google-research/morph-net

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1042 stars · 152 forks observed · 2026-10-15

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

MorphNet is a TensorFlow library for resource-constrained learning of deep network structure. It adds regularizers during training that induce activation sparsity, pruning channels to optimize targets like FLOPs, model size, or latency.

Use cases

• shrink a convolutional neural network to fit memory or latency constraints
• prune filters from an existing seed network during training
• perform differentiable architecture search with FiGS
• reduce model size for mobile or embedded deployment
• optimize a network for a target cost such as FLOPs or device latency

When to choose

• you have a working TensorFlow model and want to compress it under a resource budget
• you want structure learning without changing network topology

When to avoid

• you need to change layer counts or connectivity patterns of the network
• you work primarily outside TensorFlow or need actively maintained NAS tooling

Facets

library · maturity maintenance

machine-learning deep-learning machine-learning deep-learning python neural-architecture-search automl pruning tensorflow model-compression network-structure-learning gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="google-research/morph-net")