def set_global_seed(seed): random.seed(seed) if opt.has_numpy: opt.np.random.seed(seed) if module_is_in_cache('tensorflow'): import tensorflow as tf tf.set_random_seed(seed) if module_is_in_cache('torch'): import torch torch.manual_seed(seed) if torch.cuda.is_available(): torch.cuda.manual_seed_all(seed)
def set_global_seed(seed): random.seed(seed) if opt.has_numpy: opt.np.random.seed(seed) if module_is_in_cache("tensorflow"): tf = opt.get_tensorflow() tf.set_random_seed(seed) if module_is_in_cache("torch"): import torch torch.manual_seed(seed) if torch.cuda.is_available(): torch.cuda.manual_seed_all(seed)
def set_global_seed(seed): random.seed(seed) if opt.has_numpy: opt.np.random.seed(seed) if module_is_in_cache('tensorflow'): import tensorflow as tf tf.set_random_seed(seed)
def set_global_seed(seed): random.seed(seed) if opt.has_numpy: opt.np.random.seed(seed) if module_is_in_cache('tensorflow'): import tensorflow as tf from packaging import version if version.parse(tf.__version__) < version.parse('2.0.0a0'): tf.set_random_seed(seed) else: tf.random.set_seed(seed) if module_is_in_cache('torch'): import torch torch.manual_seed(seed) if torch.cuda.is_available(): torch.cuda.manual_seed_all(seed)
def set_global_seed(seed): random.seed(seed) if opt.has_numpy: opt.np.random.seed(seed) if module_is_in_cache('tensorflow'): # Ensures backward and forward compatibility with TensorFlow 1 and 2. if get_package_version('tensorflow') < parse_version('1.13.1'): import warnings warnings.warn("Use of TensorFlow 1.12 and older is deprecated. " "Use Tensorflow 1.13 or newer instead.", DeprecationWarning) import tensorflow as tf else: import tensorflow.compat.v1 as tf tf.set_random_seed(seed) if module_is_in_cache('torch'): import torch torch.manual_seed(seed) if torch.cuda.is_available(): torch.cuda.manual_seed_all(seed)
def set_global_seed(seed): random.seed(seed) if opt.has_numpy: opt.np.random.seed(seed) if module_is_in_cache('tensorflow'): # Ensures backward and forward compatibility with TensorFlow 1 and 2. if get_package_version('tensorflow') < parse_version('1.13.1'): import warnings warnings.warn( "Use of TensorFlow 1.12 and older is deprecated. " "Use Tensorflow 1.13 or newer instead.", DeprecationWarning) import tensorflow as tf else: import tensorflow.compat.v1 as tf tf.set_random_seed(seed) if module_is_in_cache('torch'): import torch torch.manual_seed(seed) if torch.cuda.is_available(): torch.cuda.manual_seed_all(seed)
def test_module_is_in_cache(): assert module_is_in_cache("pytest") assert module_is_in_cache("pkgutil") assert not module_is_in_cache("does_not_even_exist")
def test_module_is_in_cache(): assert module_is_in_cache('pytest') assert module_is_in_cache('pkgutil') assert not module_is_in_cache('does_not_even_exist')