case class ModelInstance[In, TrainIn, Out, TrainOut, Loss, EvalIn](model: TrainableModel[In, TrainIn, Out, TrainOut, Loss, EvalIn], configuration: Configuration, trainInputIterator: Option[DatasetIterator[TrainIn]] = None, trainInput: Option[TrainIn] = None, output: Option[Out] = None, trainOutput: Option[TrainOut] = None, loss: Option[ops.Output[Loss]] = None, gradientsAndVariables: Option[Seq[(ops.OutputLike[Loss], ops.variables.Variable[Any])]] = None, trainOp: Option[ops.UntypedOp] = None)(implicit evidence$1: core.types.TF[Loss], evidence$2: core.types.IsFloatOrDouble[Loss]) extends Product with Serializable
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- new ModelInstance(model: TrainableModel[In, TrainIn, Out, TrainOut, Loss, EvalIn], configuration: Configuration, trainInputIterator: Option[DatasetIterator[TrainIn]] = None, trainInput: Option[TrainIn] = None, output: Option[Out] = None, trainOutput: Option[TrainOut] = None, loss: Option[ops.Output[Loss]] = None, gradientsAndVariables: Option[Seq[(ops.OutputLike[Loss], ops.variables.Variable[Any])]] = None, trainOp: Option[ops.UntypedOp] = None)(implicit arg0: core.types.TF[Loss], arg1: core.types.IsFloatOrDouble[Loss])
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- val gradientsAndVariables: Option[Seq[(ops.OutputLike[Loss], ops.variables.Variable[Any])]]
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- val loss: Option[ops.Output[Loss]]
- val model: TrainableModel[In, TrainIn, Out, TrainOut, Loss, EvalIn]
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- val trainInput: Option[TrainIn]
- val trainInputIterator: Option[DatasetIterator[TrainIn]]
- val trainOp: Option[ops.UntypedOp]
- val trainOutput: Option[TrainOut]
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