http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
from sparse_operation_kit import operations as sok_ops
from tensorflow.python.framework import load_library, ops
from tensorflow.python.ops import array_ops
from tensorflow.python.framework.tensor_shape import TensorShape
from tensorflow.python.ops import resource_variable_ops
from tensorflow import __version__ as tf_version
if tf_version.startswith("2"):
using_tf2 = True
elif tf_version.startswith("1"):
using_tf2 = False
else:
raise RuntimeError("Not supported TF version: {}".format(tf_version))
import os
def in_tensorflow2():
"""
This function will tell whether the installed TensorFlow is 2.x
"""
return using_tf2
from __future__ import print_function, unicode_literals, absolute_import, division
from six.moves import range, zip, map, reduce, filter
import numpy as np
import os
import warnings
import shutil
import datetime
from importlib import import_module
from tensorflow import __version__ as _tf_version
IS_TF_1 = _tf_version.startswith('1.')
_KERAS = 'keras' if IS_TF_1 else 'tensorflow.keras'
def keras_import(sub=None, *names):
if sub is None:
return import_module(_KERAS)
else:
mod = import_module('{_KERAS}.{sub}'.format(_KERAS=_KERAS,sub=sub))
if len(names) == 0:
return mod
elif len(names) == 1:
return getattr(mod, names[0])
return tuple(getattr(mod, name) for name in names)
import tensorflow as tf
# if IS_TF_1:
# import tensorflow as tf
# else:
# import tensorflow.compat.v1 as tf
# # tf.disable_v2_behavior()
"""
# Modules imported
import sys
import os
import argparse
import imghdr
import numpy as np
from cv2 import imread, imwrite, resize, cvtColor, COLOR_BGR2GRAY
from tensorflow.keras.models import load_model
from tensorflow import __version__ as tf_version
#from PIL import Image
#import matplotlib.pyplot as plt
from models import istl
from utils import root_sum_squared_error
if tf_version.startswith('1'):
from tensorflow import ConfigProto, Session
config = ConfigProto()
config.gpu_options.allow_growth = True
sess = Session(config=config)
else:
from tensorflow import config
physical_devices = config.experimental.list_physical_devices('GPU')
config.experimental.set_memory_growth(physical_devices[0], True)
# Constants
CUBOIDS_LENGTH = 8
CUBOIDS_WIDTH = 224
CUBOIDS_HEIGHT = 224
"""
Copyright (c) 2021, NVIDIA CORPORATION.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
"""
optimizers from TensorFlow
"""
from .adam import Adam
from tensorflow import __version__ as tf_version
if tf_version.startswith("1"):
from .lazy_adam import LazyAdamOptimizer
__all__ = [item for item in dir() if not item.startswith("__")]