib_calloc(int cnt, int size, int align)
static void *dl_lib_calloc(int cnt, int size, int align)
{
int total_size = cnt * size + align + sizeof(void *);
void *res = malloc(total_size);
if (NULL == res)
{
#if CONFIG_SPIRAM_SUPPORT
#if DL_SPIRAM_SUPPORT
res = heap_caps_malloc(total_size, MALLOC_CAP_8BIT | MALLOC_CAP_SPIRAM);
}
if (NULL == res)
{
printf("Item psram alloc failed. Size: %d x %d\n", cnt, size);
#else
printf("Item alloc failed. Size: %d x %d\n", cnt, size);
printf("Item alloc failed. Size: %d x %d, SPIRAM_FLAG: %d\n", cnt, size, DL_SPIRAM_SUPPORT);
#endif
return NULL;
}
@ -109,6 +119,10 @@ static inline void *dl_lib_calloc(int cnt, int size, int align)
return (void *)aligned;
}
/**
* @brief Free the memory space allocated by 'dl_lib_calloc'
*
*/
static inline void dl_lib_free(void *d)
{
if (NULL == d)
@ -286,15 +300,15 @@ void dl_matrix3d_sliced_transform_nchw(dl_matrix3d_t *out,
/**
* @brief Do a general CNN layer pass, dimension is (number, width, height, channel)
*
* @param in Input matrix3d
* @param filter Weights of the neurons
* @param bias Bias for the CNN layer
* @param stride_x The step length of the convolution window in x(width) direction
* @param stride_y The step length of the convolution window in y(height) direction
* @param padding One of VALID or SAME
* @param mode Do convolution using C implement or xtensa implement, 0 or 1, with respect
* If ESP_PLATFORM is not defined, this value is not used. Default is 0
* @return The result of CNN layer
* @param in Input matrix3d
* @param filter Weights of the neurons
* @param bias Bias for the CNN layer
* @param stride_x The step length of the convolution window in x(width) direction
* @param stride_y The step length of the convolution window in y(height) direction
* @param padding One of VALID or SAME
* @param mode Do convolution using C implement or xtensa implement, 0 or 1, with respect
* If ESP_PLATFORM is not defined, this value is not used. Default is 0
* @return dl_matrix3d_t* The result of CNN layer
*/
dl_matrix3d_t *dl_matrix3d_conv(dl_matrix3d_t *in,
dl_matrix3d_t *filter,
@ -316,14 +330,14 @@ dl_matrix3d_t *dl_matrix3d_global_pool(dl_matrix3d_t *in);
/**
* @brief Calculate pooling layer of a feature map
*
* @param in Input matrix, size (1, w, h, c)
* @param f_w Window width
* @param f_h Window height
* @param stride_x Stride in horizontal direction
* @param stride_y Stride in vertical direction
* @param padding Padding type: PADDING_VALID and PADDING_SAME
* @param pooling_type Pooling type: DL_POOLING_MAX and POOLING_AVG
* @return Resulting matrix, size (1, w', h', c)
* @param in Input matrix, size (1, w, h, c)
* @param f_w Window width
* @param f_h Window height
* @param stride_x Stride in horizontal direction
* @param stride_y Stride in vertical direction
* @param padding Padding type: PADDING_VALID and PADDING_SAME
* @param pooling_type Pooling type: DL_POOLING_MAX and POOLING_AVG
* @return dl_matrix3d_t* Resulting matrix, size (1, w', h', c)
*/
dl_matrix3d_t *dl_matrix3d_pooling(dl_matrix3d_t *in,
int f_w,
@ -346,20 +360,20 @@ void dl_matrix3d_batch_normalize(dl_matrix3d_t *m,
/**
* @brief Add a pair of matrix3d item-by-item: res=in_1+in_2
*
* @param in_1 First Floating point input matrix3d
* @param in_2 Second Floating point input matrix3d
* @param in_1 First Floating point input matrix3d
* @param in_2 Second Floating point input matrix3d
*
* @return Added data
* @return dl_matrix3d_t* Added data
*/
dl_matrix3d_t *dl_matrix3d_add(dl_matrix3d_t *in_1, dl_matrix3d_t *in_2);
/**
* @brief Concatenate the channels of two matrix3ds into a new matrix3d
*
* @param in_1 First Floating point input matrix3d
* @param in_2 Second Floating point input matrix3d
* @param in_1 First Floating point input matrix3d
* @param in_2 Second Floating point input matrix3d
*
* @return A newly allocated matrix3d with as avlues in_1|in_2
* @return dl_matrix3d_t* A newly allocated matrix3d with as avlues in_1|in_2
*/
dl_matrix3d_t *dl_matrix3d_concat(dl_matrix3d_t *in_1, dl_matrix3d_t *in_2);
@ -477,8 +491,21 @@ dl_matrix3d_t *dl_matrix3d_mobilefaceblock_split(dl_matrix3d_t *in,
int mode,
int shortcut);
/**
* @brief Initialize the matrix3d feature map to bias
*
* @param out The matrix3d feature map needs to be initialized
* @param bias The bias of a convlotion operation
*/
void dl_matrix3d_init_bias(dl_matrix3d_t *out, dl_matrix3d_t *bias);
/**
* @brief Do a elementwise multiplication of two matrix3ds
*
* @param out Preallocated matrix3d, size (n, w, h, c)
* @param in1 Input matrix 1, size (n, w, h, c)
* @param in2 Input matrix 2, size (n, w, h, c)
*/
void dl_matrix3d_multiply(dl_matrix3d_t *out, dl_matrix3d_t *in1, dl_matrix3d_t *in2);
//
@ -519,19 +546,49 @@ void dl_matrix3d_leaky_relu(dl_matrix3d_t *m, fptp_t alpha);
//
// Conv 1x1
//
/**
* @brief Do 1x1 convolution with a matrix3d
*
* @param out Preallocated matrix3d, size (1, w, h, n)
* @param in Input matrix, size (1, w, h, c)
* @param filter 1x1 filter, size (n, 1, 1, c)
*/
void dl_matrix3dff_conv_1x1(dl_matrix3d_t *out,
dl_matrix3d_t *in,
dl_matrix3d_t *filter);
/**
* @brief Do 1x1 convolution with a matrix3d, with bias adding
*
* @param out Preallocated matrix3d, size (1, w, h, n)
* @param in Input matrix, size (1, w, h, c)
* @param filter 1x1 filter, size (n, 1, 1, c)
* @param bias Bias, size (1, 1, 1, n)
*/
void dl_matrix3dff_conv_1x1_with_bias(dl_matrix3d_t *out,
dl_matrix3d_t *in,
dl_matrix3d_t *filter,
dl_matrix3d_t *bias);
/**
* @brief Do 1x1 convolution with an 8-bit fixed point matrix
*
* @param out Preallocated matrix3d, size (1, w, h, n)
* @param in Input matrix, size (1, w, h, c)
* @param filter 1x1 filter, size (n, 1, 1, c)
*/
void dl_matrix3duf_conv_1x1(dl_matrix3d_t *out,
dl_matrix3du_t *in,
dl_matrix3d_t *filter);
/**
* @brief Do 1x1 convolution with an 8-bit fixed point matrix, with bias adding
*
* @param out Preallocated matrix3d, size (1, w, h, n)
* @param in Input matrix, size (1, w, h, c)
* @param filter 1x1 filter, size (n, 1, 1, c)
* @param bias Bias, size (1, 1, 1, n)
*/
void dl_matrix3duf_conv_1x1_with_bias(dl_matrix3d_t *out,
dl_matrix3du_t *in,
dl_matrix3d_t *filter,
@ -540,12 +597,33 @@ void dl_matrix3duf_conv_1x1_with_bias(dl_matrix3d_t *out,
//
// Conv 3x3
//
/**
* @brief Do 3x3 convolution with a matrix3d, without padding
*
* @param out Preallocated matrix3d, size (1, w, h, n)
* @param in Input matrix, size (1, w, h, c)
* @param f 3x3 filter, size (n, 3, 3, c)
* @param step_x Stride of width
* @param step_y Stride of height
*/
void dl_matrix3dff_conv_3x3_op(dl_matrix3d_t *out,
dl_matrix3d_t *in,
dl_matrix3d_t *f,
int step_x,
int step_y);
/**
* @brief Do 3x3 convolution with a matrix3d, with bias adding
*
* @param input Input matrix, size (1, w, h, c)
* @param filter 3x3 filter, size (n, 3, 3, c)
* @param bias Bias, size (1, 1, 1, n)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type
* @return dl_matrix3d_t* Resulting matrix3d
*/
dl_matrix3d_t *dl_matrix3dff_conv_3x3(dl_matrix3d_t *in,
dl_matrix3d_t *filter,
dl_matrix3d_t *bias,
@ -557,6 +635,17 @@ dl_matrix3d_t *dl_matrix3dff_conv_3x3(dl_matrix3d_t *in,
// Conv Common
//
/**
* @brief Do a general convolution layer pass with an 8-bit fixed point matrix, size is (number, width, height, channel)
*
* @param in Input image
* @param filter Weights of the neurons
* @param bias Bias for the CNN layer
* @param stride_x The step length of the convolution window in x(width) direction
* @param stride_y The step length of the convolution window in y(height) direction
* @param padding Padding type
* @return dl_matrix3d_t* Resulting matrix3d
*/
dl_matrix3d_t *dl_matrix3duf_conv_common(dl_matrix3du_t *in,
dl_matrix3d_t *filter,
dl_matrix3d_t *bias,
@ -564,6 +653,17 @@ dl_matrix3d_t *dl_matrix3duf_conv_common(dl_matrix3du_t *in,
int stride_y,
dl_padding_type padding);
/**
* @brief Do a general convolution layer pass, size is (number, width, height, channel)
*
* @param in Input image
* @param filter Weights of the neurons
* @param bias Bias for the CNN layer
* @param stride_x The step length of the convolution window in x(width) direction
* @param stride_y The step length of the convolution window in y(height) direction
* @param padding Padding type
* @return dl_matrix3d_t* Resulting matrix3d
*/
dl_matrix3d_t *dl_matrix3dff_conv_common(dl_matrix3d_t *in,
dl_matrix3d_t *filter,
dl_matrix3d_t *bias,
@ -575,18 +675,47 @@ dl_matrix3d_t *dl_matrix3dff_conv_common(dl_matrix3d_t *in,
// Depthwise 3x3
//
/**
* @brief Do 3x3 depthwise convolution with a float matrix3d
*
* @param in Input matrix, size (1, w, h, c)
* @param filter 3x3 filter, size (1, 3, 3, c)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type, 0: valid, 1: same
* @return dl_matrix3d_t* Resulting float matrix3d
*/
dl_matrix3d_t *dl_matrix3dff_depthwise_conv_3x3(dl_matrix3d_t *in,
dl_matrix3d_t *filter,
int stride_x,
int stride_y,
int padding);
/**
* @brief Do 3x3 depthwise convolution with a 8-bit fixed point matrix
*
* @param in Input matrix, size (1, w, h, c)
* @param filter 3x3 filter, size (1, 3, 3, c)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type, 0: valid, 1: same
* @return dl_matrix3d_t* Resulting float matrix3d
*/
dl_matrix3d_t *dl_matrix3duf_depthwise_conv_3x3(dl_matrix3du_t *in,
dl_matrix3d_t *filter,
int stride_x,
int stride_y,
int padding);
/**
* @brief Do 3x3 depthwise convolution with a float matrix3d, without padding
*
* @param out Preallocated matrix3d, size (1, w, h, n)
* @param in Input matrix, size (1, w, h, c)
* @param f 3x3 filter, size (1, 3, 3, c)
* @param step_x Stride of width
* @param step_y Stride of height
*/
void dl_matrix3dff_depthwise_conv_3x3_op(dl_matrix3d_t *out,
dl_matrix3d_t *in,
dl_matrix3d_t *f,
@ -630,6 +759,14 @@ void dl_matrix3dff_fc(dl_matrix3d_t *out,
dl_matrix3d_t *in,
dl_matrix3d_t *filter);
/**
* @brief Do fully connected layer forward, with bias adding
*
* @param out Preallocated resulting matrix, size (1, 1, 1, h)
* @param in Input matrix, size (1, 1, 1, w)
* @param filter Filter matrix, size (1, w, h, 1)
* @param bias Bias matrix, size (1, 1, 1, h)
*/
void dl_matrix3dff_fc_with_bias(dl_matrix3d_t *out,
dl_matrix3d_t *in,
dl_matrix3d_t *filter,