{"id":26918,"library":"dynamic-network-architectures","title":"DynamicNetworkArchitectures","description":"A library for dynamic network architectures, including Deep Belief Networks and other configurable neural network structures. Version 0.4.3 supports Python 3.8+, focuses on flexible network building and training utilities. Release cadence is irregular.","status":"active","version":"0.4.3","language":"python","source_language":"en","source_url":"https://github.com/NeuroSYS-pl/dynamic-network-architectures","tags":["deep-belief-networks","restricted-boltzmann-machines","neural-networks","deep-learning","dynamic-architecture"],"install":[{"cmd":"pip install dynamic-network-architectures","lang":"bash","label":"Install from PyPI"}],"dependencies":[{"reason":"Core dependency for tensor operations and neural network building blocks","package":"torch","optional":false},{"reason":"Used for numerical operations and data handling","package":"numpy","optional":false}],"imports":[{"wrong":"from dynamic_network_architectures import DeepBeliefNetwork","symbol":"DeepBeliefNetwork","correct":"from dynamic_network_architectures import DeepBeliefNetwork"}],"quickstart":{"code":"from dynamic_network_architectures import DeepBeliefNetwork\nimport torch\n\n# Create a simple Deep Belief Network\nmodel = DeepBeliefNetwork(\n    layers=[784, 500, 200],\n    learning_rate=0.01,\n    n_epochs=10,\n    batch_size=64\n)\n\n# Generate random data (e.g., MNIST-like)\ndata = torch.randn(64, 784)\n\n# Train the model\nmodel.fit(data)\n\n# Generate samples\nsamples = model.generate(n_samples=10)\nprint(samples.shape)","lang":"python","description":"Create and train a Deep Belief Network with random data."},"warnings":[{"fix":"Update to use simple integers for layer sizes, e.g., layers=[784, 500, 200].","message":"In version 0.4.0, the 'layers' parameter in DeepBeliefNetwork changed from list of dicts to list of ints. Old code with dict configurations will break.","severity":"breaking","affected_versions":"<0.4.0"},{"fix":"Replace n_gibbs_steps with chain_length: model.generate(n_samples, chain_length=10).","message":"The 'n_gibbs_steps' argument in DeepBeliefNetwork.generate() is deprecated in 0.4.3 and will be removed in next release. Use 'chain_length' instead.","severity":"deprecated","affected_versions":">=0.4.0"},{"fix":"Convert numpy arrays to torch tensors before calling fit().","message":"Training with mini-batches requires data to be a torch.Tensor. Passing bare numpy arrays to fit() will raise a TypeError.","severity":"gotcha","affected_versions":"all"}],"env_vars":null,"search_vec":"'0.4.3':19 '3.8':22 'architectur':7,51 'belief':10,37 'boltzmann':41 'build':27 'cadenc':32 'configur':14 'deep':9,36,47 'deep-belief-network':35 'deep-learn':46 'dynam':5,50 'dynamic-architectur':49 'dynamicnetworkarchitectur':1 'flexibl':25 'focus':23 'includ':8 'irregular':34 'learn':48 'librari':3 'machin':42 'network':6,11,16,26,38,45 'neural':15,44 'neural-network':43 'python':21 'releas':31 'restrict':40 'restricted-boltzmann-machin':39 'structur':17 'support':20 'train':29 'util':30 'version':18","created_at":"2026-05-01T17:43:33.122738+00:00","updated_at":"2026-05-01T17:43:33.122738+00:00","problems":{"verify_error":"Traceback (most recent call last):\n  File \"<string>\", line 1, in <module>\nImportError: cannot import name 'DeepBeliefNetwork' from 'dynamic_network_architectures' (/tmp/tmp7olaxl68/venv/lib/python3.12/site-packages/dynamic_network_architectures/__init__.py)"},"ecosystem":"pypi","meta_description":null,"install_score":null,"quickstart_score":null,"quickstart_tag":null,"pypi_latest":null,"cli_name":"","cli_version":null,"type":"library","homepage":null,"github":null,"docs":null,"changelog":null,"pypi":"https://pypi.org/project/dynamic-network-architectures/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"categories":["ai-ml"],"base_url":null,"auth_type":null,"provenance":{"verified_status":"import_fail","verified_at":"2026-07-03","last_verified":"2026-07-03","next_check":"2026-07-10","install_tag":null}}