1 files changed, 47 insertions, 0 deletions
diff --git a/tensorflow/compiler/tf2xla/kernels/qr_op.cc b/tensorflow/compiler/tf2xla/kernels/qr_op.cc
new file mode 100644
index 0000000000..de9068a640
--- /dev/null
+++ b/tensorflow/compiler/tf2xla/kernels/qr_op.cc
@@ -0,0 +1,47 @@
+/* Copyright 2018 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/tf2xla/lib/qr.h"
+#include "tensorflow/compiler/tf2xla/xla_op_kernel.h"
+#include "tensorflow/compiler/tf2xla/xla_op_registry.h"
+
+namespace tensorflow {
+namespace {
+
+class QROp : public XlaOpKernel {
+ public:
+  explicit QROp(OpKernelConstruction* ctx) : XlaOpKernel(ctx) {
+    bool full_matrices;
+    OP_REQUIRES_OK(ctx, ctx->GetAttr("full_matrices", &full_matrices));
+    OP_REQUIRES(
+        ctx, full_matrices,
+        errors::Unimplemented("full_matrices=False case of QR decomposition is "
+                              "not implemented in TF/XLA"));
+  }
+  void Compile(XlaOpKernelContext* ctx) override {
+    auto result = QRDecomposition(ctx->Input(0));
+    if (!result.ok()) {
+      ctx->SetStatus(result.status());
+      return;
+    }
+    ctx->SetOutput(0, result.ValueOrDie().q);
+    ctx->SetOutput(1, result.ValueOrDie().r);
+  }
+};
+
+REGISTER_XLA_OP(Name("Qr").TypeConstraint("T", kFloatTypes), QROp);
+
+}  // namespace
+}  // namespace tensorflow