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Model Memory Utility is a tool designed to help developers and researchers calculate the memory requirements for training AI models. It provides a straightforward way to estimate the memory needed based on model architecture, batch size, and optimizer settings. This utility is particularly useful for optimizing model training in environments with limited computational resources.
• Model Architecture Support: Compatible with popular frameworks like TensorFlow, PyTorch, and others.
• Batch Size Calculation: Estimates memory usage based on different batch sizes.
• Optimizer Integration: Accounts for memory overhead from various optimizers.
• Offline Functionality: No internet connection required for calculations.
• Customizable Parameters: Allows users to input specific model configurations.
• Detailed Reports: Provides a breakdown of memory usage for different components.
• Cross-Platform Compatibility: Runs on multiple operating systems, including Windows, Linux, and macOS.
What frameworks does Model Memory Utility support?
Model Memory Utility supports TensorFlow, PyTorch, and other popular deep learning frameworks.
Do I need to install any additional libraries to use the utility?
No, the utility is self-contained and does not require additional libraries beyond the installation package.
Can I customize the output format of the memory report?
Yes, the utility allows users to choose between CSV, JSON, or plain text formats for the memory report.