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...Common network families (MPS/TT, PEPS, MERA, tree networks) are expressed with concise APIs that encourage experimentation and comparison. The library provides automatic path finding and cost estimation, exposing when contractions will explode in memory and suggesting better orders. Because it supports backends such as NumPy, TensorFlow, PyTorch, and JAX, the same model can run on CPUs, GPUs, or TPUs with minimal code changes. Tutorials and visualization helpers make it easier to understand how network topology affects expressive power and computational cost.