burn-tensor 0.16.1

Tensor library with user-friendly APIs and automatic differentiation support
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
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98

use core::future::Future;

use super::{BasicOps, Tensor, TensorPrimitive};
use crate::{
    backend::Backend,
    ops::{BoolTensor, IntTensor, TransactionPrimitive},
    TensorData,
};
use alloc::vec::Vec;

#[derive(Default)]
/// A transaction can [read](Self::register) multiple tensors at once with a single operation improving
/// compute utilization with optimized laziness.
///
/// # Example
///
/// ```rust,ignore
///  let [output_data, loss_data, targets_data] = Transaction::default()
///    .register(output)
///    .register(loss)
///    .register(targets)
///    .execute()
///    .try_into()
///    .expect("Correct amount of tensor data");
/// ```
pub struct Transaction<B: Backend> {
    op: TransactionPrimitive<B>,
    orders: Vec<Order>,
}

enum Order {
    Float(usize),
    QFloat(usize),
    Int(usize),
    Bool(usize),
}

impl<B: Backend> Transaction<B> {
    /// Add a [tensor](Tensor) to the transaction to be read.
    pub fn register<const D: usize, K: BasicOps<B>>(mut self, tensor: Tensor<B, D, K>) -> Self {
        K::register_transaction(&mut self, tensor.into_primitive());
        self
    }

    /// Executes the transaction synchronously and returns the [data](TensorData) in the same order
    /// in which they were [registered](Self::register).
    pub fn execute(self) -> Vec<TensorData> {
        burn_common::future::block_on(self.execute_async())
    }

    /// Executes the transaction asynchronously and returns the [data](TensorData) in the same order
    /// in which they were [registered](Self::register).
    pub fn execute_async(self) -> impl Future<Output = Vec<TensorData>> {
        let fut = B::tr_execute(self.op);

        async move {
            let result = fut.await;

            let mut floats: Vec<_> = result.read_floats.into_iter().map(Some).collect();
            let mut qfloats: Vec<_> = result.read_qfloats.into_iter().map(Some).collect();
            let mut ints: Vec<_> = result.read_ints.into_iter().map(Some).collect();
            let mut bools: Vec<_> = result.read_bools.into_iter().map(Some).collect();

            self.orders
                .into_iter()
                .map(|order| match order {
                    Order::Float(index) => floats.get_mut(index).unwrap().take().unwrap(),
                    Order::QFloat(index) => qfloats.get_mut(index).unwrap().take().unwrap(),
                    Order::Int(index) => ints.get_mut(index).unwrap().take().unwrap(),
                    Order::Bool(index) => bools.get_mut(index).unwrap().take().unwrap(),
                })
                .collect::<Vec<_>>()
        }
    }

    pub(crate) fn register_float(&mut self, tensor: TensorPrimitive<B>) {
        match tensor {
            TensorPrimitive::Float(tensor) => {
                self.orders.push(Order::Float(self.op.read_floats.len()));
                self.op.read_floats.push(tensor);
            }
            TensorPrimitive::QFloat(tensor) => {
                self.orders.push(Order::QFloat(self.op.read_qfloats.len()));
                self.op.read_qfloats.push(tensor);
            }
        }
    }

    pub(crate) fn register_int(&mut self, tensor: IntTensor<B>) {
        self.orders.push(Order::Int(self.op.read_ints.len()));
        self.op.read_ints.push(tensor);
    }

    pub(crate) fn register_bool(&mut self, tensor: BoolTensor<B>) {
        self.orders.push(Order::Bool(self.op.read_bools.len()));
        self.op.read_bools.push(tensor);
    }
}