Data Augmentation Planner

Augmentation Techniques

Synonym Replacement Replace random words with synonyms. ~1.3x multiplier.

Back-Translation Translate to other lang & back. ~1.5x multiplier.

Random Insertion Insert random synonyms into text. ~1.2x multiplier.

Random Swap Randomly swap word positions. ~1.4x multiplier.

Contextual Word Embeddings Generate variations using language model. ~1.3x.

Paraphrasing Generate paraphrases with same meaning. ~1.6x.

Effective Dataset Multiplier

1.0x

Dataset size increase from augmentation

Training Time Increase

Approximate epoch-based increase

Augmentation Intensity 0%

Selected Techniques

Take the next step in your own PyTorch model.

Trace a local forward pass, inspect tensor shapes in an HTML report, and turn a repair into a regression check. Includes eight broken-and-fixed workflows, source code and setup instructions.

Is this toolkit right for my problem?

Use the free calculator for a layer formula or a quick shape check.

Consider Tensor Preflight when you have a local PyTorch model and want a forward-pass report plus repeatable checks. Python 3.9+ and PyTorch 2.8+ are required. It does not run your model in this website or automatically repair it.

Open the sample report before buying to check the output format.

Python 3.9+ · PyTorch 2.8+ · Runs locally