# A function handle, that is used to evaluate the performance of a run.
_PERFORMANCE_EVAL_HANDLE = hpsplit._performance_criteria
# A key that must appear in the `_SUMMARY_KEYWORDS` list. If `None`, the first
# entry in this list will be selected.
# The CSV file will be sorted based on this keyword. See also attribute
# `_PERFORMANCE_SORT_ASC`.
_PERFORMANCE_KEY = 'acc_avg_final'
assert (_PERFORMANCE_KEY is None or _PERFORMANCE_KEY in _SUMMARY_KEYWORDS)
# Whether the CSV should be sorted ascending or descending based on the
# `_PERFORMANCE_KEY`.
_PERFORMANCE_SORT_ASC = False
# FIXME: This attribute will vanish in future releases.
# This attribute is only required by the `hpsearch_postprocessing` script.
# A function handle to the argument parser function used by the simulation
# script. The function handle should expect the list of command line options
# as only parameter.
# Example:
# >>> from classifier.imagenet import train_args as targs
# >>> f = lambda argv : targs.parse_cmd_arguments(mode='cl_ilsvrc_cub',
# ... argv=argv)
# >>> _ARGPARSE_HANDLE = f
import probabilistic.multitask_args as targs
_ARGPARSE_HANDLE = lambda argv : targs.parse_cmd_arguments( \
mode='perm_mnist_mt', argv=argv)
if __name__ == '__main__':
pass
# 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. # # @title :probabilistic/prob_mnist/train_split_mt.py # @author :ch # @contact :[email protected] # @created :09/03/2021 # @version :1.0 # @python_version :3.8.10 """ Multitask baseline for SplitMNIST --------------------------------- This script is used to run Multitask experiments on SplitMNIST. """ # Do not delete the following import for all executable scripts! import __init__ # pylint: disable=unused-import from probabilistic import multitask_args from probabilistic import multitask_utils if __name__ == '__main__': config = multitask_args.parse_cmd_arguments(mode='split_mnist_mt') multitask_utils.run(config, experiment='split_mnist_mt') if __name__ == '__main__': pass
# 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. # # @title :probabilistic/prob_cifar/train_resnet_mt.py # @author :ch # @contact :[email protected] # @created :09/03/2021 # @version :1.0 # @python_version :3.8.10 """ Multitask baseline for SplitCIFAR --------------------------------- This script is used to run Multitask experiments on SplitCIFAR. """ # Do not delete the following import for all executable scripts! import __init__ # pylint: disable=unused-import from probabilistic import multitask_args from probabilistic import multitask_utils if __name__ == '__main__': config = multitask_args.parse_cmd_arguments(mode='cifar_resnet_mt') multitask_utils.run(config, experiment='cifar_resnet_mt') if __name__ == '__main__': pass
# A function handle, that is used to evaluate the performance of a run.
_PERFORMANCE_EVAL_HANDLE = hpsplit._performance_criteria
# A key that must appear in the `_SUMMARY_KEYWORDS` list. If `None`, the first
# entry in this list will be selected.
# The CSV file will be sorted based on this keyword. See also attribute
# `_PERFORMANCE_SORT_ASC`.
_PERFORMANCE_KEY = 'acc_avg_final'
assert (_PERFORMANCE_KEY is None or _PERFORMANCE_KEY in _SUMMARY_KEYWORDS)
# Whether the CSV should be sorted ascending or descending based on the
# `_PERFORMANCE_KEY`.
_PERFORMANCE_SORT_ASC = False
# FIXME: This attribute will vanish in future releases.
# This attribute is only required by the `hpsearch_postprocessing` script.
# A function handle to the argument parser function used by the simulation
# script. The function handle should expect the list of command line options
# as only parameter.
# Example:
# >>> from classifier.imagenet import train_args as targs
# >>> f = lambda argv : targs.parse_cmd_arguments(mode='cl_ilsvrc_cub',
# ... argv=argv)
# >>> _ARGPARSE_HANDLE = f
import probabilistic.multitask_args as targs
_ARGPARSE_HANDLE = lambda argv : targs.parse_cmd_arguments( \
mode='cifar_resnet_mt', argv=argv)
if __name__ == '__main__':
pass
# See the License for the specific language governing permissions and # limitations under the License. # # @title :probabilistic/prob_gmm/train_gmm_mt.py # @author :ch # @contact :[email protected] # @created :09/03/2021 # @version :1.0 # @python_version :3.8.10 """ Multitask baseline for GMM CL Classification Experiment ------------------------------------------------------- This script is used to run Multitask experiments on the GMM datasets. """ # Do not delete the following import for all executable scripts! import __init__ # pylint: disable=unused-import from probabilistic import multitask_args from probabilistic import multitask_utils if __name__ == '__main__': config = multitask_args.parse_cmd_arguments(mode='gmm_mt') multitask_utils.run(config, experiment='gmm_mt') if __name__ == '__main__': pass