def config_tf():
from mCNN.queueGPU import queueGPU
CUDA_rate = '0.25'
## config TF
queueGPU(USER_MEM=3500, INTERVAL=60)
# os.environ['CUDA_VISIBLE_DEVICES'] = CUDA
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
if CUDA_rate != 'full':
config = tf.ConfigProto()
if float(CUDA_rate) < 0.1:
config.gpu_options.allow_growth = True
else:
config.gpu_options.per_process_gpu_memory_fraction = float(CUDA_rate)
set_session(tf.Session(config=config))
# objective = pearson_coeff * 2 + std
# return {'loss': -objective, 'status': STATUS_OK}
#
# elif obj == 'val_mae':
# validation_mae = np.amax(result.history['val_mean_absolute_error'])
# print('Best validation mae of epoch:', validation_mae)
# return {'loss': validation_mae, 'status': STATUS_OK}
if __name__ == '__main__':
import sys
neighbor_obj, CUDA_rate = sys.argv[1:]
## config TF
#os.environ['CUDA_VISIBLE_DEVICES'] = '0'
from mCNN.queueGPU import queueGPU
queueGPU()
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
if CUDA_rate != 'full':
config = tf.ConfigProto()
if float(CUDA_rate) < 0.1:
config.gpu_options.allow_growth = True
else:
config.gpu_options.per_process_gpu_memory_fraction = float(
CUDA_rate)
set_session(tf.Session(config=config))
x_train, y_train, ddg_train, x_test, y_test, ddg_test, class_weights_dict, obj, kneighbor = data(
neighbor_obj)
model = Conv2DRegressorIn1(x_train, y_train, ddg_train, x_test, y_test,
ddg_test, class_weights_dict, obj, kneighbor)
y=ddg_train,
batch_size=batch_size,
epochs=epochs,
verbose=verbose,
callbacks=my_callbacks,
validation_data=(x_val, ddg_val),
shuffle=True,
)
return network, result.history
if __name__ == '__main__':
from mCNN.queueGPU import queueGPU
CUDA_rate = '0.2'
## config TF
queueGPU(USER_MEM=3000, INTERVAL=60)
# os.environ['CUDA_VISIBLE_DEVICES'] = CUDA
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
if CUDA_rate != 'full':
config = tf.ConfigProto()
if float(CUDA_rate) < 0.1:
config.gpu_options.allow_growth = True
else:
config.gpu_options.per_process_gpu_memory_fraction = float(
CUDA_rate)
set_session(tf.Session(config=config))
# modeldir = '/dl/sry/mCNN/src/Network/deepddg/regressor/TrySimpleConv1D_CrossValid_%s'%time.strftime("%Y.%m.%d.%H.%M.%S", time.localtime())
modeldir = '/dl/sry/mCNN/src/Network/deepddg/regressor/%s_%s' % (
sys.argv[0][:-3], time.strftime("%Y.%m.%d.%H.%M.%S", time.localtime()))
os.makedirs(modeldir, exist_ok=True)