feat: update tensors.py

01-tensors.py

@@ -42,3 +42,36 @@ tensor_attr = torch.rand(3,4).to('xpu')
 
 tensor = torch.ones(4,4).to('xpu')
 print(f"First row: {tensor[0]}")
+print(f"First column: {tensor[:,0]}")
+print(f"Last column: {tensor[...,-1]}")
+print(tensor)
+
+# joining tensors using torch.cat
+t1 = torch.cat([tensor, tensor, tensor], dim=1).to('xpu')
+print(t1)
+
+
+
+# different ways to do matrix multiplication (y1, y2, y3 will have same values)
+y1 = tensor @ tensor.T
+y2 = tensor.matmul(tensor.T)
+
+y3 = torch.rand_like(y1) # create a new tensor with same shape as y1
+torch.matmul(tensor, tensor.T, out=y3)
+
+
+# comput the element-wise product (z1, z2, z3 will have same values)
+z1 = tensor * tensor
+z2 = tensor.mul(tensor)
+
+z3 = torch.rand_like(z1)
+torch.mul(tensor, tensor, out=z3)
+
+# convert a one-item tensor into a number with `item()`
+agg = tensor.sum()
+agg_item = agg.item()
+print(agg, type(agg))
+print(agg_item, type(agg_item))
+
+# in-place operations, will assign the result into the operand
+tensor.add_(5) # will assign the result to tensor (ie. override the original tensor)