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Merged
samsja merged 2 commits into from
May 24, 2023
Merged

docs: add mention and example for type coercion #1572

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docs: add mention and example for type coercion
Tanguyabel May 24, 2023
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Merge branch 'main' into docs-type-coercion
Tanguyabel May 24, 2023
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34 changes: 34 additions & 0 deletions README.md
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Expand Up @@ -108,6 +108,39 @@ class MyDocument(BaseDoc):

So not only can you define the types of your data, you can even **specify the shape of your tensors!**

> :bulb: **Type coercion:** When submitting a tensor-like structure to a tensor field, the resulting `TorchTensor` is typed after the provided data.

See:

```python
from docarray import BaseDoc
from docarray.typing import TorchTensor
import numpy as np


class MyTensorsDoc(BaseDoc):
tensor1: TorchTensor[512]
tensor2: TorchTensor[512]


rand_series_f64 = np.random.rand(512).astype('float64')
rand_series_f32 = np.random.rand(512).astype('float32')

doc = MyTensorsDoc(tensor1=rand_series_f64, tensor2=rand_series_f32)
doc.summary()
```

```
📄 MyTensorsDoc : 84877dd ...
╭──────────────────────┬──────────────────────────────────────────────────────────────────────────────────────────╮
│ Attribute │ Value │
├──────────────────────┼──────────────────────────────────────────────────────────────────────────────────────────┤
│ tensor1: TorchTensor │ TorchTensor of shape (512,), dtype: torch.float64 │
│ tensor2: TorchTensor │ TorchTensor of shape (512,), dtype: torch.float32 │
╰──────────────────────┴──────────────────────────────────────────────────────────────────────────────────────────╯
```


Once you have your model in the form of a document, you can work with it!

```python
Expand All @@ -120,6 +153,7 @@ doc = MyDocument(
# Load image tensor from URL
doc.image_tensor = doc.image_url.load()


# Compute embedding with any model of your choice
def clip_image_encoder(image_tensor: TorchTensor) -> TorchTensor: # dummy function
return torch.rand(512)
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