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Check for multiple synapses #39

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merged 3 commits into from
Mar 20, 2017
Merged

Check for multiple synapses #39

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239be58
Exit with an error message if more than one synapse per neuron pair i…
mstimberg Nov 18, 2016
34e2b58
Set a custom error code for multiple synapses, and check for this err…
mstimberg Nov 18, 2016
a103cc1
Merge remote-tracking branch 'origin/master' into check_for_multiple_…
mstimberg Mar 18, 2017
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176 changes: 99 additions & 77 deletions brian2genn/b2glib/convert_synapses.h
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Original file line number Diff line number Diff line change
Expand Up @@ -14,19 +14,29 @@ void convert_dynamic_arrays_2_dense_matrix(vector<int32_t> &source, vector<int32
assert(source.size() == gvector.size());
unsigned int size= source.size();
for (int s= 0; s < srcNN; s++) {
for (int t= 0; t < trgNN; t++) {
g[s*trgNN+t]= (scalar) 0.0;
}
for (int t= 0; t < trgNN; t++) {
g[s*trgNN+t]= (scalar)NAN;
}
}
// cerr << size << "!!!!!!" << endl;

for (int i= 0; i < size; i++) {
assert(source[i] < srcNN);
assert(target[i] < trgNN);
// cerr << source[i] << " " << target[i] << " " << gvector[i] << endl;
g[source[i]*trgNN+target[i]]= gvector[i];
assert(source[i] < srcNN);
assert(target[i] < trgNN);
// Check for duplicate entries
if (! isnan(g[source[i]*trgNN+target[i]])) {
std::cerr << "*****" << std::endl;
std::cerr << "ERROR Cannot run GeNN simulation: More than one synapse for pair " << source[i] << " - " << target[i] << std::endl;
std::cerr << "*****" << std::endl;
exit(222);
}
g[source[i]*trgNN+target[i]]= gvector[i];
}
for (int s= 0; s < srcNN; s++) {
for (int t= 0; t < trgNN; t++) {
if (isnan(g[s*trgNN+t]))
g[s*trgNN+t] = 0.0;
}
}
// cerr << endl;
// cerr << "-------------------------";
}

namespace b2g {
Expand All @@ -46,52 +56,64 @@ void convert_dynamic_arrays_2_sparse_synapses(vector<int32_t> &source, vector<in
static vector<vector<scalar> > bypreG;
static unsigned int size;
if (mode == b2g::FULL_MONTY) {
assert(source.size() == target.size());
assert(source.size() == gvector.size());
bypre.clear();
bypre.resize(srcNN);
bypreG.clear();
bypreG.resize(srcNN);
size= source.size();
for (int i= 0; i < size; i++) {
assert(source[i] < srcNN);
assert(target[i] < trgNN);
bypre[source[i]].push_back(target[i]);
bypreG[source[i]].push_back(gvector[i]);
}
// convert this intermediate representation into the sparse synapses struct
// assume it has been allocated properly
unsigned int cnt= 0;
for (int i= 0; i < srcNN; i++) {
size= bypre[i].size();
c.indInG[i]= cnt;
for (int j= 0; j < size; j++) {
c.ind[cnt]= bypre[i][j];
gv[cnt]= bypreG[i][j];
assert(source.size() == target.size());
assert(source.size() == gvector.size());
bypre.clear();
bypre.resize(srcNN);
bypreG.clear();
bypreG.resize(srcNN);
size= source.size();
for (int i= 0; i < size; i++) {
assert(source[i] < srcNN);
assert(target[i] < trgNN);
bypre[source[i]].push_back(target[i]);
bypreG[source[i]].push_back(gvector[i]);
}
// convert this intermediate representation into the sparse synapses struct
// assume it has been allocated properly
unsigned int cnt= 0;
for (int i= 0; i < srcNN; i++) {
size= bypre[i].size();
c.indInG[i]= cnt;
for (int j= 0; j < size; j++) {
c.ind[cnt]= bypre[i][j];
gv[cnt]= bypreG[i][j];
// os << i << " " << c.ind[cnt] << " " << gv[cnt] << endl;
cnt++;
}
}
c.indInG[srcNN]= cnt;
cnt++;
}
}
c.indInG[srcNN]= cnt;
}
else { // COPY_ONLY
bypreG.clear();
bypreG.resize(srcNN);
size= source.size();
for (int i= 0; i < size; i++) {
bypreG[source[i]].push_back(gvector[i]);
}
unsigned int cnt= 0;
for (int i= 0; i < srcNN; i++) {
size= bypre[i].size();
for (int j= 0; j < size; j++) {
gv[cnt]= bypreG[i][j];
bypreG.clear();
bypreG.resize(srcNN);
size= source.size();
for (int i= 0; i < size; i++) {
bypreG[source[i]].push_back(gvector[i]);
}
unsigned int cnt= 0;
for (int i= 0; i < srcNN; i++) {
size= bypre[i].size();
for (int j= 0; j < size; j++) {
gv[cnt]= bypreG[i][j];
// os << i << " " << c.ind[cnt] << " " << gv[cnt] << endl;
cnt++;
}
}
cnt++;
}
}
}

// Check for duplicate entries
for (int i=0; i<srcNN; i++) {
vector<int32_t> targets = bypre[i];
std::sort(targets.begin(), targets.end());
auto duplicate_pos = std::adjacent_find(targets.begin(), targets.end());
if (duplicate_pos != targets.end()) {
std::cerr << "*****" << std::endl;
std::cerr << "ERROR Cannot run GeNN simulation: More than one synapse for pair " << source[i] << " - " << *duplicate_pos << std::endl;
std::cerr << "*****" << std::endl;
exit(222);
}
}
// convertCnt++;
}

template<class scalar>
Expand All @@ -101,9 +123,9 @@ void convert_dense_matrix_2_dynamic_arrays(scalar *g, int srcNN, int trgNN, vect
assert(source.size() == gvector.size());
unsigned int size= source.size();
for (int i= 0; i < size; i++) {
assert(source[i] < srcNN);
assert(target[i] < trgNN);
gvector[i]= g[source[i]*trgNN+target[i]];
assert(source[i] < srcNN);
assert(target[i] < trgNN);
gvector[i]= g[source[i]*trgNN+target[i]];
}
}

Expand All @@ -116,28 +138,28 @@ void convert_sparse_synapses_2_dynamic_arrays(Conductance &c, scalar *gv, int sr
// ofstream os(name.c_str());
// note: this does not preserve the original order of entries in the brian arrays - is that a problem?
if (mode == b2g::FULL_MONTY) {
assert(source.size() == target.size());
assert(source.size() == gvector.size());
unsigned int size= source.size();
unsigned int cnt= 0;
for (int i= 0; i < srcNN; i++) {
for (int j= c.indInG[i]; j < c.indInG[i+1]; j++) {
source[cnt]= i;
target[cnt]= c.ind[j];
gvector[cnt]= gv[j];
assert(source.size() == target.size());
assert(source.size() == gvector.size());
unsigned int size= source.size();
unsigned int cnt= 0;
for (int i= 0; i < srcNN; i++) {
for (int j= c.indInG[i]; j < c.indInG[i+1]; j++) {
source[cnt]= i;
target[cnt]= c.ind[j];
gvector[cnt]= gv[j];
// os << source[cnt] << " " << target[cnt] << " " << gvector[cnt] << endl;
cnt++;
}
}
cnt++;
}
}
}
else {
unsigned int size= source.size();
unsigned int cnt= 0;
for (int i= 0; i < srcNN; i++) {
for (int j= c.indInG[i]; j < c.indInG[i+1]; j++) {
gvector[cnt++]= gv[j];
}
}
unsigned int size= source.size();
unsigned int cnt= 0;
for (int i= 0; i < srcNN; i++) {
for (int j= c.indInG[i]; j < c.indInG[i+1]; j++) {
gvector[cnt++]= gv[j];
}
}
}
// os.close();
// convertCnt++;
Expand All @@ -146,12 +168,12 @@ void convert_sparse_synapses_2_dynamic_arrays(Conductance &c, scalar *gv, int sr
void create_hidden_weightmatrix(vector<int32_t> &source, vector<int32_t> &target, char* hwm, int srcNN, int trgNN)
{
for (int s= 0; s < srcNN; s++) {
for (int t= 0; t < trgNN; t++) {
hwm[s*trgNN+t]= 0;
}
for (int t= 0; t < trgNN; t++) {
hwm[s*trgNN+t]= 0;
}
}
for (int i= 0; i < source.size(); i++) {
hwm[source[i]*trgNN+target[i]]= 1;
hwm[source[i]*trgNN+target[i]]= 1;
}
}
#endif
17 changes: 11 additions & 6 deletions brian2genn/device.py
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Original file line number Diff line number Diff line change
Expand Up @@ -677,12 +677,17 @@ def build(self, directory='GeNNworkspace', compile=True, run=True,
try:
self.run(directory, use_GPU, with_output)
except CalledProcessError as ex:
raise RuntimeError(('Project run failed (Command {cmd} '
'failed with error code {returncode}).\n'
'See the output above (if any) for more '
'details.').format(cmd=ex.cmd,
returncode=ex.returncode)
)
if ex.returncode == 222:
raise NotImplementedError('GeNN does not support multiple '
'synapses per neuron pair (use '
'multiple Synapses objects).')
else:
raise RuntimeError(('Project run failed (Command {cmd} '
'failed with error code {returncode}).\n'
'See the output above (if any) for more '
'details.').format(cmd=ex.cmd,
returncode=ex.returncode)
)

def generate_code_objects(self, writer):
# Generate data for non-constant values
Expand Down