pub fn from_clap(matches: &clap::ArgMatches) -> CliResult<Parameters> {
        let name = matches.value_of("model").unwrap();
        let format = matches.value_of("format").unwrap_or(if name.ends_with(".onnx") {
            "onnx"
        } else {
            "tf"
        });
        let (graph, mut raw_model) = if format == "onnx" {
            #[cfg(not(feature = "onnx"))]
            {
                panic!("Tract compiled without onnx feature");
            }
            #[cfg(feature = "onnx")]
            {
                let onnx = tract_onnx::onnx();
                let graph = onnx.proto_model_for_path(&name)?;
                let tract = onnx.model_for_proto_model(&graph)?;
                (SomeGraphDef::Onnx(graph), tract)
            }
        } else {
            #[cfg(not(feature = "tf"))]
            {
                panic!("Tract compiled without tensorflow feature");
            }
            #[cfg(feature = "tf")]
            {
                let tf = tract_tensorflow::tensorflow();
                let graph = tf.proto_model_for_path(&name)?;
                let tract = tf.model_for_proto_model(&graph)?;
                (SomeGraphDef::Tf(graph), tract)
            }
        };

        info!("Model {:?} loaded", name);

        #[cfg(feature = "conform")]
        let tf_model = if format == "tf" {
            info!("Tensorflow version: {}", tract_tensorflow::conform::tf::version());
            Some(tract_tensorflow::conform::tf::for_path(&name)?)
        } else {
            None
        };

        #[cfg(not(feature = "conform"))]
        let tf_model = ();

        if let Some(inputs) = matches.values_of("input_node") {
            raw_model.set_input_names(inputs)?;
        };

        if let Some(outputs) = matches.values_of("output_node") {
            raw_model.set_output_names(outputs)?;
        };

        let machine_friendly = matches.is_present("machine_friendly");

        let inputs = if let Some(inputs) = matches.values_of("input") {
            let mut vs = vec![];
            for (ix, v) in inputs.enumerate() {
                let t = tensor::for_string(v)?;
                let outlet = raw_model.input_outlets()?[ix];
                vs.push(t.value.concretize());
                raw_model.set_outlet_fact(outlet, t)?;
            }
            Some(vs)
        } else {
            None
        };

        let pulse: Option<usize> = matches.value_of("pulse").map(|s| s.parse()).transpose()?;

        //        println!("{:?}", raw_model);

        let mut unoptimized_model = None;
        let mut tract_model = if !matches.is_present("skip_analyse") {
            info!("Running analyse");
            if let Err(e) = raw_model.analyse(true) {
                // do not stop on mere analyse error
                error!("{}", e);
            }
            if matches.is_present("skip_type") {
                SomeModel::Inference(raw_model)
            } else {
                let typed = raw_model.into_typed()?;
                unoptimized_model = Some(typed.clone());
                SomeModel::Typed(typed)
            }
        } else {
            info!("Skipping analyse");
            SomeModel::Inference(raw_model)
        };

        if matches.is_present("optimize")
            || matches.is_present("declutter")
            || pulse.is_some()
            || matches.subcommand().0 == "optimize-check"
        {
            if let SomeModel::Typed(typed) = tract_model {
                info!("Declutter");
                tract_model = SomeModel::Typed(typed.declutter()?);
            } else {
                bail!("Can not run optimize without analyse")
            }
        }

        if let (Some(pulse), &SomeModel::Typed(ref model)) = (pulse, &tract_model) {
            info!("Convert to normalized net");
            let normalized = model.clone().into_normalized()?;
            info!("Pulsify {}", pulse);
            let pulsed = ::tract_core::pulse::PulsedModel::new(&normalized, pulse)?;
            tract_model = SomeModel::Pulsed(normalized, pulsed);
        };

        if matches.is_present("optimize") {
            if let SomeModel::Typed(typed) = tract_model {
                tract_model = SomeModel::Typed(typed.codegen()?);
            } else if let SomeModel::Pulsed(_, pulsed) = tract_model {
                tract_model = SomeModel::Typed(pulsed.into_typed()?.codegen()?);
            }
        }

        info!("Model ready");

        Ok(Parameters {
            name: name.to_string(),
            graph,
            unoptimized_model,
            tract_model,
            tf_model,
            inputs,
            assertions: None,
            machine_friendly,
        })
    }
/// Parses the command-line arguments.
Parses the command-line arguments.
Parses the command - line arguments .
pub fn from_clap(matches: &clap::ArgMatches) -> CliResult<Parameters> {
        let name = matches.value_of("model").unwrap();
        let format = matches.value_of("format").unwrap_or(if name.ends_with(".onnx") {
            "onnx"
        } else {
            "tf"
        });
        let (graph, mut raw_model) = if format == "onnx" {
            #[cfg(not(feature = "onnx"))]
            {
                panic!("Tract compiled without onnx feature");
            }
            #[cfg(feature = "onnx")]
            {
                let onnx = tract_onnx::onnx();
                let graph = onnx.proto_model_for_path(&name)?;
                let tract = onnx.model_for_proto_model(&graph)?;
                (SomeGraphDef::Onnx(graph), tract)
            }
        } else {
            #[cfg(not(feature = "tf"))]
            {
                panic!("Tract compiled without tensorflow feature");
            }
            #[cfg(feature = "tf")]
            {
                let tf = tract_tensorflow::tensorflow();
                let graph = tf.proto_model_for_path(&name)?;
                let tract = tf.model_for_proto_model(&graph)?;
                (SomeGraphDef::Tf(graph), tract)
            }
        };
        info!("Model {:?} loaded", name);
        #[cfg(feature = "conform")]
        let tf_model = if format == "tf" {
            info!("Tensorflow version: {}", tract_tensorflow::conform::tf::version());
            Some(tract_tensorflow::conform::tf::for_path(&name)?)
        } else {
            None
        };
        #[cfg(not(feature = "conform"))]
        let tf_model = ();
        if let Some(inputs) = matches.values_of("input_node") {
            raw_model.set_input_names(inputs)?;
        };
        if let Some(outputs) = matches.values_of("output_node") {
            raw_model.set_output_names(outputs)?;
        };
        let machine_friendly = matches.is_present("machine_friendly");
        let inputs = if let Some(inputs) = matches.values_of("input") {
            let mut vs = vec![];
            for (ix, v) in inputs.enumerate() {
                let t = tensor::for_string(v)?;
                let outlet = raw_model.input_outlets()?[ix];
                vs.push(t.value.concretize());
                raw_model.set_outlet_fact(outlet, t)?;
            }
            Some(vs)
        } else {
            None
        };
        let pulse: Option<usize> = matches.value_of("pulse").map(|s| s.parse()).transpose()?;
        //        println!("{:?}", raw_model);
        let mut unoptimized_model = None;
        let mut tract_model = if !matches.is_present("skip_analyse") {
            info!("Running analyse");
            if let Err(e) = raw_model.analyse(true) {
                // do not stop on mere analyse error
                error!("{}", e);
            }
            if matches.is_present("skip_type") {
                SomeModel::Inference(raw_model)
            } else {
                let typed = raw_model.into_typed()?;
                unoptimized_model = Some(typed.clone());
                SomeModel::Typed(typed)
            }
        } else {
            info!("Skipping analyse");
            SomeModel::Inference(raw_model)
        };
        if matches.is_present("optimize")
            || matches.is_present("declutter")
            || pulse.is_some()
            || matches.subcommand().0 == "optimize-check"
        {
            if let SomeModel::Typed(typed) = tract_model {
                info!("Declutter");
                tract_model = SomeModel::Typed(typed.declutter()?);
            } else {
                bail!("Can not run optimize without analyse")
            }
        }
        if let (Some(pulse), &SomeModel::Typed(ref model)) = (pulse, &tract_model) {
            info!("Convert to normalized net");
            let normalized = model.clone().into_normalized()?;
            info!("Pulsify {}", pulse);
            let pulsed = ::tract_core::pulse::PulsedModel::new(&normalized, pulse)?;
            tract_model = SomeModel::Pulsed(normalized, pulsed);
        };
        if matches.is_present("optimize") {
            if let SomeModel::Typed(typed) = tract_model {
                tract_model = SomeModel::Typed(typed.codegen()?);
            } else if let SomeModel::Pulsed(_, pulsed) = tract_model {
                tract_model = SomeModel::Typed(pulsed.into_typed()?.codegen()?);
            }
        }
        info!("Model ready");
        Ok(Parameters {
            name: name.to_string(),
            graph,
            unoptimized_model,
            tract_model,
            tf_model,
            inputs,
            assertions: None,
            machine_friendly,
        })
    }
pub fn from_clap ( matches : & clap :: ArgMatches ) -> CliResult < Parameters > { let name = matches . value_of ( " " ) . unwrap ( ) ; let format = matches . value_of ( " " ) . unwrap_or ( if name . ends_with ( " " ) { " " } else { " " } ) ; let ( graph , mut raw_model ) = if format == " " { # [ cfg ( not ( feature " " ) ) ] { panic ! ( " " ) ; } # [ cfg ( feature " " ) ] { let onnx = tract_onnx :: onnx ( ) ; let graph = onnx . proto_model_for_path ( & name ) ? ; let tract = onnx . model_for_proto_model ( & graph ) ? ; ( SomeGraphDef :: Onnx ( graph ) , tract ) } } else { # [ cfg ( not ( feature " " ) ) ] { panic ! ( " " ) ; } # [ cfg ( feature " " ) ] { let tf = tract_tensorflow :: tensorflow ( ) ; let graph = tf . proto_model_for_path ( & name ) ? ; let tract = tf . model_for_proto_model ( & graph ) ? ; ( SomeGraphDef :: Tf ( graph ) , tract ) } } ; info ! ( " " name ) ; # [ cfg ( feature " " ) ] let tf_model = if format == " " { info ! ( " " tract_tensorflow conform tf version ( ) ) ; Some ( tract_tensorflow :: conform :: tf :: for_path ( & name ) ? ) } else { None } ; # [ cfg ( not ( feature " " ) ) ] let tf_model = ( ) ; if let Some ( inputs ) = matches . values_of ( " " ) { raw_model . set_input_names ( inputs ) ? ; } ; if let Some ( outputs ) = matches . values_of ( " " ) { raw_model . set_output_names ( outputs ) ? ; } ; let machine_friendly = matches . is_present ( " " ) ; let inputs = if let Some ( inputs ) = matches . values_of ( " " ) { let mut vs = vec ! [ ] ; for ( ix , v ) in inputs . enumerate ( ) { let t = tensor :: for_string ( v ) ? ; let outlet = raw_model . input_outlets ( ) ? [ ix ] ; vs . push ( t . value . concretize ( ) ) ; raw_model . set_outlet_fact ( outlet , t ) ? ; } Some ( vs ) } else { None } ; let pulse : Option < usize > = matches . value_of ( " " ) . map ( | s | s . parse ( ) ) . transpose ( ) ? ; //        println!("{:?}", raw_model); let mut unoptimized_model = None ; let mut tract_model = if ! matches . is_present ( " " ) { info ! ( " " ) ; if let Err ( e ) = raw_model . analyse ( true ) { // do not stop on mere analyse error error ! ( " " e ) ; } if matches . is_present ( " " ) { SomeModel :: Inference ( raw_model ) } else { let typed = raw_model . into_typed ( ) ? ; unoptimized_model = Some ( typed . clone ( ) ) ; SomeModel :: Typed ( typed ) } } else { info ! ( " " ) ; SomeModel :: Inference ( raw_model ) } ; if matches . is_present ( " " ) || matches . is_present ( " " ) || pulse . is_some ( ) || matches . subcommand ( ) . 0 == " " { if let SomeModel :: Typed ( typed ) = tract_model { info ! ( " " ) ; tract_model = SomeModel :: Typed ( typed . declutter ( ) ? ) ; } else { bail ! ( " " ) } } if let ( Some ( pulse ) , & SomeModel :: Typed ( ref model ) ) = ( pulse , & tract_model ) { info ! ( " " ) ; let normalized = model . clone ( ) . into_normalized ( ) ? ; info ! ( " " pulse ) ; let pulsed = :: tract_core :: pulse :: PulsedModel :: new ( & normalized , pulse ) ? ; tract_model = SomeModel :: Pulsed ( normalized , pulsed ) ; } ; if matches . is_present ( " " ) { if let SomeModel :: Typed ( typed ) = tract_model { tract_model = SomeModel :: Typed ( typed . codegen ( ) ? ) ; } else if let SomeModel :: Pulsed ( _ , pulsed ) = tract_model { tract_model = SomeModel :: Typed ( pulsed . into_typed ( ) ? . codegen ( ) ? ) ; } } info ! ( " " ) ; Ok ( Parameters { name : name . to_string ( ) , graph , unoptimized_model , tract_model , tf_model , inputs , assertions : None , machine_friendly , } ) }
Parses the command-line arguments.
Parses the command - line arguments .
matches
&clap::ArgMatches
matches
&clap::ArgMatches