Partially fix the error when crop image.

src/TensorFlowNET.Core/Operations/image_ops_impl.cs

@@ -542,32 +542,32 @@ or rank = 4. Had rank = {0}", rank));
                          image_shape));
                  }
 
-                 var assert_ops = _CheckAtLeast3DImage(image, require_static: false);
+                 var assert_ops = _CheckAtLeast3DImage(image, require_static: false).ToList();
 
                  // batch: [0], height: [1], width: [2], depth: [3]
                  var bhwd = _ImageDimensions(image, rank: 4);
 
-                 assert_ops[assert_ops.Length] = _assert(check_ops.assert_greater_equal(tf.constant(offset_height),
+                 assert_ops.Add(_assert(check_ops.assert_greater_equal(tf.constant(offset_height),
                                                          tf.constant(0)), typeof(ValueError),
-                                                         "offset_height must be >= 0.");
-                 assert_ops[assert_ops.Length] = _assert(check_ops.assert_greater_equal(tf.constant(offset_width),
+                                                         "offset_height must be >= 0."));
+                 assert_ops.Add(_assert(check_ops.assert_greater_equal(tf.constant(offset_width),
                                                          tf.constant(0)), typeof(ValueError),
-                                                         "offset_width must be >= 0.");
-                 assert_ops[assert_ops.Length] = _assert(check_ops.assert_less(tf.constant(0),
+                                                         "offset_width must be >= 0."));
+                 assert_ops.Add(_assert(check_ops.assert_less(tf.constant(0),
                                                          tf.constant(target_width)), typeof(ValueError),
-                                                         "target_width must be > 0.");
-                 assert_ops[assert_ops.Length] = _assert(check_ops.assert_less(tf.constant(0),
+                                                         "target_width must be > 0."));
+                 assert_ops.Add(_assert(check_ops.assert_less(tf.constant(0),
                                                          tf.constant(target_height)), typeof(ValueError),
-                                                         "target_height must be > 0.");
-                 assert_ops[assert_ops.Length] = _assert(check_ops.assert_greater_equal(tf.constant(bhwd[2]),
+                                                         "target_height must be > 0."));
+                 assert_ops.Add(_assert(check_ops.assert_greater_equal(tf.constant(bhwd[2]),
                                                          tf.constant(target_width + offset_width)),
                                                          typeof(ValueError),
-                                                         "width must be >= target + offset.");
-                 assert_ops[assert_ops.Length] = _assert(check_ops.assert_greater_equal(tf.constant(bhwd[1]),
+                                                         "width must be >= target + offset."));
+                 assert_ops.Add(_assert(check_ops.assert_greater_equal(tf.constant(bhwd[1]),
                                                          tf.constant(target_height + offset_height)),
                                                          typeof(ValueError),
-                                                         "height must be >= target + offset.");
-                 image = control_flow_ops.with_dependencies(assert_ops, image);
+                                                         "height must be >= target + offset."));
+                 image = control_flow_ops.with_dependencies(assert_ops.ToArray(), image);
 
                  var cropped = array_ops.slice(
                      image, array_ops.stack(new[] { 0, offset_height, offset_width, 0 }),
@@ -575,12 +575,16 @@ or rank = 4. Had rank = {0}", rank));
 
                  Shape cropped_shape_result()
                  {
-                     long[] i_remnants = { };
+                     long[] i_remnants = new long[4];
+                     int idx = 0;
                      foreach (var i in new[] { bhwd[0], target_height, target_width, bhwd[3] })
+                     {
                          if (_is_tensor(i))
-                             return null;
+                             i_remnants[idx] = -1;
                          else
-                             i_remnants[i_remnants.Length] = i;
+                             i_remnants[idx] = i;
+                         idx++;
+                     }
                      return new Shape(i_remnants);
                  };
                  var cropped_shape = cropped_shape_result();