Create nsynth-script.py

nsynth-script.py

@@ -0,0 +1,97 @@
+# coding=utf-8
+
+"""Nsynth Database."""
+
+
+import os
+import textwrap
+import datasets
+import itertools
+import typing as tp
+from pathlib import Path
+from sklearn.model_selection import train_test_split
+
+SAMPLE_RATE = 16_000
+
+_TRAIN_FILENAME = 'nsynth-train.jsonwav.tar.gz'
+_VAL_FILENAME = 'nsynth-valid.jsonwav.tar.gz'
+_TEST_FILENAME = 'nsynth-test.jsonwav.tar.gz'
+
+CLASSES = ['bass', 'brass', 'flute', 'guitar', 'keyboard', 'mallet', 'organ', 'reed', 'string', 'synth_lead', 'vocal']
+
+
+class NsynthConfig(datasets.BuilderConfig):
+    """BuilderConfig for Nsynth."""
+    
+    def __init__(self, features, **kwargs):
+        super(NsynthConfig, self).__init__(version=datasets.Version("0.0.1", ""), **kwargs)
+        self.features = features
+
+
+class Nsynth(datasets.GeneratorBasedBuilder):
+
+    BUILDER_CONFIGS = [
+        NsynthConfig(
+            features=datasets.Features(
+                {
+                    "file": datasets.Value("string"),
+                    "audio": datasets.Audio(sampling_rate=SAMPLE_RATE),
+                    "instrument": datasets.Value("string"),
+                    "label": datasets.ClassLabel(names=CLASSES),
+                }
+            ),
+            name="nsynth", 
+            description='',
+        ), 
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description="",
+            features=self.config.features,
+            supervised_keys=None,
+            homepage="",
+            citation="",
+            task_templates=None,
+        )
+
+    def _split_generators(self, dl_manager):
+        dl_paths = dl_manager.extract({
+            'train': _TRAIN_FILENAME,
+            'validation': _VAL_FILENAME,
+            'test': _TEST_FILENAME,
+        })
+        return[
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": dl_paths['train']}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"filepath": dl_paths['validation']}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"filepath": dl_paths['test']}
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        dir_list = os.listdir(filepath)
+        folder_path = os.path.join(filepath, dir_list[0])
+        examples_path = os.path.join(folder_path, 'examples.json')
+        with open(examples_path) as examples_file:
+            examples = json.load(examples_file)
+        wav_dict = {}
+        audio_path = os.path.join(folder_path, "audio")
+
+        for filename in os.listdir(audio_path):
+            audio_filename = os.path.join(audio_path, filename)
+            guid = filename.replace('.wav', '')
+            yield guid, {
+                "id": str(guid),
+                # "file": audio_path, 
+                "audio": audio_filename, 
+                "instrument": examples[key]["instrument_family_str"], 
+                "label": examples[key]["instrument_family_str"], 
+            }