Thank you for your great job！
I would like to follow your guidance to pre train icentia11k, but I have encountered some issues. The format of the 11k dataset I downloaded from the official website cannot be directly loaded using the dataset.
# Get paths to samples self.paths: List[Tuple[str, str]] = [] for index in self.split: self.paths.append((os.path.join(self.path, "{}_batched.pkl.gz".format(str(index).zfill(5))), os.path.join(self.path, "{}_batched_lbls.pkl.gz".format(str(index).zfill(5))))) # Check if files exists for file_input, file_label in self.paths: assert os.path.isfile(file_input), "File {} not found!".format(file_input) assert os.path.isfile(file_label), "File {} not found!".format(file_label)
I don't have batched. pkl. gz. I am a beginner and I want to know if there is any corresponding script that can convert data and successfully load the dataset. Looking forward to your reply~
Thank you for your great job！
I would like to follow your guidance to pre train icentia11k, but I have encountered some issues. The format of the 11k dataset I downloaded from the official website cannot be directly loaded using the dataset.
# Get paths to samples self.paths: List[Tuple[str, str]] = [] for index in self.split: self.paths.append((os.path.join(self.path, "{}_batched.pkl.gz".format(str(index).zfill(5))), os.path.join(self.path, "{}_batched_lbls.pkl.gz".format(str(index).zfill(5))))) # Check if files exists for file_input, file_label in self.paths: assert os.path.isfile(file_input), "File {} not found!".format(file_input) assert os.path.isfile(file_label), "File {} not found!".format(file_label)I don't have batched. pkl. gz. I am a beginner and I want to know if there is any corresponding script that can convert data and successfully load the dataset. Looking forward to your reply~