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noodle_internal.h File Reference
Private declarations shared by Noodle implementation files. More...
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Functions | |
| float * | noodle_temp1_require (size_t required_floats) |
| Ensure temp buffer 1 can hold a number of floats. | |
| float * | noodle_temp2_require (size_t required_floats) |
| Ensure temp buffer 2 can hold a number of floats. | |
| void | noodle_temp_buffers_free (void) |
| Free Noodle-owned scratch buffers and detach external scratch buffers. | |
| float * | noodle_slice (float *flat, size_t W, size_t z) |
| Return a channel plane from a packed [Z][W][W] tensor. | |
| size_t | noodle_read_raw (NDL_File &f, void *dst, size_t n) |
| Read raw bytes from a backend file handle. | |
| size_t | noodle_write_raw (NDL_File &f, const void *src, size_t n) |
| Write raw bytes to a backend file handle. | |
| size_t | noodle_read_float_block (NDL_File &f, float *dst, size_t n_floats) |
| Read a block of floats using the configured scalar file format. | |
| float | noodle_dot_float_block (const float *x, const float *w, uint16_t n) |
| Compute a dot product with a small unrolled loop. | |
| 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. | |
| void | noodle_find_max (float *input, uint16_t n, float &max_val, uint16_t &max_idx) |
| Find the maximum value and its index in a vector. | |
| void | noodle_unpack_bn_params (const float *bn_params, uint16_t N, const float **gamma, const float **beta, const float **mean, const float **var) |
| Split packed batch-normalization parameters into four arrays. | |
| uint16_t | noodle_bn1d (float *x, uint16_t N, const float *gamma, const float *beta, const float *mean, const float *var, float eps) |
| Apply 1D batch normalization in place to a raw vector. | |
| uint16_t | noodle_bn1d (float *x, uint16_t N, const float *bn_params, float eps) |
| Apply 1D batch normalization from packed parameters. | |
| uint16_t | noodle_bn1d_relu (float *x, uint16_t N, const float *gamma, const float *beta, const float *mean, const float *var, float eps) |
| Apply 1D batch normalization followed by ReLU in place. | |
| uint16_t | noodle_bn1d_relu (float *x, uint16_t N, const float *bn_params, float eps) |
| Apply packed 1D batch normalization followed by ReLU in place. | |
| uint16_t | noodle_bn2d (float *x, uint16_t C, uint16_t W, const float *gamma, const float *beta, const float *mean, const float *var, float eps) |
| Apply 2D channel-wise batch normalization in place. | |
| uint16_t | noodle_bn2d (float *x, uint16_t C, uint16_t W, const float *bn_params, float eps) |
| Apply 2D channel-wise batch normalization from packed parameters. | |
| uint16_t | noodle_bn2d_relu (float *x, uint16_t C, uint16_t W, const float *gamma, const float *beta, const float *mean, const float *var, float eps) |
| Apply 2D channel-wise batch normalization followed by ReLU. | |
| uint16_t | noodle_bn2d_relu (float *x, uint16_t C, uint16_t W, const float *bn_params, float eps) |
| Apply packed 2D batch normalization followed by ReLU. | |
| 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. | |
| uint16_t | noodle_conv1d (float *in, uint16_t n_inputs, float *out, uint16_t n_outputs, uint16_t W, const ConvMem &conv, CBFPtr progress_cb) |
| Raw memory-to-memory 1D convolution without pooling. | |
| uint16_t | noodle_conv1d (float *in, uint16_t n_inputs, float *out, uint16_t n_outputs, uint16_t W, const ConvMem &conv, const Pool &pool, CBFPtr progress_cb) |
| Raw memory-to-memory 1D convolution with pooling. | |
| uint16_t | noodle_conv1d (float *in, uint16_t n_inputs, const char *out_fn, uint16_t n_outputs, uint16_t W, const ConvMem &conv, CBFPtr progress_cb) |
| Raw memory-to-file 1D convolution without pooling. | |
| uint16_t | noodle_conv1d (const char *in_fn, uint16_t n_inputs, float *out, uint16_t n_outputs, uint16_t W, const ConvMem &conv, CBFPtr progress_cb) |
| Raw file-to-memory 1D convolution without pooling. | |
| uint16_t | noodle_conv_float (const char *in_fn, uint16_t n_inputs, uint16_t n_outputs, float *output, uint16_t W, const Conv &conv, const Pool &pool, CBFPtr progress_cb) |
| File-to-memory 2D convolution with file-backed parameters. | |
| uint16_t | noodle_conv_float (float *input, uint16_t n_inputs, uint16_t n_outputs, const char *out_fn, uint16_t W, const Conv &conv, const Pool &pool, CBFPtr progress_cb) |
| Memory-to-file 2D convolution with file-backed parameters. | |
| uint16_t | noodle_conv_float (float *input, uint16_t n_inputs, uint16_t n_outputs, const char *out_fn, uint16_t W, const ConvMem &conv, const Pool &pool, CBFPtr progress_cb) |
| Memory-to-file 2D convolution with memory-backed parameters. | |
| uint16_t | noodle_conv_float (float *input, uint16_t n_inputs, uint16_t n_outputs, float *output, uint16_t W, const Conv &conv, const Pool &pool, CBFPtr progress_cb) |
| Raw memory-to-memory 2D convolution with file-backed parameters. | |
| uint16_t | noodle_conv_float (float *input, uint16_t n_inputs, uint16_t n_outputs, float *output, uint16_t W, const ConvMem &conv, const Pool &pool, CBFPtr progress_cb) |
| Raw memory-to-memory 2D convolution with memory-backed parameters. | |
| uint16_t | noodle_conv_float (float *input, uint16_t n_inputs, uint16_t n_outputs, float *output, uint16_t W, const ConvProgmem &conv, const Pool &pool, CBFPtr progress_cb) |
| Raw memory-to-memory 2D convolution with near-PROGMEM parameters. | |
| uint16_t | noodle_conv_transpose_float (float *input, uint16_t n_inputs, uint16_t n_outputs, float *output, uint16_t W, const ConvMem &conv, CBFPtr progress_cb) |
| Raw memory-to-memory 2D transpose convolution. | |
| uint16_t | noodle_dwconv_float (float *input, uint16_t n_channels, float *output, uint16_t W, const Conv &conv, const Pool &pool, CBFPtr progress_cb) |
| Raw memory-to-memory depthwise convolution with file-backed parameters. | |
| uint16_t | noodle_dwconv_float (float *input, uint16_t n_channels, float *output, uint16_t W, const ConvMem &conv, const Pool &pool, CBFPtr progress_cb) |
| Raw memory-to-memory depthwise convolution with memory-backed parameters. | |
| uint16_t | noodle_dwconv_float (float *input, uint16_t n_channels, float *output, uint16_t W, const ConvProgmem &conv, const Pool &pool, CBFPtr progress_cb) |
| Raw memory-to-memory depthwise convolution with near-PROGMEM parameters. | |
| uint16_t | noodle_fcn (const byte *input, uint16_t n_inputs, uint16_t n_outputs, float *output, const FCNFile &fcn, CBFPtr progress_cb) |
| Byte-input fully connected layer with file-backed parameters. | |
| uint16_t | noodle_fcn (const int8_t *input, uint16_t n_inputs, uint16_t n_outputs, float *output, const FCNFile &fcn, CBFPtr progress_cb) |
| Int8-input fully connected layer with file-backed parameters. | |
| uint16_t | noodle_fcn (const float *input, uint16_t n_inputs, uint16_t n_outputs, float *output, const FCNFile &fcn, CBFPtr progress_cb) |
| Float-input fully connected layer with file-backed parameters. | |
| uint16_t | noodle_fcn (const float *input, uint16_t n_inputs, uint16_t n_outputs, const char *out_fn, const FCNFile &fcn, CBFPtr progress_cb) |
| Float-input fully connected layer that writes output to a file. | |
| uint16_t | noodle_fcn (const char *in_fn, uint16_t n_inputs, uint16_t n_outputs, float *output, const FCNFile &fcn, CBFPtr progress_cb) |
| File-input fully connected layer that writes output to memory. | |
| uint16_t | noodle_fcn (const float *input, uint16_t n_inputs, uint16_t n_outputs, float *output, const FCNMem &fcn, CBFPtr progress_cb) |
| Float-input fully connected layer with memory-backed parameters. | |
| uint16_t | noodle_fcn (const float *input, uint16_t n_inputs, uint16_t n_outputs, float *output, const FCNProgmem &fcn, CBFPtr progress_cb) |
| Float-input fully connected layer with far-PROGMEM parameters. | |
| uint16_t | noodle_fcn_progmem (const float *input, uint16_t n_inputs, uint16_t n_outputs, float *output, const float *weight, const float *bias, Activation act, CBFPtr progress_cb) |
| Float-input fully connected layer with near-PROGMEM parameters. | |
| void | noodle_array_to_file (float *array, NDL_File &fo, uint16_t n) |
| Write a float array to an already-open file. | |
| void | noodle_grid_to_file (byte *grid, NDL_File &fo, uint16_t n) |
| Write a byte grid to an already-open file. | |
| void | noodle_grid_to_file (float *grid, NDL_File &fo, uint16_t n) |
| Write a float grid to an already-open file. | |
| void | noodle_array_from_file (NDL_File &fi, float *buffer, uint16_t K) |
| Read a float array from an already-open file. | |
| void | noodle_grid_from_file (NDL_File &fi, byte *buffer, uint16_t K) |
| Read a byte grid from an already-open file. | |
| void | noodle_grid_from_file (NDL_File &fi, int8_t *buffer, uint16_t K) |
| Read an int8 grid from an already-open file. | |
| void | noodle_grid_from_file (NDL_File &fi, float *buffer, uint16_t K) |
| Read a float grid from an already-open file. | |
| 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. | |
| uint16_t | noodle_flat (const char *in_fn, float *output, uint16_t V, uint16_t n_filters) |
| Flatten a packed file tensor into an HWC-like raw vector. | |
| uint16_t | noodle_flat (float *input, float *output, uint16_t V, uint16_t n_filters) |
| Flatten a packed memory tensor into an HWC-like raw vector. | |
| uint16_t | noodle_reshape (const float *src_hwc, float *dst_chw, uint16_t W, uint16_t C) |
| Convert HWC-like raw data to packed channel-first raw data. | |
| uint16_t | noodle_gap (float *inout, uint16_t C, uint16_t W) |
| Apply global average pooling in place to packed channel-first maps. | |
| uint16_t | noodle_gmp (float *inout, uint16_t C, uint16_t W) |
| Apply global max pooling in place to packed channel-first data. | |
| uint16_t | noodle_soft_max (float *input_output, uint16_t n) |
| Apply numerically stabilized softmax in place. | |
| uint16_t | noodle_sigmoid (float *input_output, uint16_t n) |
| Apply sigmoid in place. | |
| float | noodle_sigmoidf (float x) |
| Compute sigmoid for one scalar. | |
| uint16_t | noodle_logit (float *input_output, uint16_t n) |
| Apply logistic sigmoid in place. | |
| uint16_t | noodle_relu (float *input_output, uint16_t n) |
| Apply ReLU in place. | |
| uint16_t | noodle_bn (float *x, uint16_t C, uint16_t W, const float *gamma, const float *beta, const float *mean, const float *var, float eps) |
| Backward-compatible raw alias for noodle_bn2d(). | |
| uint16_t | noodle_bn (float *x, uint16_t C, uint16_t W, const float *bn_params, float eps) |
| Backward-compatible raw alias for packed-parameter noodle_bn2d(). | |
| uint16_t | noodle_bn_relu (float *x, uint16_t C, uint16_t W, const float *gamma, const float *beta, const float *mean, const float *var, float eps) |
| Backward-compatible raw alias for noodle_bn2d_relu(). | |
| uint16_t | noodle_bn_relu (float *x, uint16_t C, uint16_t W, const float *bn_params, float eps) |
| Backward-compatible raw alias for packed-parameter noodle_bn2d_relu(). | |
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 |
| Global input scratch buffer, either Noodle-owned or caller-owned. | |
| void * | temp_buff2 |
| Global accumulation scratch buffer, either Noodle-owned or caller-owned. | |
Detailed Description
Private declarations shared by Noodle implementation files.
Application code should include noodle.h. This header exists so the split implementation files can share global file handles, scratch-buffer helpers, low-level math kernels, and raw-pointer layer implementations behind the public NoodleBuffer API.
Variable Documentation
◆ fb
|
extern |
Shared bias file handle used by streaming layer implementations.
◆ fi
|
extern |
Shared input file handle used by streaming layer implementations.
◆ fo
|
extern |
Shared output file handle used by streaming layer implementations.
◆ fw
|
extern |
Shared weight file handle used by streaming layer implementations.
◆ NOODLE_FS
|
extern |
SdFat filesystem object used by the SdFat backend.
◆ temp_buff1
|
extern |
Global input scratch buffer, either Noodle-owned or caller-owned.
◆ temp_buff2
|
extern |
Global accumulation scratch buffer, either Noodle-owned or caller-owned.
