nncombinator::layer

Trait BatchPreTrainBase

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pub trait BatchPreTrainBase<U>: BatchForwardBase + PreTrain<U>
where
    U: UnitValue<U>,
{
    type BatchPreOutput: Debug + 'static;
    type BatchOutStack: Stack<Head = Self::BatchPreOutput> + Sized + Debug;
}
Expand description

Trait that defines the relevant type of implementation that calculates the results of forward propagation prior to processing the error back propagation of the neural network by batch processing.

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type BatchPreOutput: Debug + 'static

The type of output that is piled on the stack during the back-propagation process for errors in a batch run.

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type BatchOutStack: Stack<Head = Self::BatchPreOutput> + Sized + Debug

Type of object to keep the results of forward propagation needed to perform error back propagation for batch execution.

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impl<U, C, BC, P, D, I, PI, OP, const NI: usize, const NO: usize> BatchPreTrainBase<U> for LinearLayer<U, C, BC, P, D, I, PI, OP, NI, NO>
where P: ForwardAll<Input = I, Output = PI> + BackwardAll<U, LossInput = PI> + PreTrain<U, PreOutput = PI> + Loss<U> + BatchForwardBase<BatchInput = <I as BatchDataType>::Type, BatchOutput = <PI as BatchDataType>::Type> + BatchForward + BatchPreTrainBase<U, BatchPreOutput = <PI as BatchDataType>::Type>, U: Default + Clone + Copy + Send + UnitValue<U>, I: Debug + Send + Sync + BatchDataType, OP: Optimizer<U, D>, <PI as BatchDataType>::Type: BatchSize, <I as BatchDataType>::Type: Debug, D: Device<U> + DeviceLinear<U, C, BC, PI, NI, NO>, PI: Debug + BatchDataType + From<<D as DeviceLinear<U, C, BC, PI, NI, NO>>::LossOutput>, <D as DeviceLinear<U, C, BC, PI, NI, NO>>::BatchOutput: Debug, Self: PreTrain<U, PreOutput = <D as DeviceLinear<U, C, BC, PI, NI, NO>>::Output>,

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type BatchPreOutput = <D as DeviceLinear<U, C, BC, PI, NI, NO>>::BatchOutput

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type BatchOutStack = Cons<<P as BatchPreTrainBase<U>>::BatchOutStack, <LinearLayer<U, C, BC, P, D, I, PI, OP, NI, NO> as BatchPreTrainBase<U>>::BatchPreOutput>

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impl<U, C, P, OP, D, I, PI, S, const N: usize> BatchPreTrainBase<U> for BatchNormalizationLayer<U, C, P, OP, D, I, PI, S, N>
where P: ForwardAll<Input = I, Output = PI> + BackwardAll<U, LossInput = PI> + PreTrain<U, PreOutput = PI> + Loss<U> + BatchForwardBase<BatchInput = <I as BatchDataType>::Type, BatchOutput = <PI as BatchDataType>::Type> + BatchForward + BatchPreTrainBase<U, BatchPreOutput = <PI as BatchDataType>::Type>, U: Default + Clone + Copy + Debug + Send + UnitValue<U>, D: Device<U> + DeviceBatchNorm<U, C, PI, N>, I: Debug + Send + Sync + BatchDataType, S: Debug + Sized + 'static, C: Debug, OP: Optimizer<U, D>, PI: BatchDataType + Debug + 'static, <PI as BatchDataType>::Type: Debug + 'static, <I as BatchDataType>::Type: Debug, Self: PreTrain<U, PreOutput = PI>,

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type BatchPreOutput = <PI as BatchDataType>::Type

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type BatchOutStack = Cons<Cons<<P as BatchPreTrainBase<U>>::BatchOutStack, MeanAndVariance<C>>, <BatchNormalizationLayer<U, C, P, OP, D, I, PI, S, N> as BatchPreTrainBase<U>>::BatchPreOutput>

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impl<U, C, P, OP, D, I, PI, const N: usize> BatchPreTrainBase<U> for BiasLayer<U, C, P, OP, D, I, PI, N>
where P: ForwardAll<Input = I, Output = PI> + BackwardAll<U, LossInput = PI> + PreTrain<U, PreOutput = PI> + Loss<U> + BatchForwardBase<BatchInput = <I as BatchDataType>::Type, BatchOutput = <PI as BatchDataType>::Type> + BatchForward + BatchPreTrainBase<U, BatchPreOutput = <PI as BatchDataType>::Type>, U: Default + Clone + Copy + Send + UnitValue<U>, D: Device<U> + DeviceBias<U, C, PI, N>, I: Debug + Send + Sync + BatchDataType, PI: Debug + BatchDataType + 'static, <PI as BatchDataType>::Type: Debug + BatchSize + 'static, <I as BatchDataType>::Type: Debug, OP: Optimizer<U, D>, Self: PreTrain<U, PreOutput = PI>,

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type BatchPreOutput = <PI as BatchDataType>::Type

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type BatchOutStack = Cons<<P as BatchPreTrainBase<U>>::BatchOutStack, <BiasLayer<U, C, P, OP, D, I, PI, N> as BatchPreTrainBase<U>>::BatchPreOutput>

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impl<U, O, LI, D> BatchPreTrainBase<U> for InputLayer<U, O, LI, D>
where U: UnitValue<U>, O: Debug + BatchDataType + Send + Sync + 'static, LI: Debug, D: Device<U> + DeviceInput<U, O>, <O as BatchDataType>::Type: Debug + 'static,

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type BatchPreOutput = <D as DeviceInput<U, O>>::BatchOutput

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type BatchOutStack = Cons<Nil, <InputLayer<U, O, LI, D> as BatchPreTrainBase<U>>::BatchPreOutput>

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impl<U, P, A, I, PI, D, const N: usize> BatchPreTrainBase<U> for ActivationLayer<U, P, A, I, PI, D, N>
where P: PreTrain<U, PreOutput = PI> + ForwardAll<Input = I, Output = PI> + BackwardAll<U, LossInput = PI> + Loss<U> + BatchForwardBase<BatchInput = <I as BatchDataType>::Type, BatchOutput = <PI as BatchDataType>::Type> + BatchPreTrainBase<U, BatchPreOutput = <PI as BatchDataType>::Type> + BatchPreTrain<U> + BatchBackward<U> + BatchLoss<U, BatchLossInput = <PI as BatchDataType>::Type>, U: Default + Clone + Copy + UnitValue<U>, D: Device<U> + DeviceActivation<U, PI, A, N>, PI: Debug + BatchDataType, I: Debug + Send + Sync + BatchDataType, <PI as BatchDataType>::Type: Debug, <I as BatchDataType>::Type: Debug,

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type BatchPreOutput = <PI as BatchDataType>::Type

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type BatchOutStack = Cons<<P as BatchPreTrainBase<U>>::BatchOutStack, <ActivationLayer<U, P, A, I, PI, D, N> as BatchPreTrainBase<U>>::BatchPreOutput>

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impl<U, P, D, I, PI, const N: usize> BatchPreTrainBase<U> for LinearOutputLayer<U, P, D, I, PI, N>
where P: ForwardAll<Input = I, Output = PI> + BackwardAll<U, LossInput = PI> + PreTrain<U, PreOutput = PI> + Loss<U> + BatchForwardBase<BatchInput = <I as BatchDataType>::Type, BatchOutput = <PI as BatchDataType>::Type> + BatchForward + BatchPreTrainBase<U, BatchPreOutput = <PI as BatchDataType>::Type>, U: Default + Clone + Copy + Send + UnitValue<U>, PI: Debug + BatchDataType + ToHost<U, Output = Arr<U, N>> + 'static, I: Debug + Send + Sync + BatchDataType, <PI as BatchDataType>::Type: Debug + ToHost<U, Output = SerializedVec<U, Arr<U, N>>>, <PI as ToHost<U>>::Output: Debug + 'static, <I as BatchDataType>::Type: Debug, <<PI as BatchDataType>::Type as ToHost<U>>::Output: Debug + 'static, for<'a> D: Device<U> + DeviceLinearOutput<'a, U, N, IO = PI>,

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type BatchPreOutput = <PI as BatchDataType>::Type

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type BatchOutStack = <P as BatchPreTrainBase<U>>::BatchOutStack

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impl<U, P, I, PI, CI, D> BatchPreTrainBase<U> for BridgeLayer<U, P, I, PI, CI, D>
where P: PreTrain<U, PreOutput = PI> + ForwardAll<Input = I, Output = PI> + BackwardAll<U, LossInput = PI> + Loss<U> + BatchForwardBase<BatchInput = <I as BatchDataType>::Type, BatchOutput = <PI as BatchDataType>::Type> + BatchPreTrainBase<U> + BatchPreTrain<U, BatchPreOutput = <PI as BatchDataType>::Type> + BatchBackward<U> + BatchLoss<U, BatchLossInput = <PI as BatchDataType>::Type>, U: Default + Clone + Copy + UnitValue<U>, D: Device<U>, PI: Debug + From<CI> + BatchDataType, I: Debug + Send + Sync + BatchDataType, <PI as BatchDataType>::Type: Debug, <I as BatchDataType>::Type: Debug, for<'a> CI: Debug + SliceSize + AsRawSlice<U> + MakeView<'a, U> + MakeViewMut<'a, U> + 'static,

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type BatchPreOutput = <PI as BatchDataType>::Type

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type BatchOutStack = <P as BatchPreTrainBase<U>>::BatchOutStack