neuronika 0.2.0

Tensors and dynamic neural networks.
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mod addition;
mod division;
mod multiplication;
mod subtraction;

use super::{
    broadcasted_zeros, expect_tensor, expect_tensor_mut, push_gradient, reduce, Backward,
    BroadTensor, Broadcasted, Data, Forward, Gradient, Overwrite, Tensor,
};

#[cfg(test)]
use super::{assert_almost_equals, new_backward_input, new_input, new_tensor};

pub(crate) use addition::{Addition, AdditionBackward, AdditionBackwardUnary};
pub(crate) use division::{
    Division, DivisionBackward, DivisionBackwardLeft, DivisionBackwardRight,
};
pub(crate) use multiplication::{
    Multiplication, MultiplicationBackward, MultiplicationBackwardUnary,
};
pub(crate) use subtraction::{
    Subtraction, SubtractionBackward, SubtractionBackwardLeft, SubtractionBackwardRight,
};