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[mieb] Memotion preprocessing code made more robust and readable #2519

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Merged
isaac-chung merged 3 commits into from
Apr 7, 2025
Merged

[mieb] Memotion preprocessing code made more robust and readable #2519

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b78b5f4
make memotion code robust
gowitheflow-1998 Apr 7, 2025
4b71a3d
lint
gowitheflow-1998 Apr 7, 2025
40986ca
clean comment
gowitheflow-1998 Apr 7, 2025
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35 changes: 17 additions & 18 deletions mteb/tasks/Image/Any2AnyRetrieval/eng/MemotionI2TRetrieval.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -21,15 +21,20 @@ def _load_data(path: str, splits: str, cache_dir: str = None, revision: str = No
def map_function(split_name):
return lambda x, idx: {
"id": f"corpus-{split_name}-{idx}",
"text": x["text_corrected"] if x["text_corrected"] else "",
"text": x["text_corrected"],
"modality": "text",
"image": None,
}

# Apply the map function to each split and concatenate
split_datasets = {}
for split in dataset_splits:
split_datasets[split] = dataset[split].filter(
lambda example: example["text_corrected"] != None
)

shared_corpus = concatenate_datasets(
[
dataset[split].map(
split_datasets[split].map(
map_function(split),
with_indices=True,
remove_columns=[
Expand All @@ -46,13 +51,11 @@ def map_function(split_name):
for split in dataset_splits
]
)
# image corrupted & caption empty
shared_corpus = shared_corpus.select(
[i for i in range(len(shared_corpus)) if i not in [4578, 6781, 6784, 6786]]
)

for split in splits:
corpus[split] = shared_corpus
split_dataset = dataset[split]
split_dataset = split_datasets[split]

queries[split] = split_dataset.map(
lambda x, idx: {
"id": f"query-{split}-{idx}",
Expand All @@ -72,18 +75,14 @@ def map_function(split_name):
"text_corrected",
],
)
if split == "test":
queries[split] = queries[split].select(
[i for i in range(len(queries[split])) if i not in [489, 492, 494]]
)

relevant_docs[split] = {}
for index in range(len(split_dataset)):
if index not in [489, 492, 494]:
query_id = f"query-{split}-{index}"
doc_id = f"corpus-{split}-{index}"
if query_id not in relevant_docs[split]:
relevant_docs[split][query_id] = {}
relevant_docs[split][query_id][doc_id] = 1
query_id = f"query-{split}-{index}"
doc_id = f"corpus-{split}-{index}"
if query_id not in relevant_docs[split]:
relevant_docs[split][query_id] = {}
relevant_docs[split][query_id][doc_id] = 1
return corpus, queries, relevant_docs


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32 changes: 15 additions & 17 deletions mteb/tasks/Image/Any2AnyRetrieval/eng/MemotionT2IRetrieval.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -25,10 +25,15 @@ def map_function(split_name):
"modality": "image",
}

# Apply the map function to each split and concatenate
split_datasets = {}
for split in dataset_splits:
split_datasets[split] = dataset[split].filter(
lambda example: example["text_corrected"] != None
)

shared_corpus = concatenate_datasets(
[
dataset[split].map(
split_datasets[split].map(
map_function(split),
with_indices=True,
remove_columns=[
Expand All @@ -45,13 +50,10 @@ def map_function(split_name):
for split in dataset_splits
]
)
# image corrupted
shared_corpus = shared_corpus.select(
[i for i in range(len(shared_corpus)) if i not in [4578, 6781, 6784, 6786]]
)

for split in splits:
corpus[split] = shared_corpus
split_dataset = dataset[split]
split_dataset = split_datasets[split]
queries[split] = split_dataset.map(
lambda x, idx: {
"id": f"query-{split}-{idx}",
Expand All @@ -71,18 +73,14 @@ def map_function(split_name):
"text_corrected",
],
)
if split == "test":
queries[split] = queries[split].select(
[i for i in range(len(queries[split])) if i not in [489, 492, 494]]
)

relevant_docs[split] = {}
for index in range(len(split_dataset)):
if index not in [489, 492, 494]:
query_id = f"query-{split}-{index}"
doc_id = f"corpus-{split}-{index}"
if query_id not in relevant_docs[split]:
relevant_docs[split][query_id] = {}
relevant_docs[split][query_id][doc_id] = 1
query_id = f"query-{split}-{index}"
doc_id = f"corpus-{split}-{index}"
if query_id not in relevant_docs[split]:
relevant_docs[split][query_id] = {}
relevant_docs[split][query_id][doc_id] = 1
return corpus, queries, relevant_docs


Expand Down