def get_metrics(generator_inputs, generated_data, real_data, discriminator_real_outputs, discriminator_gen_outputs): del generator_inputs, discriminator_real_outputs, discriminator_gen_outputs return { 'mse_custom_metric': metrics_lib.mean_squared_error( real_data, generated_data) }
def _metric_fn(x): labels = x["labels"] predictions = x["predictions"] return metrics.mean_squared_error(labels, predictions)
def _metric_fn(x): labels = x["labels"] predictions = x["predictions"] return metrics.mean_squared_error(labels, predictions)
def get_metrics(gan_model): return { 'mse_custom_metric': metrics_lib.mean_squared_error(gan_model.real_data, gan_model.generated_data) }
def get_metrics(gan_model): return { 'mse_custom_metric': metrics_lib.mean_squared_error( gan_model.real_data, gan_model.generated_data) }