ONNX: GatherElements, Xor

candle-onnx/src/eval.rs

@@ -670,6 +670,49 @@ fn simple_eval_(
  };
  values.insert(node.output[0].clone(), xs);
  }
+ // https://onnx.ai/onnx/operators/onnx__GatherElements.html#gatherelements
+ // A Note to fellow lurkers:
+ // The numpy based `gather_elements` implementation in `onnx` tests [here](https://github.com/onnx/onnx/blob/main/onnx/backend/test/case/node/gatherelements.py)
+ // and examples is incorrect.
+ // Use `torch.gather` for the validating/ verifying against the proper behaviour
+ "GatherElements" => {
+ let data = get(&node.input[0])?;
+ let indices = get(&node.input[1])?;
+
+ let rank = data.rank();
+ if rank != indices.rank() {
+ bail!("indices must have same rank as input data. Data rank [{}] != indices rank [{}]", data.rank(), indices.rank());
+ }
+
+ let axis = {
+ let axis_i64 = get_attr_opt::<i64>(node, "axis")?.copied().unwrap_or(0);
+ let axis = data.normalize_axis(axis_i64)?;
+
+ if axis >= rank {
+ bail!(
+ "axis ({}) out of accepted range [-rank, rank-1] which was [-{rank}, {}]",
+ axis_i64,
+ rank - 1
+ )
+ }
+
+ axis
+ };
+
+ // index_select does not support negative indices, so normalize them
+ // to positive indices.
+ let indices = &{
+ let zeros = Tensor::zeros(indices.shape(), indices.dtype(), indices.device())?;
+ let max = Tensor::new(data.dims()[axis] as i64, indices.device())?
+ .to_dtype(indices.dtype())?;
+ let mask = indices.lt(&zeros)?;
+ mask.to_dtype(indices.dtype())?
+ .broadcast_mul(&max)?
+ .add(indices)?
+ };
+
+ values.insert(node.output[0].clone(), data.gather(indices, axis)?);
+ }
  "Shape" => {
  // https://github.com/onnx/onnx/blob/main/docs/Operators.md#Shape
  let xs = get(&node.input[0])?;
@@ -1891,6 +1934,16 @@ fn simple_eval_(
  );
  }
  }
+ // https://onnx.ai/onnx/operators/onnx__Xor.html
+ "Xor" => {
+ // Since we don't have a `DType::Bool` yet, this ensures that we are working with `0`(False) & `1`(True)
+ let a = get(&node.input[0])?.gt(0_u8)?;
+ let b = get(&node.input[1])?.gt(0_u8)?;
+
+ let out = a.broadcast_add(&b)?.eq(1_u8)?;
+
+ values.insert(node.output[0].clone(), out);
+ }
  op_type => bail!("unsupported op_type {op_type} for op {node:?}"),
  }
  }