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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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557
tools/sdk/include/esp-face/dl_lib_matrix3dq.h
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@ -56,6 +56,20 @@ typedef struct
int compress_exponent; /*!< Exponent of compress filter */
} dl_matrix3dq_mobilenet_config_t;
typedef struct
{
int stride_x; /*!< Strides of width */
int stride_y; /*!< Strides of height */
dl_padding_type padding; /*!< Padding type */
dl_conv_mode mode; /*!< Implementation mode */
int dw1_exponent; /*!< Exponent of dw1 filter */
int pw1_exponent; /*!< Exponent of pw1 filter */
int dw2_exponent; /*!< Exponent of dw2 filter */
int pw2_exponent; /*!< Exponent of pw2 filter */
int shortcut; /*!< Shortcut connection flag */
int save_input; /*!< Input save flag */
} dl_matrix3dq_blazeblock_config_t;
//
// Utility
//
@ -163,6 +177,13 @@ dl_matrix3dq_t *dl_matrixq_from_matrix3d_qmf(dl_matrix3d_t *m, int exponent);
*/
dl_matrix3dq_t *dl_matrixq_from_matrix3d(dl_matrix3d_t *m);
/**
* @brief Truncate the overflowed 16bit number
*
* @param value Input value
* @param location Location tag
* @return qtp_t Truncated value
*/
qtp_t dl_matrix3dq_quant_range_exceeded_checking(int64_t value, char *location);
/**
@ -186,13 +207,23 @@ void dl_matrix3dq_batch_normalize(dl_matrix3dq_t *m, dl_matrix3dq_t *scale, dl_m
/**
* @brief Add two quantized matrix with a pre-defined exponent
*
* @param in_1 Adder 1
* @param in_2 Adder 2
* @param exponent Exponent for resulting matrix
* @return Result of accumulation of two matrix
* @param in_1 Adder 1
* @param in_2 Adder 2
* @param exponent Exponent for resulting matrix
* @return dl_matrix3dq_t* Result of accumulation of two matrix
*/
dl_matrix3dq_t *dl_matrix3dq_add(dl_matrix3dq_t *in_1, dl_matrix3dq_t *in_2, int exponent);
/**
* @brief Add two quantized matrix with different channels
*
* @param in_1 Adder 1
* @param in_2 Adder 2
* @param exponent Exponent for resulting matrix
* @return dl_matrix3dq_t* Result of accumulation of two matrix
*/
dl_matrix3dq_t *dl_matrix3dq_add_channel_diff(dl_matrix3dq_t *in_1, dl_matrix3dq_t *in_2, int exponent);
//
// Activation
//
@ -287,6 +318,7 @@ dl_matrix3dq_t *dl_matrix3dq_concat_8(dl_matrix3dq_t *in_1,
* @param in Input matrix, size (1, w, h, c)
* @param filter 1x1 filter, size (n, 1, 1, c)
* @param mode Implementation mode
* @param name Layer name to debug
*/
void dl_matrix3dqq_conv_1x1(dl_matrix3dq_t *out,
dl_matrix3dq_t *in,
@ -301,6 +333,7 @@ void dl_matrix3dqq_conv_1x1(dl_matrix3dq_t *out,
* @param in Input matrix, size (1, w, h, c)
* @param filter 1x1 filter, size (n, 1, 1, c)
* @param mode Implementation mode
* @param name Layer name to debug
*/
void dl_matrix3dqq_conv_1x1_with_relu(dl_matrix3dq_t *out,
dl_matrix3dq_t *in,
@ -326,13 +359,14 @@ void dl_matrix3dqq_conv_1x1_with_bias(dl_matrix3dq_t *out,
char *name);
/**
* @brief Do 1x1 convolution with a quantized matrix, with bias adding and relu activation
* @brief Do 1x1 convolution with a quantized matrix, with bias adding
*
* @param out Preallocated quantized matrix, 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)
* @param mode Implementation mode
* @param name Layer name to debug
*/
void dl_matrix3dqq_conv_1x1_with_bias_relu(dl_matrix3dq_t *out,
dl_matrix3dq_t *in,
@ -342,14 +376,14 @@ void dl_matrix3dqq_conv_1x1_with_bias_relu(dl_matrix3dq_t *out,
char *name);
/**
* @brief
* @brief Do 1x1 convolution with a quantized matrix, with prelu activation
*
* @param out
* @param in
* @param filter
* @param prelu
* @param mode
* @param name
* @param out Preallocated quantized matrix, size (1, w, h, n)
* @param in Input matrix, size (1, w, h, c)
* @param filter 1x1 filter, size (n, 1, 1, c)
* @param prelu prelu params, size (1, 1, 1, n)
* @param mode Implementation mode
* @param name Layer name to debug
*/
void dl_matrix3dqq_conv_1x1_with_prelu(dl_matrix3dq_t *out,
dl_matrix3dq_t *in,
@ -365,6 +399,7 @@ void dl_matrix3dqq_conv_1x1_with_prelu(dl_matrix3dq_t *out,
* @param in Input matrix, size (1, w, h, c)
* @param filter 1x1 filter, size (n, 1, 1, c)
* @param mode Implementation mode
* @param name Layer name to debug
*/
void dl_matrix3duq_conv_1x1(dl_matrix3dq_t *out,
dl_matrix3du_t *in,
@ -380,6 +415,7 @@ void dl_matrix3duq_conv_1x1(dl_matrix3dq_t *out,
* @param filter 1x1 filter, size (n, 1, 1, c)
* @param bias Bias, size (1, 1, 1, n)
* @param mode Implementation mode
* @param name Layer name to debug
*/
void dl_matrix3duq_conv_1x1_with_bias(dl_matrix3dq_t *out,
dl_matrix3du_t *in,
@ -401,7 +437,7 @@ void dl_matrix3duq_conv_1x1_with_bias(dl_matrix3dq_t *out,
* @param stride_y Stride of height
* @param padding Padding type, 0: valid, 1: same
* @param exponent Exponent for resulting matrix
* @param name
* @param name Layer name to debug
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_conv_3x3(dl_matrix3dq_t *input,
@ -420,9 +456,9 @@ dl_matrix3dq_t *dl_matrix3dqq_conv_3x3(dl_matrix3dq_t *input,
* @param bias Bias, size (1, 1, 1, n)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding
* @param padding Padding type
* @param exponent Exponent for resulting matrix
* @param name
* @param name Layer name to debug
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_conv_3x3_with_bias(dl_matrix3dq_t *input,
@ -442,9 +478,9 @@ dl_matrix3dq_t *dl_matrix3dqq_conv_3x3_with_bias(dl_matrix3dq_t *input,
* @param bias Bias, size (1, 1, 1, n)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding
* @param padding Padding type
* @param exponent Exponent for resulting matrix
* @param name
* @param name Layer name to debug
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_conv_3x3_with_bias_relu(dl_matrix3dq_t *input,
@ -457,17 +493,17 @@ dl_matrix3dq_t *dl_matrix3dqq_conv_3x3_with_bias_relu(dl_matrix3dq_t *input,
char *name);
/**
* @brief
* @brief Do 3x3 convolution with an 8-bit fixed point matrix, with bias adding
*
* @param input
* @param filter
* @param bias
* @param stride_x
* @param stride_y
* @param padding
* @param exponent
* @param name
* @return dl_matrix3dq_t*
* @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
* @param exponent Exponent for resulting matrix
* @param name Layer name to debug
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3duq_conv_3x3_with_bias(dl_matrix3du_t *input,
dl_matrix3dq_t *filter,
@ -479,18 +515,18 @@ dl_matrix3dq_t *dl_matrix3duq_conv_3x3_with_bias(dl_matrix3du_t *input,
char *name);
/**
* @brief
* @brief Do 3x3 convolution with an 8-bit fixed point matrix, with bias adding, prelu activation
*
* @param input
* @param filter
* @param bias
* @param prelu
* @param stride_x
* @param stride_y
* @param padding
* @param exponent
* @param name
* @return dl_matrix3dq_t*
* @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 prelu prelu params, size (1, 1, 1, n)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type
* @param exponent Exponent for resulting matrix
* @param name Layer name to debug
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3duq_conv_3x3_with_bias_prelu(dl_matrix3du_t *input,
dl_matrix3dq_t *filter,
@ -503,7 +539,20 @@ dl_matrix3dq_t *dl_matrix3duq_conv_3x3_with_bias_prelu(dl_matrix3du_t *input,
char *name);
/**
* @brief Do 3x3 convolution with a quantized matrix, with bias adding, prelu activation
*
* @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 prelu prelu params, size (1, 1, 1, n)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type
* @param exponent Exponent for resulting matrix
* @param name Layer name to debug
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_conv_3x3_with_bias_prelu(dl_matrix3dq_t *input,
dl_matrix3dq_t *filter,
dl_matrix3dq_t *bias,
@ -573,6 +622,7 @@ dl_matrix3dq_t *dl_matrix3duq_conv_common(dl_matrix3du_t *in,
* @param stride_y Stride of height
* @param padding Padding type, 0: valid, 1: same
* @param exponent Exponent for resulting matrix
* @param name Layer name to debug
* @return Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3duq_depthwise_conv_3x3(dl_matrix3du_t *in,
@ -591,7 +641,9 @@ dl_matrix3dq_t *dl_matrix3duq_depthwise_conv_3x3(dl_matrix3du_t *in,
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type, 0: valid, 1: same
* @param relu ReLU, 0: don't, 1: do
* @param exponent Exponent for resulting matrix
* @param name Layer name to debug
* @return Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_3x3(dl_matrix3dq_t *in,
@ -599,6 +651,7 @@ dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_3x3(dl_matrix3dq_t *in,
int stride_x,
int stride_y,
dl_padding_type padding,
int relu,
int exponent,
char *name);
@ -624,13 +677,14 @@ dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_3x3_3(dl_matrix3dq_t *in,
* @brief Do 3x3 depthwise convolution with a quantized matrix, with bias adding
*
* @param in Input matrix, size (1, w, h, c)
* @param filter 3x3 filter, size (1, 3, 3, c)
* @param f 3x3 filter, size (1, 3, 3, c)
* @param bias Bias, size (1, 1, 1, c)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type, 0: valid, 1: same
* @param exponent Exponent for resulting matrix
* @param relu Whether to use relu activation
* @param name Layer name to debug
* @return Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_3x3_with_bias(dl_matrix3dq_t *in,
@ -647,11 +701,12 @@ dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_3x3_with_bias(dl_matrix3dq_t *in,
* @brief Do 3x3 depthwise convolution with a quantized matrix, with bias adding and stride 1
*
* @param in Input matrix, size (1, w, h, c)
* @param filter 3x3 filter, size (1, 3, 3, c)
* @param bias Bias, size (1, 1, 1, n)
* @param f 3x3 filter, size (1, 3, 3, c)
* @param bias Bias, size (1, 1, 1, c)
* @param padding Padding type, 0: valid, 1: same
* @param exponent Exponent for resulting matrix
* @param relu Whether to use relu activation
* @param name Layer name to debug
* @return Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_3x3s1_with_bias(dl_matrix3dq_t *in,
@ -662,6 +717,19 @@ dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_3x3s1_with_bias(dl_matrix3dq_t *in,
int relu,
char *name);
/**
* @brief Do 3x3 depthwise convolution with a quantized matrix, with prelu activation
*
* @param in Input matrix, size (1, w, h, c)
* @param filter 3x3 filter, size (1, 3, 3, c)
* @param prelu prelu params, size (1, 1, 1, c)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type
* @param exponent Exponent for resulting matrix
* @param name Layer name to debug
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_3x3_with_prelu(dl_matrix3dq_t *in,
dl_matrix3dq_t *filter,
dl_matrix3dq_t *prelu,
@ -671,6 +739,20 @@ dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_3x3_with_prelu(dl_matrix3dq_t *in,
int exponent,
char *name);
/**
* @brief Do 3x3 depthwise convolution with a quantized matrix, with bias adding and prelu activation
*
* @param in Input matrix, size (1, w, h, c)
* @param f 3x3 filter, size (1, 3, 3, c)
* @param bias Bias, size (1, 1, 1, c)
* @param prelu prelu params, size (1, 1, 1, c)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type
* @param exponent Exponent for resulting matrix
* @param name Layer name to debug
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_3x3_with_bias_prelu(dl_matrix3dq_t *in,
dl_matrix3dq_t *f,
dl_matrix3dq_t *bias,
@ -681,16 +763,226 @@ dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_3x3_with_bias_prelu(dl_matrix3dq_t
int exponent,
char *name);
/**
* @brief Do global depthwise convolution with a quantized matrix, with bias adding
*
* @param in Input matrix, size (1, w, h, c)
* @param filter filter, size (1, w, h, c)
* @param bias Bias, size (1, 1, 1, c)
* @param exponent Exponent for resulting matrix
* @param name Layer name to debug
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_global_depthwise_conv_with_bias(dl_matrix3dq_t *in,
dl_matrix3dq_t *filter,
dl_matrix3dq_t *bias,
int exponent,
char *name);
//
// Depthwise 2x2
//
/**
* @brief Do 2x2 depthwise convolution with a quantized matrix
*
* @param in Input matrix, size (1, w, h, c)
* @param filter 2x2 filter, size (1, 2, 2, c)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type, 0: valid, 1: same
* @param exponent Exponent for resulting matrix
* @param name Layer name to debug
* @return Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_2x2(dl_matrix3dq_t *in,
dl_matrix3dq_t *filter,
int stride_x,
int stride_y,
dl_padding_type padding,
int exponent,
char *name);
/**
* @brief Do 2x2 depthwise convolution with a quantized matrix, with bias adding
*
* @param in Input matrix, size (1, w, h, c)
* @param f 2x2 filter, size (1, 2, 2, c)
* @param bias Bias, size (1, 1, 1, c)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type, 0: valid, 1: same
* @param exponent Exponent for resulting matrix
* @param relu Whether to use relu activation
* @param name Layer name to debug
* @return Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_2x2_with_bias(dl_matrix3dq_t *in,
dl_matrix3dq_t *f,
dl_matrix3dq_t *bias,
int stride_x,
int stride_y,
dl_padding_type padding,
int exponent,
int relu,
char *name);
/**
* @brief Do 2x2 depthwise convolution with a quantized matrix, with prelu activation
*
* @param in Input matrix, size (1, w, h, c)
* @param filter 2x2 filter, size (1, 2, 2, c)
* @param prelu prelu params, size (1, 1, 1, c)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type
* @param exponent Exponent for resulting matrix
* @param name Layer name to debug
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_2x2_with_prelu(dl_matrix3dq_t *in,
dl_matrix3dq_t *filter,
dl_matrix3dq_t *prelu,
int stride_x,
int stride_y,
dl_padding_type padding,
int exponent,
char *name);
/**
* @brief Do 2x2 depthwise convolution with a quantized matrix, with bias adding and prelu activation
*
* @param in Input matrix, size (1, w, h, c)
* @param f 2x2 filter, size (1, 2, 2, c)
* @param bias Bias, size (1, 1, 1, c)
* @param prelu prelu params, size (1, 1, 1, c)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type
* @param exponent Exponent for resulting matrix
* @param name Layer name to debug
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_2x2_with_bias_prelu(dl_matrix3dq_t *in,
dl_matrix3dq_t *f,
dl_matrix3dq_t *bias,
dl_matrix3dq_t *prelu,
int stride_x,
int stride_y,
dl_padding_type padding,
int exponent,
char *name);
//
// Depthwise 5x5
//
/**
* @brief Do 5x5 depthwise convolution with a quantized matrix
*
* @param in Input matrix, size (1, w, h, c)
* @param filter 5x5 filter, size (1, 5, 5, c)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type, 0: valid, 1: same
* @param exponent Exponent for resulting matrix
* @param name Layer name to debug
* @return Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_5x5(dl_matrix3dq_t *in,
dl_matrix3dq_t *filter,
int stride_x,
int stride_y,
dl_padding_type padding,
int exponent,
char *name);
/**
* @brief Do 5x5 depthwise convolution with a quantized matrix, with bias adding
*
* @param in Input matrix, size (1, w, h, c)
* @param f 5x5 filter, size (1, 5, 5, c)
* @param bias Bias, size (1, 1, 1, c)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type, 0: valid, 1: same
* @param exponent Exponent for resulting matrix
* @param relu Whether to use relu activation
* @param name Layer name to debug
* @return Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_5x5_with_bias(dl_matrix3dq_t *in,
dl_matrix3dq_t *f,
dl_matrix3dq_t *bias,
int stride_x,
int stride_y,
dl_padding_type padding,
int exponent,
int relu,
char *name);
/**
* @brief Do 5x5 depthwise convolution with a quantized matrix, with prelu activation
*
* @param in Input matrix, size (1, w, h, c)
* @param filter 5x5 filter, size (1, 5, 5, c)
* @param prelu prelu params, size (1, 1, 1, c)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type
* @param exponent Exponent for resulting matrix
* @param name Layer name to debug
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_5x5_with_prelu(dl_matrix3dq_t *in,
dl_matrix3dq_t *filter,
dl_matrix3dq_t *prelu,
int stride_x,
int stride_y,
dl_padding_type padding,
int exponent,
char *name);
/**
* @brief Do 5x5 depthwise convolution with a quantized matrix, with bias adding and prelu activation
*
* @param in Input matrix, size (1, w, h, c)
* @param f 5x5 filter, size (1, 5, 5, c)
* @param bias Bias, size (1, 1, 1, c)
* @param prelu prelu params, size (1, 1, 1, c)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type
* @param exponent Exponent for resulting matrix
* @param name Layer name to debug
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_5x5_with_bias_prelu(dl_matrix3dq_t *in,
dl_matrix3dq_t *f,
dl_matrix3dq_t *bias,
dl_matrix3dq_t *prelu,
int stride_x,
int stride_y,
dl_padding_type padding,
int exponent,
char *name);
//
// Depthwise Common
//
#if CONFIG_DEVELOPING_CODE
/**
* @brief Do a general depthwise convolution layer pass with a quantized matrix
*
* @param in Input matrix, size (1, w, h, c)
* @param filter Weights of the neurons, size (1, k_w, k_h, c)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type
* @param exponent Exponent for resulting matrix
* @param mode Implementation mode
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_common(dl_matrix3dq_t *in,
dl_matrix3dq_t *filter,
int stride_x,
@ -699,6 +991,18 @@ dl_matrix3dq_t *dl_matrix3dqq_depthwise_conv_common(dl_matrix3dq_t *in,
int exponent,
dl_conv_mode mode);
/**
* @brief Do a general depthwise convolution layer pass with an 8-bit fixed point matrix
*
* @param in Input matrix, size (1, w, h, c)
* @param filter Weights of the neurons, size (1, k_w, k_h, c)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type
* @param exponent Exponent for resulting matrix
* @param mode Implementation mode
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3duq_depthwise_conv_common(dl_matrix3du_t *in,
dl_matrix3dq_t *filter,
int stride_x,
@ -712,6 +1016,14 @@ dl_matrix3dq_t *dl_matrix3duq_depthwise_conv_common(dl_matrix3du_t *in,
// Dot Product
//
/**
* @brief Do dot product operation with a quantized matrix
*
* @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 mode Implementation mode
*/
void dl_matrix3dqq_dot_product(dl_matrix3dq_t *out,
dl_matrix3dq_t *in,
dl_matrix3dq_t *filter,
@ -727,7 +1039,7 @@ void dl_matrix3dqq_dot_product(dl_matrix3dq_t *out,
* @param in Input matrix, size (1, 1, 1, w)
* @param filter Filter matrix, size (1, w, h, 1)
* @param mode Implementation mode
* @param name
* @param name Layer name to debug
*/
void dl_matrix3dqq_fc(dl_matrix3dq_t *out,
dl_matrix3dq_t *in,
@ -743,6 +1055,7 @@ void dl_matrix3dqq_fc(dl_matrix3dq_t *out,
* @param filter Filter matrix, size (1, w, h, 1)
* @param bias Bias matrix, size (1, 1, 1, h)
* @param mode Implementation mode
* @param name Layer name to debug
*/
void dl_matrix3dqq_fc_with_bias(dl_matrix3dq_t *out,
dl_matrix3dq_t *in,
@ -830,6 +1143,28 @@ dl_matrix3dq_t *dl_matrix3dqq_mobilefaceblock(dl_matrix3dq_t *in,
dl_conv_mode mode,
int shortcut);
/**
* @brief Do mobilefacenet process, the process sequence is 1x1 pointwise->bn->prelu->3x3 depthwise->bn->prelu->1x1 pointwise->bn
*
* @param in Input matrix, size (1, w, h, c)
* @param pw Pointwise 1x1 filter, size (n1, 1, 1, c)
* @param pw_bias Pointwise bias, size (1, 1, 1, n1)
* @param pw_prelu Pointwise prelu, size (1, 1, 1, n1)
* @param dw Depthwise 3x3 filter, size (1, 3, 3, n1)
* @param dw_bias Depthwise bias, size (1, 1, 1, n1)
* @param dw_prelu Depthwise prelu, size(1, 1, 1, n1)
* @param pw_linear Pointwise 1x1 filter, size (n2, 1, 1, n1)
* @param pw_linear_bias Pointwise bias, size (1, 1, 1, n2)
* @param pw_exponent Exponent for pointwise resulting matrix
* @param dw_exponent Exponent for depthwise resulting matrix
* @param pw_linear_exponent Exponent for pointwise resulting matrix
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Depthwise Convlution Padding type
* @param mode Implementation mode
* @param shortcut Whether has a shortcut at pointwise linear
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_mobilefaceblock_prelu(dl_matrix3dq_t *in,
dl_matrix3dq_t *pw,
dl_matrix3dq_t *pw_bias,
@ -848,6 +1183,15 @@ dl_matrix3dq_t *dl_matrix3dqq_mobilefaceblock_prelu(dl_matrix3dq_t *in,
dl_conv_mode mode,
int shortcut);
/**@{*/
/**
* @brief Do mobilefacenet process, the process sequence is 1x1 pointwise->bn->prelu->3x3 depthwise->bn->prelu->1x1 pointwise->bn
*
* Compared to ‘dl_matrix3dqq_mobilefaceblock_prelu’， this family of functions 'dl_matrix3dqq_mobilefaceblock_prelu_split_x1_x2'
* split the first pointwise convlution into x1 pointwise convlutions, and split the second pointwise convlution into x2 pointwise convlutions.
*
*
*/
dl_matrix3dq_t *dl_matrix3dqq_mobilefaceblock_prelu_split_2_2(dl_matrix3dq_t *in,
dl_matrix3dq_t *pw_1,
dl_matrix3dq_t *pw_2,
@ -910,6 +1254,59 @@ dl_matrix3dq_t *dl_matrix3dqq_mobilefaceblock_prelu_split_1_2(dl_matrix3dq_t *in
dl_padding_type padding,
dl_conv_mode mode,
int shortcut);
/**@}*/
//
// blazeblock
//
/**
* @brief Do blazeblock process, the process sequence is depthwise->bn->1x1 pointwise->bn->shortcut->relu
*
* @param in Input matrix, size (1, w, h, c)
* @param dw1_kernel Depthwise filter, size (1, k, k, c)
* @param dw1_bias Depthwise bias, size (1, 1, 1, c)
* @param pw1_kernel Pointwise 1x1 filter, size (n, 1, 1, c)
* @param pw1_bias Pointwise bias, size (1, 1, 1, n)
* @param config blazeblock configuration
* @param name Layer name to debug
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_blazeblock(dl_matrix3dq_t *in,
dl_matrix3dq_t *dw1_kernel,
dl_matrix3dq_t *dw1_bias,
dl_matrix3dq_t *pw1_kernel,
dl_matrix3dq_t *pw1_bias,
dl_matrix3dq_blazeblock_config_t config,
char *name);
/**
* @brief Do double blazeblock process, the process sequence is depthwise->bn->1x1 pointwise->bn->relu->depthwise->bn->1x1 pointwise->bn->shortcut->relu
*
* @param in Input matrix, size (1, w, h, c)
* @param dw1_kernel Depthwise filter, size (1, k, k, c)
* @param dw1_bias Depthwise bias, size (1, 1, 1, c)
* @param pw1_kernel Pointwise 1x1 filter, size (n1, 1, 1, c)
* @param pw1_bias Pointwise bias, size (1, 1, 1, n1)
* @param dw2_kernel Depthwise filter, size (1, k, k, n1)
* @param dw2_bias Depthwise bias, size (1, 1, 1, n1)
* @param pw2_kernel Pointwise 1x1 filter, size (n2, 1, 1, n1)
* @param pw2_bias Pointwise bias, size (1, 1, 1, n2)
* @param config blazeblock configuration
* @param name Layer name to debug
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_double_blazeblock(dl_matrix3dq_t *in,
dl_matrix3dq_t *dw1_kernel,
dl_matrix3dq_t *dw1_bias,
dl_matrix3dq_t *pw1_kernel,
dl_matrix3dq_t *pw1_bias,
dl_matrix3dq_t *dw2_kernel,
dl_matrix3dq_t *dw2_bias,
dl_matrix3dq_t *pw2_kernel,
dl_matrix3dq_t *pw2_bias,
dl_matrix3dq_blazeblock_config_t config,
char *name);
//
// Mobilenet
//
@ -925,7 +1322,8 @@ dl_matrix3dq_t *dl_matrix3dqq_mobilefaceblock_prelu_split_1_2(dl_matrix3dq_t *in
* @param compress Pointwise 1x1 filter, size (n2, 1, 1, n1)
* @param bias Pointwise bias, size (1, 1, 1, n2)
* @param config Mobilenet configuration
* @return Resulting quantized matrix
* @param name Block name to debug
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3dqq_mobilenet(dl_matrix3dq_t *in,
dl_matrix3dq_t *dilate,
@ -948,7 +1346,8 @@ dl_matrix3dq_t *dl_matrix3dqq_mobilenet(dl_matrix3dq_t *in,
* @param compress Pointwise 1x1 filter, size (n2, 1, 1, n1)
* @param bias Pointwise bias, size (1, 1, 1, n2)
* @param config Mobilenet configuration
* @return Resulting quantized matrix
* @param name Block name to debug
* @return dl_matrix3dq_t* Resulting quantized matrix
*/
dl_matrix3dq_t *dl_matrix3duq_mobilenet(dl_matrix3du_t *in,
dl_matrix3dq_t *dilate,
@ -964,18 +1363,19 @@ dl_matrix3dq_t *dl_matrix3duq_mobilenet(dl_matrix3du_t *in,
// Padding
//
/**@{*/
/**
* @brief
* @brief This family of functions do a padding operation before a convlution
*
* @param padded_input
* @param output_height
* @param output_width
* @param input
* @param stride_x
* @param stride_y
* @param kernel_size
* @param padding_type
* @return dl_error_type
* @param padded_input the padded result pointer
* @param output_height the output height pointer
* @param output_width the output width pointer
* @param input Input matrix, size (1, w, h, c)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param kernel_size Kernel size of the next convlution
* @param padding_type Padding type
* @return dl_error_type Return DL_SUCCESS if padding successfully, else return DL_FAIL
*/
dl_error_type dl_matrix3dqq_padding(dl_matrix3dq_t **padded_input,
int *output_height,
@ -986,19 +1386,6 @@ dl_error_type dl_matrix3dqq_padding(dl_matrix3dq_t **padded_input,
int kernel_size,
dl_padding_type padding_type);
/**
* @brief
*
* @param padded_input
* @param output_height
* @param output_width
* @param input
* @param stride_x
* @param stride_y
* @param kernel_size
* @param padding_type
* @return dl_error_type
*/
dl_error_type dl_matrix3duq_padding(dl_matrix3du_t **padded_input,
int *output_height,
int *output_width,
@ -1007,6 +1394,20 @@ dl_error_type dl_matrix3duq_padding(dl_matrix3du_t **padded_input,
int stride_y,
int kernel_size,
dl_padding_type padding_type);
/**@}*/
//
// Upsample
//
/**
* @brief Upsample a feature map to twice the size
*
* @param in Input matrix, size (1, w, h, c)
* @param upsample upsample type
* @return dl_matrix3dq_t* Resulting matrix, size (1, 2*w, 2*h, c)
*/
dl_matrix3dq_t *dl_matrix3dqq_upsample_2x(dl_matrix3dq_t *in,
dl_upsample_type upsample);
//
// Pooling
@ -1014,22 +1415,22 @@ dl_error_type dl_matrix3duq_padding(dl_matrix3du_t **padded_input,
/**
* @brief Calculate average value of a feature map
*
* @param in Input matrix, size (1, w, h, c)
* @return Resulting matrix, size (1, 1, 1, c)
* @param in Input matrix, size (1, w, h, c)
* @return dl_matrix3dq_t* Resulting matrix, size (1, 1, 1, c)
*/
dl_matrix3dq_t *dl_matrix3dq_global_pool(dl_matrix3dq_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_matrix3dq_t* Resulting matrix, size (1, w', h', c)
*/
dl_matrix3dq_t *dl_matrix3dq_pooling(dl_matrix3dq_t *in,
int f_w,