[GitHub] [tvm] jikechao opened a new issue, #15283: [Bug]

["jikechao (via GitHub)" <gi...@apache.org>]

jikechao opened a new issue, #15283:
URL: https://github.com/apache/tvm/issues/15283

   conv_transpose3d gives an inconsistent inference result with PyTorch.
   
   
   
   
   ### Actual behavior
   ![image](https://github.com/apache/tvm/assets/29506758/d6c2bec6-ad2d-44fb-85a8-78c04e9629c7)
   
   
   ### Steps to reproduce
   
   ```
   import torch
   from tvm import relay
   import tvm
   import numpy as np
   from torch.nn import Module
   
   input_data = torch.randn([1, 64, 8, 128, 172], dtype=torch.float32)
   para_1 = torch.randn([64, 128, 5, 5, 5], dtype=torch.float32)
   para_2 = torch.randn([128], dtype=torch.float32)
   para_3 = (2, 2, 2)
   para_4 = (2, 2, 2)
   para_5 = (1, 1, 1)
   para_6 = 1
   para_7 = (1, 1, 1)
   class conv_transpose3d(Module):
       def forward(self, *args):
           return torch.nn.functional.conv_transpose3d(args[0], para_1,para_2,para_3,para_4,para_5,para_6,para_7,)
   
   
   m = conv_transpose3d().float().eval()
   
   torch_outputs = m(input_data)
   
   trace = torch.jit.trace(m, input_data)
   input_shapes = [('input0', torch.Size([1, 64, 8, 128, 172]))]
   
   mod, params = relay.frontend.from_pytorch(trace, input_shapes)
   with tvm.transform.PassContext(opt_level=3):
       exe = relay.create_executor('graph', mod=mod, params=params, device=tvm.device('llvm', 0), target='llvm').evaluate()
   
   input_tvm = {'input0': np.array(input_data, dtype='float32')}
   tvm_outputs = exe(**input_tvm).asnumpy()
   
   np.testing.assert_allclose(torch_outputs, tvm_outputs, rtol=1e-4, atol=1e-4)
   
   ```
   
   ### Triage
   
   * needs-triage
   * frontend:pytorch


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Re: [I] [Bug] inconsistent inference result about conv_transpose3d operator in pytorch [tvm]

["tqchen (via GitHub)" <gi...@apache.org>]

tqchen closed issue #15283: [Bug] inconsistent inference result about conv_transpose3d operator in pytorch
URL: https://github.com/apache/tvm/issues/15283


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