Move shape inference pass description to ODS

This moves the description of the TF shape inference pass to ODS. Generating the documentation for the pass in a follow up.

PiperOrigin-RevId: 344145233
Change-Id: Ic435f441a563c39060abc2d5c418b9f574335700

tensorflow/compiler/mlir/tensorflow/BUILD

@@ -825,6 +825,22 @@ cc_library(
     ],
 )
 
+gentbl(
+    name = "tf_pass_inc_gen",
+    compatible_with = get_compatible_with_cloud(),
+    tbl_outs = [
+        (
+            "-gen-pass-decls -name TensorFlow",
+            "transforms/tf_passes.h.inc",
+        ),
+    ],
+    tblgen = "@llvm-project//mlir:mlir-tblgen",
+    td_file = "transforms/tf_passes.td",
+    td_srcs = [
+        "@llvm-project//mlir:PassBaseTdFiles",
+    ],
+)
+
 cc_library(
     name = "tensorflow_passes",
     srcs = [
@@ -920,6 +936,8 @@ cc_library(
     includes = ["include"],
     textual_hdrs = [
         "ir/tf_ops_helpers.inc",
+        "transforms/passes_detail.h",
+        "transforms/tf_passes.h.inc",
     ],
     deps = [
         ":attribute_utils",
@@ -942,6 +960,7 @@ cc_library(
         ":tensorflow_optimize_inc_gen",
         ":tensorflow_types",
         ":tf_data_optimization",
+        ":tf_pass_inc_gen",
         ":tpu_rewrite_device_util",
         ":translate_utils",
         ":unroll_batch_matmul_pass",

tensorflow/compiler/mlir/tensorflow/transforms/passes.h

@@ -193,8 +193,6 @@ std::unique_ptr<FunctionPass> CreateClusterTFOpsByHostPass();
 }  // namespace TF
 
 namespace tf_executor {
-class GraphOp;
-
 // Returns a pass that folds switch nodes with constant predicates.
 std::unique_ptr<OperationPass<FuncOp>> CreateSwitchFoldPass();
 
@@ -221,14 +219,10 @@ CreateTFExecutorTPUV1IslandInliningPass();
 // Creates a pass to prune tf_executor.graph from dead nodes.
 std::unique_ptr<OperationPass<FuncOp>> CreateTFExecutorGraphPruningPass();
 
-// Prunes unreachable operations of a tf_executor.graph operation.
-void PruneGraph(GraphOp graph);
-
 // Sink `tf.Const` operations in the LaunchOp region using them. This is
 // performed in order to limit the number of values implicitly captured in this
 // region before outlining.
 std::unique_ptr<OperationPass<FuncOp>> CreateTFExecutorConstantSinkingPass();
-
 }  // namespace tf_executor
 
 namespace TFDevice {

tensorflow/compiler/mlir/tensorflow/transforms/passes_detail.h

@@ -0,0 +1,31 @@
+/* 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.
+==============================================================================*/
+
+#ifndef TENSORFLOW_COMPILER_MLIR_TENSORFLOW_TRANSFORMS_TF_PASS_DETAIL_H_
+#define TENSORFLOW_COMPILER_MLIR_TENSORFLOW_TRANSFORMS_TF_PASS_DETAIL_H_
+
+#include "mlir/IR/Dialect.h"
+#include "mlir/Pass/Pass.h"
+
+namespace mlir {
+namespace TF {
+
+#define GEN_PASS_CLASSES
+#include "tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.h.inc"
+
+}  // namespace TF
+}  // namespace mlir
+
+#endif  // TENSORFLOW_COMPILER_MLIR_TENSORFLOW_TRANSFORMS_TF_PASS_DETAIL_H_

tensorflow/compiler/mlir/tensorflow/transforms/shape_inference.h

@@ -35,8 +35,6 @@ LogicalResult InferModuleShape(ModuleOp module, int64_t max_iterations = 10);
 // If arg_shapes are empty, then argument shapes will be left unchanged.
 // Note: This affects the entire module, and changes are not just scoped to the
 // function being inferred.
-// TODO(b/154065712): Remove propagate_caller_callee_constants once using
-// SCCP pass instead.
 LogicalResult InferShapeForFunction(FuncOp func,
                                     ArrayRef<ArrayRef<int64_t>> arg_shapes,
                                     int64_t graph_version,

tensorflow/compiler/mlir/tensorflow/transforms/shape_inference_pass.cc

@@ -17,11 +17,10 @@ limitations under the License.
 #include "mlir/Pass/Pass.h"  // from @llvm-project
 #include "mlir/Support/LLVM.h"  // from @llvm-project
 #include "mlir/Support/LogicalResult.h"  // from @llvm-project
+#include "tensorflow/compiler/mlir/tensorflow/transforms/passes_detail.h"
 #include "tensorflow/compiler/mlir/tensorflow/transforms/shape_inference.h"
 #include "tensorflow/core/framework/shape_inference.h"
 
-#define DEBUG_TYPE "tf-shape-inference"
-
 namespace mlir {
 namespace TF {
 
@@ -29,25 +28,12 @@ namespace {
 
 // This transformation pass propagate shapes on the TensorFlow graph.
 // It is a ModulePass in order to be able to change function types.
-class ShapeInference
-    : public PassWrapper<ShapeInference, OperationPass<ModuleOp>> {
+class ShapeInference : public TensorFlowShapeInferencePassBase<ShapeInference> {
  public:
-  ShapeInference() = default;
-  ShapeInference(const ShapeInference &) {}
-  explicit ShapeInference(int64_t max_iterations) {
-    max_iterations_ = max_iterations;
-  }
   void runOnOperation() override {
-    if (failed(InferModuleShape(getOperation(), max_iterations_))) {
+    if (failed(InferModuleShape(getOperation(), max_iterations_)))
       return signalPassFailure();
-    }
   }
-
- private:
-  Option<int64_t> max_iterations_{
-      *this, "max-iterations",
-      llvm::cl::desc("Maximum shape inference iterations."),
-      llvm::cl::init(10)};
 };
 
 PassRegistration<ShapeInference> pass(

tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.td

@@ -0,0 +1,30 @@
+/* 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 "mlir/Pass/PassBase.td"
+
+// TF dialect passes.
+
+def TensorFlowShapeInferencePass : Pass<"tf-shape-inference", "ModuleOp"> {
+  let summary = "Simple Shape Inference on TensorFlow Dialect";
+  // TODO(jpienaar): Write `description`.
+
+  let constructor = "CreateTFShapeInferencePass()";
+
+  let options = [
+    Option<"max_iterations_", "max-iterations", "int64_t", /*default=*/"10",
+           "Maximum shape inference iterations">
+  ];
+}