// fingerprints' saved_model_checksums.
  EXPECT_GT(fingerprint_def.saved_model_checksum(), 0);
  EXPECT_GT(fingerprint_def2.saved_model_checksum(), 0);
  EXPECT_EQ(fingerprint_def.graph_def_program_hash(),
            fingerprint_def2.graph_def_program_hash());
  EXPECT_EQ(fingerprint_def.signature_def_hash(),
            fingerprint_def2.signature_def_hash());
  EXPECT_EQ(fingerprint_def.saved_object_graph_hash(),

  TF_EXPECT_OK(internal::FlattenSignature(value, &flattened));
  EXPECT_EQ(flattened.size(), 0);
}

TEST(SignatureFlatteningTest, SingleArgInputSignature) {
  std::vector<const TensorSpecProto*> flattened;
  StructuredValue value = testing::SingleArgInputSignature();
  TF_EXPECT_OK(internal::FlattenSignature(value, &flattened));
  EXPECT_EQ(flattened.size(), 1);
  EXPECT_TRUE(TensorSpecsAreEqual(*flattened[0],

      "/tensorflow/core/tf2xla/v1/mlir_failed_xla_legalize_tf_pass_count");

  auto status = BuildAndRunPipeline(kMlirIllegalOpStr, legalizeTFPasses());

  EXPECT_TRUE(status);
  EXPECT_EQ(legalize_failure_count.Read("tf.DoesntExist", "Unknown"), 1);
}

TEST(XlaLegalizeTest, LegalOp) {
  // We expect legalization to fail for legal op with dynamic shapes:
  static constexpr char kMlirLegalOpStr[] = R"(

  EXPECT_EQ(Explain(add.node(), NodeWith(Inputs())),
            "\nexpected 0 inputs but node has 2");
  EXPECT_EQ(
      Explain(add.node(), NodeWith(Inputs(Out(NodeWith(Name("blah"))), _))),
      "\ninput 0 does not match expected:\nname: blah, \nsource does not match "
      "expected name: blah\n\t\nexpected name blah but found placeholder_a");
  EXPECT_EQ(

  EXPECT_EQ(revived_tensor->Type(), expected.dtype());
  EXPECT_EQ(revived_tensor->NumElements(), expected.NumElements());
  EXPECT_EQ(revived_tensor->NumDims(), expected.dims());
  for (int i = 0; i < expected.dims(); ++i) {
    EXPECT_EQ(revived_tensor->Dim(i), expected.dim_size(i));
  }

  testing::CheckBufferDataIsEqual(expected.dtype(), expected.NumElements(),

  string upper_snake;
};

void TestSingleVariation(const string &str, Variations expected,
                         char delimiter = '_') {
  EXPECT_EQ(expected.lower_camel, toLowerCamel(str, delimiter));
  EXPECT_EQ(expected.lower_snake, toLowerSnake(str, delimiter));
  EXPECT_EQ(expected.upper_camel, toUpperCamel(str, delimiter));
  EXPECT_EQ(expected.upper_snake, toUpperSnake(str, delimiter));
}

Christian Wansart <******@****.***> 1573139799 +0100

  EXPECT_EQ(tensor.dims(), 1);
  EXPECT_EQ(tensor.dtype(), dtype);
  absl::Span<const typename TypeParam::type> tensor_view(
      reinterpret_cast<typename TypeParam::type*>(tensor.data()), value.size());
  EXPECT_EQ(tensor_view[0], 42);
  EXPECT_EQ(tensor_view[1], 100);
  EXPECT_EQ(tensor_view[2], 0);
  EXPECT_EQ(tensor_view[3], 1);
  EXPECT_EQ(tensor_view[4], 4);

Christian Wansart <******@****.***> 1573139799 +0100

                  .ok());
  ASSERT_TRUE(worker_server2->Start().ok());

  TFE_ContextSetServerDef(context.get(), 0, serialized.data(),
                          serialized.size(), status.get());
  EXPECT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  BasicTestsForTwoDevices(context.get(),
                          "/job:worker/replica:0/task:1/device:CPU:0",