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Merged
hanxiao merged 1 commit into from
Aug 30, 2022
Merged

fix(find): make device more generic #515

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15 changes: 6 additions & 9 deletions docarray/math/distance/torch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,9 +18,8 @@ def cosine(
:param device: the computational device for `embed_model`, can be either `cpu` or `cuda`.
:return: np.ndarray with ndim=2
"""
if device == 'cuda':
x_mat = x_mat.cuda()
y_mat = y_mat.cuda()
x_mat = x_mat.to(device)
y_mat = y_mat.to(device)

a_n, b_n = x_mat.norm(dim=1)[:, None], y_mat.norm(dim=1)[:, None]
a_norm = x_mat / torch.clamp(a_n, min=eps)
Expand All @@ -37,9 +36,8 @@ def euclidean(x_mat: 'tensor', y_mat: 'tensor', device: str = 'cpu') -> 'numpy.n
:param device: the computational device for `embed_model`, can be either `cpu` or `cuda`.
:return: np.ndarray with ndim=2
"""
if device == 'cuda':
x_mat = x_mat.cuda()
y_mat = y_mat.cuda()
x_mat = x_mat.to(device)
y_mat = y_mat.to(device)

return torch.cdist(x_mat, y_mat).cpu().detach().numpy()

Expand All @@ -54,8 +52,7 @@ def sqeuclidean(
:param device: the computational device for `embed_model`, can be either `cpu` or `cuda`.
:return: np.ndarray with ndim=2
"""
if device == 'cuda':
x_mat = x_mat.cuda()
y_mat = y_mat.cuda()
x_mat = x_mat.to(device)
y_mat = y_mat.to(device)

return (torch.cdist(x_mat, y_mat) ** 2).cpu().detach().numpy()
4 changes: 2 additions & 2 deletions docs/advanced/document-store/index.md
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Expand Up @@ -157,9 +157,9 @@ DocArray supports multiple storage backends with different search features. The
| [`Sqlite`](./sqlite.md) | `DocumentArray(storage='sqlite')` | ❌ | ❌ | ✅ |
| [`Weaviate`](./weaviate.md) | `DocumentArray(storage='weaviate')` | ✅ | ✅ | ✅ |
| [`Qdrant`](./qdrant.md) | `DocumentArray(storage='qdrant')` | ✅ | ✅ | ❌ |
| [`Annlite`](./annlite.md) | `DocumentArray(storage='annlite')` | ✅ | ✅ | ✅ |
| [`Annlite`](./annlite.md) | `DocumentArray(storage='annlite')` | ✅ | ✅ | ✅ |
| [`ElasticSearch`](./elasticsearch.md) | `DocumentArray(storage='elasticsearch')` | ✅ | ✅ | ✅ |
| [`Redis`](./redis.md) | `DocumentArray(storage='elasticsearch')` | ✅ | ✅ | ✅ |
| [`Redis`](./redis.md) | `DocumentArray(storage='redis')` | ✅ | ✅ | ✅ |


Here we understand by
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