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())