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        "description": "# torch-parameter-groups [![Build Status](https://travis-ci.com/FebruaryBreeze/torch-parameter-groups.svg?branch=master)](https://travis-ci.com/FebruaryBreeze/torch-parameter-groups) [![codecov](https://codecov.io/gh/FebruaryBreeze/torch-parameter-groups/branch/master/graph/badge.svg)](https://codecov.io/gh/FebruaryBreeze/torch-parameter-groups) [![PyPI version](https://badge.fury.io/py/torch-parameter-groups.svg)](https://pypi.org/project/torch-parameter-groups/)\n\nGroup PyTorch Parameters according to Rules.\n\n## Installation\n\nNeed Python 3.6+.\n\n```bash\npip install torch-parameter-groups\n```\n\n## Usage\n\n```python\nimport torch\nimport torch.nn as nn\nimport torch_basic_models\nimport torch_parameter_groups\n\n\nmodel = torch_basic_models.MobileNetV2.factory()\noptimizer = torch_parameter_groups.optimizer_factory(\n    model=model,\n    config={\n        'type': 'SGD',\n        'kwargs': {\n            'momentum': 0.9,\n            'nesterov': True,\n            'weight_decay': 0.0001,\n        },\n        'rules': [\n            {\n                'param_name_list': ['weight'],\n                'kwargs': {\n                    'weight_decay': 0\n                }\n            },\n            {\n            }\n        ]\n    },\n)\n\ncriterion = nn.CrossEntropyLoss()\noutput = model(torch.randn(1, 3, 224, 224))\nloss = criterion(output, torch.Tensor([0]).long())\nloss.backward()\noptimizer.step(closure=None)\n```",
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