sPyNNaker neural_modelling 7.3.1
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formation_distance_dependent_impl.c
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1/*
2 * Copyright (c) 2017 The University of Manchester
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * https://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16
20
21formation_params_t *synaptogenesis_formation_init(uint8_t **data) {
22 // Reference the parameters to read the sizes
23 formation_params_t *form_params = (formation_params_t *) *data;
24 uint32_t data_size = sizeof(formation_params_t) + (sizeof(uint16_t) *
25 (form_params->ff_prob_size + form_params->lat_prob_size));
26
27 // Allocate the space for the data and copy it in
28 form_params = spin1_malloc(data_size);
29 if (form_params == NULL) {
30 log_error("Out of memory when allocating parameters");
32 }
33 spin1_memcpy(form_params, *data, data_size);
34 log_debug("Formation distance dependent %u bytes, grid=(%u, %u), %u ff probs, %u lat probs",
35 data_size, form_params->grid_x, form_params->grid_y,
36 form_params->ff_prob_size, form_params->lat_prob_size);
37
38 *data += data_size;
39
40 return form_params;
41}
void log_error(const char *message,...)
void log_debug(const char *message,...)
formation_params_t * synaptogenesis_formation_init(uint8_t **data)
Read and return an formation parameter data structure from the data stream.
Synapse formation using a distance-dependent rule.
RTE_SWERR
void rt_error(uint code,...)
#define NULL
void spin1_memcpy(void *dst, void const *src, uint len)