Traceback (most recent call last):
File "/mnt/d/code/SEMamba/mytrain.py", line 575, in
main()
File "/mnt/d/code/SEMamba/mytrain.py", line 572, in main
train(0, args, cfg)
File "/mnt/d/code/SEMamba/mytrain.py", line 378, in train
mag_g, pha_g, com_g = generator(noisy_mag, noisy_pha)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, kwargs)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
return forward_call(*args, *kwargs)
File "/mnt/d/code/SEMamba/mytrain.py", line 83, in forward
x = block(x)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
return self._call_impl(args, kwargs)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
return forward_call(*args, kwargs)
File "/mnt/d/code/SEMamba/models/mamba_block.py", line 109, in forward
x = self.flinear( self.freq_mamba(x).permute(0,2,1) ).permute(0,2,1) + x
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, *kwargs)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
return forward_call(args, kwargs)
File "/mnt/d/code/SEMamba/models/mamba_block.py", line 65, in forward
x_backward, resi_backward = layer(x_backward, resi_backward)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, kwargs)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
return forward_call(args, kwargs)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/mamba_ssm/modules/block.py", line 67, in forward
hidden_states = self.mixer(hidden_states, inference_params=inference_params, mixer_kwargs)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
return self._call_impl(args, kwargs)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
return forward_call(*args, *kwargs)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/mamba_ssm/modules/mamba_simple.py", line 189, in forward
y = selective_scan_fn(
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/mamba_ssm/ops/selective_scan_interface.py", line 88, in selective_scan_fn
return SelectiveScanFn.apply(u, delta, A, B, C, D, z, delta_bias, delta_softplus, return_last_state)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/autograd/function.py", line 553, in apply
return super().apply(args, *kwargs) # type: ignore[misc]
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/mamba_ssm/ops/selective_scan_interface.py", line 42, in forward
out, x, rest = selective_scan_cuda.fwd(u, delta, A, B, C, D, z, delta_bias, delta_softplus)
RuntimeError: CUDA error: unknown error
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.
Traceback (most recent call last): File "/mnt/d/code/SEMamba/mytrain.py", line 575, in
main()
File "/mnt/d/code/SEMamba/mytrain.py", line 572, in main
train(0, args, cfg)
File "/mnt/d/code/SEMamba/mytrain.py", line 378, in train
mag_g, pha_g, com_g = generator(noisy_mag, noisy_pha)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, kwargs)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
return forward_call(*args, *kwargs)
File "/mnt/d/code/SEMamba/mytrain.py", line 83, in forward
x = block(x)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
return self._call_impl(args, kwargs)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
return forward_call(*args, kwargs)
File "/mnt/d/code/SEMamba/models/mamba_block.py", line 109, in forward
x = self.flinear( self.freq_mamba(x).permute(0,2,1) ).permute(0,2,1) + x
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, *kwargs)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
return forward_call(args, kwargs)
File "/mnt/d/code/SEMamba/models/mamba_block.py", line 65, in forward
x_backward, resi_backward = layer(x_backward, resi_backward)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, kwargs)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
return forward_call(args, kwargs)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/mamba_ssm/modules/block.py", line 67, in forward
hidden_states = self.mixer(hidden_states, inference_params=inference_params, mixer_kwargs)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
return self._call_impl(args, kwargs)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
return forward_call(*args, *kwargs)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/mamba_ssm/modules/mamba_simple.py", line 189, in forward
y = selective_scan_fn(
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/mamba_ssm/ops/selective_scan_interface.py", line 88, in selective_scan_fn
return SelectiveScanFn.apply(u, delta, A, B, C, D, z, delta_bias, delta_softplus, return_last_state)
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/torch/autograd/function.py", line 553, in apply
return super().apply(args, *kwargs) # type: ignore[misc]
File "/home/ubuntu22/miniconda3/envs/mambase/lib/python3.9/site-packages/mamba_ssm/ops/selective_scan_interface.py", line 42, in forward
out, x, rest = selective_scan_cuda.fwd(u, delta, A, B, C, D, z, delta_bias, delta_softplus)
RuntimeError: CUDA error: unknown error
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with
TORCH_USE_CUDA_DSA
to enable device-side assertions.