added dataloader script

alloy_composition_dataset.py

@@ -0,0 +1,97 @@
+# coding=utf-8
+# 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: Add a description here."""
+
+
+import csv
+import json
+import os
+
+import datasets
+
+
+_DESCRIPTION = """\
+This is an alloy composition dataset
+"""
+
+_LICENSE = "MIT"
+
+# link to the dataset
+_URL = "https://drive.google.com/uc?export=download&id="
+_URLs = {
+'train': _URL+'1wAERHsEBvWvCgfiWjtodM_5lV2OPlapC',
+'test': _URL+'1TvC3R0gIjFNj2HWyvMZuuubv78vuZpSF',
+}
+
+class AlloyCompositionDataset(datasets.GeneratorBasedBuilder):
+    """TODO: Short description of my dataset."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="train", version=VERSION, description="Training split of the complete dataset"),
+        datasets.BuilderConfig(name="test", version=VERSION, description="Testing split of the complete dataset"),
+    ]
+
+    DEFAULT_CONFIG_NAME = "train" 
+    
+    def _info(self):
+        """Basic information about the dataset is specified here"""
+
+        features = datasets.Features(
+            {
+                "alloy_composition": datasets.Value("string")
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Generates the training and testing split of the dataset"""
+
+        urls_to_download = _URLs
+        downloaded_data = dl_manager.download_and_extract(urls_to_download)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": downloaded_data['train']
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": downloaded_data['test']
+                },
+            ),
+        ]
+
+    def _generate_examples(
+        self, filepath
+    ):
+        # Specify the format in which the data is to be returned
+        with open(filepath, encoding="utf-8") as f:
+            for i, line in enumerate(f.readlines()):
+                _id = i
+                row = ' '.join(w for w in line.strip().split(","))
+                yield _id, {"alloy_composition": row}