Add bool() op for numerical tensor (#1402)

Fixes #1395

burn-book/src/building-blocks/tensor.md

@@ -181,6 +181,7 @@ Those operations are available for numeric tensor kinds: `Float` and `Int`.
 | `tensor.all_close(other, atol, rtol)`                           | `torch.allclose(tensor, other, atol, rtol)`    |
 | `tensor.argmax(dim)`                                            | `tensor.argmax(dim)`                           |
 | `tensor.argmin(dim)`                                            | `tensor.argmin(dim)`                           |
+| `tensor.bool()`                                                 | `tensor.bool()`                                |
 | `tensor.clamp(min, max)`                                        | `torch.clamp(tensor, min=min, max=max)`        |
 | `tensor.clamp_max(max)`                                         | `torch.clamp(tensor, max=max)`                 |
 | `tensor.clamp_min(min)`                                         | `torch.clamp(tensor, min=min)`                 |

crates/burn-candle/src/lib.rs

@@ -58,6 +58,7 @@ mod tests {
     burn_tensor::testgen_arange!();
     burn_tensor::testgen_arange_step!();
     burn_tensor::testgen_arg!();
+    burn_tensor::testgen_bool!();
     burn_tensor::testgen_cast!();
     burn_tensor::testgen_cat!();
     burn_tensor::testgen_recip!();

crates/burn-tensor/src/tensor/api/numeric.rs

@@ -2,6 +2,7 @@ use crate::{
     backend::Backend, check, check::TensorCheck, BasicOps, Bool, Element, ElementConversion, Float,
     Int, Shape, Tensor, TensorKind,
 };
+use num_traits::Zero;
 
 impl<B, const D: usize, K> Tensor<B, D, K>
 where
@@ -640,6 +641,15 @@ where
     pub fn all_close(self, other: Self, rtol: Option<f64>, atol: Option<f64>) -> bool {
         self.is_close(other, rtol, atol).all().into_scalar()
     }
+
+    /// Converts the tensor to a boolean tensor by checking if the elements are non-zero.
+    ///
+    /// # Returns
+    ///
+    /// A boolean tensor with the same shape as the input tensor.
+    pub fn bool(self) -> Tensor<B, D, Bool> {
+        K::not_equal_elem::<D>(self.primitive, K::Elem::zero())
+    }
 }
 
 impl<B, K> Tensor<B, 2, K>

crates/burn-tensor/src/tensor/element.rs

@@ -1,11 +1,12 @@
 use crate::Distribution;
 use half::{bf16, f16};
-use num_traits::ToPrimitive;
+use num_traits::{identities::Zero, ToPrimitive};
 use rand::RngCore;
 
 /// Element trait for tensor.
 pub trait Element:
     ToPrimitive
+    + Zero
     + ElementRandom
     + ElementConversion
     + ElementPrecision

crates/burn-tensor/src/tests/mod.rs

@@ -85,6 +85,7 @@ macro_rules! testgen_all {
         burn_tensor::testgen_powf!();
         burn_tensor::testgen_any!();
         burn_tensor::testgen_all_op!();
+        burn_tensor::testgen_bool!();
         burn_tensor::testgen_argwhere_nonzero!();
 
         // test stats

crates/burn-tensor/src/tests/ops/bool.rs

@@ -0,0 +1,21 @@
+#[burn_tensor_testgen::testgen(bool)]
+mod tests {
+    use super::*;
+    use burn_tensor::{Data, Tensor};
+
+    #[test]
+    fn test_from_float() {
+        let tensor1 = TestTensor::from([[0.0, 43.0, 0.0], [2.0, -4.2, 31.33]]);
+        let data_actual = tensor1.bool().into_data();
+        let data_expected = Data::from([[false, true, false], [true, true, true]]);
+        assert_eq!(data_expected, data_actual);
+    }
+
+    #[test]
+    fn test_from_int() {
+        let tensor1 = TestTensorInt::from([[0, 43, 0], [2, -4, 31]]);
+        let data_actual = tensor1.bool().into_data();
+        let data_expected = Data::from([[false, true, false], [true, true, true]]);
+        assert_eq!(data_expected, data_actual);
+    }
+}

crates/burn-tensor/src/tests/ops/mod.rs

@@ -7,6 +7,7 @@ mod arange;
 mod arange_step;
 mod arg;
 mod argwhere_nonzero;
+mod bool;
 mod cast;
 mod cat;
 mod chunk;