mirror of
https://github.com/huggingface/candle.git
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123 lines
3.6 KiB
Rust
123 lines
3.6 KiB
Rust
use anyhow::Result;
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use candle_core::{Device, IndexOp, Tensor};
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#[test]
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fn integer_index() -> Result<()> {
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let dev = Device::Cpu;
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let tensor = Tensor::arange(0u32, 2 * 3, &dev)?.reshape((2, 3))?;
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let result = tensor.i(1)?;
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assert_eq!(result.dims(), &[3]);
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assert_eq!(result.to_vec1::<u32>()?, &[3, 4, 5]);
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let result = tensor.i((.., 2))?;
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assert_eq!(result.dims(), &[2]);
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assert_eq!(result.to_vec1::<u32>()?, &[2, 5]);
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Ok(())
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}
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#[test]
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fn range_index() -> Result<()> {
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let dev = Device::Cpu;
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// RangeFull
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let tensor = Tensor::arange(0u32, 2 * 3, &dev)?.reshape((2, 3))?;
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let result = tensor.i(..)?;
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assert_eq!(result.dims(), &[2, 3]);
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assert_eq!(result.to_vec2::<u32>()?, &[[0, 1, 2], [3, 4, 5]]);
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// Range
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let tensor = Tensor::arange(0u32, 4 * 3, &dev)?.reshape((4, 3))?;
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let result = tensor.i(1..3)?;
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assert_eq!(result.dims(), &[2, 3]);
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assert_eq!(result.to_vec2::<u32>()?, &[[3, 4, 5], [6, 7, 8]]);
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// RangeFrom
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let result = tensor.i(2..)?;
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assert_eq!(result.dims(), &[2, 3]);
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assert_eq!(result.to_vec2::<u32>()?, &[[6, 7, 8], [9, 10, 11]]);
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// RangeTo
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let result = tensor.i(..2)?;
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assert_eq!(result.dims(), &[2, 3]);
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assert_eq!(result.to_vec2::<u32>()?, &[[0, 1, 2], [3, 4, 5]]);
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// RangeInclusive
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let result = tensor.i(1..=2)?;
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assert_eq!(result.dims(), &[2, 3]);
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assert_eq!(result.to_vec2::<u32>()?, &[[3, 4, 5], [6, 7, 8]]);
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// RangeTo
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let result = tensor.i(..1)?;
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assert_eq!(result.dims(), &[1, 3]);
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assert_eq!(result.to_vec2::<u32>()?, &[[0, 1, 2]]);
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// RangeToInclusive
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let result = tensor.i(..=1)?;
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assert_eq!(result.dims(), &[2, 3]);
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assert_eq!(result.to_vec2::<u32>()?, &[[0, 1, 2], [3, 4, 5]]);
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// Empty range
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let result = tensor.i(1..1)?;
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assert_eq!(result.dims(), &[0, 3]);
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let empty: [[u32; 3]; 0] = [];
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assert_eq!(result.to_vec2::<u32>()?, &empty);
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// Similar to PyTorch, allow empty ranges when the computed length is negative.
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#[allow(clippy::reversed_empty_ranges)]
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let result = tensor.i(1..0)?;
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assert_eq!(result.dims(), &[0, 3]);
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let empty: [[u32; 3]; 0] = [];
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assert_eq!(result.to_vec2::<u32>()?, &empty);
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Ok(())
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}
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#[test]
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fn index_3d() -> Result<()> {
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let tensor = Tensor::from_iter(0..24u32, &Device::Cpu)?.reshape((2, 3, 4))?;
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assert_eq!(tensor.i((0, 0, 0))?.to_scalar::<u32>()?, 0);
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assert_eq!(tensor.i((1, 0, 0))?.to_scalar::<u32>()?, 12);
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assert_eq!(tensor.i((0, 1, 0))?.to_scalar::<u32>()?, 4);
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assert_eq!(tensor.i((0, 1, 3))?.to_scalar::<u32>()?, 7);
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assert_eq!(tensor.i((0..2, 0, 0))?.to_vec1::<u32>()?, &[0, 12]);
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assert_eq!(
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tensor.i((0..2, .., 0))?.to_vec2::<u32>()?,
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&[[0, 4, 8], [12, 16, 20]]
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);
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assert_eq!(
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tensor.i((..2, .., 3))?.to_vec2::<u32>()?,
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&[[3, 7, 11], [15, 19, 23]]
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);
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assert_eq!(tensor.i((1, .., 3))?.to_vec1::<u32>()?, &[15, 19, 23]);
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Ok(())
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}
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#[test]
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fn slice_assign() -> Result<()> {
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let dev = Device::Cpu;
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let tensor = Tensor::arange(0u32, 4 * 5, &dev)?.reshape((4, 5))?;
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let src = Tensor::arange(0u32, 2 * 3, &dev)?.reshape((3, 2))?;
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let out = tensor.slice_assign(&[1..4, 3..5], &src)?;
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assert_eq!(
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out.to_vec2::<u32>()?,
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&[
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[0, 1, 2, 3, 4],
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[5, 6, 7, 0, 1],
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[10, 11, 12, 2, 3],
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[15, 16, 17, 4, 5]
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]
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);
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let out = tensor.slice_assign(&[0..3, 0..2], &src)?;
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assert_eq!(
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out.to_vec2::<u32>()?,
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&[
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[0, 1, 2, 3, 4],
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[2, 3, 7, 8, 9],
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[4, 5, 12, 13, 14],
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[15, 16, 17, 18, 19]
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]
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);
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Ok(())
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}
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