Add a simple full method. (#1455)

* Add a simple implementation of the full method.

* Add the docstring.

candle-core/src/tensor.rs

@@ -361,6 +361,16 @@ impl Tensor {
         Self::new_impl(array, shape, device, false)
     }
 
+    /// Returns a new tensor with all the elements having the same specified value. Note that
+    /// the tensor is not contiguous so you would have to call `.contiguous()` on it if needed.
+    pub fn full<D: crate::WithDType, S: Into<Shape>>(
+        value: D,
+        shape: S,
+        device: &Device,
+    ) -> Result<Self> {
+        Self::from_vec_impl(vec![value], (), device, false)?.broadcast_as(shape)
+    }
+
     /// Creates a new 1D tensor from an iterator.
     pub fn from_iter<D: crate::WithDType>(
         iter: impl IntoIterator<Item = D>,

candle-core/tests/tensor_tests.rs

@@ -32,6 +32,14 @@ fn ones(device: &Device) -> Result<()> {
     Ok(())
 }
 
+fn full(device: &Device) -> Result<()> {
+    assert_eq!(
+        Tensor::full(42u32, (2, 3), device)?.to_vec2::<u32>()?,
+        [[42, 42, 42], [42, 42, 42]],
+    );
+    Ok(())
+}
+
 fn arange(device: &Device) -> Result<()> {
     assert_eq!(
         Tensor::arange(0u8, 5u8, device)?.to_vec1::<u8>()?,
@@ -1072,6 +1080,7 @@ fn randn(device: &Device) -> Result<()> {
 
 test_device!(zeros, zeros_cpu, zeros_gpu, zeros_metal);
 test_device!(ones, ones_cpu, ones_gpu, ones_metal);
+test_device!(full, full_cpu, full_gpu, full_metal);
 test_device!(arange, arange_cpu, arange_gpu, arange_metal);
 test_device!(add_mul, add_mul_cpu, add_mul_gpu, add_mul_metal);
 test_device!(tensor_2d, tensor_2d_cpu, tensor_2d_gpu, tensor_2d_metal);