# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # TODO: Address all TODOs and remove all explanatory comments """NIST LPBF Scan Tracks""" import os import datasets import pickle # # TODO: Add BibTeX citation # # Find for instance the citation on arxiv or on the dataset repo/website # _CITATION = """\ # @InProceedings{huggingface:dataset, # title = {A great new dataset}, # author={huggingface, Inc. # }, # year={2020} # } # """ # TODO: Add description of the dataset here # You can copy an official description _DESCRIPTION = """\ Dataset from https://doi.org/10.18434/M3C37Q """ # TODO: Add a link to an official homepage for the dataset here _HOMEPAGE = "" # TODO: Add the licence for the dataset here if you can find it _LICENSE = "MIT" # TODO: Add link to the official dataset URLs here # The HuggingFace Datasets library doesn't host the datasets but only points to the original files. # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method) _URLS = { "powder_single_track_radiant_temperature": "https://huggingface.co/datasets/ppak10/NIST-LPBF-Scan-Tracks/resolve/main/data/powder_plate_1_single_line/radiant_temperature.pkl", "powder_single_track_camera_signal": "https://huggingface.co/datasets/ppak10/NIST-LPBF-Scan-Tracks/resolve/main/data/powder_plate_1_single_line/camera_signal.pkl", "powder_multiple_track_radiant_temperature": "https://huggingface.co/datasets/ppak10/NIST-LPBF-Scan-Tracks/resolve/main/data/powder_plate_2_pad/radiant_temperature.pkl", "powder_multiple_track_camera_signal": "https://huggingface.co/datasets/ppak10/NIST-LPBF-Scan-Tracks/resolve/main/data/powder_plate_2_pad/camera_signal.pkl", "bare_single_track_radiant_temperature": "https://huggingface.co/datasets/ppak10/NIST-LPBF-Scan-Tracks/resolve/main/data/powder_plate_6_bare_single_line_195_w_800_mm_s/radiant_temperature.pkl", "bare_single_track_camera_signal": "https://huggingface.co/datasets/ppak10/NIST-LPBF-Scan-Tracks/resolve/main/data/powder_plate_6_bare_single_line_195_w_800_mm_s/camera_signal.pkl", "bare_multiple_track_radiant_temperature": "https://huggingface.co/datasets/ppak10/NIST-LPBF-Scan-Tracks/resolve/main/data/powder_plate_7_bare_pad_195_w_800_mm_s/radiant_temperature.pkl", "bare_multiple_track_camera_signal": "https://huggingface.co/datasets/ppak10/NIST-LPBF-Scan-Tracks/resolve/main/data/powder_plate_7_bare_pad_195_w_800_mm_s/camera_signal.pkl", } # TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case class Dataset(datasets.GeneratorBasedBuilder): """TODO: Short description of my dataset.""" VERSION = datasets.Version("0.0.1") # This is an example of a dataset with multiple configurations. # If you don't want/need to define several sub-sets in your dataset, # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes. # If you need to make complex sub-parts in the datasets with configurable options # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig # BUILDER_CONFIG_CLASS = MyBuilderConfig # You will be able to load one or the other configurations in the following list with # data = datasets.load_dataset('my_dataset', 'first_domain') # data = datasets.load_dataset('my_dataset', 'second_domain') BUILDER_CONFIGS = [ datasets.BuilderConfig( name="powder_single_track_radiant_temperature", version=VERSION, description="Radiant temperature from single track raster with powder" ), datasets.BuilderConfig( name="powder_single_track_camera_signal", version=VERSION, description="Camera signal from single track raster with powder" ), datasets.BuilderConfig( name="powder_multiple_track_radiant_temperature", version=VERSION, description="Radiant temperature from multiple track raster with powder" ), datasets.BuilderConfig( name="powder_multiple_track_camera_signal", version=VERSION, description="Camera signal from multiple track raster with powder" ), datasets.BuilderConfig( name="bare_single_track_radiant_temperature", version=VERSION, description="Radiant temperature from single track raster without powder" ), datasets.BuilderConfig( name="bare_single_track_camera_signal", version=VERSION, description="Camera signal from single track raster without powder" ), datasets.BuilderConfig( name="bare_multiple_track_radiant_temperature", version=VERSION, description="Radiant temperature from multiple track raster without powder" ), datasets.BuilderConfig( name="bare_multiple_track_camera_signal", version=VERSION, description="Camera signal from multiple track raster without powder" ), ] DEFAULT_CONFIG_NAME = "powder_single_track_radiant_temperature" # It's not mandatory to have a default configuration. Just use one if it make sense. def _info(self): return datasets.DatasetInfo( # This is the description that will appear on the datasets page. description=_DESCRIPTION, # This defines the different columns of the dataset and their types features = datasets.Features({ "sentence": datasets.Value("string"), }), # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and # specify them. They'll be used if as_supervised=True in builder.as_dataset. # supervised_keys=("sentence", "label"), # Homepage of the dataset for documentation homepage=_HOMEPAGE, # License for the dataset if available license=_LICENSE, # Citation for the dataset # citation=_CITATION, ) def _split_generators(self, dl_manager): # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files. # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive # urls = _URLS[self.config.name] downloaded_files = dl_manager.download_and_extract(_URLS) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, # These kwargs will be passed to _generate_examples gen_kwargs={ # "filepath": os.path.join(data_dir, "train.jsonl"), # "split": "train", "files": downloaded_files }, ), # datasets.SplitGenerator( # name=datasets.Split.VALIDATION, # # These kwargs will be passed to _generate_examples # # gen_kwargs={ # # "filepath": os.path.join(data_dir, "dev.jsonl"), # # "split": "dev", # # }, # ), # datasets.SplitGenerator( # name=datasets.Split.TEST, # # These kwargs will be passed to _generate_examples # # gen_kwargs={ # # "filepath": os.path.join(data_dir, "test.jsonl"), # # "split": "test" # # }, # ), ] # method parameters are unpacked from `gen_kwargs` as given in `_split_generators` def _generate_examples(self, files): # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset. # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example. for index, file in enumerate(files): with open(file, "rb") as f: track = pickle.load(f) yield index, { "track": track } # with open(filepath, encoding="utf-8") as f: # for key, row in enumerate(f): # data = json.loads(row) # if self.config.name == "raw": # # Yields examples as (key, example) tuples # yield key, { # "sentence": data["sentence"], # "option1": data["option1"], # "answer": "" if split == "test" else data["answer"], # } # else: # yield key, { # "sentence": data["sentence"], # "option2": data["option2"], # "second_domain_answer": "" if split == "test" else data["second_domain_answer"], # }