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
python类OptimizerOptions()的实例源码
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 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 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.log_device_placement = False
config.allow_soft_placement = False
return config
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 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(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)