From 919c8f27384de150a806d0b8d83e235f1f2f803d Mon Sep 17 00:00:00 2001
From: Michael Gester <mgester@google.com>
Date: Tue, 29 Dec 2020 16:19:24 -0800
Subject: [PATCH] Added error message for unsupported uninitialized resource
 variables

Previously, we ran into a generic error message when encountering unsupported
uninitialized resource variables so it wasn't clear what the actual problem was.

PiperOrigin-RevId: 349483176
Change-Id: Id3819e7c7802d2b2decdd63c8292de88fadcd0ae
---
 .../compiler/mlir/tensorflow/utils/compile_mlir_util.cc     | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/tensorflow/compiler/mlir/tensorflow/utils/compile_mlir_util.cc b/tensorflow/compiler/mlir/tensorflow/utils/compile_mlir_util.cc
index 6b09455d9c0..26741f30ed8 100644
--- a/tensorflow/compiler/mlir/tensorflow/utils/compile_mlir_util.cc
+++ b/tensorflow/compiler/mlir/tensorflow/utils/compile_mlir_util.cc
@@ -529,6 +529,12 @@ static StatusOr<std::vector<int>> RewriteWithArgs(
     mlir::BlockArgument mlir_arg = main_fn.getArgument(idx);
     if (xla_arg.kind == XlaArgument::kResource) {
       mlir::Type element_type;
+      if (xla_arg.type == DT_INVALID) {
+        return errors::Unimplemented(absl::StrCat(
+            "Argument ", idx,
+            " is an uninitialized resource variable which is currently"
+            " unsupported in the MLIR-based TPU bridge"));
+      }
       TF_RETURN_IF_ERROR(ConvertDataType(xla_arg.type, builder, &element_type));
       TF_ASSIGN_OR_RETURN(TensorShape arg_shape,
                           GetTensorShapeFromXlaArgument(xla_arg));