def _connect():
try:
self.connection_props = deepdrive_client.create(
'127.0.0.1', 9876)
if isinstance(self.connection_props, int):
raise Exception(
'You have an old version of the deepdrive client - try uninstalling and reinstalling with pip'
)
if not self.connection_props or not self.connection_props[
'max_capture_resolution']:
# Try again
return
self.client_id = self.connection_props['client_id']
server_version = semvar(
self.connection_props['server_protocol_version']).version
# TODO: For dev, store hash of .cpp and .h files on extension build inside VERSION_DEV, then when
# connecting, compute same hash and compare. (Need to figure out what to do on dev packaged version as
# files may change - maybe ignore as it's uncommon).
# Currently, we timestamp the build, and set that as the version in the extension. This is fine unless
# you change shared code and build the extension only, then the versions won't change, and you could
# see incompatibilities.
if semvar(
self.client_version).version[:2] != server_version[:2]:
raise RuntimeError(
'Server and client major/minor version do not match - server is %s and client is %s'
% (server_version, self.client_version))
except deepdrive_client.time_out:
_connect()
def check_bindings_version():
# TODO: Bindings name change
bindings_version = semvar(
pkg_resources.get_distribution(
c.BINDINGS_PACKAGE_NAME).version).version[:2]
client_version = c.MAJOR_MINOR_VERSION
if bindings_version != client_version:
print("""ERROR: Python bindings version mismatch.
Expected {client_version_str}, got {bindings_version_str}
HINT:
For binary sim distributions, try:
pip install package=={client_version_str}.*
For source sim distributions, try:
cd <your-sim-sources>/Plugins/DeepDrivePlugin/Source/DeepDrivePython
python build/build.py --type dev
""".format(
client_version=client_version,
bindings_version=bindings_version,
client_version_str='.'.join(str(vx) for vx in client_version),
bindings_version_str='.'.join(str(vx) for vx in bindings_version),
))
exit(1)
def check_tensorflow_gpu(is_install=False):
error_msg = \
'\n\n*** Warning: %s, Tensorflow agents will not be available. ' \
'HINT: Install Tensorflow or use the python / virtualenv ' \
'you have it already installed to. ' \
'If you install, check out our Tensorflow install ' \
'tips on the README ' \
'\n\n'
print('Checking for valid Tensorflow installation')
# noinspection PyUnresolvedReferences
if not check_nvidia_docker():
print(error_msg % 'Using Docker but not nvidia-docker runtime',
file=sys.stderr)
ret = False
else:
if not is_install:
import h5py # importing tensorflow later causes seg faults
try:
# noinspection PyUnresolvedReferences
import tensorflow as tf
except ImportError:
print(error_msg % 'Tensorflow not installed', file=sys.stderr)
ret = False
else:
min_version = '1.7'
max_version = '2.0'
if semvar(tf.__version__) < semvar(min_version):
warn_msg = 'Tensorflow %s is less than the minimum ' \
'required version (%s)' \
% (tf.__version__, min_version)
print(error_msg % warn_msg, file=sys.stderr)
ret = False
elif semvar(tf.__version__) >= semvar(max_version):
warn_msg = 'Tensorflow %s is greater or equal to the maximum ' \
'required version (%s)' \
% (tf.__version__, min_version)
print(error_msg % warn_msg, file=sys.stderr)
ret = False
else:
print('Tensorflow %s detected - meets min version'
' (%s)' % (tf.__version__, min_version))
ret = True
return ret
def get_tf_valid():
error_msg = '\n\n*** Warning: %s, baseline imitation learning agent will not be available. ' \
'HINT: Install Tensorflow or use the python / virtualenv you have it already installed to. If you install, check out our Tensorflow install tips on the README ' \
'\n\n'
print('Checking for valid Tensorflow installation')
try:
# noinspection PyUnresolvedReferences
import tensorflow as tf
check = tf.constant(
'string tensors are not tensors but are called tensors in tensorflow'
)
with tf.Session(config=tf.ConfigProto(
log_device_placement=False,
gpu_options=tf.GPUOptions(per_process_gpu_memory_fraction=0.01,
allow_growth=True))) as sess:
if not get_available_gpus():
print(
'\n\n*** Warning: %s \n\n' %
'Tensorflow could not find a GPU, performance will be severely degraded on CPU. '
'HINT: Try "pip install tensorflow-gpu"')
return False
sess.run(check)
print('Tensorflow is working on the GPU.')
except ImportError:
print(error_msg % 'Tensorflow not installed', file=sys.stderr)
return False
except Exception:
print(error_msg % 'Tensorflow not working', file=sys.stderr)
return False
min_version = '1.1'
if semvar(tf.__version__) < semvar(min_version):
warn_msg = 'Tensorflow %s is less than the minimum required version (%s)' % (
tf.__version__, min_version)
print(error_msg % warn_msg, file=sys.stderr)
return False
else:
print('Tensorflow %s detected - meets min version (%s)' %
(tf.__version__, min_version))
return True
from distutils.version import LooseVersion as semvar from config.directories import * # Version VERSION_STR = open(os.path.join(ROOT_DIR, 'VERSION')).read() MAJOR_MINOR_VERSION = semvar(VERSION_STR).version[:2] MAJOR_MINOR_VERSION_STR = '.'.join(str(vx) for vx in MAJOR_MINOR_VERSION)
def get_version_info():
version_str = open(os.path.join(DIR, 'VERSION')).read().strip()
major_minor_version = semvar(version_str).version[:2]
major_minor_version_str = '.'.join(str(vx) for vx in major_minor_version)
return version_str, major_minor_version, major_minor_version_str