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@@ -20,42 +20,6 @@ class Explanation(object):
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"""
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Base class for all explanation algorithms.
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"""
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- def __init__(self, explanation_algorithm_name, predict_fn, **kwargs):
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- supported_algorithms = {
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- 'cam': CAM,
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- 'lime': LIME,
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- 'normlime': NormLIME
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- }
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-
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- self.algorithm_name = explanation_algorithm_name.lower()
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- assert self.algorithm_name in supported_algorithms.keys()
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- self.predict_fn = predict_fn
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-
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- # initialization for the explanation algorithm.
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- self.explain_algorithm = supported_algorithms[self.algorithm_name](
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- self.predict_fn, **kwargs
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- )#copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
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-#
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-#Licensed under the Apache License, Version 2.0 (the "License");
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-#you may not use this file except in compliance with the License.
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-#You may obtain a copy of the License at
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-#
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-# http://www.apache.org/licenses/LICENSE-2.0
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-#
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-#Unless required by applicable law or agreed to in writing, software
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-#distributed under the License is distributed on an "AS IS" BASIS,
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-#WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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-#See the License for the specific language governing permissions and
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-#limitations under the License.
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-
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-from .explanation_algorithms import CAM, LIME, NormLIME
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-from .normlime_base import precompute_normlime_weights
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-
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-
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-class Explanation(object):
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- """
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- Base class for all explanation algorithms.
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- """
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def __init__(self, explanation_algorithm_name, predict_fn, label_names, **kwargs):
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supported_algorithms = {
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'cam': CAM,
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@@ -85,18 +49,3 @@ class Explanation(object):
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"""
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return self.explain_algorithm.explain(data_, visualization, save_to_disk, save_dir)
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-
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-
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- def explain(self, data_, visualization=True, save_to_disk=True, save_dir='./tmp'):
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- """
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-
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- Args:
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- data_: data_ can be a path or numpy.ndarray.
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- visualization: whether to show using matplotlib.
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- save_to_disk: whether to save the figure in local disk.
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- save_dir: dir to save figure if save_to_disk is True.
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-
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- Returns:
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-
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- """
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- return self.explain_algorithm.explain(data_, visualization, save_to_disk, save_dir)
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