Eager execution coverage for image_ops_test.py. Removed run_deprecated_v1 decorators.

Part 14 (class FormatTest, NonMaxSuppression*Test)

PiperOrigin-RevId: 339106641
Change-Id: I504ff77c3713bc294124e3e5b449cd5bc5807786

Author: hyeygit

tensorflow/core/kernels/image/non_max_suppression_op.cc

@@ -43,10 +43,14 @@ static inline void CheckScoreSizes(OpKernelContext* context, int num_boxes,
                                    const Tensor& scores) {
   // The shape of 'scores' is [num_boxes]
   OP_REQUIRES(context, scores.dims() == 1,
-              errors::InvalidArgument("scores must be 1-D",
-                                      scores.shape().DebugString()));
-  OP_REQUIRES(context, scores.dim_size(0) == num_boxes,
-              errors::InvalidArgument("scores has incompatible shape"));
+              errors::InvalidArgument(
+                  "scores must be 1-D", scores.shape().DebugString(),
+                  " (Shape must be rank 1 but is rank ", scores.dims(), ")"));
+  OP_REQUIRES(
+      context, scores.dim_size(0) == num_boxes,
+      errors::InvalidArgument("scores has incompatible shape (Dimensions must "
+                              "be equal, but are ",
+                              num_boxes, " and ", scores.dim_size(0), ")"));
 }
 
 static inline void ParseAndCheckOverlapSizes(OpKernelContext* context,
@@ -67,11 +71,14 @@ static inline void ParseAndCheckBoxSizes(OpKernelContext* context,
                                          const Tensor& boxes, int* num_boxes) {
   // The shape of 'boxes' is [num_boxes, 4]
   OP_REQUIRES(context, boxes.dims() == 2,
-              errors::InvalidArgument("boxes must be 2-D",
-                                      boxes.shape().DebugString()));
+              errors::InvalidArgument(
+                  "boxes must be 2-D", boxes.shape().DebugString(),
+                  " (Shape must be rank 2 but is rank ", boxes.dims(), ")"));
   *num_boxes = boxes.dim_size(0);
   OP_REQUIRES(context, boxes.dim_size(1) == 4,
-              errors::InvalidArgument("boxes must have 4 columns"));
+              errors::InvalidArgument("boxes must have 4 columns (Dimension "
+                                      "must be 4 but is ",
+                                      boxes.dim_size(1), ")"));
 }
 
 static inline void CheckCombinedNMSScoreSizes(OpKernelContext* context,
@@ -670,12 +677,16 @@ class NonMaxSuppressionV3Op : public OpKernel {
     OP_REQUIRES(
         context, TensorShapeUtils::IsScalar(max_output_size.shape()),
         errors::InvalidArgument("max_output_size must be 0-D, got shape ",
-                                max_output_size.shape().DebugString()));
+                                max_output_size.shape().DebugString(),
+                                " (Shape must be rank 0 but is ", "rank ",
+                                max_output_size.dims(), ")"));
     // iou_threshold: scalar
     const Tensor& iou_threshold = context->input(3);
     OP_REQUIRES(context, TensorShapeUtils::IsScalar(iou_threshold.shape()),
                 errors::InvalidArgument("iou_threshold must be 0-D, got shape ",
-                                        iou_threshold.shape().DebugString()));
+                                        iou_threshold.shape().DebugString(),
+                                        " (Shape must be rank 0 but is rank ",
+                                        iou_threshold.dims(), ")"));
     const T iou_threshold_val = iou_threshold.scalar<T>()();
     OP_REQUIRES(context,
                 iou_threshold_val >= static_cast<T>(0.0) &&

tensorflow/core/kernels/image/non_max_suppression_op.cu.cc

@@ -15,6 +15,8 @@ limitations under the License.
 
 #if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
 #define EIGEN_USE_GPU
+#include "tensorflow/core/kernels/image/non_max_suppression_op.h"
+
 #include <limits>
 
 #include "absl/strings/str_cat.h"
@@ -23,7 +25,6 @@ limitations under the License.
 #include "tensorflow/core/framework/op_kernel.h"
 #include "tensorflow/core/framework/tensor_types.h"
 #include "tensorflow/core/kernels/gpu_prim.h"
-#include "tensorflow/core/kernels/image/non_max_suppression_op.h"
 #include "tensorflow/core/util/gpu_kernel_helper.h"
 #include "tensorflow/core/util/gpu_launch_config.h"
 #include "tensorflow/stream_executor/stream_executor.h"
@@ -550,30 +551,44 @@ Status CheckValidInputs(const Tensor& boxes, const Tensor& scores,
                         const Tensor& iou_threshold) {
   if (!TensorShapeUtils::IsScalar(max_output_size.shape())) {
     return errors::InvalidArgument("max_output_size must be 0-D, got shape ",
-                                   max_output_size.shape().DebugString());
+                                   max_output_size.shape().DebugString(),
+                                   " (Shape must be rank 0 but is ", "rank ",
+                                   max_output_size.dims(), ")");
   }
   if (!TensorShapeUtils::IsScalar(iou_threshold.shape())) {
     return errors::InvalidArgument("iou_threshold must be 0-D, got shape ",
-                                   iou_threshold.shape().DebugString());
+                                   iou_threshold.shape().DebugString(),
+                                   " (Shape must be rank 0 but is rank ",
+                                   iou_threshold.dims(), ")");
   }
   const float iou_threshold_val = iou_threshold.scalar<float>()();
   if (iou_threshold_val < 0 || iou_threshold_val > 1) {
     return errors::InvalidArgument("iou_threshold must be in [0, 1]");
   }
   if (boxes.dims() != 2) {
-    return errors::InvalidArgument("boxes must be a rank 2 tensor!");
+    return errors::InvalidArgument(
+        "boxes must be a rank 2 tensor! (Shape must "
+        "be rank 2 but is rank ",
+        boxes.dims(), ")");
   }
   int num_boxes = boxes.dim_size(0);
   if (boxes.dim_size(1) != 4) {
-    return errors::InvalidArgument("boxes must be Nx4");
+    return errors::InvalidArgument(
+        "boxes must be Nx4 (Dimension must be 4 but"
+        " is ",
+        boxes.dim_size(1), ")");
   }
   if (scores.dims() != 1) {
-    return errors::InvalidArgument("scores must be a vector!");
+    return errors::InvalidArgument(
+        "scores must be a vector! (Shape must be "
+        "rank 1 but is rank ",
+        scores.dims(), ")");
   }
   if (scores.dim_size(0) != num_boxes) {
     return errors::InvalidArgument(
-        "scores has incompatible shape");  // message must be exactly this
-                                           // otherwise tests fail!
+        "scores has incompatible shape "        // message must be exactly this
+        "(Dimensions must be equal, but are ",  // otherwise tests fail!
+        num_boxes, " and ", scores.dim_size(0), ")");
   }
   return Status::OK();
 }