fix build

Author: hcur

src/TensorFlowNET.Core/Operations/gen_image_ops.cs

@@ -21,6 +21,12 @@ namespace Tensorflow
 {
     public class gen_image_ops
     {
+        public static (Tensor, Tensor, Tensor, Tensor) combined_non_max_suppression(Tensor boxes, Tensor scores, Tensor max_output_size_per_class, Tensor max_total_size,
+            Tensor iou_threshold, Tensor score_threshold, bool pad_per_class, bool clip_boxes)
+        {
+            throw new NotImplementedException("combined_non_max_suppression");
+        }
+
         public static Tensor convert_image_dtype(Tensor image, TF_DataType dtype, bool saturate = false, string name= null)
         {
             if (dtype == image.dtype)

src/TensorFlowNET.Core/Operations/gen_math_ops.cs

@@ -1086,17 +1086,17 @@ public static Tensor _min<Tx, Ty>(Tx input, Ty axis, bool keep_dims = false, str
 
         public static Tensor pow<Tx, Ty>(Tx x, Ty y, string name = null)
         {
-            if (tf.context.executing_eagerly())
+            if (tf.Context.executing_eagerly())
             {
-                var results = tf.Runner.TFE_FastPathExecute(tf.context, tf.context.device_name,
+                var results = tf.Runner.TFE_FastPathExecute(tf.Context, tf.Context.DeviceName,
                     "Pow", name, 
                     null,
                     x, y);
 
                 return results[0];
             }
 
-            var _op = tf._op_def_lib._apply_op_helper("Pow", name, args: new { x, y });
+            var _op = tf.OpDefLib._apply_op_helper("Pow", name, args: new { x, y });
 
             return _op.outputs[0];
         }
@@ -1214,4 +1214,4 @@ public static Tensor zero_fraction(Tensor value, string name = null)
             return _op.outputs[0];
         }
     }
-}
+}

src/TensorFlowNET.Core/Operations/gen_ops.cs

@@ -1,4 +1,5 @@
-using System.Linq;
+using System;
+using System.Linq;
 using System.Collections.Generic;
 using static Tensorflow.Binding;
 
@@ -9881,6 +9882,11 @@ public static Tensor encode_jpeg (Tensor image, string format = null, int? quali
             return op.output;
         }
 
+        public static Tensor encode_jpeg_variable_quality(Tensor image, Tensor quality)
+        {
+            throw new NotImplementedException("");
+        }
+
         /// <summary>
         ///    PNG-encode an image.
         /// </summary>
@@ -28061,6 +28067,11 @@ public static Operation save_v2 (Tensor prefix, Tensor tensor_names, Tensor shap
             return op;
         }
 
+        public static Tensor scale_and_translate (Tensor images_t, Tensor new_size, Tensor[] scale, Tensor zeroes, string kernel_type, bool antialias)
+        {
+            throw new NotImplementedException("scale_and_translate");
+        }
+
         /// <summary>
         ///    Outputs a <c>Summary</c> protocol buffer with scalar values.
         /// </summary>

src/TensorFlowNET.Core/Operations/image_ops_impl.cs

@@ -337,7 +337,7 @@ object[] _get_dim(Tensor tensor, int idx) {
                 object hd, bbox_h_start;
                 if ((bool)h[1])
                 {
-                    hd = math_ops.cast(h[0], dtypes.float64);
+                    hd = math_ops.cast((IVariableV1)h[0], dtypes.float64);
                     bbox_h_start = math_ops.cast(((int)hd - (int)hd * central_fraction) / 2, dtypes.int32);
                 } else
                 {
@@ -348,7 +348,7 @@ object[] _get_dim(Tensor tensor, int idx) {
                 object wd, bbox_w_start;
                 if ((bool)w[1])
                 {
-                    wd = math_ops.cast((RefVariable)w[0], dtypes.float64);
+                    wd = math_ops.cast((IVariableV1)w[0], dtypes.float64);
                     bbox_w_start = math_ops.cast(((int)wd - (int)wd * central_fraction) / 2, dtypes.int32);
                 } else
                 {
@@ -1743,7 +1743,7 @@ public static Tensor decode_image(Tensor contents, int channels = 0, TF_DataType
 
         public static Tensor crop_and_resize(Tensor image, Tensor boxes, Tensor box_ind, Tensor crop_size, string method, float extrapolation_value, string name)
         {
-            var _op = tf._op_def_lib._apply_op_helper("CropAndResize", name: name, args: new
+            var _op = tf.OpDefLib._apply_op_helper("CropAndResize", name: name, args: new
             {
                 image,
                 boxes,
@@ -1780,8 +1780,8 @@ public static (Tensor, Tensor, Tensor, Tensor) combined_non_max_suppression(Tens
                 Tensor score_threshold_tensor = ops.convert_to_tensor(
                     score_threshold, dtype: dtypes.float32, name: "score_threshold");
                 return gen_image_ops.combined_non_max_suppression(
-                    boxes, scores, max_output_size_per_class, max_total_size, iou_threshold, 
-                    score_threshold, pad_per_class, clip_boxes);
+                    boxes, scores, max_output_size_per_class, max_total_size, iou_threshold_tensor, 
+                    score_threshold_tensor, pad_per_class, clip_boxes);
             });
         }