Pantheon S2E3 @ 2:44

[zontasticality]

Thought this was kinda cool :)

Pantheon IMDB: https://www.imdb.com/title/tt11680642/

C-Plus-Plus/machine_learning/neural_network.cpp

Lines 149 to 191 in f1eddf4

	activation_function = neural_network::activations::relu;
	dactivation_function = neural_network::activations::drelu;
	} else if (activation == "tanh") {
	activation_function = neural_network::activations::tanh;
	dactivation_function = neural_network::activations::dtanh;
	} else if (activation == "none") {
	// Set identity function in casse of none is supplied
	activation_function =
	neural_network::util_functions::identity_function;
	dactivation_function =
	neural_network::util_functions::identity_function;
	} else {
	// If supplied activation is invalid
	std::cerr << "ERROR (" << __func__ << ") : ";
	std::cerr << "Invalid argument. Expected {none, sigmoid, relu, "
	"tanh} got ";
	std::cerr << activation << std::endl;
	std::exit(EXIT_FAILURE);
	}
	this->activation = activation; // Setting activation name
	this->neurons = neurons; // Setting number of neurons
	// Initialize kernel according to flag
	if (random_kernel) {
	uniform_random_initialization(kernel, kernel_shape, -1.0, 1.0);
	} else {
	unit_matrix_initialization(kernel, kernel_shape);
	}
	}
	/**
	* Constructor for neural_network::layers::DenseLayer class
	* @param neurons number of neurons
	* @param activation activation function for layer
	* @param kernel values of kernel (useful in loading model)
	*/
	DenseLayer(const int &neurons, const std::string &activation,
	const std::vector<std::valarray<double>> &kernel) {
	// Choosing activation (and it's derivative)
	if (activation == "sigmoid") {
	activation_function = neural_network::activations::sigmoid;
	dactivation_function = neural_network::activations::sigmoid;
	} else if (activation == "relu") {
	activation_function = neural_network::activations::relu;
	dactivation_function = neural_network::activations::drelu;

[realstealthninja]

Did this tv show show code from this repo? thats very cool! thanks for sharing