Adding MSD data providers.

mlp/data_providers.py

@@ -135,6 +135,8 @@ class OneOfKDataProvider(DataProvider):
     """1-of-K classification target data provider.
 
     Transforms integer target labels to binary 1-of-K encoded targets.
+
+    Derived classes must set self.num_classes appropriately.
     """
 
     def next(self):
@@ -302,6 +304,96 @@ class CIFAR100DataProvider(OneOfKDataProvider):
             inputs, targets, batch_size, max_num_batches, shuffle_order, rng)
 
 
+class MSD10GenreDataProvider(OneOfKDataProvider):
+    """Data provider for Million Song Dataset 10-genre classification task."""
+
+    def __init__(self, which_set='train', batch_size=100, max_num_batches=-1,
+                 shuffle_order=True, rng=None):
+        """Create a new Million Song Dataset 10-genre data provider object.
+
+        Args:
+            which_set: One of 'train' or 'valid'. Determines which
+                portion of the MSD 10-genre data this object should provide.
+            batch_size (int): Number of data points to include in each batch.
+            max_num_batches (int): Maximum number of batches to iterate over
+                in an epoch. If `max_num_batches * batch_size > num_data` then
+                only as many batches as the data can be split into will be
+                used. If set to -1 all of the data will be used.
+            shuffle_order (bool): Whether to randomly permute the order of
+                the data before each epoch.
+            rng (RandomState): A seeded random number generator.
+        """
+        # check a valid which_set was provided
+        assert which_set in ['train', 'valid'], (
+            'Expected which_set to be either train or valid. '
+            'Got {0}'.format(which_set)
+        )
+        self.which_set = which_set
+        self.num_classes = 10
+        # construct path to data using os.path.join to ensure the correct path
+        # separator for the current platform / OS is used
+        # MLP_DATA_DIR environment variable should point to the data directory
+        data_path = os.path.join(
+            os.environ['MLP_DATA_DIR'],
+            'msd-10-genre-{0}.npz'.format(which_set))
+        assert os.path.isfile(data_path), (
+            'Data file does not exist at expected path: ' + data_path
+        )
+        # load data from compressed numpy file
+        loaded = np.load(data_path)
+        inputs, targets = loaded['inputs'], loaded['targets']
+        # label map gives strings corresponding to integer label targets
+        self.label_map = loaded['label_map']
+        # pass the loaded data to the parent class __init__
+        super(MSD10GenreDataProvider, self).__init__(
+            inputs, targets, batch_size, max_num_batches, shuffle_order, rng)
+
+
+class MSD25GenreDataProvider(OneOfKDataProvider):
+    """Data provider for Million Song Dataset 25-genre classification task."""
+
+    def __init__(self, which_set='train', batch_size=100, max_num_batches=-1,
+                 shuffle_order=True, rng=None):
+        """Create a new Million Song Dataset 25-genre data provider object.
+
+        Args:
+            which_set: One of 'train' or 'valid'. Determines which
+                portion of the MSD 25-genre data this object should provide.
+            batch_size (int): Number of data points to include in each batch.
+            max_num_batches (int): Maximum number of batches to iterate over
+                in an epoch. If `max_num_batches * batch_size > num_data` then
+                only as many batches as the data can be split into will be
+                used. If set to -1 all of the data will be used.
+            shuffle_order (bool): Whether to randomly permute the order of
+                the data before each epoch.
+            rng (RandomState): A seeded random number generator.
+        """
+        # check a valid which_set was provided
+        assert which_set in ['train', 'valid'], (
+            'Expected which_set to be either train or valid. '
+            'Got {0}'.format(which_set)
+        )
+        self.which_set = which_set
+        self.num_classes = 25
+        # construct path to data using os.path.join to ensure the correct path
+        # separator for the current platform / OS is used
+        # MLP_DATA_DIR environment variable should point to the data directory
+        data_path = os.path.join(
+            os.environ['MLP_DATA_DIR'],
+            'msd-25-genre-{0}.npz'.format(which_set))
+        assert os.path.isfile(data_path), (
+            'Data file does not exist at expected path: ' + data_path
+        )
+        # load data from compressed numpy file
+        loaded = np.load(data_path)
+        inputs, targets = loaded['inputs'], loaded['targets']
+        # label map gives strings corresponding to integer label targets
+        self.label_map = loaded['label_map']
+        # pass the loaded data to the parent class __init__
+        super(MSD25GenreDataProvider, self).__init__(
+            inputs, targets, batch_size, max_num_batches, shuffle_order, rng)
+
+
 class MetOfficeDataProvider(DataProvider):
     """South Scotland Met Office weather data provider."""