sync

test/TensorFlowNET.Examples/TextProcess/TextClassificationTrain.cs

@@ -55,7 +55,7 @@ namespace TensorFlowNET.Examples.CnnTextClassification
         {
             var stopwatch = Stopwatch.StartNew();
             Console.WriteLine("Building dataset...");
-            var (x, y, alphabet_size) = DataHelpers.build_char_dataset("train", model_name, CHAR_MAX_LEN, DataLimit=null);
+            var (x, y, alphabet_size) = DataHelpers.build_char_dataset("train", model_name, CHAR_MAX_LEN, DataLimit = null);
             Console.WriteLine("\tDONE ");
 
             var (train_x, valid_x, train_y, valid_y) = train_test_split(x, y, test_size: 0.15f);
@@ -169,8 +169,8 @@ namespace TensorFlowNET.Examples.CnnTextClassification
             //int classes = y.Data<int>().Distinct().Count();
             //int samples = len / classes;
             int train_size = (int)Math.Round(len * (1 - test_size));
-            var train_x = x[new Slice(stop:train_size), new Slice()];
-            var valid_x = x[new Slice(start: train_size+1), new Slice()];
+            var train_x = x[new Slice(stop: train_size), new Slice()];
+            var valid_x = x[new Slice(start: train_size + 1), new Slice()];
             var train_y = y[new Slice(stop: train_size)];
             var valid_y = y[new Slice(start: train_size + 1)];
             Console.WriteLine("\tDONE");
@@ -179,7 +179,7 @@ namespace TensorFlowNET.Examples.CnnTextClassification
 
         private IEnumerable<(NDArray, NDArray, int)> batch_iter(NDArray inputs, NDArray outputs, int batch_size, int num_epochs)
         {
-            var num_batches_per_epoch = (len(inputs) - 1) / batch_size +1;
+            var num_batches_per_epoch = (len(inputs) - 1) / batch_size + 1;
             var total_batches = num_batches_per_epoch * num_epochs;
             foreach (var epoch in range(num_epochs))
             {
@@ -189,7 +189,7 @@ namespace TensorFlowNET.Examples.CnnTextClassification
                     var end_index = Math.Min((batch_num + 1) * batch_size, len(inputs));
                     if (end_index <= start_index)
                         break;
-                    yield return (inputs[new Slice(start_index, end_index)], outputs[new Slice(start_index,end_index)], total_batches);
+                    yield return (inputs[new Slice(start_index, end_index)], outputs[new Slice(start_index, end_index)], total_batches);
                 }
             }
         }