Adds {batch_}matrix_solve and {batch_}triangular_matrix_solve ops.

Change: 112289410

1 files changed, 109 insertions, 0 deletions

diff --git a/tensorflow/core/kernels/matrix_triangular_solve_op.cc b/tensorflow/core/kernels/matrix_triangular_solve_op.cc
new file mode 100644
index 0000000000..c0e362a32c
--- /dev/null
+++ b/tensorflow/core/kernels/matrix_triangular_solve_op.cc
@@ -0,0 +1,109 @@
+/* Copyright 2015 Google Inc. 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.
+==============================================================================*/
+
+// See docs in ../ops/linalg_ops.cc.
+#include <cmath>
+
+#include "third_party/eigen3/Eigen/Core"
+#include "tensorflow/core/framework/kernel_def_builder.h"
+#include "tensorflow/core/framework/op_kernel.h"
+#include "tensorflow/core/kernels/binary_linalg_ops_common.h"
+#include "tensorflow/core/lib/core/errors.h"
+#include "tensorflow/core/platform/logging.h"
+#include "tensorflow/core/platform/macros.h"
+#include "tensorflow/core/platform/port.h"
+#include "tensorflow/core/public/tensor_shape.h"
+
+namespace tensorflow {
+
+template <class Scalar, bool SupportsBatchOperationT>
+class MatrixTriangularSolveOp
+    : public BinaryLinearAlgebraOp<Scalar, SupportsBatchOperationT> {
+ public:
+  explicit MatrixTriangularSolveOp(OpKernelConstruction* context)
+      : BinaryLinearAlgebraOp<Scalar, SupportsBatchOperationT>(context),
+        lower_(true) {
+    OP_REQUIRES_OK(context, context->GetAttr("lower", &lower_));
+  }
+  ~MatrixTriangularSolveOp() override {}
+
+  TensorShape GetOutputMatrixShape(
+      const TensorShape& input_matrix_shape,
+      const TensorShape& rhs_matrix_shape) override {
+    CHECK_EQ(input_matrix_shape.dims(), rhs_matrix_shape.dims());
+    TensorShape output_matrix_shape = input_matrix_shape;
+    output_matrix_shape.set_dim(
+        output_matrix_shape.dims() - 1,
+        rhs_matrix_shape.dim_size(output_matrix_shape.dims() - 1));
+    return output_matrix_shape;
+  }
+
+  int64 GetCostPerUnit(const TensorShape& input_matrix_shape,
+                       const TensorShape& rhs_matrix_shape) override {
+    const int64 rows = input_matrix_shape.dim_size(0);
+    const int64 rhss = rhs_matrix_shape.dim_size(1);
+    if (rows > (1LL << 20)) {
+      // A big number to cap the cost in case overflow.
+      return kint32max;
+    } else {
+      return rows * rows * rhss;
+    }
+  }
+
+  using typename BinaryLinearAlgebraOp<Scalar,
+                                       SupportsBatchOperationT>::MatrixMap;
+  using typename BinaryLinearAlgebraOp<Scalar,
+                                       SupportsBatchOperationT>::ConstMatrixMap;
+
+  void ComputeMatrix(OpKernelContext* context, const ConstMatrixMap& matrix,
+                     const ConstMatrixMap& rhs, MatrixMap* output) override {
+    OP_REQUIRES(context, matrix.rows() == matrix.cols(),
+                errors::InvalidArgument("Input matrix must be square."));
+    OP_REQUIRES(
+        context, matrix.rows() == rhs.rows(),
+        errors::InvalidArgument("Input matrix and rhs are incompatible."));
+    if (matrix.rows() == 0) {
+      // To be consistent with the MatrixInverse op, we define the solution for
+      // an empty set of equation is the empty matrix.
+      return;
+    }
+    const Scalar min_abs_pivot = matrix.diagonal().cwiseAbs().minCoeff();
+    OP_REQUIRES(context, min_abs_pivot > Scalar(0),
+                errors::InvalidArgument("Input matrix is not invertible."));
+    if (lower_) {
+      output->noalias() =
+          matrix.template triangularView<Eigen::Lower>().solve(rhs);
+    } else {
+      output->noalias() =
+          matrix.template triangularView<Eigen::Upper>().solve(rhs);
+    }
+  }
+
+ private:
+  bool lower_;
+
+  TF_DISALLOW_COPY_AND_ASSIGN(MatrixTriangularSolveOp);
+};
+
+REGISTER_BINARY_LINALG_OP("MatrixTriangularSolve",
+                          (MatrixTriangularSolveOp<float, false>), float);
+REGISTER_BINARY_LINALG_OP("MatrixTriangularSolve",
+                          (MatrixTriangularSolveOp<double, false>), double);
+REGISTER_BINARY_LINALG_OP("BatchMatrixTriangularSolve",
+                          (MatrixTriangularSolveOp<float, true>), float);
+REGISTER_BINARY_LINALG_OP("BatchMatrixTriangularSolve",
+                          (MatrixTriangularSolveOp<double, true>), double);
+
+}  // namespace tensorflow