PyTorch Developer Tools

Free calculators, debuggers, and references for deep learning engineers. All tools run in your browser — no sign-up, no server, no tracking.

Built by Michael Lip

Shape Calculators

Conv2d Output Size Calculator

Calculate output height, width, and channels for PyTorch Conv2d layers.

Shape Calculator

Conv1d Output Size Calculator

Calculate output length for 1D convolutions on sequences and audio.

Shape Calculator

Linear Layer Shape Calculator

Calculate output dimensions for nn.Linear fully connected layers.

Shape Calculator

LSTM Output Shape Calculator

Calculate output shape for LSTM layers including bidirectional and multi-layer.

Shape Calculator

MaxPool2d Output Size Calculator

Calculate pooling output dimensions with kernel, stride, and padding.

Shape Calculator

BatchNorm Shape Calculator

Verify BatchNorm2d configuration and num_features matching.

Shape Calculator

Embedding Layer Shape Calculator

Calculate output shape for nn.Embedding lookup layers.

Shape Calculator

Flatten Output Shape Calculator

See how nn.Flatten collapses dimensions for fully connected layers.

Shape Calculator

ConvTranspose2d Output Size Calculator

Calculate output dimensions for transposed convolutions (upsampling).

Shape Calculator

MultiHead Attention Shape Calculator

Verify transformer attention layer configuration and output shapes.

Shape Calculator

Error Debuggers

PyTorch Shape Mismatch Error Debugger

Paste any shape error and get a plain English explanation with fix.

Error Debugger

mat1 and mat2 shapes cannot be multiplied

Fix the most common Linear layer error with dimension analysis.

Error Debugger

CUDA Out of Memory — Solutions

Quick solutions and memory optimization techniques for GPU training.

Error Debugger

view size not compatible — Fix

Understand contiguous memory, view vs reshape, and how to fix it.

Error Debugger

References

Activation Functions Comparison

Interactive plots, formulas, and pros/cons for ReLU, GELU, SiLU, and more.

Reference

Loss Functions Guide

Formulas, code examples, and when to use each PyTorch loss function.

Reference

Optimizers Comparison

Adam vs SGD vs AdamW — key parameters, memory usage, and best practices.

Reference

Einsum Calculator

Interactive einsum notation calculator for NumPy and PyTorch.

Reference

Model Analysis

Neural Network Parameter Counter

Add layers and get exact parameter counts with per-layer breakdown.

Model Tool

GPU Memory Calculator for Training

Estimate VRAM for parameters, gradients, optimizer states, and activations.

Model Tool

About These Tools

Every tool on this page runs entirely in your browser. No data is sent to any server. No cookies, no analytics, no tracking. The source code is open on GitHub.

These tools are built for ML engineers, researchers, and students who need quick answers about tensor shapes, layer configurations, and training requirements. All formulas match the official PyTorch documentation exactly.

Contact

Built and maintained by Michael Lip. Questions or feedback: [email protected].