Struct CrossFrameworkConverter 

pub struct CrossFrameworkConverter { /* private fields */ }

Cross-framework optimizer converter

Implementations

impl CrossFrameworkConverter

pub fn new() -> Self

Create a new cross-framework converter

pub fn to_universal( &self, config: &dyn ConfigSource, source_framework: Framework, ) -> Result<UniversalOptimizerConfig>

Convert optimizer configuration to universal format

pub fn from_universal( &self, config: &UniversalOptimizerConfig, target_framework: Framework, ) -> Result<Box<dyn ConfigTarget>>

Convert from universal format to target framework

pub fn convert( &self, config: &dyn ConfigSource, source_framework: Framework, target_framework: Framework, ) -> Result<Box<dyn ConfigTarget>>

Direct conversion between frameworks

pub fn pytorch_adam_to_tensorflow( &self, lr: f32, betas: (f32, f32), eps: f32, weight_decay: f32, ) -> Result<TensorFlowOptimizerConfig>

Convert PyTorch Adam to TensorFlow Adam

pub fn tensorflow_adam_to_pytorch( &self, lr: f32, beta_1: f32, beta_2: f32, epsilon: f32, weight_decay: f32, ) -> Result<PyTorchOptimizerConfig>

Convert TensorFlow Adam to PyTorch Adam

pub fn jax_adam_to_pytorch( &self, learning_rate: f32, b1: f32, b2: f32, eps: f32, ) -> Result<PyTorchOptimizerConfig>

Convert JAX Adam to PyTorch Adam

pub fn onnx_to_pytorch( &self, onnx_config: &ONNXConfig, ) -> Result<PyTorchOptimizerConfig>

Convert ONNX optimizer to PyTorch

pub fn batch_convert( &self, configs: Vec<(&dyn ConfigSource, Framework)>, target_framework: Framework, ) -> Result<Vec<Box<dyn ConfigTarget>>>

Batch convert multiple optimizers

pub fn generate_conversion_report( &self, source: Framework, target: Framework, ) -> String

Generate conversion report

Trait Implementations

impl Default for CrossFrameworkConverter

fn default() -> Self

Returns the “default value” for a type.