nncombinator 0.9.8

A library of neural networks that can be written type-safely
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82

//! Implementation of the calculation process for input layers

use std::fmt::Debug;
use crate::device::{Device, DeviceCpu};
use crate::error::{TypeConvertError};
use crate::layer::BatchDataType;
use crate::ope::UnitValue;
#[cfg(feature = "cuda")]
use crate::cuda::allocator::CudaAllocator;
#[cfg(feature = "cuda")]
use crate::cuda::{ToCuda};
#[cfg(feature = "cuda")]
use crate::device::{DeviceGpu};

/// Trait that defines the function of processing data input in the input layer
/// into a form that can be passed to subsequent intermediate layers.
pub trait DeviceInput<U,I>: Device<U>
    where U: UnitValue<U>,
          I: BatchDataType + Debug + 'static,
          <I as BatchDataType>::Type: Debug + 'static {
    type Output: Debug + 'static;
    type BatchOutput: Debug + 'static;

    /// Type conversion during forward propagation
    /// # Arguments
    /// * `input` - input
    ///
    /// # Errors
    ///
    /// This function may return the following errors
    /// * [`TypeConvertError`]
    ///
    fn forward_input(&self,input: I) -> Result<Self::Output,TypeConvertError>;

    /// Type conversion during forward propagation in batch
    /// # Arguments
    /// * `input` - input
    ///
    /// # Errors
    ///
    /// This function may return the following errors
    /// * [`TypeConvertError`]
    ///
    fn batch_forward_input(&self,input: <I as BatchDataType>::Type) -> Result<Self::BatchOutput,TypeConvertError>;
}

impl<U,I> DeviceInput<U,I> for DeviceCpu<U>
    where U: UnitValue<U>,
          I: BatchDataType + Debug + 'static,
          <I as BatchDataType>::Type: Debug + 'static {
    type Output = I;
    type BatchOutput = <I as BatchDataType>::Type;

    fn forward_input(&self,input: I) -> Result<Self::Output,TypeConvertError> {
        Ok(input)
    }

    fn batch_forward_input(&self,input: <I as BatchDataType>::Type) -> Result<Self::BatchOutput,TypeConvertError> {
        Ok(input)
    }
}
#[cfg(feature = "cuda")]

impl<U,I,A> DeviceInput<U,I> for DeviceGpu<U,A>
    where U: UnitValue<U>,
          I: BatchDataType + ToCuda<U,A> + Debug + 'static,
          <I as BatchDataType>::Type: ToCuda<U,A> + Debug + 'static,
          <I as ToCuda<U,A>>::Output: Debug + 'static,
          <<I as BatchDataType>::Type as ToCuda<U,A>>::Output: Debug + 'static,
          A: CudaAllocator,
          DeviceGpu<U,A>: Device<U> {
    type Output = <I as ToCuda<U,A>>::Output;
    type BatchOutput = <<I as BatchDataType>::Type as ToCuda<U,A>>::Output;

    fn forward_input(&self,input: I) -> Result<Self::Output,TypeConvertError> {
        input.to_cuda(self)
    }

    fn batch_forward_input(&self, input: <I as BatchDataType>::Type) -> Result<Self::BatchOutput, TypeConvertError> {
        input.to_cuda(self)
    }
}