def setup():
"""
Very use full if you use tensorflow-gpu and your using your GPU at the ame time -> tensorflow want to use the
whole Video Ram
:return: None
"""
config = ConfigProto()
config.gpu_options.allow_growth = True
config.log_device_placement = True
session = InteractiveSession(config=config)
set_session(session)
# check if directories for models and logs exists, if not there are created
if not os.path.isdir("models"):
os.mkdir("models")
if not os.path.isdir("logs"):
os.mkdir("logs")
#!/usr/bin/env python3
# if version.parse(tf.__version__).release[0] >= 2:
# THIS SEEMS TO WORK IN BOTH tf 2 and 1
from packaging import version
import tensorflow as tf
from tensorflow.keras.backend import set_session
from tensorflow.compat.v1 import ConfigProto
from tensorflow.compat.v1 import InteractiveSession, Session
config = ConfigProto()
config.gpu_options.allow_growth = True
config.log_device_placement = True # to log device placement (on which device the operation ran)
# session = InteractiveSession(config=config)
import tensorflow as tf
session = Session(config=config)
set_session(
session) # set this TensorFlow session as the default session for Keras
import tensorflow.keras as keras
from tensorflow.keras.datasets import mnist
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout
from tensorflow.keras.layers import Flatten, MaxPooling2D, Conv2D
from tensorflow.keras.callbacks import TensorBoard
(X_train, y_train), (X_test, y_test) = mnist.load_data()
X_train = X_train.reshape(60000, 28, 28, 1).astype('float32')
X_test = X_test.reshape(10000, 28, 28, 1).astype('float32')
import tensorflow as tf
from tensorflow.python.framework import ops
ops.reset_default_graph()
#tf.compat.v1.disable_eager_execution()
#init = tf.compat.v1.global_variables_initializer()
from model import build_model
from tensorflow.compat.v1 import ConfigProto
from tensorflow.compat.v1 import InteractiveSession
config = ConfigProto()
config.gpu_options.allow_growth = True
config.allow_soft_placement = True
config.log_device_placement = True
#session = InteractiveSession(config=config)
tensor_regex = re.compile('.*:\d*')
# Get a tensor by name, convenience method
def t(tensor_name):
tensor_name = tensor_name + ":0" if not tensor_regex.match(
tensor_name) else tensor_name
return tf.compat.v1.get_default_graph().get_tensor_by_name(tensor_name)
# Called from train_ann to perform a test of the train or test data, needs to separate pos/neg to get accurate #'s
def train_ann_test_batch(
sess,
from keras.backend.tensorflow_backend import set_session from tensorflow.compat.v1 import ConfigProto from tensorflow.compat.v1 import InteractiveSession, Session config = ConfigProto() config.gpu_options.allow_growth = True config.log_device_placement = True # to log device placement (on which device the operation ran) # session = InteractiveSession(config=config) import tensorflow as tf session = tf.Session(config=config) set_session(session) # set this TensorFlow session as the default session for Keras
