Enum Op

pub enum Op<B>where
    B: Backend,{
Show 22 variants    None,
    Binary {
        lhs: Tensor<B>,
        rhs: Tensor<B>,
        op: BinaryOp,
    },
    Unary {
        input: Tensor<B>,
        op: UnaryOp,
    },
    Reduce {
        input: Tensor<B>,
        op: ReduceOp,
        dims: Vec<usize>,
        keep_dim: bool,
    },
    Matmul {
        lhs: Tensor<B>,
        rhs: Tensor<B>,
    },
    Reshape {
        input: Tensor<B>,
        src_shape: Shape,
    },
    Transpose {
        input: Tensor<B>,
        dim0: usize,
        dim1: usize,
    },
    Narrow {
        input: Tensor<B>,
        dim: usize,
        start: usize,
        len: usize,
    },
    Affine {
        input: Tensor<B>,
        mul: f64,
        add: f64,
    },
    Contiguous {
        input: Tensor<B>,
    },
    Conv2d {
        input: Tensor<B>,
        weight: Tensor<B>,
        bias: Option<Tensor<B>>,
        stride: [usize; 2],
        padding: [usize; 2],
    },
    MaxPool2d {
        input: Tensor<B>,
        kernel_size: [usize; 2],
        stride: [usize; 2],
        padding: [usize; 2],
        indices: Vec<usize>,
    },
    Cat {
        inputs: Vec<Tensor<B>>,
        dim: usize,
        sizes: Vec<usize>,
    },
    Powf {
        input: Tensor<B>,
        exponent: f64,
    },
    Clamp {
        input: Tensor<B>,
        min: f64,
        max: f64,
    },
    WhereCond {
        mask: Tensor<B>,
        on_true: Tensor<B>,
        on_false: Tensor<B>,
    },
    Gather {
        input: Tensor<B>,
        index: Tensor<B>,
        dim: usize,
    },
    Pad {
        input: Tensor<B>,
        padding: Vec<[usize; 2]>,
    },
    AvgPool2d {
        input: Tensor<B>,
        kernel_size: [usize; 2],
        stride: [usize; 2],
        padding: [usize; 2],
    },
    Conv1d {
        input: Tensor<B>,
        weight: Tensor<B>,
        bias: Option<Tensor<B>>,
        stride: usize,
        padding: usize,
    },
    IndexSelect {
        input: Tensor<B>,
        indices: Tensor<B>,
        dim: usize,
    },
    ToDtype {
        input: Tensor<B>,
        src_dtype: DType,
    },
}

Expand description

Re-export core types. Records the operation that produced a tensor, storing references to inputs.

Each variant holds the actual input Tensor(s) (Arc-wrapped, cheap to clone) plus the operation parameters. backward() uses these to compute gradients via the chain rule.

Op is generic over the Backend because it stores Tensor.

Variants§

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None

No operation — this is a leaf tensor (input data or trainable parameter).

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Binary

Element-wise binary: result = op(lhs, rhs)

Fields

§lhs: Tensor

§rhs: Tensor

§op: BinaryOp

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Unary

Element-wise unary: result = op(input)

Fields

§input: Tensor

§op: UnaryOp

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Reduce

Reduction: result = reduce(input, dims)

Fields

§input: Tensor

§op: ReduceOp

§dims: Vec<usize>

§keep_dim: bool

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Matmul

Matrix multiplication: result = lhs @ rhs

Fields

§lhs: Tensor

§rhs: Tensor

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Reshape

Reshape (includes squeeze/unsqueeze): same data, different shape. src_shape records the original shape so backward can reshape gradients back.

Fields

§input: Tensor

§src_shape: Shape

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Transpose

Transpose: swap two dimensions

Fields

§input: Tensor

§dim0: usize

§dim1: usize

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Narrow

Narrow/slice along a dimension

Fields

§input: Tensor

§dim: usize

§start: usize

§len: usize

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Affine

Affine transform: result = input * mul + add

Fields

§input: Tensor

§mul: f64

§add: f64

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Contiguous

Contiguous copy: same logical values, but data is now contiguous in memory. Gradient passes through unchanged.

Fields

§input: Tensor

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Conv2d

2D convolution: result = conv2d(input, weight) + bias input: [N, C_in, H, W], weight: [C_out, C_in, kH, kW]

Fields

§input: Tensor

§weight: Tensor

§bias: Option<Tensor>

§stride: [usize; 2]

§padding: [usize; 2]

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MaxPool2d

2D max-pooling. input: [N, C, H, W] indices stores the argmax positions for backward.

Fields

§input: Tensor

§kernel_size: [usize; 2]

§stride: [usize; 2]

§padding: [usize; 2]

§indices: Vec<usize>

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Cat

Concatenation along a dimension. inputs are the original tensors that were concatenated. dim is the concatenation dimension. sizes stores the size of each input along dim (needed by backward to slice the gradient back into per-input pieces via narrow).

Fields

§inputs: Vec<Tensor>

§dim: usize

§sizes: Vec<usize>

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Powf

Element-wise power: result = input ^ exponent.

Fields

§input: Tensor

§exponent: f64

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Clamp

Element-wise clamp: result = clamp(input, min, max).

Fields

§input: Tensor

§min: f64

§max: f64

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WhereCond

Conditional select: result[i] = if mask[i] { on_true[i] } else { on_false[i] }.

Fields

§mask: Tensor

§on_true: Tensor

§on_false: Tensor

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Gather

Gather elements along a dimension using index tensor.

Fields

§input: Tensor

§index: Tensor

§dim: usize

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Pad

Constant padding.

Fields

§input: Tensor

§padding: Vec<[usize; 2]>

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AvgPool2d

2D average-pooling. input: [N, C, H, W]

Fields

§input: Tensor

§kernel_size: [usize; 2]

§stride: [usize; 2]

§padding: [usize; 2]

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Conv1d

1D convolution: result = conv1d(input, weight) + bias input: [N, C_in, L], weight: [C_out, C_in, K]

Fields

§input: Tensor

§weight: Tensor

§bias: Option<Tensor>

§stride: usize

§padding: usize

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IndexSelect

Index select along a dimension: result = input.index_select(dim, indices) Backward = scatter-add of grad_output into grad_input at index positions.

Fields

§input: Tensor

§indices: Tensor

§dim: usize

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ToDtype

Dtype conversion: result = input.to_dtype(target_dtype) Backward casts gradient back to the original dtype.

Fields

§input: Tensor

§src_dtype: DType

Implementations§

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impl Op
where B: Backend,

pub fn inputs(&self) -> Vec<&Tensor>

Return references to all input tensors of this operation. Used by topological sort in backward() to traverse the graph.

Trait Implementations§

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impl Clone for Op
where B: Backend,

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fn clone(&self) -> Op

Returns a duplicate of the value. Read more

1.0.0 · Source§
fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more

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impl Debug for Op
where B: Backend,

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fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter. Read more

Auto Trait Implementations§

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impl Freeze for Op

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impl RefUnwindSafe for Op
where ::Device: RefUnwindSafe,

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impl Send for Op

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impl Sync for Op

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impl Unpin for Op

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impl UnwindSafe for Op
where ::Device: RefUnwindSafe,

Blanket Implementations§

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impl<T> Any for T
where T: 'static + ?Sized,

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fn type_id(&self) -> TypeId

Gets the TypeId of self. Read more

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impl<T> Borrow<T> for T
where T: ?Sized,

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fn borrow(&self) -> &T

Immutably borrows from an owned value. Read more

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impl<T> BorrowMut<T> for T
where T: ?Sized,

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fn borrow_mut(&mut self) -> &mut T

Mutably borrows from an owned value. Read more

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impl<T> CloneToUninit for T
where T: Clone,

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unsafe fn clone_to_uninit(&self, dest: *mut u8)

🔬This is a nightly-only experimental API. (clone_to_uninit)
Performs copy-assignment from self to dest. Read more

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impl<T> From<T> for T

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fn from(t: T) -> T

Returns the argument unchanged.

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impl<T, U> Into for T
where U: From<T>,

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fn into(self) -> U

Calls U::from(self).

That is, this conversion is whatever the implementation of From<T> for U chooses to do.

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impl<T> IntoEither for T

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fn into_either(self, into_left: bool) -> Either<Self, Self>

Converts self into a Left variant of Either<Self, Self> if into_left is true. Converts self into a Right variant of Either<Self, Self> otherwise. Read more

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fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
where F: FnOnce(&Self) -> bool,

Converts self into a Left variant of Either<Self, Self> if into_left(&self) returns true. Converts self into a Right variant of Either<Self, Self> otherwise. Read more

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impl<T> Pointable for T

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const ALIGN: usize

The alignment of pointer.

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type Init = T

The type for initializers.

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unsafe fn init(init: <T as Pointable>::Init) -> usize

Initializes a with the given initializer. Read more

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unsafe fn deref<'a>(ptr: usize) -> &'a T

Dereferences the given pointer. Read more

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unsafe fn deref_mut<'a>(ptr: usize) -> &'a mut T

Mutably dereferences the given pointer. Read more

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unsafe fn drop(ptr: usize)

Drops the object pointed to by the given pointer. Read more

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impl<T> ToOwned for T
where T: Clone,

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type Owned = T

The resulting type after obtaining ownership.

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fn to_owned(&self) -> T

Creates owned data from borrowed data, usually by cloning. Read more

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fn clone_into(&self, target: &mut T)

Uses borrowed data to replace owned data, usually by cloning. Read more

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impl<T, U> TryFrom for T
where U: Into<T>,

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type Error = Infallible

The type returned in the event of a conversion error.

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fn try_from(value: U) -> Result<T, <T as TryFrom>::Error>

Performs the conversion.

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impl<T, U> TryInto for T
where U: TryFrom<T>,

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type Error = >::Error

The type returned in the event of a conversion error.

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fn try_into(self) -> Result<U, >::Error>

Performs the conversion.

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impl<V, T> VZip<V> for T
where V: MultiLane<T>,

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fn vzip(self) -> V

Enum Op Copy item path

Variants§

None

Binary

Fields

Unary

Fields

Reduce

Fields

Matmul

Fields

Reshape

Fields

Transpose

Fields

Narrow

Fields

Affine

Fields

Contiguous

Fields

Conv2d

Fields

MaxPool2d

Fields

Cat

Fields

Powf

Fields

Clamp

Fields

WhereCond

Fields

Gather

Fields

Pad

Fields

AvgPool2d

Fields

Conv1d

Fields

IndexSelect

Fields

ToDtype

Fields

Implementations§

impl<B> Op<B>where B: Backend,

pub fn inputs(&self) -> Vec<&Tensor<B>>

Trait Implementations§

impl<B> Clone for Op<B>where B: Backend,

fn clone(&self) -> Op<B>

fn clone_from(&mut self, source: &Self)

impl<B> Debug for Op<B>where B: Backend,

fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Auto Trait Implementations§

impl<B> Freeze for Op<B>

impl<B> RefUnwindSafe for Op<B>where <B as Backend>::Device: RefUnwindSafe,

impl<B> Send for Op<B>

impl<B> Sync for Op<B>

impl<B> Unpin for Op<B>

impl<B> UnwindSafe for Op<B>where <B as Backend>::Device: RefUnwindSafe,

Blanket Implementations§

impl<T> Any for Twhere T: 'static + ?Sized,

fn type_id(&self) -> TypeId

impl<T> Borrow<T> for Twhere T: ?Sized,

fn borrow(&self) -> &T

impl<T> BorrowMut<T> for Twhere T: ?Sized,

fn borrow_mut(&mut self) -> &mut T

impl<T> CloneToUninit for Twhere T: Clone,

unsafe fn clone_to_uninit(&self, dest: *mut u8)

impl<T> From<T> for T

fn from(t: T) -> T

impl<T, U> Into<U> for Twhere U: From<T>,

fn into(self) -> U

impl<T> IntoEither for T

fn into_either(self, into_left: bool) -> Either<Self, Self>

fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>where F: FnOnce(&Self) -> bool,

impl<T> Pointable for T

const ALIGN: usize

type Init = T

Enum Op

impl<B> Op<B>
where B: Backend,

impl<B> Clone for Op<B>
where B: Backend,

impl<B> Debug for Op<B>
where B: Backend,

impl<B> RefUnwindSafe for Op<B>
where <B as Backend>::Device: RefUnwindSafe,

impl<B> UnwindSafe for Op<B>
where <B as Backend>::Device: RefUnwindSafe,

impl<T> Any for T
where T: 'static + ?Sized,

impl<T> Borrow<T> for T
where T: ?Sized,

impl<T> BorrowMut<T> for T
where T: ?Sized,

impl<T> CloneToUninit for T
where T: Clone,

impl<T, U> Into<U> for T
where U: From<T>,

fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
where F: FnOnce(&Self) -> bool,

impl<T> ToOwned for T
where T: Clone,

impl<T, U> TryFrom<U> for T
where U: Into<T>,

impl<T, U> TryInto<U> for T
where U: TryFrom<T>,

impl<V, T> VZip<V> for T
where V: MultiLane<T>,