[GitHub] [tvm] lazycal opened a new pull request #10106: [onnx] fix onnx where broadcast

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

lazycal opened a new pull request #10106:
URL: https://github.com/apache/tvm/pull/10106


   Thanks for contributing to TVM!   Please refer to guideline https://tvm.apache.org/docs/contribute/ for useful information and tips. After the pull request is submitted, please request code reviews from [Reviewers](https://github.com/apache/incubator-tvm/blob/master/CONTRIBUTORS.md#reviewers) by @ them in the pull request thread.
   
   
   Previous logic for importing `where` only considers the shape of the tensors with the largest rank. This is incorrect, for instance when cond, x, and y are of the following shapes: [3,1], [2], [2]. The resulting shape should be [3,2], but original logic gives [3,1]. Below is the code snippet to reproduce.
   
   ```python
   from tvm import relay
   import numpy as np
   import onnx
   from onnx import TensorProto, helper, mapping, numpy_helper
   
   
   def get_onnx_model(condition, x, y):
       outdata = np.where(condition, x, y)
       dtype = TensorProto.FLOAT
       where_inputs = ["cond", "x", "y"]
       node = helper.make_node("Where", inputs=where_inputs, outputs=["out"])
       node_list = [node]
       graph = helper.make_graph(
           node_list,
           "where_test",
           inputs=[
               helper.make_tensor_value_info(
                   "cond", TensorProto.BOOL, list(condition.shape)),
               helper.make_tensor_value_info("x", dtype, list(x.shape)),
               helper.make_tensor_value_info("y", dtype, list(y.shape)),
           ],
           outputs=[helper.make_tensor_value_info(
               "out", dtype, list(outdata.shape))],
       )
       model = helper.make_model(graph, producer_name="where_test")
       return model
   
   
   def main():
       condition = np.random.uniform(size=(3, 1)) < 0.5
       x = np.random.uniform(size=(2,)).astype(np.float32)
       y = np.random.uniform(size=(2,)).astype(np.float32)
       model = get_onnx_model(condition, x, y)
       mod, params = relay.frontend.from_onnx(model, freeze_params=True)
   
       res = relay.build_module.create_executor('graph', mod).evaluate()(
           **{'cond': condition, 'x': x, 'y': y})
       assert np.allclose(res.asnumpy(), np.where(
           condition, x, y), rtol=0, atol=0)
   
   
   main()
   ```
   
   This PR simply delegates the broadcast logic to `relay.where`, instead of handling during import.


-- 
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

To unsubscribe, e-mail: commits-unsubscribe@tvm.apache.org

For queries about this service, please contact Infrastructure at:
users@infra.apache.org

[GitHub] [tvm] AndrewZhaoLuo merged pull request #10106: [onnx] fix onnx where broadcast

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

AndrewZhaoLuo merged pull request #10106:
URL: https://github.com/apache/tvm/pull/10106


   


-- 
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

To unsubscribe, e-mail: commits-unsubscribe@tvm.apache.org

For queries about this service, please contact Infrastructure at:
users@infra.apache.org

[GitHub] [tvm] AndrewZhaoLuo commented on pull request #10106: [onnx] fix onnx where broadcast

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

AndrewZhaoLuo commented on pull request #10106:
URL: https://github.com/apache/tvm/pull/10106#issuecomment-1026296351


   @lazycal yeah looks like a spurious error. You need to jostle ci by pushing an empty commit. E.g. `git commit -m 'jostle ci' --allow-empty` and `git push`


-- 
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

To unsubscribe, e-mail: commits-unsubscribe@tvm.apache.org

For queries about this service, please contact Infrastructure at:
users@infra.apache.org

[GitHub] [tvm] lazycal commented on pull request #10106: [onnx] fix onnx where broadcast

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

lazycal commented on pull request #10106:
URL: https://github.com/apache/tvm/pull/10106#issuecomment-1025994297


   Not sure why but the test succeeded in my local computer, and the failed test is autotvm which does not seem related. Maybe it's stability issue of the CI?


-- 
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

To unsubscribe, e-mail: commits-unsubscribe@tvm.apache.org

For queries about this service, please contact Infrastructure at:
users@infra.apache.org

[GitHub] [tvm] lazycal commented on pull request #10106: [onnx] fix onnx where broadcast

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

lazycal commented on pull request #10106:
URL: https://github.com/apache/tvm/pull/10106#issuecomment-1025045493


   @Laurawly Can you take a look?


-- 
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

To unsubscribe, e-mail: commits-unsubscribe@tvm.apache.org

For queries about this service, please contact Infrastructure at:
users@infra.apache.org

[GitHub] [tvm] AndrewZhaoLuo commented on pull request #10106: [onnx] fix onnx where broadcast

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

AndrewZhaoLuo commented on pull request #10106:
URL: https://github.com/apache/tvm/pull/10106#issuecomment-1027119594


   Once more, looks like you got unlucky again :( 


-- 
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

To unsubscribe, e-mail: commits-unsubscribe@tvm.apache.org

For queries about this service, please contact Infrastructure at:
users@infra.apache.org