[Docs] Update torch.(squeeze, split, set_printoptions, save) docs. (#39303)

Summary:
I added the following to the docs:
1. `torch.save`.
    1. Added doc for `_use_new_zipfile_serialization` argument.
    2. Added a note telling that extension does not matter while saving.
    3. Added an example showing the use of above argument along with `pickle_protocol=5`.

2. `torch.split`
    1. Added an example showing the use of the function.

3. `torch.squeeze`
   1. Added a warning for batch_size=1 case.

4. `torch.set_printoptions`
    1. Changed the docs of `sci_mode` argument from
        ```
        sci_mode: Enable (True) or disable (False) scientific notation. If
                 None (default) is specified, the value is defined by `_Formatter`
        ```
        to
        ```
        sci_mode: Enable (True) or disable (False) scientific notation. If
                 None (default=False) is specified, the value is defined by
                `torch._tensor_str._Formatter`.
        ```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/39303

Differential Revision: D21904504

Pulled By: zou3519

fbshipit-source-id: 92a324257d09d6bcfa0b410d4578859782b94488

torch/_tensor_str.py

@@ -38,7 +38,9 @@ def set_printoptions(
         profile: Sane defaults for pretty printing. Can override with any of
             the above options. (any one of `default`, `short`, `full`)
         sci_mode: Enable (True) or disable (False) scientific notation. If
-            None (default) is specified, the value is defined by `_Formatter`
+            None (default) is specified, the value is defined by 
+            `torch._tensor_str._Formatter`. This value is automatically chosen
+            by the framework.
     """
     if profile is not None:
         if profile == "default":

torch/_torch_docs.py

@@ -5637,6 +5637,10 @@ will squeeze the tensor to the shape :math:`(A \times B)`.
 .. note:: The returned tensor shares the storage with the input tensor,
           so changing the contents of one will change the contents of the other.
 
+.. warning:: If the tensor has a batch dimension of size 1, then `squeeze(input)` 
+          will also remove the batch dimension, which can lead to unexpected 
+          errors.
+
 Args:
     {input}
     dim (int, optional): if given, the input will be squeezed only in

torch/functional.py

@@ -82,6 +82,27 @@ def split(tensor, split_size_or_sections, dim=0):
         split_size_or_sections (int) or (list(int)): size of a single chunk or
             list of sizes for each chunk
         dim (int): dimension along which to split the tensor.
+
+    Example::
+        >>> a = torch.arange(10).reshape(5,2)
+        >>> a
+        tensor([[0, 1],
+                [2, 3],
+                [4, 5],
+                [6, 7],
+                [8, 9]])
+        >>> torch.split(a, 2)
+        (tensor([[0, 1],
+                 [2, 3]]),
+         tensor([[4, 5],
+                 [6, 7]]),
+         tensor([[8, 9]]))
+        >>> torch.split(a, [1,4])
+        (tensor([[0, 1]]),
+         tensor([[2, 3],
+                 [4, 5],
+                 [6, 7],
+                 [8, 9]]))
     """
     if not torch.jit.is_scripting():
         if type(tensor) is not Tensor and has_torch_function((tensor,)):

torch/serialization.py

@@ -339,6 +339,9 @@ def save(obj, f, pickle_module=pickle, pickle_protocol=DEFAULT_PROTOCOL, _use_ne
         pickle_module: module used for pickling metadata and objects
         pickle_protocol: can be specified to override the default protocol
 
+    .. note::
+        A common PyTorch convention is to save tensors using .pt file extension.
+
     .. warning::
         If you are using Python 2, :func:`torch.save` does NOT support :class:`StringIO.StringIO`
         as a valid file-like object. This is because the write method should return