TensorFlow Error. With Rust Failed to start training: InvalidArgument:

TensorFlow General Discussion
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I am using rust with TensorFlow and I keep getting this error for this part of the code on the last line nd.finish and I cannot figure out why. Any ideas?

    print!("Setting up TensorFlow disc_optimizer_op operations \n");    
    let disc_optimizer_op = {
        print!("- let mut nd = graph.new_operation \n");
        let mut nd = graph.new_operation("ApplyGradientDescent", "disc_optimizer")?;
        print!("- let learning_rate = 0.001f32 \n");
        let learning_rate = 0.001f32;
        // determine the learning_rate type

        print!("- nd.set_attr_float \n");
        nd.set_attr_float("learning_rate", learning_rate)?;
        print!("- nd.add_input \n");
    
        nd.add_input(disc_loss_op.clone());
        print!("- nd.finish \n");
        let result = nd.finish()?;
        println!("Result from nd.finish(): {:?}", result);
        result
    };

ERROR:

Failed to start training: InvalidArgument: 2 errors while building NodeDef 'disc_optimizer' using Op<name=ApplyGradientDescent; signature=var:Ref(T), alpha:T, delta:T -> out:Ref(T); attr=T:type,allowed=[DT_FLOAT, DT_DOUBLE, DT_INT32, DT_UINT8, DT_INT16, DT_INT8, DT_COMPLEX64, DT_INT64, DT_QINT8, DT_QUINT8, DT_QINT32, DT_BFLOAT16, DT_QINT16, DT_QUINT16, DT_UINT16, DT_COMPLEX128, DT_HALF, DT_UINT32, DT_UINT64]; attr=use_locking:bool,default=false>:
Input 'var' passed float expected ref type
1 inputs specified of 3 inputs in Op