Added file on movedim

content/pytorch/concepts/tensor-operations/terms/movedim/movedim.md

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+---
+Title: '.movedim()'
+Description: 'Returns a tensor with the dimensions moved from the positions specified in source to the positions specified in destination.'
+Subjects:
+  - 'AI'
+  - 'Data Science'
+Tags:
+  - 'AI'
+  - 'Arrays'
+  - 'Data Structures'
+  - 'Deep Learning'
+CatalogContent:
+  - 'intro-to-py-torch-and-neural-networks'
+  - 'paths/computer-science'
+---
+
+In Pytorch, **`.movedim()`** is used to move specific dimensions of the input tensor to a specified positions, while the other dimensions that are not explicitly mentioned remain in their original order.
+
+## Syntax
+
+```pseudo
+torch.movedim(input, source, destination)
+```
+
+- `input`: The input tensor whose dimensions are to be rearranged.
+- `source`: The dimensions to be moved. Can be a single integer or a tuple of integers.
+- `destination`: The target positions for the dimensions specified in `source`. It should have the same length as `source`.
+
+## Example
+
+The following example demonstrates the use of `.movedim()`:
+
+```py
+import torch
+
+# Define a 1D tensor
+a = torch.tensor([[1, 2, 3, -8]])
+
+# Define a 2D tensor
+b = torch.tensor([[1, 2, 3, -8],
+                    [4, 3, 8, 0],
+                    [-1, 7, 6, 3],
+                    [5, 6, 9, 0]])
+
+# Define a 3D tensor
+c = torch.randn(2, 2, 3)
+
+# Define a 4D tensor
+d = torch.randn(2, 3, 2, 3)
+
+# Move dimension 0 to dimension 1 for 1D tensor
+a1 = torch.movedim(a, 0, 1)
+print("One Dimensional tensor:")
+print(a1)
+print("\n")
+
+# Move dimension 0 to dimension 1 for 2D tensor
+b1 = torch.movedim(b, 0, 1)
+print("Two Dimensional tensor:")
+print(b1)
+print("\n")
+
+# Move dimension 0 to dimension 1 for 3D tensor
+c1 = torch.movedim(c, 0, 1)
+print("Three Dimensional tensor (Dim 1):")
+print(c1)
+print("\n")
+
+# Move dimension 0 to dimension 2 for 3D tensor
+c2 = torch.movedim(c, 0, 2)
+print("Three Dimensional tensor (Dim 2):")
+print(c2)
+print("\n")
+
+# Move dimensions [0, 1] to positions [2, 3] for 4D tensor
+d1 = torch.movedim(d, [0, 1], [2, 3])
+print("Four Dimensional tensor:")
+print(d1)
+```
+This example will generate the following output:
+
+```shell
+One Dimensional tensor:
+tensor([[ 1],
+        [ 2],
+        [ 3],
+        [-8]])
+
+Two Dimensional tensor:
+tensor([[ 1,  4, -1,  5],
+        [ 2,  3,  7,  6],
+        [ 3,  8,  6,  9],
+        [-8,  0,  3,  0]])
+
+Three Dimensional tensor (Dim 1):
+tensor([[[ 1.0064, -1.2284, -1.1452],
+         [-0.9374,  1.2943, -1.7862]],
+
+        [[ 0.4316,  3.1050, -0.4264],
+         [-0.9219,  1.6863, -0.3411]]])
+
+Three Dimensional tensor (Dim 2):
+tensor([[[ 1.0064, -0.9374],
+         [-1.2284,  1.2943],
+         [-1.1452, -1.7862]],
+
+        [[ 0.4316, -0.9219],
+         [ 3.1050,  1.6863],
+         [-0.4264, -0.3411]]])
+
+Four Dimensional tensor:
+tensor([[[[ 0.0753,  1.5373,  0.0765],
+          [-3.1675,  0.2926,  0.5799]],
+
+         [[-0.1520, -0.4855,  1.9026],
+          [-1.6107,  0.5367, -0.3401]],
+
+         [[-0.9148, -0.6213,  0.5939],
+          [-0.6407, -1.0397, -0.7044]]],
+
+
+        [[[ 0.3897,  0.6399,  1.0818],
+          [ 0.7111, -1.3950, -1.3415]],
+
+         [[-0.3749,  2.3008, -0.2464],
+          [ 1.4121, -0.3554, -0.5184]],
+
+         [[-0.3224, -0.9296,  0.1633],
+          [-0.2641,  0.8230,  0.1766]]]])
+```