noodle_internal.cpp File Reference

Private shared globals and helpers for Noodle implementation files. More...

#include "noodle_internal.h"

Include dependency graph for noodle_internal.cpp:

Functions
uint16_t	noodle_do_conv1d (float *input, float *kernel, uint16_t W, uint16_t K, float *output, uint16_t P, uint16_t S)
	Accumulate one 1D convolution into an output sequence.
uint16_t	noodle_do_pooling1d (float *input, uint16_t W, uint16_t K, uint16_t S, const char *fn)
	Apply valid 1D max pooling and write to a file.
uint16_t	noodle_do_pooling1d (float *input, uint16_t W, uint16_t K, uint16_t S, NDL_File &fo)
	Apply valid 1D max pooling and write to an open file.
uint16_t	noodle_do_pooling1d (const float *input, uint16_t W, uint16_t K, uint16_t S, float *output)
	Apply valid 1D pooling and write to memory.
float	noodle_get_padded_x (byte *grid, int16_t i, int16_t j, int16_t W, int16_t P0, int16_t P1)
	Read a byte grid sample with asymmetric zero padding.
float	noodle_get_padded_x (float *grid, int16_t i, int16_t j, int16_t W, int16_t P0, int16_t P1)
	Read a float grid sample with asymmetric zero padding.
uint16_t	noodle_do_bias (float *output, float bias, uint16_t n)
	Add bias to a square output map and apply ReLU.
uint16_t	noodle_do_pooling (const float *input, uint16_t W, uint16_t K, uint16_t S, const char *fn)
	Apply 2D pooling and write to a file.
uint16_t	noodle_do_pooling (const float *input, uint16_t W, uint16_t K, uint16_t S, NDL_File &fo)
	Apply 2D pooling and write to an open file.
uint16_t	noodle_do_pooling (const float *input, uint16_t W, uint16_t K, uint16_t S, float *output)
	Apply 2D pooling and write to memory.
uint16_t	noodle_do_conv (byte *grid, const float *kernel, uint16_t K, uint16_t W, float *output, uint16_t P, uint16_t S)
	Accumulate one byte-input 2D convolution plane.
uint16_t	noodle_do_conv (float *grid, const float *kernel, uint16_t K, uint16_t W, float *output, uint16_t P, uint16_t S)
	Accumulate one float-input 2D convolution plane.
void	noodle_reset_buffer (float *buffer, uint16_t n)
	Clear a float buffer.
uint16_t	noodle_do_bias_act (float *output, float bias, uint16_t n, Activation act)
	Add bias to a square output map and apply the requested activation.
uint16_t	noodle_do_conv_transpose (float *input, const float *kernel, uint16_t K, uint16_t W, float *output, uint16_t P, uint16_t S, uint16_t OP)
	Accumulate one 2D transpose-convolution plane.
uint16_t	noodle_compute_V (uint16_t K, uint16_t W, uint16_t P, uint16_t S)
	Compute 2D convolution output width.
uint16_t	noodle_compute_V_and_P (uint16_t K, uint16_t W, uint16_t P, uint16_t S, uint16_t &P0, uint16_t &P1)
	Compute 2D convolution output width and effective asymmetric padding.
uint16_t	noodle_valid_max_pool (float *inplace, uint16_t W, uint16_t C, const Pool &pool)
	Apply valid max pooling to a packed channel-first tensor in place.
uint16_t	noodle_compute_Vt (uint16_t K, uint16_t W, uint16_t P, uint16_t S, uint16_t OP)
	Compute transpose-convolution output width.
uint16_t	noodle_compute_Vt_and_P (uint16_t K, uint16_t W, uint16_t P, uint16_t S, uint16_t OP, uint16_t &P0, uint16_t &P1)
	Compute transpose-convolution output width and effective padding.
void	noodle_copy_kernel_progmem (const float *w, uint32_t base, uint16_t K, float *kernel)
	Copy one square kernel from near-PROGMEM into RAM.

Variables
SdFat	NOODLE_FS
	SdFat filesystem object used by the SdFat backend.
NDL_File	fw
	Shared weight file handle used by streaming layer implementations.
NDL_File	fb
	Shared bias file handle used by streaming layer implementations.
NDL_File	fo
	Shared output file handle used by streaming layer implementations.
NDL_File	fi
	Shared input file handle used by streaming layer implementations.
void *	temp_buff1 = 0
	Global input scratch buffer, either Noodle-owned or caller-owned.
void *	temp_buff2 = 0
	Global accumulation scratch buffer, either Noodle-owned or caller-owned.
size_t	temp_buff1_capacity = 0
size_t	temp_buff2_capacity = 0

Detailed Description

Private shared globals and helpers for Noodle implementation files.

Variable Documentation

fb

NDL_File fb

Shared bias file handle used by streaming layer implementations.

fi

NDL_File fi

Shared input file handle used by streaming layer implementations.

fo

NDL_File fo

Shared output file handle used by streaming layer implementations.

fw

NDL_File fw

Shared weight file handle used by streaming layer implementations.

NOODLE_FS

SdFat NOODLE_FS

SdFat filesystem object used by the SdFat backend.

temp_buff1

void* temp_buff1 = 0

Global input scratch buffer, either Noodle-owned or caller-owned.

temp_buff1_capacity

size_t temp_buff1_capacity = 0

temp_buff2

void* temp_buff2 = 0

Global accumulation scratch buffer, either Noodle-owned or caller-owned.

temp_buff2_capacity

size_t temp_buff2_capacity = 0