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Traceback (most recent call last):
File "run_helixfold.py", line 377, in
main(args)
File "run_helixfold.py", line 277, in main
random_seed=random_seed)
File "", line 2, in predict_structure
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/fluid/dygraph/base.py", line 356, in _decorate_function
return func(*args, **kwargs)
File "run_helixfold.py", line 138, in predict_structure
prediction = _forward_with_precision(processed_feature_dict)
File "run_helixfold.py", line 133, in _forward_with_precision
return_representations=True)
File "/public/home/qfduli3/fold/helix/helixfold/alphafold_paddle/model/model.py", line 249, in predict
compute_loss=False)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py", line 929, in call
return self._dygraph_call_func(*inputs, **kwargs)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py", line 914, in _dygraph_call_func
outputs = self.forward(*inputs, **kwargs)
File "/public/home/qfduli3/fold/helix/helixfold/alphafold_paddle/model/modules.py", line 230, in forward
ret = _run_single_recycling(prev, recycle_idx, compute_loss=False)
File "/public/home/qfduli3/fold/helix/helixfold/alphafold_paddle/model/modules.py", line 194, in _run_single_recycling
ensemble_representations=ensemble_representations)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py", line 929, in call
return self._dygraph_call_func(*inputs, **kwargs)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py", line 914, in _dygraph_call_func
outputs = self.forward(*inputs, **kwargs)
File "/public/home/qfduli3/fold/helix/helixfold/alphafold_paddle/model/modules.py", line 316, in forward
representations = self.evoformer(batch0)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py", line 929, in call
return self._dygraph_call_func(*inputs, **kwargs)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py", line 914, in _dygraph_call_func
outputs = self.forward(*inputs, **kwargs)
File "/public/home/qfduli3/fold/helix/helixfold/alphafold_paddle/model/modules.py", line 1647, in forward
preprocess_1d = self.preprocess_1d(batch['target_feat'])
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py", line 929, in call
return self._dygraph_call_func(*inputs, **kwargs)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py", line 914, in _dygraph_call_func
outputs = self.forward(*inputs, **kwargs)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/incubate/nn/layer/fused_linear.py", line 95, in forward
self.transpose_weight, self.name)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/incubate/nn/functional/fused_matmul_bias.py", line 108, in fused_linear
return fused_matmul_bias(x, weight, bias, False, transpose_weight, name)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/incubate/nn/functional/fused_matmul_bias.py", line 60, in fused_matmul_bias
return _C_ops.fused_gemm_epilogue(x, y, bias, 'trans_x', transpose_x,
AttributeError: module 'paddle.fluid.core_avx.ops' has no attribute 'fused_gemm_epilogue'
The text was updated successfully, but these errors were encountered:
helixfold,在DCU上,按README_DCU搭的环境,报以下错误
Traceback (most recent call last):
File "run_helixfold.py", line 377, in
main(args)
File "run_helixfold.py", line 277, in main
random_seed=random_seed)
File "", line 2, in predict_structure
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/fluid/dygraph/base.py", line 356, in _decorate_function
return func(*args, **kwargs)
File "run_helixfold.py", line 138, in predict_structure
prediction = _forward_with_precision(processed_feature_dict)
File "run_helixfold.py", line 133, in _forward_with_precision
return_representations=True)
File "/public/home/qfduli3/fold/helix/helixfold/alphafold_paddle/model/model.py", line 249, in predict
compute_loss=False)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py", line 929, in call
return self._dygraph_call_func(*inputs, **kwargs)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py", line 914, in _dygraph_call_func
outputs = self.forward(*inputs, **kwargs)
File "/public/home/qfduli3/fold/helix/helixfold/alphafold_paddle/model/modules.py", line 230, in forward
ret = _run_single_recycling(prev, recycle_idx, compute_loss=False)
File "/public/home/qfduli3/fold/helix/helixfold/alphafold_paddle/model/modules.py", line 194, in _run_single_recycling
ensemble_representations=ensemble_representations)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py", line 929, in call
return self._dygraph_call_func(*inputs, **kwargs)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py", line 914, in _dygraph_call_func
outputs = self.forward(*inputs, **kwargs)
File "/public/home/qfduli3/fold/helix/helixfold/alphafold_paddle/model/modules.py", line 316, in forward
representations = self.evoformer(batch0)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py", line 929, in call
return self._dygraph_call_func(*inputs, **kwargs)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py", line 914, in _dygraph_call_func
outputs = self.forward(*inputs, **kwargs)
File "/public/home/qfduli3/fold/helix/helixfold/alphafold_paddle/model/modules.py", line 1647, in forward
preprocess_1d = self.preprocess_1d(batch['target_feat'])
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py", line 929, in call
return self._dygraph_call_func(*inputs, **kwargs)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py", line 914, in _dygraph_call_func
outputs = self.forward(*inputs, **kwargs)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/incubate/nn/layer/fused_linear.py", line 95, in forward
self.transpose_weight, self.name)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/incubate/nn/functional/fused_matmul_bias.py", line 108, in fused_linear
return fused_matmul_bias(x, weight, bias, False, transpose_weight, name)
File "/public/home/qfduli3/conda-envs/paddle_dcu/lib/python3.7/site-packages/paddle/incubate/nn/functional/fused_matmul_bias.py", line 60, in fused_matmul_bias
return _C_ops.fused_gemm_epilogue(x, y, bias, 'trans_x', transpose_x,
AttributeError: module 'paddle.fluid.core_avx.ops' has no attribute 'fused_gemm_epilogue'
The text was updated successfully, but these errors were encountered: