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GeezerVison is showing github.com — feat(v2): add audio url and predefined document by anna-charlotte · Pull Request #940 · docarray/docarray
This repository was archived by the owner on Sep 9, 2026. It is now read-only.
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@JoanFM @alaeddine-13 I checked all the comments and made corresponding changes. It's ready for re-review now. |
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Signed-off-by: anna-charlotte <[email protected]>
Signed-off-by: anna-charlotte <[email protected]>
Signed-off-by: anna-charlotte <[email protected]>
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| return cls(str(url), scheme=None) | ||
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| def load(self: T) -> np.ndarray: |
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@samsja Should I return a np.ndarray here, or rather AudioNdArray or AudioTorchTensor?
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I would say AudioNdArray.
Normally we just load the np.ndarray, bc the framework specific conversion can happen when putting it back into the document, and having it as np.ndarray makes the least assumptions about the sorrounding code.
In this case, since there are actual audio features that come with the array, I would go with AudioNdArray. It can still be treated like a normal np.ndarray, but bring the aforementioned features.
But just verify in a test that setting a AudioNdArray to a field with type AudioTorchArray actually works without issue?
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But just verify in a test that setting a AudioNdArray to a field with type AudioTorchArray actually works without issue
Do you mean like this?
def test_load_audio_url_to_audio_torch_tensor(file_url):
class MyAudioDoc(Document):
audio_url: AudioUrl
tensor: Optional[AudioTorchTensor]
doc = MyAudioDoc(audio_url=file_url)
doc.tensor = doc.audio_url.load()
assert isinstance(doc.tensor, np.ndarray)
assert isinstance(doc.tensor, AudioNdArray)
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Ok I moved it to the computational backends
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great I like it better like this
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This pr looks really nice. I like how the idea of having different tensor types for the different modality work :) I added some comments
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Great PR, love the audio tensor stuff, this is a good pattern to use moving forward. just some things to consider
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| ) | ||
| return cls(str(url), scheme=None) | ||
|
|
||
| def load(self: T) -> np.ndarray: |
There was a problem hiding this comment.
The reason will be displayed to describe this comment to others. Learn more.
I would say AudioNdArray.
Normally we just load the np.ndarray, bc the framework specific conversion can happen when putting it back into the document, and having it as np.ndarray makes the least assumptions about the sorrounding code.
In this case, since there are actual audio features that come with the array, I would go with AudioNdArray. It can still be treated like a normal np.ndarray, but bring the aforementioned features.
But just verify in a test that setting a AudioNdArray to a field with type AudioTorchArray actually works without issue?
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Signed-off-by: anna-charlotte <[email protected]>
Signed-off-by: anna-charlotte <[email protected]>
Signed-off-by: anna-charlotte <[email protected]>
Signed-off-by: anna-charlotte <[email protected]>
Signed-off-by: anna-charlotte <[email protected]>
Signed-off-by: anna-charlotte <[email protected]>
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Just resolve the conflicts and we're good to go, great work!
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Signed-off-by: anna-charlotte <[email protected]>
Signed-off-by: anna-charlotte <[email protected]>
Signed-off-by: anna-charlotte <[email protected]>
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📝 Docs are deployed on https://ft-feat-add-audio-v2--jina-docs.netlify.app 🎉 |
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Successfully merging this pull request may close these issues.
Add audio predefined document to v2
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