fix(codec): handle multi-dimensional ndarrays with Arrow encoding #162
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PyArrow's pa.array() only handles 1D arrays, causing torch tensor serialization to fail. This implements a flatten-on-encode, reshape-on-decode strategy that maintains Arrow's binary efficiency. ## Changes ### Python Side (runtime/python_bridge.py) - Flatten multi-dimensional arrays before pa.array() - Include original shape in envelope for JS-side reconstruction - Add dtype to envelope for completeness ### JavaScript Side (src/utils/codec.ts) - Add reshapeArray() utility for reconstructing multi-dim arrays - Update ndarray decoder to reshape Arrow-decoded data when shape.length > 1 - Handle both sync and async Arrow decode paths ### Tests - Restore Arrow encoding for torch tensor test (remove JSON fallback) - Verify 2D tensor [[1,2],[3,4]] round-trips correctly ## Why This Approach - Arrow IPC is ~10x more efficient than JSON for numeric data - arrow-js doesn't support FixedShapeTensorArray yet (open issue since 2020) - Flatten+reshape is forward-compatible with future tensor support - See: apache/arrow-js#115 Closes #161 Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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Add 7 new tests for ndarray flatten+reshape functionality: - 1D arrays (no reshape needed) - 3D arrays via numpy - 3D torch tensors with Arrow encoding - Single-element arrays - Single-element multi-dimensional arrays - Float dtype preservation - 4D tensors (image-like batches) These tests verify the Arrow encoding path where multi-dimensional arrays are flattened on Python side and reshaped on JS side. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This was referenced Jan 21, 2026
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Summary
Fixes Arrow encoding failure for multi-dimensional ndarrays (e.g., torch tensors) by implementing a flatten-on-encode, reshape-on-decode strategy.
Problem
PyArrow's
pa.array()only handles 1D arrays. Multi-dimensional arrays like 2D torch tensors failed with:This was causing the
codec-suiteCI to fail.Solution
Python Side
pa.array()JavaScript Side
reshapeArray()utility for reconstructing multi-dim arraysshape.length > 1Why This Approach
Test Results
Test Plan
[[1,2],[3,4]]round-trips correctly with shape[2,2]2x3x4) flatten and reshape correctly2x2x2x2) handled correctlyCloses #161
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