implement cumprod

crates/desktop/src-tauri/src/ml/cumprod.rs

@@ -0,0 +1,150 @@
+use candle_core::shape::Dim;
+use candle_core::Tensor;
+
+/// Tensor Cumulative Product
+/// 
+/// Candle doesn't implement cumprod, only cumsum.
+/// This implementation is adapted from cumsum in candle-ext:
+///  https://github.com/mokeyish/candle-ext/blob/main/tests/cumsum.rs
+///
+/// See Also: https://pytorch.org/docs/stable/generated/torch.cumprod.html
+/// See Also: https://numpy.org/doc/stable/reference/generated/numpy.cumprod.html
+/// See Also: https://github.com/huggingface/candle/issues/1646
+///
+pub fn cumprod<D: Dim>(input: &Tensor, dim: D) -> candle_core::Result<Tensor> {
+  let dim = dim.to_index(input.shape(), "cumprod")?;
+  let dim_size = input.dim(dim)?;
+  let rank = input.rank();
+  if rank == 0 {
+    return Ok(input.clone());
+  }
+
+  let mut tensors = Vec::with_capacity(dim_size);
+
+  let mut a = input.clone();
+  for i in 0..dim_size {
+    if i > 0 {
+      a = a.narrow(dim, 1, dim_size - i)?;
+      let b = input.narrow(dim, 0, dim_size - i)?;
+      a = (a * b)?;
+    }
+    tensors.push(a.narrow(dim, 0, 1)?);
+  }
+
+  let cumsum = Tensor::cat(&tensors, dim)?;
+  Ok(cumsum)
+}
+
+#[cfg(test)]
+mod tests {
+  use crate::ml::cumprod::cumprod;
+  use candle_core::{Device, Tensor};
+
+  mod base_cases {
+    use super::*;
+
+    #[test]
+    fn zeroes_vector() -> anyhow::Result<()> {
+      let a = Tensor::new(&[0i64, 0, 0, 0], &Device::Cpu)?;
+      let b = cumprod(&a, 0)?;
+      assert_eq!(b.to_vec1::<i64>()?, &[0, 0, 0, 0]);
+      Ok(())
+    }
+
+    #[test]
+    fn zeroes_tensor() -> anyhow::Result<()> {
+      let a = Tensor::new(&[
+        [0i64, 0, 0],
+        [0i64, 0, 0],
+        [0i64, 0, 0],
+      ], &Device::Cpu)?;
+
+      let b = cumprod(&a, 0)?;
+
+      assert_eq!(b.to_vec2::<i64>()?, &[
+        [0, 0, 0],
+        [0, 0, 0],
+        [0, 0, 0],
+      ]);
+      Ok(())
+    }
+
+    #[test]
+    fn ones_vector() -> anyhow::Result<()> {
+      let a = Tensor::new(&[1i64, 1, 1, 1], &Device::Cpu)?;
+      let b = cumprod(&a, 0)?;
+      assert_eq!(b.to_vec1::<i64>()?, &[1, 1, 1, 1]);
+      Ok(())
+    }
+
+    #[test]
+    fn ones_tensor() -> anyhow::Result<()> {
+      let a = Tensor::new(&[
+        [1i64, 1, 1],
+        [1i64, 1, 1],
+        [1i64, 1, 1],
+      ], &Device::Cpu)?;
+
+      let b = cumprod(&a, 0)?;
+
+      assert_eq!(b.to_vec2::<i64>()?, &[
+        [1, 1, 1],
+        [1, 1, 1],
+        [1, 1, 1],
+      ]);
+      Ok(())
+    }
+  }
+
+  mod test_cases {
+    use super::*;
+
+    #[test]
+    fn vector() -> anyhow::Result<()> {
+      let a = Tensor::new(&[1i64, 2, 3, 4, 5], &Device::Cpu)?;
+      let b = cumprod(&a, 0)?;
+      assert_eq!(b.to_vec1::<i64>()?, &[1, 2, 6, 24, 120]);
+
+      let a = Tensor::new(&[0, 1i64, 2, 3, 4, 5], &Device::Cpu)?;
+      let b = cumprod(&a, 0)?;
+      assert_eq!(b.to_vec1::<i64>()?, &[0, 0, 0, 0, 0, 0]);
+      Ok(())
+    }
+
+    #[test]
+    fn tensor_dim_0() -> anyhow::Result<()> {
+      let a = Tensor::new(&[
+        [1i64, 2, 3],
+        [4i64, 5, 6],
+        [7i64, 8, 9],
+      ], &Device::Cpu)?;
+
+      let b = cumprod(&a, 0)?;
+
+      assert_eq!(b.to_vec2::<i64>()?, &[
+        [1, 2, 3],
+        [4, 10, 18],
+        [28, 80, 162],
+      ]);
+      Ok(())
+    }
+
+    #[test]
+    fn tensor_dim_1() -> anyhow::Result<()> {
+      let a = Tensor::new(&[
+        [1i64, 2, 3],
+        [4i64, 5, 6],
+        [7i64, 8, 9],
+      ], &Device::Cpu)?;
+
+      let b = cumprod(&a, 1)?;
+
+      assert_eq!(b.to_vec2::<i64>()?, &[
+        [1, 2, 6],
+        [4, 20, 120],
+        [7, 56, 504],
+      ]);
+      Ok(())
+    }
+  }
+}

crates/desktop/src-tauri/src/ml/mod.rs

@@ -1,3 +1,4 @@
+pub mod cumprod;
 pub mod image;
 pub mod lcm_scheduler;
 pub mod model_cache;