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FIX: .batch from Indexer #52

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merged 4 commits into from
Apr 6, 2024
Merged

FIX: .batch from Indexer #52

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38b935e
FIX: batch with tuple & FbyIDs
VincentAuriau Apr 5, 2024
36f2482
FIX: Indexe __getitem__
VincentAuriau Apr 5, 2024
53529a0
FIX: fixed recent fix
VincentAuriau Apr 5, 2024
0626d3b
ADD: test
VincentAuriau Apr 5, 2024
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108 changes: 69 additions & 39 deletions choice_learn/data/choice_dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1073,50 +1073,69 @@ def get_choices_batch(self, choices_indexes, features=None):
(len(choices_indexes), self.base_num_items)
).astype("float32")
else:
available_items_by_choice = self.available_items_by_choice[choices_indexes]
if hasattr(self.available_items_by_choice, "batch"):
available_items_by_choice = self.available_items_by_choice.batch[
choices_indexes
]
else:
available_items_by_choice = self.available_items_by_choice[choices_indexes]
# .astype(self._return_types[3])

choices = self.choices[choices_indexes].astype(self._return_types[4])
choices = self.choices[choices_indexes].astype(self._return_types[3])

###
if len(self.shared_features_by_choice_map) > 0:
mapped_features = []
for tuple_index in np.sort(list(self.shared_features_by_choice_map.keys())):
feat_ind_min = 0
unstacked_feat = []
for feature_index in np.sort(
list(self.shared_features_by_choice_map[tuple_index].keys())
):
unstacked_feat.append(
shared_features_by_choice[tuple_index][:, feat_ind_min:feature_index]
)
unstacked_feat.append(
self.shared_features_by_choice_map[tuple_index][feature_index].batch[
shared_features_by_choice[tuple_index][:, feature_index]
]
)
feat_ind_min = feature_index + 1
mapped_features.append(np.concatenate(unstacked_feat, axis=1))
###
for tuple_index in range(len(shared_features_by_choice)):
if tuple_index in self.shared_features_by_choice_map.keys():
feat_ind_min = 0
unstacked_feat = []
for feature_index in np.sort(
list(self.shared_features_by_choice_map[tuple_index].keys())
):
unstacked_feat.append(
shared_features_by_choice[tuple_index][
:, feat_ind_min:feature_index
]
)
unstacked_feat.append(
self.shared_features_by_choice_map[tuple_index][
feature_index
].batch[shared_features_by_choice[tuple_index][:, feature_index]]
)
feat_ind_min = feature_index + 1
mapped_features.append(np.concatenate(unstacked_feat, axis=1))
else:
mapped_features.append(shared_features_by_choice[tuple_index])

shared_features_by_choice = mapped_features

###
if len(self.items_features_by_choice_map) > 0:
mapped_features = []
for tuple_index in np.sort(list(self.items_features_by_choice_map.keys())):
feat_ind_min = 0
unstacked_feat = []
for feature_index in np.sort(
list(self.items_features_by_choice_map[tuple_index].keys())
):
unstacked_feat.append(
items_features_by_choice[tuple_index][:, :, feat_ind_min:feature_index]
)
unstacked_feat.append(
self.items_features_by_choice_map[tuple_index][feature_index].batch[
items_features_by_choice[tuple_index][:, :, feature_index]
]
)
feat_ind_min = feature_index + 1
mapped_features.append(np.concatenate(unstacked_feat, axis=2))
###
for tuple_index in range(len(items_features_by_choice)):
if tuple_index in self.items_features_by_choice_map.keys():
feat_ind_min = 0
unstacked_feat = []
for feature_index in np.sort(
list(self.items_features_by_choice_map[tuple_index].keys())
):
unstacked_feat.append(
items_features_by_choice[tuple_index][
:, :, feat_ind_min:feature_index
]
)
unstacked_feat.append(
self.items_features_by_choice_map[tuple_index][feature_index].batch[
items_features_by_choice[tuple_index][:, :, feature_index]
]
)
feat_ind_min = feature_index + 1
mapped_features.append(np.concatenate(unstacked_feat, axis=2))
else:
mapped_features.append(items_features_by_choice[tuple_index])

items_features_by_choice = mapped_features

Expand Down Expand Up @@ -1150,21 +1169,32 @@ def get_choices_batch(self, choices_indexes, features=None):
)

if isinstance(choices_indexes, slice):
return self.get_choice_batch(
return self.get_choices_batch(
list(range(*choices_indexes.indices(self.choices.shape[0])))
)

### Attemps at simplifying the code
choices_indexes = [choices_indexes]
(
shared_items_features_by_choices,
shared_features_by_choices,
items_features_by_choice,
available_items_by_choice,
choice,
) = self._get_choices_batch(choices_indexes)
) = self.get_choices_batch(choices_indexes)
if shared_features_by_choices is not None:
if isinstance(shared_features_by_choices, tuple):
shared_features_by_choices = tuple(feat[0] for feat in shared_features_by_choices)
else:
shared_features_by_choices = shared_features_by_choices[0]
if items_features_by_choice is not None:
if isinstance(items_features_by_choice, tuple):
items_features_by_choice = tuple(feat[0] for feat in items_features_by_choice)
else:
items_features_by_choice = items_features_by_choice[0]

return (
shared_items_features_by_choices[0],
items_features_by_choice[0],
shared_features_by_choices,
items_features_by_choice,
available_items_by_choice[0],
choice[0],
)
Expand Down
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