void apply(cube<real>& v, real bias) noexcept override
{
real* d = v.data();
size_t n = v.num_elements();
for ( size_t i = 0; i < n; ++i )
d[i] = f_(d[i] + bias);
}
typename std::enable_if<has_public_member_grad<T>::value>::type
apply_grad(cube<real>& g, const cube<real>& f, const T& fn) noexcept
{
real* gp = g.data();
const real* fp = f.data();
size_t n = g.num_elements();
for ( size_t i = 0; i < n; ++i )
gp[i] *= fn.grad(fp[i]);
}
inline void convolve_constant( cube<T> const & a,
identity_t<T> b,
cube<T> & r) noexcept
{
ZI_ASSERT(size(a)==size(r));
T const * ap = a.data();
T * rp = r.data();
for ( size_t i = 0; i < r.num_elements(); ++i )
rp[i] = ap[i] * b;
}
inline T convolve_constant_flipped( cube<T> const & a,
cube<T> const & b ) noexcept
{
ZI_ASSERT(size(a)==size(b));
T r = 0;
T const * ap = a.data();
T const * bp = b.data();
for ( size_t i = 0; i < a.num_elements(); ++i )
r += ap[i] * bp[i];
return r;
}
// performs inplace dropout backward
inline void dropout_backward(cube<real> & g)
{
ZI_ASSERT(mask_);
size_t s = g.num_elements();
for ( size_t i = 0; i < s; ++i )
{
if ( mask_->data()[i] )
g.data()[i] *= scale();
else
g.data()[i] = static_cast<real>(0);
}
// Should we reset mask_ here?
}
// performs inplace dropout and returns dropout mask
inline void dropout_forward(cube<real>& f)
{
if ( !mask_ )
{
mask_ = get_cube<bool>(size(f));
}
// new random mask
bernoulli_init<bool>(ratio_).initialize(mask_);
size_t s = f.num_elements();
for ( size_t i = 0; i < s; ++i )
{
// dropout
if ( mask_->data()[i] )
f.data()[i] *= scale();
else
f.data()[i] = static_cast<real>(0);
}
}
std::tuple<real,real,cube_p<real>> square_loss( cube<real> const & cprop,
cube<real> const & clab )
{
std::tuple<real,real,cube_p<real>> ret;
std::get<0>(ret) = 0;
std::get<1>(ret) = 0;
std::get<2>(ret) = get_copy(cprop);
real* grad = std::get<2>(ret)->data();
const real* lab = clab.data();
long_t n = clab.num_elements();
for ( long_t i = 0; i < n; ++i )
{
std::get<1>(ret) += ( grad[i] > 0.5 ? ( lab[i] > 0.5 ? 0 : 1 ) : ( lab[i] > 0.5 ? 1 : 0 ) );
grad[i] -= lab[i];
std::get<0>(ret) += grad[i]*grad[i];
grad[i] *= 2;
}
return ret;
}