Registry / ai-ml / lovely-tensors

lovely-tensors

library0.1.22pypypi✓ verified 85d ago

lovely-tensors is a Python library that provides "syntax sugar" for PyTorch tensors, enhancing their default `repr` for better readability, debugging, and development. It adds features like rich, colored, and pretty-printed output, automatic batching, and shape inference. As of version 0.1.22, it is actively maintained with frequent minor releases focusing on new features and improvements.

ai-ml

pip install lovely-tensors

github ↗package ↗docs ↗

INSTALL

IMPORT

SIG · LOVELY-TENSORS

lovely-tensors

ai-mlpythonv0.1.22

Install

80.4s avg

Import

8110ms

Disk

4915MB

Pass rate

4/ 10

Env Coverage4 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.1.22 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

glibc

py 3.10

✕ build_error

✓ 87.45s

py 3.11

✕ build_error

✓ 88.35s

py 3.12

✕ build_error

✓ 77.1s

py 3.13

✕ build_error

✓ 68.7s

py 3.9

✕ build_error

✕ timeout

4915MB installed

● package 4915MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

lovely_tensors

✓ import lovely_tensors as lt

The common alias `lt` is widely used in examples and makes the code more concise.

monkey_patch

✓ import lovely_tensors as lt lt.monkey_patch()

✗ import lovely_tensors.monkey_patch # This doesn't activate it

Calling `lt.monkey_patch()` directly is necessary to enable the enhanced `__repr__` for PyTorch tensors globally.

lovely

✓ import lovely_tensors as lt lt.lovely(my_tensor)

Use `lt.lovely()` for explicit, controlled pretty-printing of a tensor, or when monkey-patching is not desired.

This quickstart demonstrates how to import `lovely-tensors`, enable its global monkey-patching for `torch.Tensor`'s `__repr__`, and then print PyTorch tensors to see the enhanced, colored output. It also shows how to use `lt.lovely()` for explicit pretty-printing.

import torch import lovely_tensors as lt # Enable beautiful tensor repr globally lt.monkey_patch() # Create some tensors a = torch.randn(2, 3, 4) b = torch.randint(0, 10, (1, 5), dtype=torch.int) print(f"Tensor a:\n{a}") print(f"Tensor b:\n{b}") # You can also explicitly print lovely tensors without monkey-patching # For demonstration, let's pretend monkey_patch wasn't called: # import lovely_tensors as lt # lt.lovely(torch.tensor([1,2,3]))

Debug

Known issues

gotchaTo activate the enhanced `__repr__` for PyTorch tensors automatically, you must explicitly call `lovely_tensors.monkey_patch()` after importing the library. Simply importing `lovely_tensors` is not enough.

fix

Ensure you have `import lovely_tensors as lt` followed by `lt.monkey_patch()` in your initialization code, typically at the start of your script or notebook.

affects: >=0.1.0

gotchalovely-tensors modifies the `__repr__` method of `torch.Tensor` instances. If you are using other debugging tools or libraries that also monkey-patch `torch.Tensor`'s `__repr__`, this might lead to conflicts or unexpected display behavior.

fix

If conflicts arise, try to import `lovely-tensors` before other potentially conflicting libraries. Alternatively, avoid `lt.monkey_patch()` and use `lt.lovely(tensor_instance)` for explicit pretty-printing when needed, giving you more control.

affects: >=0.1.0

deprecatedOlder versions of lovely-tensors used `lovely_tensors.init()` for activation. This method has been replaced by `lovely_tensors.monkey_patch()` for clarity and consistency.

fix

Update your code to use `lt.monkey_patch()` instead of `lt.init()` for global activation.

affects: <0.1.18

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'lovely_tensors'

The `lovely-tensors` library is not installed in your current Python environment.

fix

Run `pip install lovely-tensors` to install the library.

PyTorch tensors are not displaying with pretty colors or enhanced information, even after importing lovely_tensors.

The `monkey_patch()` function was not called, which is necessary to enable the global `__repr__` enhancement.

fix

After `import lovely_tensors as lt`, add `lt.monkey_patch()` to activate the desired behavior.

AttributeError: 'Tensor' object has no attribute 'lovely'

You are trying to access `lovely` as a method directly on a `torch.Tensor` instance, but `lovely` is a function provided by the `lovely_tensors` module, not a tensor method.

fix

Instead of `my_tensor.lovely()`, use `lt.lovely(my_tensor)` to explicitly pretty-print the tensor.

Upgrade

Version history

0.1.22latest on PyPI · released Mar 11, 2026

Audit

Dependencies

torchrequiredlovely-tensors extends PyTorch's tensor functionality and requires a compatible PyTorch version to operate.

Agent activity

4 hits · last 30 days

node

Resources

githubhttps://github.com/xl0/lovely-tensors ↗

packagehttps://pypi.org/project/lovely-tensors/ ↗

docshttps://xl0.github.io/lovely-tensors ↗