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Running on Zero
Running on Zero
File size: 3,579 Bytes
d1f1097 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 | import io
def sample_loader(raw: dict) -> dict:
"""
Load the sample from the raw data.
Example content of wds data:
- Example of wds data
100_100.img
100_100.json
100_100.synthesized_683016ff-bb67-4a12-a873-a7e5d4132903.wav.flac
100_100.synthesized_6a7b3a1c-05a9-4720-b7e6-f7028415dc71.wav.flac
100_100.synthesized_7c4b39ba-20ef-4319-bd94-291c94ad362a.wav.flac
100_100.synthesized_932f067b-2b9a-425d-b8e6-f74ca83335a2.wav.flac
Content of 100_100.json:
{
"num_image": 7,
"length": 2049,
"label_length": 157,
"conversations": [
{
"from": "human",
"value": "<image><audio>"
},
{
"from": "gpt",
"value": "The stop sign is red, while the one-way signs are typically black and white."
},
...
{
"from": "human",
"value": "<audio>"
},
{
"from": "gpt",
"value": "The purpose of these street signs is to communicate..."
}
],
"audios": [
"100_100.synthesized_6a7b3a1c-05a9-4720-b7e6-f7028415dc71.wav.flac",
"100_100.synthesized_932f067b-2b9a-425d-b8e6-f74ca83335a2.wav.flac",
"100_100.synthesized_7c4b39ba-20ef-4319-bd94-291c94ad362a.wav.flac",
"100_100.synthesized_683016ff-bb67-4a12-a873-a7e5d4132903.wav.flac"
],
"images": [
"100_100.img"
]
}
- Example of read raw data for Energon
raw["json"] -> json content
raw["img"] -> bytes image content
raw["synthesized_6a7b3a1c-05a9-4720-b7e6-f7028415dc71.wav.flac"] -> bytes audio content
raw["synthesized_932f067b-2b9a-425d-b8e6-f74ca83335a2.wav.flac"] -> bytes audio content
raw["synthesized_683016ff-bb67-4a12-a873-a7e5d4132903.wav.flac"] -> bytes audio content
"""
jsn_content = raw["json"]
conversation = jsn_content["conversations"]
# Get raw image bytes
image_bytes = raw["img"]
# Get raw audio bytes
audio_names = [audio_name.split('.', 1)[1] for audio_name in jsn_content["audios"]] # example of audio_name file: "100_100.synthesized_683016ff-bb67-4a12-a873-a7e5d4132903.wav.flac" -> "synthesized_683016ff-bb67-4a12-a873-a7e5d4132903.wav"
audio_name = audio_names[0] # for now, take only the first audio
audio_bytes = raw[audio_name]
# process conversation, take only the first turn
context = conversation[0]["value"]
answers = conversation[1]["value"]
# check that context only contains one "<audio>"
# if contains more than one, replace all occurrences with a single one
if context.count("<audio>") > 1:
parts = context.split("<audio>")
context = parts[0] + "<audio>" + "".join(parts[1:])
return dict(
__key__=raw["__key__"],
context=context,
answers=answers,
image=image_bytes,
audio=audio_bytes,
)
def part_filter(part: str) -> bool:
return True |