Struct tract_tensorflow::model::Tensorflow

pub struct Tensorflow {
    pub op_register: TfOpRegister,
}

Fields

op_register: TfOpRegister

Implementations

impl Tensorflow

pub fn determinize(model: &mut GraphDef) -> TractResult<()>

pub fn read_frozen_from_path( &self, p: impl AsRef<Path> ) -> TractResult<GraphDef>

pub fn read_frozen_model(&self, r: &mut dyn Read) -> TractResult<GraphDef>

pub fn open_saved_model(&self, r: &mut dyn Read) -> TractResult<SavedModel>

pub fn read_saved_model(&self, r: &mut dyn Read) -> TractResult<GraphDef>

Convenience method: will read the first model in the saved model container. Use open_avec_model for more control.

pub fn parse_graph(&self, graph: &GraphDef) -> TractResult<TfModelAndExtensions>

pub fn parse_graph_with_symbols( &self, graph: &GraphDef, symbols: &SymbolTable ) -> TractResult<TfModelAndExtensions>

Trait Implementations

impl Framework<GraphDef, Graph<InferenceFact, Box<dyn InferenceOp, Global>>> for Tensorflow

fn proto_model_for_path(&self, r: impl AsRef<Path>) -> TractResult<GraphDef>

This method will try to read as frozen model, then as a saved model.

fn proto_model_for_read(&self, r: &mut dyn Read) -> TractResult<GraphDef>

This method expects a frozen model, use open_saved_model for TF2 saved model format.

fn model_for_proto_model_with_symbols( &self, graph: &GraphDef, symbols: &SymbolTable ) -> TractResult<InferenceModel>

Translate a proto model into a model, with some symbols already listed.

fn model_for_proto_model(&self, proto: &ProtoModel) -> Result<Model, Error>

Translate a proto model into a model.

fn model_for_read(&self, r: &mut dyn Read) -> Result<Model, Error>

Read a model from a reader

fn model_for_path(&self, p: impl AsRef<Path>) -> Result<Model, Error>

Build a model from a filename.