我们从Python开源项目中，提取了以下18个代码示例，用于说明如何使用tensorflow.GraphOptions()。
def _session_config(self): """Creates the session config with t2t default parameters.""" graph_options = tf.GraphOptions(optimizer_options=tf.OptimizerOptions( opt_level=tf.OptimizerOptions.L1, do_function_inlining=False)) if self._single_cpu_thread: config = tf.ConfigProto( intra_op_parallelism_threads=1, inter_op_parallelism_threads=1, allow_soft_placement=True, graph_options=graph_options, log_device_placement=False) else: gpu_options = tf.GPUOptions( per_process_gpu_memory_fraction=0.95) config = tf.ConfigProto( allow_soft_placement=True, graph_options=graph_options, gpu_options=gpu_options, log_device_placement=False) return config
def session_config(params): optimizer_options = tf.OptimizerOptions(opt_level=tf.OptimizerOptions.L1, do_function_inlining=False) graph_options = tf.GraphOptions(optimizer_options=optimizer_options) config = tf.ConfigProto(allow_soft_placement=True, graph_options=graph_options) if params.device_list: device_str = ",".join([str(i) for i in params.device_list]) config.gpu_options.visible_device_list = device_str return config
def session_config(params): optimizer_options = tf.OptimizerOptions(opt_level=tf.OptimizerOptions.L1, do_function_inlining=True) graph_options = tf.GraphOptions(optimizer_options=optimizer_options) config = tf.ConfigProto(allow_soft_placement=True, graph_options=graph_options) if params.device_list: device_str = ",".join([str(i) for i in params.device_list]) config.gpu_options.visible_device_list = device_str return config
def create_session(): # config = tf.ConfigProto(graph_options=tf.GraphOptions(optimizer_options=tf.OptimizerOptions(opt_level=tf.OptimizerOptions.L0))) config = tf.ConfigProto() sess = tf.InteractiveSession("", config=config) return sess
def session_config(): optimizer_options = tf.OptimizerOptions(opt_level=tf.OptimizerOptions.L0) config = tf.ConfigProto( graph_options=tf.GraphOptions(optimizer_options=optimizer_options)) config.log_device_placement = False config.allow_soft_placement = False return config
def session_config(): optimizer_options = tf.OptimizerOptions(opt_level=tf.OptimizerOptions.L0) graph_options = tf.GraphOptions(optimizer_options=optimizer_options) config = tf.ConfigProto(graph_options=graph_options, intra_op_parallelism_threads=10, inter_op_parallelism_threads=10)
def create_session(): config = tf.ConfigProto(log_device_placement=False, graph_options=tf.GraphOptions(optimizer_options=tf.OptimizerOptions(opt_level=tf.OptimizerOptions.L0))) return tf.InteractiveSession(config=config)
def worker(): """Worker script that runs on AWS machine. Adds vectors of ones forever, prints MB/s.""" def session_config(): optimizer_options = tf.OptimizerOptions(opt_level=tf.OptimizerOptions.L0) config = tf.ConfigProto( graph_options=tf.GraphOptions(optimizer_options=optimizer_options)) config.operation_timeout_in_ms = 10*1000 # abort after 10 seconds return config params_size = 250*1000*FLAGS.data_mb # 1MB is 250k floats dtype=tf.float32 val = tf.ones((), dtype=dtype) vals = tf.fill([params_size], val) params = tf.Variable(vals) update = params.assign_add(vals) sess = tf.Session(config=session_config()) sess.run(params.initializer) while True: start_time = time.perf_counter() for i in range(FLAGS.iters_per_step): sess.run(update.op) elapsed_time = time.perf_counter() - start_time rate = float(FLAGS.iters_per_step)*FLAGS.data_mb/elapsed_time print('%.2f MB/s'%(rate,))
def session_config(): optimizer_options = tf.OptimizerOptions(opt_level=tf.OptimizerOptions.L0) config = tf.ConfigProto( graph_options=tf.GraphOptions(optimizer_options=optimizer_options)) config.operation_timeout_in_ms = 10*1000 # abort after 10 seconds return config
def create_session_config(log_device_placement=False, enable_graph_rewriter=False, gpu_mem_fraction=0.95, use_tpu=False): """The TensorFlow Session config to use.""" if use_tpu: graph_options = tf.GraphOptions() else: if enable_graph_rewriter: rewrite_options = rewriter_config_pb2.RewriterConfig() rewrite_options.optimizers.append("pruning") rewrite_options.optimizers.append("constfold") rewrite_options.optimizers.append("arithmetic") rewrite_options.optimizers.append("layout") graph_options = tf.GraphOptions(rewrite_options=rewrite_options) else: graph_options = tf.GraphOptions( optimizer_options=tf.OptimizerOptions( opt_level=tf.OptimizerOptions.L1, do_function_inlining=False)) gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=gpu_mem_fraction) config = tf.ConfigProto( allow_soft_placement=True, graph_options=graph_options, gpu_options=gpu_options, log_device_placement=log_device_placement) return config
def create_session(): config = tf.ConfigProto(log_device_placement=False,graph_options=tf.GraphOptions(optimizer_options=tf.OptimizerOptions(opt_level=tf.OptimizerOptions.L0))) return tf.InteractiveSession(config=config)
def create_session(): config = tf.ConfigProto(log_device_placement=True,graph_options=tf.GraphOptions(optimizer_options=tf.OptimizerOptions(opt_level=tf.OptimizerOptions.L0))) return tf.InteractiveSession(config=config)
