[GitHub] [incubator-tvm] masahi edited a comment on issue #4964: [Torch] Add initial control flow support

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masahi edited a comment on issue #4964: [Torch] Add initial control flow 
support 
URL: https://github.com/apache/incubator-tvm/pull/4964#issuecomment-592798088
 
 
   Tests passed!!
   
   > can you dont call it parse? parse is for converting strings to an ast. 
converting ast to ast is a converter.
   
   no probelm, will do.
   
   @alexwong @zhiics a good way to get familiar with torch script is to try and 
tweak simple examples. For example, 
   
   ```Python
   import torch
   
   
   class SimpleLoop(torch.nn.Module):
       def forward(self, inp):
           a = inp
           for i in range(10):
               a += i
           return a
   
   
   class SimpleWhileLoop(torch.nn.Module):
       def forward(self, inp):
           a = inp
           i = 0
           while i < 10:
               a += i
               i += 1
           return a
   
   
   print(torch.jit.script(SimpleLoop()).graph)
   print(torch.jit.script(SimpleWhileLoop()).graph)
   ```
   
   would print
   ```
   graph(%self : __torch__.SimpleLoop,
         %inp.1 : Tensor):
     %10 : int = prim::Constant[value=1]()
     %6 : bool = prim::Constant[value=1]() # test.py:7:8
     %3 : int = prim::Constant[value=10]() # test.py:7:23
     %a : Tensor = prim::Loop(%3, %6, %inp.1) # test.py:7:8
       block0(%i.1 : int, %a.5 : Tensor):
         %a.2 : Tensor = aten::add_(%a.5, %i.1, %10) # test.py:8:12
         -> (%6, %a.2)
     return (%a)
   
   graph(%self : __torch__.SimpleWhileLoop,
         %inp.1 : Tensor):
     %i.1 : int = prim::Constant[value=0]() # test.py:15:12
     %4 : int = prim::Constant[value=9223372036854775807]() # test.py:16:8
     %6 : int = prim::Constant[value=10]() # test.py:16:18
     %16 : int = prim::Constant[value=1]() # test.py:18:17
     %39 : bool = prim::Constant[value=1]()
     %a : Tensor, %i : int = prim::Loop(%4, %39, %inp.1, %i.1) # test.py:16:8
       block0(%8 : int, %a.5 : Tensor, %i.8 : int):
         %a.2 : Tensor = aten::add_(%a.5, %i.8, %16) # test.py:17:12
         %i.6 : int = aten::add(%i.8, %16) # test.py:18:12
         %7 : bool = aten::lt(%i.6, %6) # test.py:16:14
         -> (%7, %a.2, %i.6)
     return (%a)
   ```
   
   hopefully it is much simpler than tensorflow control flow.

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