import tensorflow as tf

		'''
		# Value FC
		value         = Dense(units=1, kernel_initializer=normalized_columns_initializer(1.0), bias_initializer=None, activation=None)(inputs=self.rnn_out)

		# rnn_out_frozen = tf.stop_gradient(self.rnn_out)
		next_loc_mean  = Dense(units=2, kernel_initializer=normalized_columns_initializer(1.0), bias_initializer=None, activation=tf.math.tanh)(inputs=self.rnn_out)	# was rnn_out_frozen
		loc_std        = Dense(units=1, kernel_initializer=normalized_columns_initializer(1.0), activation=tf.nn.softplus)(inputs = self.rnn_out)

		# Policy FC
		next_loc       = tf.clip_by_value(next_loc_mean + tf.random_normal([1,2], 0, loc_std), -1, 1)
		# next_loc       = tf.stop_gradient(next_loc)

		return value, next_loc_mean, loc_std, next_loc, state_out, state_in, state_init
