# 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. # # @title :probabilistic/prob_mnist/train_split_ewc.py # @author :ch # @contact :[email protected] # @created :01/10/2021 # @version :1.0 # @python_version :3.8.5 """ SplitMNIST with EWC ------------------- This script is used to run EWC experiments on SplitMNIST. """ # Do not delete the following import for all executable scripts! import __init__ # pylint: disable=unused-import from probabilistic import ewc_args from probabilistic import ewc_utils if __name__ == '__main__': config = ewc_args.parse_cmd_arguments(mode='split_mnist_ewc') ewc_utils.run(config, experiment='split_mnist_ewc')
# 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 probabilistic.prob_mnist import train_args as targs
# >>> f = lambda argv : targs.parse_cmd_arguments(mode='split_mnist_bbb',
# ... argv=argv)
# >>> _ARGPARSE_HANDLE = f
import probabilistic.ewc_args as targs
_ARGPARSE_HANDLE = lambda argv : targs.parse_cmd_arguments( \
mode='cifar_resnet_ewc', argv=argv)
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 probabilistic.prob_mnist import train_args as targs
# >>> f = lambda argv : targs.parse_cmd_arguments(mode='split_mnist_bbb',
# ... argv=argv)
# >>> _ARGPARSE_HANDLE = f
import probabilistic.ewc_args as targs
_ARGPARSE_HANDLE = lambda argv : targs.parse_cmd_arguments( \
mode='gmm_ewc', argv=argv)
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 probabilistic.prob_mnist import train_args as targs
# >>> f = lambda argv : targs.parse_cmd_arguments(mode='split_mnist_bbb',
# ... argv=argv)
# >>> _ARGPARSE_HANDLE = f
import probabilistic.ewc_args as targs
_ARGPARSE_HANDLE = lambda argv : targs.parse_cmd_arguments( \
mode='perm_mnist_ewc', argv=argv)
if __name__ == '__main__':
pass
# 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. # # @title :probabilistic/prob_mnist/train_perm_ewc.py # @author :ch # @contact :[email protected] # @created :01/10/2021 # @version :1.0 # @python_version :3.8.5 """ PermutedMNIST with EWC ---------------------- This script is used to run EWC experiments on PermutedMNIST. """ # Do not delete the following import for all executable scripts! import __init__ # pylint: disable=unused-import from probabilistic import ewc_args from probabilistic import ewc_utils if __name__ == '__main__': config = ewc_args.parse_cmd_arguments(mode='perm_mnist_ewc') ewc_utils.run(config, experiment='perm_mnist_ewc')
"""
performance = float(summary_dict['aa_mse_final_inferred_mean'][0])
return performance < performance_criteria
_PERFORMANCE_EVAL_HANDLE = _performance_criteria
_PERFORMANCE_KEY = 'aa_mse_final_inferred_mean'
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 = True
# 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 probabilistic.prob_mnist import train_args as targs
# >>> f = lambda argv : targs.parse_cmd_arguments(mode='split_mnist_bbb',
# ... argv=argv)
# >>> _ARGPARSE_HANDLE = f
import probabilistic.ewc_args as targs
_ARGPARSE_HANDLE = lambda argv : targs.parse_cmd_arguments( \
mode='regression_ewc', argv=argv)
if __name__ == '__main__':
pass
# # 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. # # @title :probabilistic/prob_cifar/train_resnet_ewc.py # @author :ch # @contact :[email protected] # @created :01/10/2021 # @version :1.0 # @python_version :3.8.5 """ SplitCIFAR with EWC ------------------- This script is used to run EWC experiments on SplitCIFAR. """ # Do not delete the following import for all executable scripts! import __init__ # pylint: disable=unused-import from probabilistic import ewc_args from probabilistic import ewc_utils if __name__ == '__main__': config = ewc_args.parse_cmd_arguments(mode='cifar_resnet_ewc') ewc_utils.run(config, experiment='cifar_resnet_ewc')
# 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. # # @title :probabilistic/prob_gmm/train_gmm_ewc.py # @author :ch # @contact :[email protected] # @created :01/10/2021 # @version :1.0 # @python_version :3.8.5 """ GMM CL Classification Experiment with EWC ----------------------------------------- This script is used to run EWC experiments on the GMM datasets. """ # Do not delete the following import for all executable scripts! import __init__ # pylint: disable=unused-import from probabilistic import ewc_args from probabilistic import ewc_utils if __name__ == '__main__': config = ewc_args.parse_cmd_arguments(mode='gmm_ewc') ewc_utils.run(config, experiment='gmm_ewc')