Revert IMDB dataset changes.

src/TensorFlowNET.Keras/Datasets/Imdb.cs

@@ -5,8 +5,6 @@ using System.Text;
 using Tensorflow.Keras.Utils;
 using NumSharp;
 using System.Linq;
-using NumSharp.Utilities;
-using Tensorflow.Queues;
 
 namespace Tensorflow.Keras.Datasets
 {
@@ -17,10 +15,8 @@ namespace Tensorflow.Keras.Datasets
     /// </summary>
     public class Imdb
     {
-        //string origin_folder = "https://storage.googleapis.com/tensorflow/tf-keras-datasets/";
-        string origin_folder = "http://ai.stanford.edu/~amaas/data/sentiment/";
-        //string file_name = "imdb.npz";
-        string file_name = "aclImdb_v1.tar.gz";
+        string origin_folder = "https://storage.googleapis.com/tensorflow/tf-keras-datasets/";
+        string file_name = "imdb.npz";
         string dest_folder = "imdb";
 
         /// <summary>
@@ -46,61 +42,33 @@ namespace Tensorflow.Keras.Datasets
         {
             var dst = Download();
 
-            var vocab = BuildVocabulary(Path.Combine(dst, "imdb.vocab"), start_char, oov_char, index_from);
-
-            var (x_train,y_train) = GetDataSet(Path.Combine(dst, "train"));
-            var (x_test, y_test) = GetDataSet(Path.Combine(dst, "test"));
-
-            return new DatasetPass
+            var lines = File.ReadAllLines(Path.Combine(dst, "imdb_train.txt"));
+            var x_train_string = new string[lines.Length];
+            var y_train = np.zeros(new int[] { lines.Length }, NPTypeCode.Int64);
+            for (int i = 0; i < lines.Length; i++)
             {
-                Train = (x_train, y_train),
-                Test = (x_test, y_test)
-            };
-        }
+                y_train[i] = long.Parse(lines[i].Substring(0, 1));
+                x_train_string[i] = lines[i].Substring(2);
+            }
 
-        private static Dictionary<string, int> BuildVocabulary(string path, 
-            int start_char,
-            int oov_char,
-            int index_from)
-        {
-            var words = File.ReadAllLines(path);
-            var result = new Dictionary<string, int>();
-            var idx = index_from;
+            var x_train = np.array(x_train_string);
 
-            foreach (var word in words)
+            File.ReadAllLines(Path.Combine(dst, "imdb_test.txt"));
+            var x_test_string = new string[lines.Length];
+            var y_test = np.zeros(new int[] { lines.Length }, NPTypeCode.Int64);
+            for (int i = 0; i < lines.Length; i++)
             {
-                result[word] = idx;
-                idx += 1;
+                y_test[i] = long.Parse(lines[i].Substring(0, 1));
+                x_test_string[i] = lines[i].Substring(2);
             }
 
-            return result;
-        }
-
-        private static (NDArray, NDArray) GetDataSet(string path)
-        {
-            var posFiles = Directory.GetFiles(Path.Combine(path, "pos")).Slice(0,10);
-            var negFiles = Directory.GetFiles(Path.Combine(path, "neg")).Slice(0,10);
-
-            var x_string = new string[posFiles.Length + negFiles.Length];
-            var y = new int[posFiles.Length + negFiles.Length];
-            var trg = 0;
-            var longest = 0;
+            var x_test = np.array(x_test_string);
 
-            for (int i = 0; i < posFiles.Length; i++, trg++)
-            {
-                y[trg] = 1;
-                x_string[trg] = File.ReadAllText(posFiles[i]);
-                longest = Math.Max(longest, x_string[trg].Length);
-            }
-            for (int i = 0; i < posFiles.Length; i++, trg++)
+            return new DatasetPass
             {
-                y[trg] = 0;
-                x_string[trg] = File.ReadAllText(negFiles[i]);
-                longest = Math.Max(longest, x_string[trg].Length);
-            }
-            var x = np.array(x_string);
-
-            return (x, y);
+                Train = (x_train, y_train),
+                Test = (x_test, y_test)
+            };
         }
 
         (NDArray, NDArray) LoadX(byte[] bytes)
@@ -122,9 +90,8 @@ namespace Tensorflow.Keras.Datasets
 
             Web.Download(origin_folder + file_name, dst, file_name);
 
-            Tensorflow.Keras.Utils.Compress.ExtractTGZ(Path.Combine(dst, file_name), dst);
-
-            return Path.Combine(dst, "aclImdb");
+            return dst;
+            // return Path.Combine(dst, file_name);
         }
     }
-}
+}