feat: add tensors

01-tensors.py

@@ -0,0 +1,44 @@
+import torch
+import numpy as np
+
+# initialize a tensor directly as data
+data = [[1,2],[3,4]]
+x_data = torch.tensor(data).to('xpu')
+
+print(x_data)
+
+# from a numpy array
+arr = np.array(data)
+x_np = torch.from_numpy(arr).to('xpu')
+
+print(x_np)
+
+# from another tensor (could override the shape, datatype)
+x_ones = torch.ones_like(x_data) # retains properties of x_data
+print(f"Ones Tensor: \n {x_ones} \n")
+
+x_rand = torch.rand_like(x_data, dtype=torch.float) # overrides datatype
+print(f"Random Tensor: \n {x_rand} \n")
+
+# use `shape` to define dimentions
+shape = (3,5)
+rand_tensor = torch.rand(shape)
+ones_tensor = torch.ones(shape)
+zeros_tensor = torch.zeros(shape)
+
+print(f"Random: \n {rand_tensor} \n")
+print(f"Ones: \n {ones_tensor} \n")
+print(f"Zeros: \n {zeros_tensor} \n")
+
+# tensors have attributes
+
+tensor_attr = torch.rand(3,4).to('xpu')
+
+# print(f"Shape: {tensor_attr.shape}")
+# print(f"Datatype: {tensor_attr.dtype}")
+# print(f"Device: {tensor_attr.device}")
+
+# indexing & slicing
+
+tensor = torch.ones(4,4).to('xpu')
+print(f"First row: {tensor[0]}")

README.md

@@ -38,3 +38,5 @@ $ torch.xpu.get_device_name()
 ## Links
 
 - [Get started with PyTorch locally](https://pytorch.org/get-started/locally/)
+- [Getting started with Tensors](https://docs.pytorch.org/tutorials/beginner/basics/tensorqs_tutorial.html)
+- [torch operations](https://docs.pytorch.org/docs/stable/torch.html)