From e1f0d2ef46690157045d0509a4117de5ed0c6187 Mon Sep 17 00:00:00 2001
From: Justin Lebar <jlebar@google.com>
Date: Thu, 30 Aug 2018 21:07:17 -0700
Subject: [PATCH] [XLA] Add two new tests.

- Test operand_precision in HLO parser
- Test that HloInstruction::Clone() preserves operand_precision.

PiperOrigin-RevId: 211030698
---
 .../xla/service/hlo_instruction_test.cc        | 18 ++++++++++++++++++
 .../compiler/xla/service/hlo_parser_test.cc    |  2 +-
 2 files changed, 19 insertions(+), 1 deletion(-)

diff --git a/tensorflow/compiler/xla/service/hlo_instruction_test.cc b/tensorflow/compiler/xla/service/hlo_instruction_test.cc
index 81290ccd63d..76b0e940a65 100644
--- a/tensorflow/compiler/xla/service/hlo_instruction_test.cc
+++ b/tensorflow/compiler/xla/service/hlo_instruction_test.cc
@@ -1739,5 +1739,23 @@ TEST_F(HloInstructionTest, CloneDnumsOnCustomCall) {
       << clone->convolution_dimension_numbers().DebugString();
 }
 
+TEST_F(HloInstructionTest, PreserveOperandPrecisionOnCloneConv) {
+  constexpr char kHloString[] = R"(
+  HloModule test_module
+  ENTRY test {
+    arg0 = f32[1,2,1] parameter(0)
+    arg1 = f32[1,1,1] parameter(1)
+    ROOT conv = f32[1,2,1] convolution(arg0, arg1), window={size=1},
+      dim_labels=b0f_0io->b0f, operand_precision={high,default}
+  })";
+  TF_ASSERT_OK_AND_ASSIGN(auto module, ParseHloString(kHloString));
+  auto* conv = module->entry_computation()->root_instruction();
+
+  auto clone = conv->Clone();
+  EXPECT_THAT(clone->precision_config().operand_precision(),
+              ::testing::ElementsAre(PrecisionConfigProto::HIGH,
+                                     PrecisionConfigProto::DEFAULT));
+}
+
 }  // namespace
 }  // namespace xla
diff --git a/tensorflow/compiler/xla/service/hlo_parser_test.cc b/tensorflow/compiler/xla/service/hlo_parser_test.cc
index c25af2d7517..759789437c1 100644
--- a/tensorflow/compiler/xla/service/hlo_parser_test.cc
+++ b/tensorflow/compiler/xla/service/hlo_parser_test.cc
@@ -382,7 +382,7 @@ ENTRY %Convolve1D1Window_0.v3 (input: f32[1,2,1], filter: f32[1,1,1]) -> f32[1,2
   %input = f32[1,2,1]{2,1,0} parameter(0)
   %copy = f32[1,2,1]{2,0,1} copy(f32[1,2,1]{2,1,0} %input)
   %filter = f32[1,1,1]{2,1,0} parameter(1)
-  ROOT %convolution = f32[1,2,1]{2,0,1} convolution(f32[1,2,1]{2,0,1} %copy, f32[1,1,1]{2,1,0} %filter), window={size=1}, dim_labels=b0f_0io->b0f, feature_group_count=1
+  ROOT %convolution = f32[1,2,1]{2,0,1} convolution(f32[1,2,1]{2,0,1} %copy, f32[1,1,1]{2,1,0} %filter), window={size=1}, dim_labels=b0f_0io->b0f, feature_group_count=1, operand_precision={high,default}
 }
 
 )"