Comments (2)
Seems reasonable to me! I've just added this and done a new release (v0.2.15). The syntax is using =
, e.g. Float[t.Tensor, "cols=3 rows=4"]
.
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Thanks, yeah this looks awesome!
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Related Issues (20)
- BUG: Exception if array in args is modified in a function with the same name HOT 4
- Isinstance checks against a ShapeDtypeStruct HOT 2
- bug: can't type flax.struct.dataclass with vmapped functions HOT 3
- Disabling JAX import HOT 2
- einops-like packing notation HOT 4
- Symbolic expressions example doesn't run HOT 2
- v0.2.26 Release Failed HOT 1
- Allow two variadic shapes when it makes sense HOT 1
- Support for NestedTensors HOT 3
- `jaxtyped` Annotation fails
- jax dependency error when jax is not installed HOT 4
- Random instances / Hypothesis-like generation HOT 3
- Question: manual assertion HOT 4
- Move equinox "tree_pformat" into jaxtyping or allow users to configure their own HOT 1
- How to use with Sphinx autodoc? HOT 1
- Issues with torch.compile HOT 5
- Functions without type hints and import hook HOT 1
- Compatibility with multiprocessing / joblib - AttributeError: type object 'Float[Tensor, 'batch_size num_classes']' has no attribute 'index_variadic' HOT 4
- Can typeguard be an optional dependency? HOT 8
- Are pytorch named tensors supported, like in torchtyping? HOT 1
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