Rico's Nerd Cluster

「离开世界之前 一切都是过程」

[BEV] BEV Ideas and View Transformation

Training pipelines, multiview geometry, and how to lift image features into BEV

1. The Core Goal of a BEV Network A Bird’s Eye View (BEV) network aims to reconstruct, in real time using only onboard cameras, a local 3D map of comparable quality to what an offline reconstructi...

[BEV] BEV Introduction: Tesla's Challenges and Architecture

Why per-camera detection falls short, and how BEV solves it

1. Tesla’s Perception Challenges (2021) Before BEV, Tesla’s pipeline detected objects and lanes independently in each camera view and then tried to fuse the results. This created fundamental probl...

[BEV] BEV Introduction

Understanding L2 and L2+ Perception: Why the Real Challenge Is System Design, Not Just Better Detection When people talk about assisted driving, they often jump straight to compute power, percepti...

[Point Cloud Compression] Draco

Introduction Draco is Google’s open-source library for compressing 3D geometric meshes and point clouds. It quantizes floating-point attributes (positions, normals, colors, texture coordinates) in...

[ML] HuggingFace Trainer

Introduction The Trainer class provides a feature-complete training loop for PyTorch, supporting distributed training on multiple GPUs/TPUs and mixed precision via NVIDIA Apex, AMD ROCm, and torch...

[ML] Model Visualization

ONNX, Netron, Model Size

Netron Netron is a viewer for neural network models. The typical workflow is to export a PyTorch model to ONNX format and then drag the .onnx file into the Netron web app. What is ONNX? Open Neur...

[ML] PyTorch Functions

autograd Function, Convolution, Normalization, Sum, Torch Cache Emptying

Torch.autograd.Function torch.autograd.Function lets you define a custom op with explicit forward() and backward() passes. Common built-ins like MaxPool are implemented this way. It’s especially u...

PyTorch Mixed Precision Training

torch.zeros, GradScaler, GradCheck

Pytorch Setup 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 use_amp = True net = make_model(in_size, out_size, num_layers) opt = torch.optim.SGD(net.parameters(), lr=0.001) # if False, th...

Deep Learning - Mixed Floating Point Training

FP16, BF16, Mixed Precision Training

Refresher: Floating Point Calculation A floating point is represented as sign bit | exponent | mantissa. 0 | 10000001 | 10000000000000000000000 represents 6 because: Sign bit 0 represents posi...

[ML] Libraries For Point Cloud Compression

einops

einops Einops is a lightweight Python library that makes tensor reshaping, permutation, tiling, and reduction readable and explicit. It works with PyTorch, NumPy, and TensorFlow. rearrange — r...