[GitHub] [tvm] MasterJH5574 commented on pull request #10789: [TVMScript] Parser `int64` support

[GitBox <gi...@apache.org>]

MasterJH5574 commented on pull request #10789:
URL: https://github.com/apache/tvm/pull/10789#issuecomment-1079625981


   Hi @shingjan, I noted that our TVMScript parser fails when `T.int64` appears in the parameter type annotation.
   
   For example, when parsing the following script,
   ```python
   @T.prim_func
   def elementwise_shape_int64(
       A: T.Buffer[(T.int64(128), T.int64(128)), "float32"],
       C: T.Buffer[(T.int64(128), T.int64(128)), "float32"],
   ) -> None:
       B = T.alloc_buffer((T.int64(128), T.int64(128)), dtype="float32")
       for i, j in T.grid(128, 128):
           with T.block("B"):
               vi, vj = T.axis.remap("SS", [i, j])
               B[vi, vj] = A[vi, vj] * 2.0
       for i, j in T.grid(T.int64(128), T.int64(128)):
           with T.block("C"):
               vi, vj = T.axis.remap("SS", [i, j])
               C[vi, vj] = B[vi, vj] + 1.0
   ```
   the parser fails with message
   ```
   Traceback (most recent call last):
     File "tensorir.py", line 32, in Fused
       A: T.Buffer[(T.int64(128), T.int64(128)), "float32"],
   TypeError: __call__() takes 1 positional argument but 2 were given
   ```
   
   Could you help take a look into this case? If the parser cannot support `int64` in type annotation, we shouldn't print the buffer in sugar-style in the printer. Thanks a lot!!


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