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Distributed multi-GPU and multi-node learning (PyTorch implementation) (
#162) * Add PyTorch framework configuration * Initialize distributed process in trainer base class * Improve property annotation and docstrings * Add PyTorch framework config to docs * Increase seed according to worker rank in distributed runs * Update agent and trainer configuration to avoid duplicated data in distributed runs * Add method to broadcast and reduce distributed model parameters * Setup distributed runs * Add distributed implementation to PPO agent * Fix torch deprecated warning * Reduce and broadcast learning rate across all workers/processes * Update CHANGELOG * Implement distributed runs for on-policy agents * Add distributed implementation to agent features * Implement distributed runs for off-policy agents * Update off-policy agents features table in docs * Unify code style for distributed implementation * Implement distributed runs for multi-agents * Update multi-agents features table in docs
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