From 11a930760cc6a7254cbdd22d78a303775ee0a65d Mon Sep 17 00:00:00 2001 From: Aditya Goel Date: Sat, 1 Feb 2025 15:50:10 +0000 Subject: [PATCH] Fix merge --- ndonnx/_refactor/_funcs.py | 13 ------------- 1 file changed, 13 deletions(-) diff --git a/ndonnx/_refactor/_funcs.py b/ndonnx/_refactor/_funcs.py index 96c09e6..beb8d7f 100644 --- a/ndonnx/_refactor/_funcs.py +++ b/ndonnx/_refactor/_funcs.py @@ -119,19 +119,6 @@ def numeric_like(x): return [broadcast_to(a, target_shape) for a in arrays] - # TODO: Create upstream issue for a variadic broadcasting operator - # in the ONNX standard. - for a in arrays: - for el in a.shape: - if not isinstance(el, int): - raise ValueError( - "broadcasting dynamic dimensions is not (yet) supported." - ) - - res = np.broadcast_shapes(*[a.shape for a in arrays]) # type: ignore - - return [broadcast_to(a, tuple(res)) for a in arrays] - def broadcast_to(x: Array, /, shape: tuple[int, ...] | Array) -> Array: from ._typed_array.onnx import TyArrayInt64