Hello Buddy!
I am doing first steps in this sphere, and I have been impressived with your tutorial.
So can you help me with it? How to avoid some warnings with execution?
C:\Users\acid3\dev\datascencebyexample\train_prototype.py:19: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ..\torch\csrc\utils\tensor_new.cpp:264.) src_data = torch.tensor(_raw_train).unsqueeze(-1).float() C:\Users\acid3\dev\datascencebyexample\.venv\Lib\site-packages\torch\nn\modules\transformer.py:282: UserWarning: enable_nested_tensor is True, but self.use_nested_tensor is False because encoder_layer.self_attn.batch_first was not True(use batch_first for better inference performance) warnings.warn(f"enable_nested_tensor is True, but self.use_nested_tensor is False because {why_not_sparsity_fast_path}")
Something about performance.
Hello Buddy!
I am doing first steps in this sphere, and I have been impressived with your tutorial.
So can you help me with it? How to avoid some warnings with execution?
C:\Users\acid3\dev\datascencebyexample\train_prototype.py:19: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ..\torch\csrc\utils\tensor_new.cpp:264.) src_data = torch.tensor(_raw_train).unsqueeze(-1).float() C:\Users\acid3\dev\datascencebyexample\.venv\Lib\site-packages\torch\nn\modules\transformer.py:282: UserWarning: enable_nested_tensor is True, but self.use_nested_tensor is False because encoder_layer.self_attn.batch_first was not True(use batch_first for better inference performance) warnings.warn(f"enable_nested_tensor is True, but self.use_nested_tensor is False because {why_not_sparsity_fast_path}")Something about performance.