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GitHub Open Source duoan/TorchCode

πŸ”₯ LeetCode for PyTorch β€” practice implementing softmax, attention, GPT-2 and more from scratch with instant auto-grading. Jupyter-based, self-hosted or try online.

1,661
Traction Score
129
Forks
Mar 4, 2026
Launch Date
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Product Positioning & Context

AI Executive Synthesis
Incorporating advanced distributed training techniques into the PyTorch learning environment.
The issue title 'FSDP training loop' without further body content suggests a request or discussion point regarding the implementation of Fully Sharded Data Parallel (FSDP) within TorchCode. FSDP is a critical advanced distributed training technique for large models. Its inclusion or discussion indicates a demand from users for learning and practicing state-of-the-art model scaling methods. For a platform focused on 'implementing from scratch,' integrating FSDP would significantly elevate its relevance for advanced PyTorch practitioners, addressing the complexities of training large-scale models efficiently. This points to a strategic opportunity to expand the curriculum into high-performance computing for deep learning.
πŸ”₯ LeetCode for PyTorch β€” practice implementing softmax, attention, GPT-2 and more from scratch with instant auto-grading. Jupyter-based, self-hosted or try online.
interview leetcode pytorch

Active Developer Issues (GitHub)

open Outputs are not correctly checked - [9] Causal Self Attention
Logged: Apr 5, 2026
open Question: is the uniform distribution fallback in rejection sampling theoretically unreachable?
Logged: Apr 3, 2026
open Marimo instead of jupyter?
Logged: Mar 21, 2026
open Suggestion: Update Linear layer initialization from Xavier to Kaiming for ReLU compatibility
Logged: Mar 17, 2026
open ReLU Issue
Logged: Mar 9, 2026

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