Jacques Pienaar 7a6107bf83 Add missing word
Only noticed post submit.

PiperOrigin-RevId: 335519839
Change-Id: Ib00fd8476fb7080e071bf688d4cc15ec33bdf71f
2020-10-05 16:10:24 -07:00

1.3 KiB

MLIR dialects and utilities for TensorFlow, TensorFlow Lite and XLA.

This module contains the MLIR (Multi-Level Intermediate Representation) dialects and utilities for

  1. TensorFlow
  2. XLA
  3. TF Lite

See MLIR's website for complete documentation.

Getting started

Building dialects and utilities here follow the standard approach using bazel as the rest of TensorFlow.

Using local LLVM repo

To develop across MLIR core and TensorFlow, it is useful to override the repo to use a local version instead of fetching from head. This can be achieved as below but note, the BUILD files are not automatically generated from or CMake used, so if your change requires a BUILD file change (or you are using a different version of LLVM than set in tensorflow/workspace.bzl's LLVM_COMMIT) then manual BUILD file changes may be required.

LLVM_SRC=...

# Create basic workspace file
echo 'workspace(name = "llvm-project")' > $LLVM_SRC/WORKSPACE
# and copy over the bazel BUILD files.
cp third_party/llvm/llvm.autogenerated.BUILD $LLVM_SRC/llvm/BUILD
cp third_party/mlir/BUILD $LLVM_SRC/mlir
cp third_party/mlir/test.BUILD $LLVM_SRC/mlir/test/BUILD

bazel build --override_repository=llvm-project=$LLVM_SRC \
  -c opt tensorflow/compiler/mlir:tf-opt