change crop and resize fn to fit multilevel ones

research/object_detection/meta_architectures/context_rcnn_meta_arch.py

@@ -324,7 +324,7 @@ class ContextRCNNMetaArch(faster_rcnn_meta_arch.FasterRCNNMetaArch):
       A float32 Tensor with shape [K, new_height, new_width, depth].
     """
     box_features = self._crop_and_resize_fn(
-        features_to_crop, proposal_boxes_normalized,
+        [features_to_crop], proposal_boxes_normalized, None,
         [self._initial_crop_size, self._initial_crop_size])
 
     attention_features = self._context_feature_extract_fn(

research/object_detection/meta_architectures/context_rcnn_meta_arch_tf1_test.py

@@ -42,6 +42,7 @@ from object_detection.protos import box_predictor_pb2
 from object_detection.protos import hyperparams_pb2
 from object_detection.protos import post_processing_pb2
 from object_detection.utils import ops
+from object_detection.utils import spatial_transform_ops as spatial_ops
 from object_detection.utils import test_case
 from object_detection.utils import test_utils
 from object_detection.utils import tf_version
@@ -363,8 +364,9 @@ class ContextRCNNMetaArchTest(test_case.TestCase, parameterized.TestCase):
           max_negatives_per_positive=None)
 
     crop_and_resize_fn = (
-        ops.matmul_crop_and_resize
-        if use_matmul_crop_and_resize else ops.native_crop_and_resize)
+        spatial_ops.multilevel_matmul_crop_and_resize
+        if use_matmul_crop_and_resize
+        else spatial_ops.multilevel_native_crop_and_resize)
     common_kwargs = {
         'is_training':
             is_training,