{

std::vector<unsigned int> temp = shape_input[0].first;

const std::type_info& type = shape_input[0].second;

for (auto& it : dims_mean)

temp[it] = 1U;

if (!this->gamma.has_tensor())

this->gamma = value::values(temp, 1).tensor_cast(type);

if (!this->beta.has_tensor())

this->beta = value::values(temp, 0).tensor_cast(type);

if (!this->moving_mean.has_tensor())

this->moving_mean = value::values(temp, 0).tensor_cast(type);

if (!this->moving_variance.has_tensor())

this->moving_variance = value::values(temp, 1).tensor_cast(type);

this->moving_mean = this->moving_mean.clone();

this->moving_variance = this->moving_variance.clone();

{

value::Tensor normal;

if (tensor_array::value::use_grad)

{

value::Tensor temp_mean = input.mean(this->dims_mean);

value::Tensor temp_variance = input.variance(this->dims_mean);

normal = (input - temp_mean) / power(add(temp_variance, value::values(input.get_buffer().shape(), this->eps)), value::values(input.get_buffer().shape(), .5f));

this->moving_mean *= value::values(this->moving_mean.get_buffer().shape(), 1.f - momentum);

this->moving_mean += (value::values(temp_mean.get_buffer().shape(), momentum) * temp_mean);

this->moving_mean = this->moving_mean.clone();

this->moving_variance *= value::values(this->moving_variance.get_buffer().shape(), 1.f - momentum);

this->moving_variance += (value::values(temp_variance.get_buffer().shape(), momentum) * temp_variance);

this->moving_variance = this->moving_variance.clone();

}

else

normal = (input - this->moving_mean) / power(add(this->moving_variance, value::values(input.get_buffer().shape(), this->eps)), value::values(input.get_buffer().shape(), .5f)).clone();

return gamma * normal + beta;

eps(eps),

momentum(momentum),

dims_mean(dims_mean),

moving_mean(),

moving_variance(),

gamma(),

beta()

{

this->map_tensor.insert(std::make_pair("gamma", &gamma));

this->map_tensor.insert(std::make_pair("beta", &beta));

this->map_tensor.insert(std::make_pair("moving_mean", &moving_mean));

this->map_tensor.insert(std::make_pair("moving_variance", &moving_variance));