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use burn_backend::{Scalar, get_device_settings};
use crate::{
Cast, Float, Int, Shape, Tensor, TensorCreationOptions, TensorData, TensorPrimitive,
backend::Backend, cartesian_grid,
};
use core::ops::Range;
impl<B> Tensor<B, 1, Int>
where
B: Backend,
{
/// Returns a new integer tensor on the specified device.
///
/// # Arguments
///
/// * `range` - The range of values to generate.
/// * `device` - The device to create the tensor on.
pub fn arange(range: Range<i64>, options: impl Into<TensorCreationOptions<B>>) -> Self {
let opt = options.into();
let dtype = opt.resolve_dtype::<Int>();
Tensor::new(B::int_arange(range, &opt.device, dtype.into()))
}
/// Returns a new integer tensor on the specified device.
///
/// # Arguments
///
/// * `range` - The range of values to generate.
/// * `step` - The step between each value.
pub fn arange_step(
range: Range<i64>,
step: usize,
options: impl Into<TensorCreationOptions<B>>,
) -> Self {
let opt = options.into();
let dtype = opt.resolve_dtype::<Int>();
Tensor::new(B::int_arange_step(range, step, &opt.device, dtype.into()))
}
}
impl<const D: usize, B> Tensor<B, D, Int>
where
B: Backend,
{
/// Create a tensor from integers (i32), placing it on a given device.
///
/// # Example
///
/// ```rust
/// use burn_tensor::backend::Backend;
/// use burn_tensor::{Tensor, Int};
///
/// fn example<B: Backend>() {
/// let device = B::Device::default();
/// let _x: Tensor<B, 1, Int> = Tensor::from_ints([1, 2], &device);
/// let _y: Tensor<B, 2, Int> = Tensor::from_ints([[1, 2], [3, 4]], &device);
/// }
/// ```
pub fn from_ints<A: Into<TensorData>>(ints: A, device: &B::Device) -> Self {
Self::from_data(ints.into().convert::<i32>(), device)
}
/// Returns a new tensor with the same shape and device as the current tensor and the data
/// cast to Float.
///
/// # Example
///
/// ```rust
/// use burn_tensor::backend::Backend;
/// use burn_tensor::{Int, Tensor};
///
/// fn example<B: Backend>() {
/// let device = Default::default();
/// let int_tensor = Tensor::<B, 1, Int>::arange(0..5, &device);
/// let float_tensor = int_tensor.float();
/// }
/// ```
pub fn float(self) -> Tensor<B, D, Float> {
let out_dtype = get_device_settings::<B>(&self.device()).float_dtype;
Tensor::new(TensorPrimitive::Float(B::int_into_float(
self.primitive,
out_dtype,
)))
}
/// Generates a cartesian grid for the given tensor shape on the specified device.
/// The generated tensor is of dimension `D2 = D + 1`, where each element at dimension D contains the cartesian grid coordinates for that element.
///
/// # Arguments
///
/// * `shape` - The shape specifying the dimensions of the tensor.
/// * `device` - The device to create the tensor on.
///
/// # Panics
///
/// Panics if `D2` is not equal to `D+1`.
///
/// # Examples
///
/// ```rust
/// use burn_tensor::Int;
/// use burn_tensor::{backend::Backend, Shape, Tensor};
/// fn example<B: Backend>() {
/// let device = Default::default();
/// let result: Tensor<B, 3, _> = Tensor::<B, 2, Int>::cartesian_grid([2, 3], &device);
/// println!("{}", result);
/// }
/// ```
pub fn cartesian_grid<S: Into<Shape>, const D2: usize>(
shape: S,
device: &B::Device,
) -> Tensor<B, D2, Int> {
cartesian_grid::<B, S, D, D2>(shape, device)
}
/// Applies the bitwise logical and operation with each bit representing the integer.
pub fn bitwise_and(self, other: Self) -> Self {
Self::new(B::bitwise_and(self.primitive, other.primitive))
}
/// Applies the bitwise logical or operation with another tensor.
pub fn bitwise_or(self, other: Self) -> Self {
Self::new(B::bitwise_or(self.primitive, other.primitive))
}
/// Applies the bitwise logical xor operation with another tensor.
pub fn bitwise_xor(self, other: Self) -> Self {
Self::new(B::bitwise_xor(self.primitive, other.primitive))
}
/// Applies the bitwise logical not operation.
pub fn bitwise_not(self) -> Self {
Self::new(B::bitwise_not(self.primitive))
}
/// Applies the bitwise logical and operation with each bit in the scalar and the integers in the tensor.
pub fn bitwise_and_scalar(self, other: B::IntElem) -> Self {
let other = Scalar::new(other, &self.dtype());
Self::new(B::bitwise_and_scalar(self.primitive, other))
}
/// Applies the bitwise logical or operation with each bit in the scalar and the integers in the tensor.
pub fn bitwise_or_scalar(self, other: B::IntElem) -> Self {
let other = Scalar::new(other, &self.dtype());
Self::new(B::bitwise_or_scalar(self.primitive, other))
}
/// Applies bitwise logical xor operation with each bit in the scalar and the integers in the tensor.
pub fn bitwise_xor_scalar(self, other: B::IntElem) -> Self {
let other = Scalar::new(other, &self.dtype());
Self::new(B::bitwise_xor_scalar(self.primitive, other))
}
/// Applies the bitwise left shift operation with the integers in the tensor.
pub fn bitwise_left_shift(self, other: Self) -> Self {
Self::new(B::bitwise_left_shift(self.primitive, other.primitive))
}
/// Applies the bitwise right shift operation with the integers in the tensor.
pub fn bitwise_right_shift(self, other: Self) -> Self {
Self::new(B::bitwise_right_shift(self.primitive, other.primitive))
}
/// Applies the bitwise left shift operation with the scalar.
pub fn bitwise_left_shift_scalar(self, other: B::IntElem) -> Self {
let other = Scalar::new(other, &self.dtype());
Self::new(B::bitwise_left_shift_scalar(self.primitive, other))
}
/// Applies the bitwise right shift operation with the scalar.
pub fn bitwise_right_shift_scalar(self, other: B::IntElem) -> Self {
let other = Scalar::new(other, &self.dtype());
Self::new(B::bitwise_right_shift_scalar(self.primitive, other))
}
/// Converts a tensor to the specified data type.
///
/// Supports both within-kind casting (e.g., `IntDType::I64`) and cross-kind casting
/// (e.g., `FloatDType::F32` to produce a float tensor).
///
/// This is a no-op when casting to the current dtype within the same kind.
///
/// # Example
///
/// ```rust
/// use burn_tensor::backend::Backend;
/// use burn_tensor::{Tensor, Int, IntDType, FloatDType};
///
/// fn example<B: Backend>() {
/// let device = Default::default();
/// let int_tensor = Tensor::<B, 1, Int>::arange(0..5, &device);
///
/// // Within-kind cast (int to int)
/// let i64_tensor = int_tensor.clone().cast(IntDType::I64);
///
/// // Cross-kind cast (int to float)
/// let float_tensor = int_tensor.cast(FloatDType::F32);
/// }
/// ```
#[must_use]
pub fn cast<T: Cast<B, Int>>(self, dtype: T) -> Tensor<B, D, T::OutputKind> {
Tensor::new(T::cast(self.primitive, dtype))
}
}