pub struct Tensorflow {
pub op_register: TfOpRegister,
}Fields§
§op_register: TfOpRegisterImplementations§
Source§impl Tensorflow
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>
Sourcepub fn read_saved_model(&self, r: &mut dyn Read) -> TractResult<GraphDef>
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_template( &self, graph: &GraphDef, model: InferenceModel, ) -> TractResult<TfModelAndExtensions>
Trait Implementations§
Source§impl Framework<GraphDef, Graph<InferenceFact, Box<dyn InferenceOp>>> for Tensorflow
impl Framework<GraphDef, Graph<InferenceFact, Box<dyn InferenceOp>>> for Tensorflow
Source§fn proto_model_for_path(&self, r: impl AsRef<Path>) -> TractResult<GraphDef>
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.
Source§fn proto_model_for_read(&self, r: &mut dyn Read) -> TractResult<GraphDef>
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.
Source§fn model_for_proto_model_with_model_template(
&self,
proto: &GraphDef,
template: InferenceModel,
) -> TractResult<InferenceModel>
fn model_for_proto_model_with_model_template( &self, proto: &GraphDef, template: InferenceModel, ) -> TractResult<InferenceModel>
Translate a proto model into a model, with some symbols already listed.
Source§fn model_for_proto_model(&self, proto: &ProtoModel) -> Result<Model, Error>
fn model_for_proto_model(&self, proto: &ProtoModel) -> Result<Model, Error>
Translate a proto model into a model.
Auto Trait Implementations§
impl Freeze for Tensorflow
impl RefUnwindSafe for Tensorflow
impl Send for Tensorflow
impl Sync for Tensorflow
impl Unpin for Tensorflow
impl UnsafeUnpin for Tensorflow
impl UnwindSafe for Tensorflow
Blanket Implementations§
Source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
Source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
Source§impl<T> Downcast for Twhere
T: Any,
impl<T> Downcast for Twhere
T: Any,
Source§fn into_any(self: Box<T>) -> Box<dyn Any>
fn into_any(self: Box<T>) -> Box<dyn Any>
Convert
Box<dyn Trait> (where Trait: Downcast) to Box<dyn Any>. Box<dyn Any> can
then be further downcast into Box<ConcreteType> where ConcreteType implements Trait.Source§fn into_any_rc(self: Rc<T>) -> Rc<dyn Any>
fn into_any_rc(self: Rc<T>) -> Rc<dyn Any>
Convert
Rc<Trait> (where Trait: Downcast) to Rc<Any>. Rc<Any> can then be
further downcast into Rc<ConcreteType> where ConcreteType implements Trait.Source§fn as_any(&self) -> &(dyn Any + 'static)
fn as_any(&self) -> &(dyn Any + 'static)
Convert
&Trait (where Trait: Downcast) to &Any. This is needed since Rust cannot
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fn as_any_mut(&mut self) -> &mut (dyn Any + 'static)
Convert
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impl<T> DowncastSync for T
Source§impl<T> IntoEither for T
impl<T> IntoEither for T
Source§fn into_either(self, into_left: bool) -> Either<Self, Self> ⓘ
fn into_either(self, into_left: bool) -> Either<Self, Self> ⓘ
Converts
self into a Left variant of Either<Self, Self>
if into_left is true.
Converts self into a Right variant of Either<Self, Self>
otherwise. Read moreSource§fn into_either_with<F>(self, into_left: F) -> Either<Self, Self> ⓘ
fn into_either_with<F>(self, into_left: F) -> Either<Self, Self> ⓘ
Converts
self into a Left variant of Either<Self, Self>
if into_left(&self) returns true.
Converts self into a Right variant of Either<Self, Self>
otherwise. Read more