def ensure_plasma_tensorflow_op():
base_path = os.path.join(pyarrow.__path__[0], "tensorflow")
lock_path = os.path.join(base_path, "compile_op.lock")
with filelock.FileLock(lock_path):
if not os.path.exists(os.path.join(base_path, "plasma_op.so")):
plasma.build_plasma_tensorflow_op()
else:
plasma.load_plasma_tensorflow_op()
def ensure_plasma_tensorflow_op():
base_path = os.path.join(pyarrow.__path__[0], "tensorflow")
lock_path = os.path.join(base_path, "compile_op.lock")
with filelock.FileLock(lock_path):
if not os.path.exists(os.path.join(base_path, "plasma_op.so")):
plasma.build_plasma_tensorflow_op()
else:
plasma.load_plasma_tensorflow_op()
def __init__(self, worker_index, config, logdir):
logger.warning(f'Create agent {worker_index}')
self.dconfig = utils.DotDict(config)
self.logdir = logdir
self.worker_index = worker_index
self.locals = None
self.feed_dict = None
self.objective_vars_oid = None
self.datasets_initialized = False
import tensorflow as tf
plasma.load_plasma_tensorflow_op()
logger.warning(f'Created agent {worker_index}')
def __init__(self, config, init_vars):
import tensorflow as tf
dconfig = utils.DotDict(config)
plasma.load_plasma_tensorflow_op()
store_socket = utils.get_store_socket()
self.var_oid = None
self.obj_vars = [
tf.Variable(init_var, name='obj_var', dtype=tf.float32)
for init_var in init_vars
]
self.plasma_grads_oids = tf.placeholder(shape=[dconfig.agent_count],
dtype=tf.string,
name="plasma_grads_oids")
self.plasma_vars_oid = tf.placeholder(shape=[],
dtype=tf.string,
name="plasma_vars_oids")
shapes = [v.shape for v in self.obj_vars]
grads = utils.reverse_flat(
tf.reduce_mean([
plasma.tf_plasma_op.plasma_to_tensor(
self.plasma_grads_oids[a],
dtype=tf.float32,
plasma_store_socket_name=store_socket)
for a in range(dconfig.agent_count)
],
axis=0), shapes)
obj_optimizer = tf.train.AdamOptimizer(
learning_rate=dconfig.obj_func_learning_rate)
self.train_obj_op = obj_optimizer.apply_gradients(
zip(grads, self.obj_vars))
with tf.control_dependencies([self.train_obj_op]):
import tensorflow as tf
self.update_vars = plasma.tf_plasma_op.tensor_to_plasma(
[utils.flat(self.obj_vars)],
self.plasma_vars_oid,
plasma_store_socket_name=store_socket)
config = tf.ConfigProto()
config.gpu_options.allow_growth = True
self.sess = tf.Session(config=config)
self.sess.run(tf.global_variables_initializer())