mirror of
https://github.com/huggingface/candle.git
synced 2025-06-16 18:48:51 +00:00
6475bfadfe
* Simplify Tensor::randn. * Also switch Tensor::rand to use a generic dtype. * Support sampling for f16. * Cleanup.
30 lines
839 B
Rust
30 lines
839 B
Rust
#[cfg(feature = "mkl")]
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extern crate intel_mkl_src;
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use anyhow::Result;
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use candle::{Device, Tensor};
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fn main() -> Result<()> {
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let a = Tensor::randn(0f32, 1., (2, 3), &Device::Cpu)?;
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let b = Tensor::randn(0f32, 1., (3, 4), &Device::Cpu)?;
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let c = a.matmul(&b)?;
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println!("{a} {b} {c}");
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let data = &[[3f32, 1., 4., 1., 5.], [2., 7., 1., 8., 2.]];
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let t1 = Tensor::new(data, &Device::Cpu)?;
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let data2 = &[[5f32, 5., 5., 5., 5.], [2., 7., 1., 8., 2.]];
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let t2 = Tensor::new(data2, &Device::Cpu)?;
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assert_eq!(
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Tensor::cat(&[&t1.t()?, &t2.t()?], 1)?
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.t()?
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.to_vec2::<f32>()?,
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[
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[3.0, 1.0, 4.0, 1.0, 5.0],
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[2.0, 7.0, 1.0, 8.0, 2.0],
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[5.0, 5.0, 5.0, 5.0, 5.0],
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[2.0, 7.0, 1.0, 8.0, 2.0]
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]
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);
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Ok(())
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}
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