# Overview of Migration Guide [](https://gitee.com/mindspore/docs/blob/r2.5.0/docs/mindspore/source_en/migration_guide/overview.md) This migration guide contains the complete steps for migrating neural networks to MindSpore from other machine learning frameworks, mainly PyTorch. ```{mermaid} flowchart LR A(Overview)-->B(migration process) B-->|Step 1|E(<font color=blue>Environmental Preparation</font>) E-.-text1(MindSpore Installation) E-.-text2(AI Platform ModelArts) B-->|Step 2|F(<font color=blue>Model Analysis and Preparation</font>) F-.-text3("Reproducing algorithm, analyzing API compliance using MindSpore Dev Toolkit and analyzing function compliance.") B-->|Step 3|G(<font color=blue>Network Constructing Comparison</font>) G-->I(<font color=blue>Dataset</font>) I-.-text4("Aligning the process of dataset loading, augmentation and reading") G-->J(<font color=blue>Network Constructing</font>) J-.-text5(Aligning the network) G-->K(<font color=blue>Loss Function</font>) K-.-text6(Aligning the loss function) G-->L(<font color=blue>Learning Rate and Optimizer</font>) L-.-text7("Aligning the optimizer and learning rate strategy") G-->M(<font color=blue>Gradient</font>) M-.-text8("Aligning the reverse gradients") G-->N(<font color=blue>Training and Evaluation Process</font>) N-.-text9("Aligning the process of training and evaluation") B-->|Step 4|H(<font color=blue>Debug and Tune</font>) H-->O(<font color=blue>Function Debugging</font>) O-.-text10(Functional alignment) H-->P(<font color=blue>Precision Tuning</font>) P-.-text11(Precision alignment) H-->Q(<font color=blue>Performance Tuning</font>) Q-.-text12(Performance Alignment) A-->C(<font color=blue>A Migration Sample</font>) C-.-text13("The network migration sample, taking ResNet50 as an example.") A-->D(<font color=blue>Reference</font>) D-->R(<font color=blue>PyTorch and MindSpore API Mapping Table</font>) D-->S(<font color=blue>Application Practice Guide for Network Migration Tool</font>) D-->T(<font color=blue>FAQs</font>) click C "https://www.mindspore.cn/docs/en/r2.5.0/migration_guide/sample_code.html" click D "https://www.mindspore.cn/docs/en/r2.5.0/migration_guide/reference.html" click E "https://www.mindspore.cn/docs/en/r2.5.0/migration_guide/enveriment_preparation.html" click F "https://www.mindspore.cn/docs/en/r2.5.0/migration_guide/analysis_and_preparation.html" click G "https://www.mindspore.cn/docs/en/r2.5.0/migration_guide/model_development/model_development.html" click H "https://www.mindspore.cn/docs/en/r2.5.0/migration_guide/debug_and_tune.html#debug-and-tune" click I "https://www.mindspore.cn/docs/en/r2.5.0/migration_guide/model_development/dataset.html" click J "https://www.mindspore.cn/docs/en/r2.5.0/migration_guide/model_development/model_and_cell.html" click K "https://www.mindspore.cn/docs/en/r2.5.0/migration_guide/model_development/loss_function.html" click L "https://www.mindspore.cn/docs/en/r2.5.0/migration_guide/model_development/learning_rate_and_optimizer.html" click M "https://www.mindspore.cn/docs/en/r2.5.0/migration_guide/model_development/gradient.html" click N "https://www.mindspore.cn/docs/en/r2.5.0/migration_guide/model_development/training_and_evaluation.html" click O "https://www.mindspore.cn/docs/en/r2.5.0/migration_guide/debug_and_tune.html#function-debugging" click P "https://www.mindspore.cn/docs/en/r2.5.0/migration_guide/debug_and_tune.html#precision-tuning" click Q "https://www.mindspore.cn/docs/en/r2.5.0/migration_guide/debug_and_tune.html#performance-tuning" click R "https://www.mindspore.cn/docs/en/r2.5.0/note/api_mapping/pytorch_api_mapping.html" click S "https://www.mindspore.cn/docs/en/r2.5.0/migration_guide/migrator_with_tools.html" click T "https://www.mindspore.cn/docs/en/r2.5.0/migration_guide/faq.html" ```