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+# Fori_loop
+`fori_loop` is a replacement of pure python for loop, like [`jax.lax.fori_loop`](https://jax.readthedocs.io/en/latest/_autosummary/jax.lax.fori_loop.html):
+- if loop range is dynamic, its deeper implementation would be [`jax.lax.while_loop`](https://jax.readthedocs.io/en/latest/_autosummary/jax.lax.while_loop.html),
+- if loop range is not dynamic, its deeper implementation would be [`jax.lax.scan`](https://jax.readthedocs.io/en/latest/_autosummary/jax.lax.scan.html),
+
+In 2.3, PyTorch/XLA enable `while_loop` with some simple case.
+
+# while_loop
+`while_loop` is a replacement of pure python while loop, PyTorch has supported `while_loop` in
+[code](https://github.com/pytorch/pytorch/blob/ca6a0e1348ba7dcade1833d983b1b4ca12a5c1e1/torch/_higher_order_ops/while_loop.py#L69). 
+PyTorch/XLA want to support `while_loop` with the native PyTorch and the XLA backend: XLA::While.
+
+User could use `while_loop` like this:
+```python
+import torch_xla.experimental.fori_loop
+from torch._higher_order_ops.while_loop import while_loop
+res = while_loop(/*user-defined*/cond_fn, /*user-defined*/body_fn, /*tuple or list*/init)
+```
+current while_loop only support simple test like [link](https://github.com/pytorch/xla/blob/r2.3/test/test_fori_loop_with_while_loop_simple_add_dispatch_in_torch.py), and user could try [simple user guide](https://github.com/pytorch/xla/blob/ManfeiBai-patch-81/docs/fori_loop.md#simple-example-with-while_loop) with `while_loop` on TPU too.
+
+
+# [WIP]scan
+not included in 2.3, please touch more in [nightly version](https://github.com/pytorch/xla/blob/r2.3/torch_xla/experimental/fori_loop.py)
+
+
+# Simple user guide
+User could try these simple test cases to better compare difference between `pure python for loop` and `while_loop`, these three test case have similar logic: cumulative plus 1 for ten times:
+
+### simple example with pure python while loop
+```bash
+# python
+>>> import torch
+>>> 
+>>> def cond_fn(init, limit_value):
+...   return limit_value[0] > init[0]
+... 
+>>> def body_fn(init, limit_value):
+...   one_value = torch.ones(1, dtype=torch.int32)
+...   return (torch.add(init, one_value), limit_value.clone())
+... 
+>>> init = torch.tensor([0], dtype=torch.int32)
+>>> limit_value = torch.tensor([10], dtype=torch.int32)
+>>> 
+>>> while cond_fn(init, limit_value):
+...   init, _ = body_fn(init, limit_value)
+... 
+>>> init
+tensor([10], dtype=torch.int32)
+>>>
+```
+
+### simple example with `while_loop`:
+```bash
+# PJRT_DEVICE=TPU python
+>>> import torch
+>>> import torch_xla
+>>> import torch_xla.experimental.fori_loop
+>>> from torch._higher_order_ops.while_loop import while_loop
+>>> import torch_xla.core.xla_model as xm
+>>> import torch_xla.core.xla_builder as xb
+>>> 
+>>> device = xm.xla_device()
+>>> 
+>>> def cond_fn(init, limit_value):
+...   return limit_value[0] > init[0]
+... 
+>>> def body_fn(init, limit_value):
+...   one_value = torch.ones(1, dtype=torch.int32, device=device)
+...   return (torch.add(init, one_value), limit_value.clone())
+... 
+>>> init = torch.tensor([0], dtype=torch.int32, device=device)
+>>> limit_value = torch.tensor([10], dtype=torch.int32, device=device)
+>>> res_, limit_value_ = while_loop(cond_fn, body_fn, (init, limit_value))
+>>> res_
+FunctionalTensor(lvl=0, value=\
+tensor([10], device='xla:0', dtype=torch.int32))
+>>>
+```
+
+For more example and detailed user guide, please read [this test file](https://github.com/pytorch/xla/blob/r2.3/test/test_fori_loop_with_while_loop_simple_add_dispatch_in_torch.py).