def init(config_filename, log_verbosity, remaining_args=()):
"""
:param str config_filename: filename to config-file
:param int log_verbosity:
:param list[str] remaining_args:
"""
rnn.init_better_exchook()
rnn.init_thread_join_hack()
print("Using config file %r." % config_filename)
assert os.path.exists(config_filename)
rnn.init_config(config_filename=config_filename,
command_line_options=remaining_args,
extra_updates={
"use_tensorflow": True,
"log": None,
"log_verbosity": log_verbosity,
"task": "search",
},
default_config={
"debug_print_layer_output_template": True,
})
global config
config = rnn.config
rnn.init_log()
print("Returnn %s starting up." % os.path.basename(__file__), file=log.v1)
rnn.returnn_greeting()
rnn.init_backend_engine()
assert util.BackendEngine.is_tensorflow_selected(
), "this is only for TensorFlow"
rnn.init_faulthandler()
better_exchook.replace_traceback_format_tb() # makes some debugging easier
rnn.init_config_json_network()
def setup():
"""
Calls necessary setups.
"""
# Disable extensive TF debug verbosity. Must come before the first TF import.
import logging
logging.getLogger('tensorflow').disabled = True
# os.environ['TF_CPP_MIN_LOG_LEVEL'] = '0'
# logging.getLogger("tensorflow").setLevel(logging.INFO)
# Get us some further useful debug messages (in some cases, e.g. CUDA).
# For example: https://github.com/tensorflow/tensorflow/issues/24496
# os.environ["CUDNN_LOGINFO_DBG"] = "1"
# os.environ["CUDNN_LOGDEST_DBG"] = "stdout"
# The following might fix (workaround): Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
# (https://github.com/tensorflow/tensorflow/issues/24496).
# os.environ["TF_FORCE_GPU_ALLOW_GROWTH"] = "true"
import _setup_returnn_env # noqa
import returnn.util.basic as util
util.init_thread_join_hack()
from returnn.util import better_exchook
better_exchook.install()
better_exchook.replace_traceback_format_tb()
from returnn.log import log
log.initialize(verbosity=[5])
# TF is optional.
# Note that importing TF still has a small side effect:
# BackendEngine._get_default_engine() will return TF by default, if TF is already loaded.
# For most tests, this does not matter.
try:
import tensorflow as tf
except ImportError:
tf = None
if tf:
import returnn.tf.util.basic as tf_util
tf_util.debug_register_better_repr()
import returnn.util.debug as debug
debug.install_lib_sig_segfault()
try:
import faulthandler
# Enable after libSigSegfault, so that we have both,
# because faulthandler will also call the original sig handler.
faulthandler.enable()
except ImportError:
print("no faulthandler")
# -*- coding: utf8 -*-
import sys
import os
my_dir = os.path.dirname(os.path.realpath(__file__))
import _setup_test_env # noqa
from nose.tools import assert_equal, assert_not_equal, assert_raises, assert_true, assert_is
from numpy.testing.utils import assert_almost_equal
from returnn.util.basic import *
import numpy as np
import numpy
import unittest
from returnn.util import better_exchook
better_exchook.replace_traceback_format_tb()
def test_cmd_true():
r = sys_cmd_out_lines("true")
assert_equal(r, [])
def test_cmd_false():
assert_raises(CalledProcessError, lambda: sys_cmd_out_lines("false"))
def test_cmd_stdout():
r = sys_cmd_out_lines("echo 1; echo 2;")
assert_equal(r, ["1", "2"])
