jax-shape-tracker 0.1.1

Pinpoint JAX shape errors at the exact user code line

jax-shape-tracker

Pinpoint JAX shape errors at the exact line of your code — not inside XLA.

jax-shape-tracker is a lightweight debugging utility that intercepts JAX primitive execution and records a short history of operations with their input/output shapes. When a shape mismatch occurs, it prints a clear, human-readable trace showing what operation failed, where it was called, and how shapes evolved leading up to the error.

This tool exists because JAX erases Python stack information once it lowers to XLA, making shape errors notoriously painful to debug.

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Why This Exists

If you’ve ever seen this:

TypeError: dot_general requires contracting dimensions to have the same shape

…and the traceback points deep into jax/_src/lax, you already know the problem.

By the time the error is raised:

• Python stack frames are gone
• User source locations are lost
• You’re left guessing which reshape / broadcast / reduction broke things

jax-shape-tracker captures the last meaningful Python context before JAX drops into XLA, and shows you exactly what happened.

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Features

• 📍 Exact user source line for each operation
• 🧠 Recent operation history with input/output shapes
• 🔍 Clear display of the failing JAX primitive
• 🎨 Optional colored output (via colorama)
• 🧪 Zero dependencies required
• 🧩 Works with jax.numpy, jax.random, and core JAX ops
• 🛠 Context-manager based (no refactoring required)

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Installation

This is a pure-Python utility. Clone and use directly:

git clone https://github.com/KrisTHL181/jax-shape-tracker.git
cd jax-shape-tracker

Or PyPI:

pip install jax-shape-tracker

Optional (for colored output):

pip install colorama

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Basic Usage

1. Wrap your code with the context manager

from shape_tracker import JaxShapeTracker

with JaxShapeTracker():
    your_jax_function()

If a shape error occurs, a detailed operation trace will be printed automatically.

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2. Run a script directly (CLI-style)

You can run an existing script under the tracker without modifying it:

python -m shape_tracker example_buggy_code.py

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Example

Buggy Code (example_buggy_code.py)

import jax
import jax.numpy as jnp

def main():
    key = jax.random.PRNGKey(0)
    x = jax.random.normal(key, (32, 128))

    y = x.reshape(32, 64, 2)
    z = jnp.sum(y, axis=2)  # (32, 64)

    key2 = jax.random.PRNGKey(1)
    weight = jax.random.normal(key2, (100, 100))

    jnp.matmul(z, weight)  # ❌ shape mismatch

if __name__ == "__main__":
    main()

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Output

============================================================
🛑 JAX SHAPE/OP MISMATCH: TypeError
============================================================

--- Recent Operation History ---
1. [example_buggy_code.py:17 -> y = x.reshape(32, 64, 2)]
    Op: reshape
    In : (32, 128)
    Out: (32, 64, 2)

2. [example_buggy_code.py:20 -> z = jnp.sum(y, axis=2)]
    Op: reduce_sum
    In : (32, 64, 2)
    Out: (32, 64)

--- ❌ THE OPERATION THAT FAILED ---
[example_buggy_code.py:26 -> jnp.matmul(z, weight)]
    Op: dot_general
    In : (32, 64), (100, 100)
    ERROR: contracting dimensions must match (64 vs 100)

You immediately see:

• Where the error occurred
• Which shapes caused it
• How the shapes evolved

No guessing. No XLA archaeology.

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Automatic Retry Mode

You can also run code normally and only enable tracking after a shape error is detected:

from shape_tracker._shape_bug_tracker import track_when_shape_mismatch

track_when_shape_mismatch(your_function)

This avoids slowing down normal execution.

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Important Notes & Limitations

• ⚠️ Recommended: disable JIT for accurate source tracking

  jax.config.update("jax_disable_jit", True)
  

• This is a debugging tool, not intended for production

• JAX internals are intentionally filtered to reduce noise

• Some primitives are suppressed to keep logs readable

These limitations are inherent to how JAX works, not this tool.

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When Should You Use This?

Perfect for debugging:

• Matrix multiplication mismatches
• Broadcasting errors
• Silent shape drift in long pipelines
• Complex model code where shapes change dynamically

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License

MIT License © 2025 Kris

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Final Note

This tool exists because debugging shape errors should not feel like reverse-engineering a compiler.

If this saved you time, frustration, or sanity — mission accomplished.

Happy debugging 🚀