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Fixed lots of instances of passing the size in the wrong order for matrices in MLPPActivation.

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Relintai 2023-12-28 11:15:51 +01:00
parent 8c01fbf060
commit 14cd9dedb8
1 changed files with 33 additions and 33 deletions
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66
mlpp/activation/activation.cpp
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@ -845,7 +845,7 @@ Ref<MLPPVector> MLPPActivation::linear_derivv(const Ref<MLPPVector> &z) {
}
Ref<MLPPMatrix> MLPPActivation::linear_derivm(const Ref<MLPPMatrix> &z) {
MLPPLinAlg alg;
return alg.onematnm(z->size().x, z->size().y);
return alg.onematnm(z->size().y, z->size().x);
}
//SIGMOID
@ -1227,7 +1227,7 @@ Ref<MLPPVector> MLPPActivation::softplus_normv(const Ref<MLPPVector> &z) {
Ref<MLPPMatrix> MLPPActivation::softplus_normm(const Ref<MLPPMatrix> &z) {
MLPPLinAlg alg;
return alg.lognv(alg.additionnv(alg.onematnm(z->size().x, z->size().y), alg.expnv(z)));
return alg.lognv(alg.additionnv(alg.onematnm(z->size().y, z->size().x), alg.expnv(z)));
}
real_t MLPPActivation::softplus_derivr(real_t z) {
@ -1253,7 +1253,7 @@ Ref<MLPPVector> MLPPActivation::softsign_normv(const Ref<MLPPVector> &z) {
Ref<MLPPMatrix> MLPPActivation::softsign_normm(const Ref<MLPPMatrix> &z) {
MLPPLinAlg alg;
return alg.division_element_wisenvnm(z, alg.additionnv(alg.onematnm(z->size().x, z->size().y), alg.absnm(z)));
return alg.division_element_wisenvnm(z, alg.additionnv(alg.onematnm(z->size().y, z->size().x), alg.absnm(z)));
}
real_t MLPPActivation::softsign_derivr(real_t z) {
@ -1267,7 +1267,7 @@ Ref<MLPPVector> MLPPActivation::softsign_derivv(const Ref<MLPPVector> &z) {
Ref<MLPPMatrix> MLPPActivation::softsign_derivm(const Ref<MLPPMatrix> &z) {
MLPPLinAlg alg;
return alg.division_element_wisenvnm(alg.onematnm(z->size().x, z->size().y), alg.exponentiatenv(alg.additionnm(alg.onematnm(z->size().x, z->size().y), alg.absnm(z)), 2));
return alg.division_element_wisenvnm(alg.onematnm(z->size().y, z->size().x), alg.exponentiatenv(alg.additionnm(alg.onematnm(z->size().y, z->size().x), alg.absnm(z)), 2));
}
//GAUSSIANCDF
@ -1284,7 +1284,7 @@ Ref<MLPPVector> MLPPActivation::gaussian_cdf_normv(const Ref<MLPPVector> &z) {
Ref<MLPPMatrix> MLPPActivation::gaussian_cdf_normm(const Ref<MLPPMatrix> &z) {
MLPPLinAlg alg;
return alg.scalar_multiplynm(0.5, alg.additionnm(alg.onematnm(z->size().x, z->size().y), alg.erfnm(alg.scalar_multiplynm(1 / sqrt(2), z))));
return alg.scalar_multiplynm(0.5, alg.additionnm(alg.onematnm(z->size().y, z->size().x), alg.erfnm(alg.scalar_multiplynm(1 / sqrt(2), z))));
}
real_t MLPPActivation::gaussian_cdf_derivr(real_t z) {
@ -1347,7 +1347,7 @@ Ref<MLPPVector> MLPPActivation::logit_normv(const Ref<MLPPVector> &z) {
Ref<MLPPMatrix> MLPPActivation::logit_normm(const Ref<MLPPMatrix> &z) {
MLPPLinAlg alg;
return alg.lognm(alg.division_element_wisenvnm(z, alg.subtractionnm(alg.onematnm(z->size().x, z->size().y), z)));
return alg.lognm(alg.division_element_wisenvnm(z, alg.subtractionnm(alg.onematnm(z->size().y, z->size().x), z)));
}
real_t MLPPActivation::logit_derivr(real_t z) {
@ -1365,9 +1365,9 @@ Ref<MLPPMatrix> MLPPActivation::logit_derivm(const Ref<MLPPMatrix> &z) {
return alg.subtractionnm(
alg.division_element_wisenvnm(
alg.onematnm(z->size().x, z->size().y), z),
alg.division_element_wisenvnm(alg.onematnm(z->size().x, z->size().y),
alg.subtractionnm(z, alg.onematnm(z->size().x, z->size().y))));
alg.onematnm(z->size().y, z->size().x), z),
alg.division_element_wisenvnm(alg.onematnm(z->size().y, z->size().x),
alg.subtractionnm(z, alg.onematnm(z->size().y, z->size().x))));
}
//UNITSTEP
@ -2090,7 +2090,7 @@ Ref<MLPPVector> MLPPActivation::csch_normv(const Ref<MLPPVector> &z) {
Ref<MLPPMatrix> MLPPActivation::csch_normm(const Ref<MLPPMatrix> &z) {
MLPPLinAlg alg;
return alg.division_element_wisenvnm(alg.onematnm(z->size().x, z->size().y), sinh_normm(z));
return alg.division_element_wisenvnm(alg.onematnm(z->size().y, z->size().x), sinh_normm(z));
}
real_t MLPPActivation::csch_derivr(real_t z) {
@ -2124,7 +2124,7 @@ Ref<MLPPVector> MLPPActivation::sech_normv(const Ref<MLPPVector> &z) {
Ref<MLPPMatrix> MLPPActivation::sech_normm(const Ref<MLPPMatrix> &z) {
MLPPLinAlg alg;
return alg.division_element_wisenvnm(alg.onematnm(z->size().x, z->size().y), cosh_normm(z));
return alg.division_element_wisenvnm(alg.onematnm(z->size().y, z->size().x), cosh_normm(z));
// return activation(z, deriv, static_cast<void (*)(real_t, bool)>(&sech));
}
@ -2157,7 +2157,7 @@ Ref<MLPPVector> MLPPActivation::coth_normv(const Ref<MLPPVector> &z) {
Ref<MLPPMatrix> MLPPActivation::coth_normm(const Ref<MLPPMatrix> &z) {
MLPPLinAlg alg;
return alg.division_element_wisenvnm(alg.onematnm(z->size().x, z->size().y), tanh_normm(z));
return alg.division_element_wisenvnm(alg.onematnm(z->size().y, z->size().x), tanh_normm(z));
}
real_t MLPPActivation::coth_derivr(real_t z) {
@ -2189,7 +2189,7 @@ Ref<MLPPVector> MLPPActivation::arsinh_normv(const Ref<MLPPVector> &z) {
Ref<MLPPMatrix> MLPPActivation::arsinh_normm(const Ref<MLPPMatrix> &z) {
MLPPLinAlg alg;
return alg.lognm(alg.additionnm(z, alg.sqrtnm(alg.additionnm(alg.hadamard_productnm(z, z), alg.onematnm(z->size().x, z->size().y)))));
return alg.lognm(alg.additionnm(z, alg.sqrtnm(alg.additionnm(alg.hadamard_productnm(z, z), alg.onematnm(z->size().y, z->size().x)))));
}
real_t MLPPActivation::arsinh_derivr(real_t z) {
@ -2205,7 +2205,7 @@ Ref<MLPPVector> MLPPActivation::arsinh_derivv(const Ref<MLPPVector> &z) {
Ref<MLPPMatrix> MLPPActivation::arsinh_derivm(const Ref<MLPPMatrix> &z) {
MLPPLinAlg alg;
return alg.division_element_wisenvnm(alg.onematnm(z->size().x, z->size().y), alg.sqrtnm(alg.additionnm(alg.hadamard_productnm(z, z), alg.onematnm(z->size().x, z->size().y))));
return alg.division_element_wisenvnm(alg.onematnm(z->size().y, z->size().x), alg.sqrtnm(alg.additionnm(alg.hadamard_productnm(z, z), alg.onematnm(z->size().y, z->size().x))));
}
//ARCOSH
@ -2222,7 +2222,7 @@ Ref<MLPPVector> MLPPActivation::arcosh_normv(const Ref<MLPPVector> &z) {
Ref<MLPPMatrix> MLPPActivation::arcosh_normm(const Ref<MLPPMatrix> &z) {
MLPPLinAlg alg;
return alg.lognm(alg.additionnm(z, alg.sqrtnm(alg.subtractionnm(alg.hadamard_productnm(z, z), alg.onematnm(z->size().x, z->size().y)))));
return alg.lognm(alg.additionnm(z, alg.sqrtnm(alg.subtractionnm(alg.hadamard_productnm(z, z), alg.onematnm(z->size().y, z->size().x)))));
}
real_t MLPPActivation::arcosh_derivr(real_t z) {
@ -2237,7 +2237,7 @@ Ref<MLPPVector> MLPPActivation::arcosh_derivv(const Ref<MLPPVector> &z) {
Ref<MLPPMatrix> MLPPActivation::arcosh_derivm(const Ref<MLPPMatrix> &z) {
MLPPLinAlg alg;
return alg.division_element_wisenvnm(alg.onematnm(z->size().x, z->size().y), alg.sqrtnm(alg.subtractionnm(alg.hadamard_productnm(z, z), alg.onematnm(z->size().x, z->size().y))));
return alg.division_element_wisenvnm(alg.onematnm(z->size().y, z->size().x), alg.sqrtnm(alg.subtractionnm(alg.hadamard_productnm(z, z), alg.onematnm(z->size().y, z->size().x))));
}
//ARTANH
@ -2254,7 +2254,7 @@ Ref<MLPPVector> MLPPActivation::artanh_normv(const Ref<MLPPVector> &z) {
Ref<MLPPMatrix> MLPPActivation::artanh_normm(const Ref<MLPPMatrix> &z) {
MLPPLinAlg alg;
return alg.scalar_multiplynm(0.5, alg.lognm(alg.division_element_wisenvnm(alg.additionnm(alg.onematnm(z->size().x, z->size().y), z), alg.subtractionnm(alg.onematnm(z->size().x, z->size().y), z))));
return alg.scalar_multiplynm(0.5, alg.lognm(alg.division_element_wisenvnm(alg.additionnm(alg.onematnm(z->size().y, z->size().x), z), alg.subtractionnm(alg.onematnm(z->size().y, z->size().x), z))));
}
real_t MLPPActivation::artanh_derivr(real_t z) {
@ -2269,7 +2269,7 @@ Ref<MLPPVector> MLPPActivation::artanh_derivv(const Ref<MLPPVector> &z) {
Ref<MLPPMatrix> MLPPActivation::artanh_derivm(const Ref<MLPPMatrix> &z) {
MLPPLinAlg alg;
return alg.division_element_wisenvnm(alg.onematnm(z->size().x, z->size().y), alg.subtractionnv(alg.onematnm(z->size().x, z->size().y), alg.hadamard_productnm(z, z)));
return alg.division_element_wisenvnm(alg.onematnm(z->size().y, z->size().x), alg.subtractionnv(alg.onematnm(z->size().y, z->size().x), alg.hadamard_productnm(z, z)));
}
//ARCSCH
@ -2294,9 +2294,9 @@ Ref<MLPPMatrix> MLPPActivation::arcsch_normm(const Ref<MLPPMatrix> &z) {
return alg.lognm(
alg.additionnm(
alg.sqrtnm(
alg.additionnm(alg.onematnm(z->size().x, z->size().y),
alg.division_element_wisenvnm(alg.onematnm(z->size().x, z->size().y), alg.hadamard_productnm(z, z)))),
alg.division_element_wisenvnm(alg.onematnm(z->size().x, z->size().y), z)));
alg.additionnm(alg.onematnm(z->size().y, z->size().x),
alg.division_element_wisenvnm(alg.onematnm(z->size().y, z->size().x), alg.hadamard_productnm(z, z)))),
alg.division_element_wisenvnm(alg.onematnm(z->size().y, z->size().x), z)));
}
real_t MLPPActivation::arcsch_derivr(real_t z) {
@ -2315,10 +2315,10 @@ Ref<MLPPMatrix> MLPPActivation::arcsch_derivm(const Ref<MLPPMatrix> &z) {
MLPPLinAlg alg;
return alg.division_element_wisenvnm(
alg.fullnm(z->size().x, z->size().y, -1),
alg.fullnm(z->size().y, z->size().x, -1),
alg.hadamard_productnm(alg.hadamard_productnm(z, z),
alg.sqrtnm(alg.additionnm(alg.onematnm(z->size().x, z->size().y),
alg.division_element_wisenvnm(alg.onematnm(z->size().x, z->size().y), alg.hadamard_productnm(z, z))))));
alg.sqrtnm(alg.additionnm(alg.onematnm(z->size().y, z->size().x),
alg.division_element_wisenvnm(alg.onematnm(z->size().y, z->size().x), alg.hadamard_productnm(z, z))))));
}
//ARSECH
@ -2345,16 +2345,16 @@ Ref<MLPPMatrix> MLPPActivation::arsech_normm(const Ref<MLPPMatrix> &z) {
return alg.lognm(
alg.additionnm(
alg.division_element_wisenvnm(
alg.onematnm(z->size().x, z->size().y), z),
alg.onematnm(z->size().y, z->size().x), z),
alg.hadamard_productnm(
alg.additionnm(
alg.division_element_wisenvnm(
alg.onematnm(z->size().x, z->size().y), z),
alg.onematnm(z->size().x, z->size().y)),
alg.onematnm(z->size().y, z->size().x), z),
alg.onematnm(z->size().y, z->size().x)),
alg.subtractionnm(
alg.division_element_wisenvnm(
alg.onematnm(z->size().x, z->size().y), z),
alg.onematnm(z->size().x, z->size().y)))));
alg.onematnm(z->size().y, z->size().x), z),
alg.onematnm(z->size().y, z->size().x)))));
}
real_t MLPPActivation::arsech_derivr(real_t z) {
@ -2376,10 +2376,10 @@ Ref<MLPPMatrix> MLPPActivation::arsech_derivm(const Ref<MLPPMatrix> &z) {
MLPPLinAlg alg;
return alg.division_element_wisenvnm(
alg.fullnm(z->size().x, z->size().y, -1),
alg.fullnm(z->size().y, z->size().x, -1),
alg.hadamard_productnm(
z,
alg.sqrtnm(alg.subtractionnm(alg.onematnm(z->size().x, z->size().y), alg.hadamard_productnm(z, z)))));
alg.sqrtnm(alg.subtractionnm(alg.onematnm(z->size().y, z->size().x), alg.hadamard_productnm(z, z)))));
}
//ARCOTH
@ -2400,7 +2400,7 @@ Ref<MLPPMatrix> MLPPActivation::arcoth_normm(const Ref<MLPPMatrix> &z) {
return alg.scalar_multiplynm(
0.5,
alg.lognm(alg.division_element_wisenvnm(alg.additionnm(alg.onematnm(z->size().x, z->size().y), z), alg.subtractionnm(z, alg.onematnm(z->size().x, z->size().y)))));
alg.lognm(alg.division_element_wisenvnm(alg.additionnm(alg.onematnm(z->size().y, z->size().x), z), alg.subtractionnm(z, alg.onematnm(z->size().y, z->size().x)))));
}
real_t MLPPActivation::arcoth_derivr(real_t z) {
@ -2415,7 +2415,7 @@ Ref<MLPPVector> MLPPActivation::arcoth_derivv(const Ref<MLPPVector> &z) {
Ref<MLPPMatrix> MLPPActivation::arcoth_derivm(const Ref<MLPPMatrix> &z) {
MLPPLinAlg alg;
return alg.division_element_wisenvnm(alg.onematnm(z->size().x, z->size().y), alg.subtractionnm(alg.onematnm(z->size().x, z->size().y), alg.hadamard_productnm(z, z)));
return alg.division_element_wisenvnm(alg.onematnm(z->size().y, z->size().x), alg.subtractionnm(alg.onematnm(z->size().y, z->size().x), alg.hadamard_productnm(z, z)));
}
void MLPPActivation::_bind_methods() {