// size.  So we first use a Placeholder to placate the shape refiner, and
  // later replace it with a bogus constant.
  Output size_placeholder =
      ops::Placeholder(root.WithOpName("size_placeholder"), DT_INT32);
  Output slice =
      ops::Slice(root.WithOpName("slice"), input, begin, size_placeholder);

  Output size = ops::Const(root.WithOpName("size"), {-8, 500});
  TF_ASSERT_OK(root.graph()->UpdateEdge(/*new_src=*/size.node(),

// RUN: tf-opt -tf-init-text-file-to-import-test %s | FileCheck %s

// Tests that the tf.InitializeTableFromTextFileV2 op are inlined.

func.func @init_all_tables() {
  %cst = arith.constant dense<"%FILE_PLACEHOLDER"> : tensor<!tf_type.string>
  %0 = "tf.HashTableV2"() {container = "", device = "", key_dtype = !tf_type.string, shared_name = "hash_table_/tmp/vocab.txt_-2_-1", use_node_name_sharing = false, value_dtype = i64} : () -> tensor<!tf_type.resource>

      if (!matchPattern(op.getOperation(), m_Constant(&attr))) {
        continue;
      }

      ArrayRef<StringRef> values = attr.getRawStringData();
      if (values.size() != 1 || values[0] != "%FILE_PLACEHOLDER") {
        continue;
      }

      op.setValueAttr(DenseStringElementsAttr::get(shaped_type, {filename}));
    }
  }

  // Run the lowering pass.
  PassManager pm(context);

//===--------------------------------------------------------------------===//

// CHECK-LABEL: func @placeholderattr
func.func @placeholderattr() -> ()
// CHECK:    attributes {some_placeholder = #tf_type.placeholder<"foo">} {
    attributes {some_placeholder = #tf_type.placeholder<"foo">} {
  func.return
}
//===--------------------------------------------------------------------===//
//  Test TF operations (tf.*)