Adding examples of numpy and tensor usage

examples/npy_serialize.rs

@@ -0,0 +1,19 @@
+use dfdx::numpy as np;
+
+fn main() {
+    np::save("0d-rs.npy", &1.234).expect("Saving failed");
+    np::save("1d-rs.npy", &[1.0, 2.0, 3.0]).expect("Saving failed");
+    np::save("2d-rs.npy", &[[1.0, 2.0, 3.0], [-1.0, -2.0, -3.0]]).expect("Saving failed");
+
+    let mut expected_0d = 0.0;
+    np::load("0d-rs.npy", &mut expected_0d).expect("Loading failed");
+    assert_eq!(expected_0d, 1.234);
+
+    let mut expected_1d = [0.0; 3];
+    np::load("1d-rs.npy", &mut expected_1d).expect("Loading failed");
+    assert_eq!(expected_1d, [1.0, 2.0, 3.0]);
+
+    let mut expected_2d = [[0.0; 3]; 2];
+    np::load("2d-rs.npy", &mut expected_2d).expect("Loading failed");
+    assert_eq!(expected_2d, [[1.0, 2.0, 3.0], [-1.0, -2.0, -3.0]]);
+}

examples/tensors.rs

@@ -0,0 +1,22 @@
+use dfdx::prelude::*;
+
+fn main() {
+    let a: Tensor2D<2, 3> = TensorCreator::zeros();
+
+    // since add() expects tensors with the same size, we dont need a type for this
+    let b = TensorCreator::ones();
+    let c = add(a, &b);
+
+    // tensors just store raw rust arrays, use `.data()` to access this.
+    assert_eq!(c.data(), &[[1.0; 3]; 2]);
+
+    // since we pass in an array, rust will figure out that we mean Tensor1D<5> since its an [f32; 5]
+    let mut d = Tensor1D::new([1.0, 2.0, 3.0, 4.0, 5.0]);
+
+    // use `.mut_data()` to access underlying mutable array. type is provided for readability
+    let raw_data: &mut [f32; 5] = d.mut_data();
+    for i in 0..5 {
+        raw_data[i] *= 2.0;
+    }
+    assert_eq!(d.data(), &[2.0, 4.0, 6.0, 8.0, 10.0]);
+}