[XLA] Fix the interpreter to use the dynamic dimension inference when run separately

PiperOrigin-RevId: 297875268
Change-Id: I97e735cfd57ad74122469d29afa606e922f566bd

tensorflow/compiler/xla/service/interpreter/compiler.cc

@@ -104,9 +104,8 @@ StatusOr<std::unique_ptr<Executable>> InterpreterCompiler::RunBackend(
 
   VLOG(1) << "Run backend " << hlo_module->name();
 
-  // Typically you would visit the HLO graph, building up a compiled equivalent
-  // In this case we are using an HloEvaluator at execution time, so we don't
-  // need to compile anything
+  TF_ASSIGN_OR_RETURN(DynamicDimensionInference dynamic_dimension_inference,
+                      DynamicDimensionInference::Run(hlo_module.get()));
 
   auto evaluator = absl::make_unique<HloEvaluator>();
   evaluator->set_use_fast_path(
@@ -115,8 +114,9 @@ StatusOr<std::unique_ptr<Executable>> InterpreterCompiler::RunBackend(
 
   // Create executable from only the Hlo module.
   std::unique_ptr<Executable> executable =
-      absl::make_unique<InterpreterExecutable>(std::move(hlo_module),
-                                               std::move(evaluator));
+      absl::make_unique<InterpreterExecutable>(
+          std::move(hlo_module), std::move(evaluator),
+          std::move(dynamic_dimension_inference));
 
   return std::move(executable);
 }

tensorflow/compiler/xla/service/interpreter/executable.cc

@@ -39,10 +39,17 @@ namespace interpreter {
 
 InterpreterExecutable::InterpreterExecutable(
     std::unique_ptr<HloModule> hlo_module,
-    std::unique_ptr<HloEvaluator> evaluator)
+    std::unique_ptr<HloEvaluator> evaluator,
+    absl::optional<DynamicDimensionInference> dynamic_dymension_inference)
     : Executable(std::move(hlo_module), /*hlo_profile_printer_data=*/nullptr,
                  /*hlo_profile_index_map=*/nullptr),
-      evaluator_(std::move(evaluator)) {}
+      evaluator_(std::move(evaluator)),
+      dynamic_dimension_inference_(std::move(dynamic_dymension_inference)) {
+  if (dynamic_dimension_inference_.has_value()) {
+    evaluator_->set_dynamic_dimension_inference(
+        &dynamic_dimension_inference_.value());
+  }
+}
 
 InterpreterExecutable::~InterpreterExecutable() {}
 

tensorflow/compiler/xla/service/interpreter/executable.h

@@ -42,8 +42,10 @@ namespace interpreter {
 // buffer allocation. Refer to interpreter/README.md for more.
 class InterpreterExecutable : public Executable {
  public:
-  InterpreterExecutable(std::unique_ptr<HloModule> hlo_module,
-                        std::unique_ptr<HloEvaluator> evaluator);
+  InterpreterExecutable(
+      std::unique_ptr<HloModule> hlo_module,
+      std::unique_ptr<HloEvaluator> evaluator,
+      absl::optional<DynamicDimensionInference> dynamic_dymension_inference);
   ~InterpreterExecutable() override;
 
   StatusOr<ExecutionOutput> ExecuteAsyncOnStream(
@@ -60,6 +62,7 @@ class InterpreterExecutable : public Executable {
   mutable tensorflow::mutex evaluator_lock_;
 
  private:
+  absl::optional<DynamicDimensionInference> dynamic_dimension_inference_;
   TF_DISALLOW_COPY_AND_ASSIGN(InterpreterExecutable);
 };
 

tensorflow/compiler/xla/tests/BUILD

@@ -2513,6 +2513,18 @@ xla_test(
     ],
 )
 
+xla_test(
+    name = "get_dimension_size_test",
+    srcs = ["get_dimension_size_test.cc"],
+    deps = [
+        ":hlo_test_base",
+        ":test_macros_header",
+        ":xla_internal_test_main",  # fixdeps: keep
+        "//tensorflow/compiler/xla:debug_options_flags",
+        "//tensorflow/compiler/xla:test",
+    ],
+)
+
 xla_test(
     name = "triangular_solve_test",
     srcs = ["triangular_solve_test.cc"],

tensorflow/compiler/xla/tests/get_dimension_size_test.cc

@@ -0,0 +1,48 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/compiler/xla/debug_options_flags.h"
+#include "tensorflow/compiler/xla/test.h"
+#include "tensorflow/compiler/xla/tests/hlo_test_base.h"
+#include "tensorflow/compiler/xla/tests/test_macros.h"
+
+namespace xla {
+namespace {
+
+class GetDimensionSizeTest : public HloTestBase {};
+
+// Test that the interpreter can correctly compute get_dimension_size.
+TEST_F(GetDimensionSizeTest, DoIt) {
+  const char* const kModuleStr = R"(
+HloModule a_inference_call_110__.55
+
+ENTRY %a_inference_call_110__.55 (arg0.1: f32[1,8], arg1.2: f32[8], arg2.3: f32[8]) -> s32[] {
+  %constant.37 = f32[] constant(1e-12)
+  %broadcast.38 = f32[1,1]{1,0} broadcast(f32[] %constant.37), dimensions={}
+  %arg0.1 = f32[1,8]{1,0} parameter(0), parameter_replication={false}
+  %reshape.4 = f32[1,8]{1,0} reshape(f32[1,8]{1,0} %arg0.1)
+  %convert.5 = f32[1,8]{1,0} convert(f32[1,8]{1,0} %reshape.4)
+  %constant.6 = f32[] constant(0)
+  %convert.7 = f32[] convert(f32[] %constant.6)
+  ROOT %get-dimension-size.13 = s32[] get-dimension-size(f32[1,8]{1,0} %convert.5), dimensions={1}
+}
+)";
+  TF_ASSERT_OK_AND_ASSIGN(auto module,
+                          ParseAndReturnVerifiedModule(kModuleStr));
+  EXPECT_TRUE(RunAndCompare(std::move(module), ErrorSpec{0.01, 0.01}));
+}
+
+}  // anonymous namespace
+}  // namespace xla