Add Initialize A PyTorch Tensor as a Python TIL

python/initialize-a-pytorch-tensor.md

@@ -0,0 +1,81 @@
+# Initialize A PyTorch Tensor
+
+A _tensor_ is an n-dimensional array that takes on a specified shape and holds
+scalars, typically floats, in each of its positions.
+[PyTorch](https://pytorch.org/) has a comprehensive suite of tools for working
+with tensors. To work with tenors, the first thing I need to do is initialize
+one. Here are a handful of ways to create a 2-dimensional tensor (a matrix)
+depending on various needs.
+
+Here is a 3x4 matrix full of zeros:
+
+```python
+>>> torch.zeros(torch.Size((3, 4)))
+tensor([[0., 0., 0., 0.],
+        [0., 0., 0., 0.],
+        [0., 0., 0., 0.]])
+```
+
+Here is a 3x4 matrix full of ones:
+
+```python
+>>> torch.ones(3,4)
+tensor([[1., 1., 1., 1.],
+        [1., 1., 1., 1.],
+        [1., 1., 1., 1.]])
+```
+
+And here is a 3x4 matrix full of a specific other value:
+
+```python
+>>> torch.full((3,4), 13.0)
+tensor([[13., 13., 13., 13.],
+        [13., 13., 13., 13.],
+        [13., 13., 13., 13.]])
+```
+
+PyTorch is very flexible. I can specify the shape of the `tensor` with
+positional arguments or a tuple for the dimensions. I can even construct a
+`torch.Size` object.
+
+Here is an arguably more useful example where the matrix is seeded with random
+values in the range `[0,1)` using
+[`torch.rand`](https://docs.pytorch.org/docs/2.13/generated/torch.rand.html):
+
+```python
+>>> torch.rand(torch.Size((3,4)))
+tensor([[0.4148, 0.8045, 0.3093, 0.3363],
+        [0.0120, 0.7161, 0.1108, 0.5510],
+        [0.4805, 0.9430, 0.2852, 0.0966]])
+```
+
+These could be used as starting weights in a training process that then get
+tweaked over time.
+
+There are other random tensor functions like
+[`torch.randint`](https://docs.pytorch.org/docs/2.13/generated/torch.randint.html)
+and
+[`torch.randn`](https://docs.pytorch.org/docs/2.13/generated/torch.randn.html).
+
+How about a [random permutation](https://docs.pytorch.org/docs/2.13/generated/torch.randperm.html)
+of integers `[0,12)` reshaped into a 3x4 matrix:
+
+```python
+>>> torch.randperm(12).reshape(3,4)
+tensor([[ 0,  3,  1, 11],
+        [ 7,  8,  9,  4],
+        [10,  5,  6,  2]])
+```
+
+And though there are many other ways to initialize a tensor, the last one I will
+show is
+[`torch.eye`](https://docs.pytorch.org/docs/2.13/generated/torch.eye.html) which
+creates a matrix with ones down the diagonal.
+
+```python
+>>> torch.eye(4)
+tensor([[1., 0., 0., 0.],
+        [0., 1., 0., 0.],
+        [0., 0., 1., 0.],
+        [0., 0., 0., 1.]])
+```