Enhance error reporting.

PiperOrigin-RevId: 197390052

diff --git a/tensorflow/contrib/lite/kernels/activations.cc b/tensorflow/contrib/lite/kernels/activations.cc
index 4972159..add36b4 100644 (file)
--- a/tensorflow/contrib/lite/kernels/activations.cc
+++ b/tensorflow/contrib/lite/kernels/activations.cc
@@ -191,7 +191,8 @@ TfLiteStatus ReluEval(TfLiteContext* context, TfLiteNode* node) {
       return kTfLiteOk;
     } break;
     default:
-      context->ReportError(context, "Only float32 supported currently.");
+      context->ReportError(context, "Only float32 supported currently, got %d.",
+                           input->type);
       return kTfLiteError;
   }
 }
@@ -211,7 +212,8 @@ TfLiteStatus Relu1Eval(TfLiteContext* context, TfLiteNode* node) {
       return kTfLiteOk;
     } break;
     default:
-      context->ReportError(context, "Only float32 supported currently.");
+      context->ReportError(context, "Only float32 supported currently, got %d.",
+                           input->type);
       return kTfLiteError;
   }
 }
@@ -229,7 +231,8 @@ TfLiteStatus Relu6Eval(TfLiteContext* context, TfLiteNode* node) {
       return kTfLiteOk;
     } break;
     default:
-      context->ReportError(context, "Only float32 supported currently.");
+      context->ReportError(context, "Only float32 supported currently, got %d.",
+                           input->type);
       return kTfLiteError;
   }
 }
@@ -256,7 +259,8 @@ TfLiteStatus TanhEval(TfLiteContext* context, TfLiteNode* node) {
       return kTfLiteOk;
     } break;
     default:
-      context->ReportError(context, "Only float32 supported currently.");
+      context->ReportError(context, "Only float32 supported currently, got %d.",
+                           input->type);
       return kTfLiteError;
   }
 }
@@ -285,7 +289,8 @@ TfLiteStatus SigmoidEval(TfLiteContext* context, TfLiteNode* node) {
       break;
     }
     default:
-      context->ReportError(context, "Only float32 supported currently.");
+      context->ReportError(context, "Only float32 supported currently, got %d.",
+                           input->type);
       return kTfLiteError;
   }
   return kTfLiteOk;
@@ -377,8 +382,9 @@ TfLiteStatus SoftmaxEval(TfLiteContext* context, TfLiteNode* node) {
         Softmax4DFloat(input, output, params);
         return kTfLiteOk;
       }
-      context->ReportError(context,
-                           "Only 2D and 4D tensors supported currently.");
+      context->ReportError(
+          context, "Only 2D and 4D tensors supported currently, got %dD.",
+          NumDimensions(input));
       return kTfLiteError;
     }
     case kTfLiteUInt8: {
@@ -390,13 +396,15 @@ TfLiteStatus SoftmaxEval(TfLiteContext* context, TfLiteNode* node) {
         Softmax4DQuantized(input, output, params, data);
         return kTfLiteOk;
       }
-      context->ReportError(context,
-                           "Only 2D and 4D tensors supported currently.");
+      context->ReportError(
+          context, "Only 2D and 4D tensors supported currently, got %dD.",
+          NumDimensions(input));
       return kTfLiteError;
     }
     default:
-      context->ReportError(context,
-                           "Only float32 and uint8_t supported currently.");
+      context->ReportError(
+          context, "Only float32 and uint8_t supported currently, got %d.",
+          input->type);
       return kTfLiteError;
   }
 }
@@ -411,7 +419,8 @@ TfLiteStatus LogSoftmaxEval(TfLiteContext* context, TfLiteNode* node) {
           GetTensorData<float>(output), GetTensorDims(output));
       return kTfLiteOk;
     default:
-      context->ReportError(context, "Only float32 supported currently.");
+      context->ReportError(context, "Only float32 supported currently., got %d",
+                           input->type);
       return kTfLiteError;
   }
 }
@@ -422,7 +431,8 @@ TfLiteStatus PreluEval(TfLiteContext* context, TfLiteNode* node) {
   const TfLiteTensor* output = GetOutput(context, node, 0);
 
   if (input->type != kTfLiteFloat32) {
-    context->ReportError(context, "Only float32 supported currently.");
+    context->ReportError(context, "Only float32 supported currently, got %d.",
+                         input->type);
     return kTfLiteError;
   }
   TF_LITE_ENSURE_EQ(context, input->dims->size, 4);

diff --git a/tensorflow/contrib/lite/kernels/arg_max.cc b/tensorflow/contrib/lite/kernels/arg_max.cc
index 738d475..26f57e8 100644 (file)
--- a/tensorflow/contrib/lite/kernels/arg_max.cc
+++ b/tensorflow/contrib/lite/kernels/arg_max.cc
@@ -52,7 +52,8 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
       output->type = kTfLiteInt64;
       break;
     default:
-      context->ReportError(context, "Unknown index output data type");
+      context->ReportError(context, "Unknown index output data type: %d",
+                           params->output_type);
       return kTfLiteError;
   }
 
@@ -64,7 +65,10 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
       break;
 
     default:
-      context->ReportError(context, "Only float32 and int types are supported");
+      context->ReportError(
+          context,
+          "Unkonwn input type: %d, only float32 and int types are supported",
+          input->type);
       return kTfLiteError;
   }
 

diff --git a/tensorflow/contrib/lite/kernels/basic_rnn.cc b/tensorflow/contrib/lite/kernels/basic_rnn.cc
index 0907547..7dc0c56 100644 (file)
--- a/tensorflow/contrib/lite/kernels/basic_rnn.cc
+++ b/tensorflow/contrib/lite/kernels/basic_rnn.cc
@@ -210,7 +210,8 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
                            hidden_state, output);
     }
     default:
-      context->ReportError(context, "Type not currently supported.");
+      context->ReportError(context, "Type %d not currently supported.",
+                           input_weights->type);
       return kTfLiteError;
   }
   return kTfLiteOk;

diff --git a/tensorflow/contrib/lite/kernels/batch_to_space_nd.cc b/tensorflow/contrib/lite/kernels/batch_to_space_nd.cc
index 262e1ae..c8cee88 100644 (file)
--- a/tensorflow/contrib/lite/kernels/batch_to_space_nd.cc
+++ b/tensorflow/contrib/lite/kernels/batch_to_space_nd.cc
@@ -163,8 +163,9 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
       }
       break;
     default:
-      context->ReportError(context,
-                           "Type is currently not supported by BatchToSpace.");
+      context->ReportError(
+          context, "Type %d is currently not supported by BatchToSpace.",
+          op_context.input->type);
       return kTfLiteError;
   }
 #undef TF_LITE_BATCH_TO_SPACE_ND

diff --git a/tensorflow/contrib/lite/kernels/comparisons.cc b/tensorflow/contrib/lite/kernels/comparisons.cc
index b948334..3b81062 100644 (file)
--- a/tensorflow/contrib/lite/kernels/comparisons.cc
+++ b/tensorflow/contrib/lite/kernels/comparisons.cc
@@ -85,7 +85,8 @@ TfLiteStatus GreaterEval(TfLiteContext* context, TfLiteNode* node) {
       break;
     default:
       context->ReportError(context,
-                           "Does not support type other than float|int");
+                           "Does not support type %d, requires float|int",
+                           input1->type);
       return kTfLiteError;
   }
   return kTfLiteOk;
@@ -109,7 +110,8 @@ TfLiteStatus GreaterEqualEval(TfLiteContext* context, TfLiteNode* node) {
       break;
     default:
       context->ReportError(context,
-                           "Does not support type other than float|int");
+                           "Does not support type %d, requires float|int",
+                           input1->type);
       return kTfLiteError;
   }
   return kTfLiteOk;
@@ -133,7 +135,8 @@ TfLiteStatus LessEval(TfLiteContext* context, TfLiteNode* node) {
       break;
     default:
       context->ReportError(context,
-                           "Does not support type other than float|int");
+                           "Does not support type %d, requires float|int",
+                           input1->type);
       return kTfLiteError;
   }
   return kTfLiteOk;
@@ -157,7 +160,8 @@ TfLiteStatus LessEqualEval(TfLiteContext* context, TfLiteNode* node) {
       break;
     default:
       context->ReportError(context,
-                           "Does not support type other than float|int");
+                           "Does not support type %d, requires float|int",
+                           input1->type);
       return kTfLiteError;
   }
   return kTfLiteOk;

diff --git a/tensorflow/contrib/lite/kernels/conv.cc b/tensorflow/contrib/lite/kernels/conv.cc
index 2b7e455..0b35a22 100644 (file)
--- a/tensorflow/contrib/lite/kernels/conv.cc
+++ b/tensorflow/contrib/lite/kernels/conv.cc
@@ -488,7 +488,8 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
                                  bias, im2col, hwcn_weights, output);
       break;
     default:
-      context->ReportError(context, "Type not currently supported.");
+      context->ReportError(context, "Type %d not currently supported.",
+                           input->type);
       return kTfLiteError;
   }
   return kTfLiteOk;

diff --git a/tensorflow/contrib/lite/kernels/depthwise_conv.cc b/tensorflow/contrib/lite/kernels/depthwise_conv.cc
index 3ad8d7d..abb2549 100644 (file)
--- a/tensorflow/contrib/lite/kernels/depthwise_conv.cc
+++ b/tensorflow/contrib/lite/kernels/depthwise_conv.cc
@@ -247,7 +247,8 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
                                  bias, output);
       break;
     default:
-      context->ReportError(context, "Type not currently supported.");
+      context->ReportError(context, "Type %d not currently supported.",
+                           input->type);
       return kTfLiteError;
   }
   return kTfLiteOk;

diff --git a/tensorflow/contrib/lite/kernels/div.cc b/tensorflow/contrib/lite/kernels/div.cc
index e52e4fe..d264821 100644 (file)
--- a/tensorflow/contrib/lite/kernels/div.cc
+++ b/tensorflow/contrib/lite/kernels/div.cc
@@ -118,8 +118,9 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
   if (output->type == kTfLiteFloat32) {
     EvalFloat<kernel_type>(context, node, params, data, input1, input2, output);
   } else {
-    context->ReportError(context,
-                         "Div only supports FLOAT32 and quantized UINT8 now.");
+    context->ReportError(
+        context, "Div only supports FLOAT32 and quantized UINT8 now, got %d.",
+        output->type);
     return kTfLiteError;
   }
 

diff --git a/tensorflow/contrib/lite/kernels/elementwise.cc b/tensorflow/contrib/lite/kernels/elementwise.cc
index b719a08..0bd5046 100644 (file)
--- a/tensorflow/contrib/lite/kernels/elementwise.cc
+++ b/tensorflow/contrib/lite/kernels/elementwise.cc
@@ -48,7 +48,8 @@ TfLiteStatus SinEval(TfLiteContext* context, TfLiteNode* node) {
       return kTfLiteOk;
     }
     default: {
-      context->ReportError(context, "Only float32 is supported currently");
+      context->ReportError(context, "Input type is %d, requires float32",
+                           input->type);
       return kTfLiteError;
     }
   }

diff --git a/tensorflow/contrib/lite/kernels/fully_connected.cc b/tensorflow/contrib/lite/kernels/fully_connected.cc
index a486b81..3374923 100644 (file)
--- a/tensorflow/contrib/lite/kernels/fully_connected.cc
+++ b/tensorflow/contrib/lite/kernels/fully_connected.cc
@@ -357,7 +357,8 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
       return EvalQuantized<kernel_type>(context, node, params, data, input,
                                         filter, bias, output);
     default:
-      context->ReportError(context, "Type not currently supported.");
+      context->ReportError(context, "Type %d not currently supported.",
+                           filter->type);
       return kTfLiteError;
   }
   return kTfLiteOk;

diff --git a/tensorflow/contrib/lite/kernels/gather.cc b/tensorflow/contrib/lite/kernels/gather.cc
index c452d3e..6a23414 100644 (file)
--- a/tensorflow/contrib/lite/kernels/gather.cc
+++ b/tensorflow/contrib/lite/kernels/gather.cc
@@ -59,8 +59,9 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
       TF_LITE_ENSURE_EQ(context, NumDimensions(input), 1);
     } break;
     default:
-      context->ReportError(context,
-                           "Only float32 and string types are supported");
+      context->ReportError(
+          context, "Only float32 and string types are supported, got %d",
+          input->type);
       return kTfLiteError;
   }
   const int num_dimensions =

diff --git a/tensorflow/contrib/lite/kernels/l2norm.cc b/tensorflow/contrib/lite/kernels/l2norm.cc
index 7cea63d..3205c1c 100644 (file)
--- a/tensorflow/contrib/lite/kernels/l2norm.cc
+++ b/tensorflow/contrib/lite/kernels/l2norm.cc
@@ -94,7 +94,8 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
     }
 #undef TF_LITE_L2NORM
   } else {
-    context->ReportError(context, "Inputs and outputs not all float types.");
+    context->ReportError(context, "Output type is %d, requires float.",
+                         output->type);
     return kTfLiteError;
   }
 

diff --git a/tensorflow/contrib/lite/kernels/local_response_norm.cc b/tensorflow/contrib/lite/kernels/local_response_norm.cc
index c15a517..36dca29 100644 (file)
--- a/tensorflow/contrib/lite/kernels/local_response_norm.cc
+++ b/tensorflow/contrib/lite/kernels/local_response_norm.cc
@@ -77,7 +77,8 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
     }
 #undef TF_LITE_LOCAL_RESPONSE_NORM
   } else {
-    context->ReportError(context, "Inputs and outputs not all float types.");
+    context->ReportError(context, "Output type is %d, requires float.",
+                         output->type);
     return kTfLiteError;
   }
 

diff --git a/tensorflow/contrib/lite/kernels/mul.cc b/tensorflow/contrib/lite/kernels/mul.cc
index 6c4c3a1..62f4e94 100644 (file)
--- a/tensorflow/contrib/lite/kernels/mul.cc
+++ b/tensorflow/contrib/lite/kernels/mul.cc
@@ -159,8 +159,9 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
     EvalQuantized<kernel_type>(context, node, params, data, input1, input2,
                                output);
   } else {
-    context->ReportError(context,
-                         "Mul only supports FLOAT32 and quantized UINT8 now.");
+    context->ReportError(
+        context, "Mul only supports FLOAT32 and quantized UINT8 now, got %d.",
+        output->type);
     return kTfLiteError;
   }
 

diff --git a/tensorflow/contrib/lite/kernels/neg.cc b/tensorflow/contrib/lite/kernels/neg.cc
index b8b53f3..4124c05 100644 (file)
--- a/tensorflow/contrib/lite/kernels/neg.cc
+++ b/tensorflow/contrib/lite/kernels/neg.cc
@@ -59,7 +59,8 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
       break;
     default:
       context->ReportError(
-          context, "Neg only currently supports int64, int32, and float32.",
+          context,
+          "Neg only currently supports int64, int32, and float32, got %d.",
           input->type);
       return kTfLiteError;
   }

diff --git a/tensorflow/contrib/lite/kernels/pad.cc b/tensorflow/contrib/lite/kernels/pad.cc
index ecac2dd..83668cb 100644 (file)
--- a/tensorflow/contrib/lite/kernels/pad.cc
+++ b/tensorflow/contrib/lite/kernels/pad.cc
@@ -199,7 +199,9 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
       }
     } break;
     default:
-      context->ReportError(context, "Type is currently not supported by Pad.");
+      context->ReportError(context,
+                           "Type %d is currently not supported by Pad.",
+                           op_context.input->type);
       return kTfLiteError;
   }
 #undef TF_LITE_PAD

diff --git a/tensorflow/contrib/lite/kernels/pooling.cc b/tensorflow/contrib/lite/kernels/pooling.cc
index 645d9f4..311e9b8 100644 (file)
--- a/tensorflow/contrib/lite/kernels/pooling.cc
+++ b/tensorflow/contrib/lite/kernels/pooling.cc
@@ -246,7 +246,8 @@ TfLiteStatus AverageEval(TfLiteContext* context, TfLiteNode* node) {
                                         output);
       break;
     default:
-      context->ReportError(context, "Type not currently supported.");
+      context->ReportError(context, "Type %d not currently supported.",
+                           input->type);
       return kTfLiteError;
   }
   return kTfLiteOk;
@@ -267,7 +268,8 @@ TfLiteStatus MaxEval(TfLiteContext* context, TfLiteNode* node) {
       MaxEvalQuantized<kernel_type>(context, node, params, data, input, output);
       break;
     default:
-      context->ReportError(context, "Type not currently supported.");
+      context->ReportError(context, "Type %d not currently supported.",
+                           input->type);
       return kTfLiteError;
   }
   return kTfLiteOk;
@@ -288,7 +290,8 @@ TfLiteStatus L2Eval(TfLiteContext* context, TfLiteNode* node) {
     // We don't have a quantized implementation, so just fall through to the
     // 'default' case.
     default:
-      context->ReportError(context, "Type not currently supported.");
+      context->ReportError(context, "Type %d not currently supported.",
+                           input->type);
       return kTfLiteError;
   }
   return kTfLiteOk;

diff --git a/tensorflow/contrib/lite/kernels/resize_bilinear.cc b/tensorflow/contrib/lite/kernels/resize_bilinear.cc
index e4bd0f5..f2092ea 100644 (file)
--- a/tensorflow/contrib/lite/kernels/resize_bilinear.cc
+++ b/tensorflow/contrib/lite/kernels/resize_bilinear.cc
@@ -104,7 +104,8 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
     }
 #undef TF_LITE_RESIZE_BILINEAR
   } else {
-    context->ReportError(context, "Inputs and outputs not all float types.");
+    context->ReportError(context, "Output type is %d, requires float.",
+                         output->type);
     return kTfLiteError;
   }
 

diff --git a/tensorflow/contrib/lite/kernels/select.cc b/tensorflow/contrib/lite/kernels/select.cc
index 9bc8a1a..9b6cee3 100644 (file)
--- a/tensorflow/contrib/lite/kernels/select.cc
+++ b/tensorflow/contrib/lite/kernels/select.cc
@@ -97,7 +97,9 @@ TfLiteStatus SelectEval(TfLiteContext* context, TfLiteNode* node) {
       break;                                                                   \
     default:                                                                   \
       context->ReportError(context,                                            \
-                           "Does not support type other than bool|float|int"); \
+                           "Does not support type other than bool|float|int, " \
+                           "got %d",                                           \
+                           type);                                              \
       return kTfLiteError;                                                     \
   }
 

diff --git a/tensorflow/contrib/lite/kernels/slice.cc b/tensorflow/contrib/lite/kernels/slice.cc
index b28934e..6a20e80 100644 (file)
--- a/tensorflow/contrib/lite/kernels/slice.cc
+++ b/tensorflow/contrib/lite/kernels/slice.cc
@@ -85,7 +85,8 @@ TfLiteStatus ResizeOutputShape(TfLiteContext* context,
     TF_LITE_ENSURE_STATUS(CalculateOutputShapeVector<int64_t>(
         context, input, begin, size, &output_shape_vector));
   } else {
-    context->ReportError(context, "Type is currently not supported by Slice.");
+    context->ReportError(
+        context, "Type %d is currently not supported by Slice.", begin->type);
     return kTfLiteError;
   }
 
@@ -148,7 +149,8 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
     GetBeginAndSizeVectors<int64_t>(NumDimensions(input), begin, size, &begins,
                                     &sizes);
   } else {
-    context->ReportError(context, "Type is currently not supported by Slice.");
+    context->ReportError(
+        context, "Type %d is currently not supported by Slice.", begin->type);
     return kTfLiteError;
   }
 
@@ -179,8 +181,8 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
       TF_LITE_SLICE(bool);
       break;
     default:
-      context->ReportError(context,
-                           "Type is currently not supported by Slice.");
+      context->ReportError(
+          context, "Type %d is currently not supported by Slice.", input->type);
       return kTfLiteError;
   }
 #undef TF_LITE_SLICE

diff --git a/tensorflow/contrib/lite/kernels/space_to_batch_nd.cc b/tensorflow/contrib/lite/kernels/space_to_batch_nd.cc
index 1e35869..c926959 100644 (file)
--- a/tensorflow/contrib/lite/kernels/space_to_batch_nd.cc
+++ b/tensorflow/contrib/lite/kernels/space_to_batch_nd.cc
@@ -152,8 +152,9 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
       }
       break;
     default:
-      context->ReportError(context,
-                           "Type is currently not supported by SpaceToBatch.");
+      context->ReportError(
+          context, "Type %d is currently not supported by SpaceToBatch.",
+          op_context.input->type);
       return kTfLiteError;
   }
 #undef TF_LITE_SPACE_TO_BATCH_ND

diff --git a/tensorflow/contrib/lite/kernels/space_to_depth.cc b/tensorflow/contrib/lite/kernels/space_to_depth.cc
index aafce89..9dbe9b9 100644 (file)
--- a/tensorflow/contrib/lite/kernels/space_to_depth.cc
+++ b/tensorflow/contrib/lite/kernels/space_to_depth.cc
@@ -113,7 +113,8 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
       }
       break;
     default:
-      context->ReportError(context, "Type not currently supported.");
+      context->ReportError(context, "Type %d not currently supported.",
+                           input->type);
       return kTfLiteError;
   }
 #undef TF_LITE_SPACE_TO_DEPTH

diff --git a/tensorflow/contrib/lite/kernels/split.cc b/tensorflow/contrib/lite/kernels/split.cc
index c6b94c2..43387df 100644 (file)
--- a/tensorflow/contrib/lite/kernels/split.cc
+++ b/tensorflow/contrib/lite/kernels/split.cc
@@ -138,8 +138,9 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
       break;
     }
     default:
-      context->ReportError(context,
-                           "Only float32 and uint8 are currently supported.");
+      context->ReportError(
+          context, "Only float32 and uint8 are currently supported, got %d.",
+          op_context.input->type);
       return kTfLiteError;
   }
 #undef TF_LITE_SPLIT

diff --git a/tensorflow/contrib/lite/kernels/strided_slice.cc b/tensorflow/contrib/lite/kernels/strided_slice.cc
index 9417be3..725dd81 100644 (file)
--- a/tensorflow/contrib/lite/kernels/strided_slice.cc
+++ b/tensorflow/contrib/lite/kernels/strided_slice.cc
@@ -235,8 +235,9 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
       break;
     default:
       context->ReportError(context,
-                           "Type is currently not supported "
-                           "by StridedSlice.");
+                           "Type %d is currently not supported "
+                           "by StridedSlice.",
+                           op_context.input->type);
       return kTfLiteError;
   }
 #undef TF_LITE_STRIDED_SLICE

diff --git a/tensorflow/contrib/lite/kernels/sub.cc b/tensorflow/contrib/lite/kernels/sub.cc
index 9531ecb..d788159 100644 (file)
--- a/tensorflow/contrib/lite/kernels/sub.cc
+++ b/tensorflow/contrib/lite/kernels/sub.cc
@@ -174,8 +174,9 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
     EvalQuantized<kernel_type>(context, node, params, data, input1, input2,
                                output);
   } else {
-    context->ReportError(context,
-                         "Inputs and outputs not all float|uint8 types.");
+    context->ReportError(
+        context, "output type %d is not support, requires float|uint8 types.",
+        output->type);
     return kTfLiteError;
   }
 

diff --git a/tensorflow/contrib/lite/kernels/topk_v2.cc b/tensorflow/contrib/lite/kernels/topk_v2.cc
index 0feb42b..fb0e49c 100644 (file)
--- a/tensorflow/contrib/lite/kernels/topk_v2.cc
+++ b/tensorflow/contrib/lite/kernels/topk_v2.cc
@@ -214,7 +214,9 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
            output_values->data.i64);
       break;
     default:
-      context->ReportError(context, "Type is currently not supported by TopK.");
+      context->ReportError(context,
+                           "Type %d is currently not supported by TopK.",
+                           output_values->type);
       return kTfLiteError;
   }
 

diff --git a/tensorflow/contrib/lite/kernels/transpose.cc b/tensorflow/contrib/lite/kernels/transpose.cc
index 8316a23..800b056 100644 (file)
--- a/tensorflow/contrib/lite/kernels/transpose.cc
+++ b/tensorflow/contrib/lite/kernels/transpose.cc
@@ -136,7 +136,8 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
       break;
     default:
       context->ReportError(context,
-                           "Type is currently not supported by Transpose.");
+                           "Type %d is currently not supported by Transpose.",
+                           op_context.input->type);
       return kTfLiteError;
   }
 #undef TF_LITE_TRANSPOSE

diff --git a/tensorflow/contrib/lite/kernels/unidirectional_sequence_rnn.cc b/tensorflow/contrib/lite/kernels/unidirectional_sequence_rnn.cc
index 22c80df..8429dba 100644 (file)
--- a/tensorflow/contrib/lite/kernels/unidirectional_sequence_rnn.cc
+++ b/tensorflow/contrib/lite/kernels/unidirectional_sequence_rnn.cc
@@ -283,7 +283,8 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
                            hidden_state, output);
     }
     default:
-      context->ReportError(context, "Type not currently supported.");
+      context->ReportError(context, "Type %d not currently supported.",
+                           input_weights->type);
       return kTfLiteError;
   }
   return kTfLiteOk;