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+//===- TensorOps.h - Linalg dialect TensorOps operation definition --------===//
+//
+// Copyright 2019 The MLIR Authors.
+//
+// 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 LINALG3_TENSOROPS_H_
+#define LINALG3_TENSOROPS_H_
+
+#include "linalg2/TensorOps.h"
+
+namespace linalg {
+
+///
+/// Ideally all these functions would go in an Analysis but as long as
+/// TensorContractionBase is templated, they need to remain close enough.
+///
+
+/// Takes a `tensorContraction` and a returns an AffineMap that can be used to
+/// map ranges to enclosing loops for all the operands' ranges.
+template <class ConcreteOp>
+mlir::AffineMap operandRangesToLoopsMap(
+    linalg::TensorContractionBase<ConcreteOp> &tensorContraction);
+
+/// Takes a `tensorContraction` and returns the ranges of all its operands.
+/// When an operand comes from a ViewOp, things are simple:
+///   just traverse the indexings and get all the ranges
+///     (i.e. drop the rank-reducing indices).
+/// In the case of a SliceOp, things are more involved because we need to handle
+/// potential rank-reductions.
+/// This function abstracts this complexity away and returns all the ranges.
+template <class ConcreteOp>
+llvm::SmallVector<mlir::Value *, 8>
+getRanges(linalg::TensorContractionBase<ConcreteOp> &tensorContraction);
+
+} // namespace linalg
+
+/// The TensorOp-inl.h inclusion pattern is chosen to allow gradual extension of
+/// TensorOps by adding implementations as they are needed in the appropriate
+/// step in the tutorial.
+#include "linalg3/TensorOps-inl.h"
+
+#endif // LINALG3_TENSOROPS_H_