Related Issues (20)
- Implement all Ops in PyTorch (help welcome!) HOT 13
- Update APIs to be compatible with NumPy 2.0 or pin NumPy to latest 1.x version HOT 1
- `tensor.where` does not behave like `np.where` when only one input (condition) is passed
- Default MvNormal covariance doesn't make sense HOT 2
- Allow specifying shape of dtyped tensor constructors
- AdvancedSubtensor1 and AdvancedIncSubtensor1 are not needed in JAX and Numba backends
- Allow sparse variables to have dummy dimensions to the left?
- Rewrite to remove useless Reshape
- Use `expand_dims` / `squeeze` in JAX implementation of `Dimshuffle`
- Check and Update support for Numba Ops
- More exhausitve list of functions in API section of docs
- `pt.linalg.det` should eagerly fail if known shapes are not square
- Softmax fails with integer dtypes only at runtime HOT 1
- Scipy 1.14.0 changed the upcasting rule of several special functions when passing integers HOT 1
- Recognize `dot` from naive sum of broadcasted muls
- BUG: Cannot access `ndims_params` from `rng_fn()` classmethod HOT 3
- Implement faster Multinomial JAX dispatch
- Flaky `tests/tensor/rewriting/test_linalg.py::test_local_lift_through_linalg[kron-pinv-batched] - AssertionError: `
- Add `infer_shape` method to Op base class?
- Infer flops and memory usage of each Op
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from pytensor.