--- a
+++ b/code/data_provider.py
@@ -0,0 +1,27 @@
+import numpy as np
+import os
+# import tensorflow as tf
+import h5py
+
+
+def load_h5_all(file, is_training):
+    hf = h5py.File(file, 'r+')
+    label = hf['label'][:][:]
+    num_samples = len(label)
+    train_size = num_samples - test_size
+    feat = hf['feature'][:][:, :]
+    gene = hf['gene_name'][:]
+    sample = hf['sample'][:]
+    print('%s has data:', feat.shape)
+    # train_dataset = tf.data.Dataset.from_tensor_slices((feat[:train_size, :], label[:train_size]))     #not using now
+    # test_dataset = tf.data.Dataset.from_tensor_slices((feat[-test_size:], label[-test_size:]))     #not using now
+    # train_dataset = tf.data.Dataset.from_generator((feat0[:train_size, :], label[:train_size]))
+    # test_dataset = tf.data.Dataset.from_generator((feat0[-test_size:], label[-test_size:]))
+
+    return feat, label, gene, sample
+
+
+
+if __name__ == '__main__':
+    m_rna, label, gene, sample_id = load_h5_all('../data_process/tcga.h5', True)
+