def can_train():
tf_found = importlib.util.find_spec('tensorflow')
available_backends = []
if tf_found:
# thanks to https://github.com/pydata/pandas/issues/2841
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
from tensorflow import __version__ as tfv
required = "1.6.0"
# only require major and minor release number as the patch number may contain 'rc' etc
if versiontuple(tfv, 2) >= versiontuple(required, 2):
available_backends.append("tensorflow")
# return available_backends
# removing plain tensorflow from deeprace for now, TFv1 API is just too hard to master under time constraints
return []
def can_train():
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
keras_found = importlib.util.find_spec('keras')
available_backends = []
if keras_found:
from keras import __version__ as kv
max_version = "2.2.4"
min_version = "2.1.0"
if versiontuple(kv, 3) >= versiontuple(min_version, 3) and versiontuple(kv, 3) <= versiontuple(max_version, 3):
available_backends.append("keras")
else:
logging.debug("your keras version %s is not supported (%s - %s)", str(kv), min_version, max_version)
return available_backends
def can_train():
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
tf_found = importlib.util.find_spec('tensorflow')
available_backends = []
if tf_found:
import tensorflow as tf
tf_version = tf.__version__
tfkeras_version = tf.keras.__version__
tfkeras_clean_version = tf.keras.__version__.replace("-tf", "")
min_version = "2.1.0"
if versiontuple(tfkeras_clean_version, 3) >= versiontuple(
min_version, 3):
available_backends.append("tensorflow.keras")
else:
logging.debug("your keras version %s is not supported (%s - %s)",
str(kv), min_version, max_version)
return available_backends