models/dense_net.py
def _initialize_session(self):
        """
        Starts a TensorFlow session with the correct configuration.
        Then tells TensorFlow to initialize all variables, create a saver
        and a log file writer.
        """
        config = tf.ConfigProto()

        # specify the CPU inter and intra threads used by MKL
        config.intra_op_parallelism_threads = self.num_intra_threads
        config.inter_op_parallelism_threads = self.num_inter_threads

        # restrict model GPU memory utilization to the minimum required
        config.gpu_options.allow_growth = True
        self.sess = tf.Session(config=config)

        # initialize variables, create saver, create log file writers
        self._initialize_all_variables()
        self.saver = tf.train.Saver()
        if self.should_save_logs:
            if TF_VERSION[0] >= 0 and TF_VERSION[1] >= 10:
                logswriter = tf.summary.FileWriter
            else:
                logswriter = tf.train.SummaryWriter
            self.summary_writer = logswriter(self.logs_path)
        if self.should_save_ft_logs:
            self.feature_writer = open('./%s.csv' % self.ft_logs_path, "w")

        Starts a TensorFlow session with the correct configuration.
        Then tells TensorFlow to initialize all variables, create a saver
        and a log file writer.
        
Starts a TensorFlow session with the correct configuration.
Then tells TensorFlow to initialize all variables, create a saver
and a log file writer.
Starts a TensorFlow session with the correct configuration . Then tells TensorFlow to initialize all variables create a saver and a log file writer .
def _initialize_session(self):
        config = tf.ConfigProto()
        config.intra_op_parallelism_threads = self.num_intra_threads
        config.inter_op_parallelism_threads = self.num_inter_threads
        config.gpu_options.allow_growth = True
        self.sess = tf.Session(config=config)
        self._initialize_all_variables()
        self.saver = tf.train.Saver()
        if self.should_save_logs:
            if TF_VERSION[0] >= 0 and TF_VERSION[1] >= 10:
                logswriter = tf.summary.FileWriter
            else:
                logswriter = tf.train.SummaryWriter
            self.summary_writer = logswriter(self.logs_path)
        if self.should_save_ft_logs:
            self.feature_writer = open('./%s.csv' % self.ft_logs_path, "w")
def _initialize_session ( self ) : config = tf . ConfigProto ( ) config . intra_op_parallelism_threads = self . num_intra_threads config . inter_op_parallelism_threads = self . num_inter_threads config . gpu_options . allow_growth = True self . sess = tf . Session ( config = config ) self . _initialize_all_variables ( ) self . saver = tf . train . Saver ( ) if self . should_save_logs : if TF_VERSION [ 0 ] >= 0 and TF_VERSION [ 1 ] >= 10 : logswriter = tf . summary . FileWriter else : logswriter = tf . train . SummaryWriter self . summary_writer = logswriter ( self . logs_path ) if self . should_save_ft_logs : self . feature_writer = open ( './%s.csv' % self . ft_logs_path , "w" )
Starts a TensorFlow session with the correct configuration.
Starts a TensorFlow session with the correct configuration .
"""
        Starts a TensorFlow session with the correct configuration.
        Then tells TensorFlow to initialize all variables, create a saver
        and a log file writer.
        """ # specify the CPU inter and intra threads used by MKL # restrict model GPU memory utilization to the minimum required # initialize variables, create saver, create log file writers
self