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62 Commits

Author SHA1 Message Date
Andy Ly c340367702 Add canonicalization for unpacking and repacking the same tuple (e.g. tuple -> get_tuple_element -> tuple). 
These unpacking and repacking of tuples may be generated when modifying tuple arguments or results.

PiperOrigin-RevId: 325162694
 2020-08-05 21:38:02 -07:00
Mehdi Amini cd01bb4c4e More cleanup in mlir-hlo to prepare for the standalone build 
Shuffle files around, use TableGen to register passes, and introduce
a `mlir-hlo-opt.cpp` file to hold the main entry point of the -opt tool
and stop relying on static registration for dialect/passes.

PiperOrigin-RevId: 323674455
 2020-08-03 19:28:00 -07:00
Thomas Joerg 739758f9cc Integrate LLVM at llvm/llvm-project@eed333149d 
Updates LLVM usage to match
[eed333149d17](https://github.com/llvm/llvm-project/commit/eed333149d17)

PiperOrigin-RevId: 323354988
 2020-08-03 19:27:25 -07:00
Tres Popp 63d62b7952 Change cast to dyn_cast in hlo::ReshapeOp's verification. 
With cast, a failing verification results in an assertion error rather than returning a failing status.

PiperOrigin-RevId: 322317937
 2020-07-30 22:34:36 +00:00
Stephan Herhut 7a6adc6a84 Add canonicalization patterns for dynamic_broadcast_in_dim where the target shape is the shape of the operand. 
PiperOrigin-RevId: 321312182
 2020-07-30 22:34:06 +00:00
Robert Suderman 06ae59074f Fold xla iota across a 1-length dimension into a zero value 
Iota across length-1 is just a constant. Fold into it.

PiperOrigin-RevId: 320443468
 2020-07-30 22:33:43 +00:00
Uday Bondhugula de0578b4f9 PR #40745: [MLIR] Add constant folder for xla_hlo.broadcast_in_dim op 
Imported from GitHub PR https://github.com/tensorflow/tensorflow/pull/40745

Fold broadcast_in_dim op if the operand is the result of a tensor splat.
Copybara import of the project:

--
26c9f631448b8d6ffd20ece39ea8d4132b5550c7 by Uday Bondhugula <uday@polymagelabs.com>:

[MLIR] Add constant folder for xla_hlo.broadcast_in_dim op

Fold broadcast_in_dim op if the operand is the result of a tensor
splat.

COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/tensorflow/pull/40745 from polymage-labs:broadcast_in_dim_fold 26c9f631448b8d6ffd20ece39ea8d4132b5550c7
PiperOrigin-RevId: 320365164
 2020-07-30 22:33:34 +00:00
Mehdi Amini 506ddd9c4a Cleanup build rule names in compiler/mlir/hlo to remove the redundant/obsolete xla_ prefix 
PiperOrigin-RevId: 320320140
 2020-07-30 22:33:29 +00:00
Mehdi Amini a575636862 Rename XlaHloDialect class into MhloDialect following the recent dialect namespace renaming 
PiperOrigin-RevId: 320213526
 2020-07-30 22:33:20 +00:00
Robert Suderman e1651b6090 Canonicalize multidimensional iota to use broadcast 
There is no reason to have a multidimensional iota for codegen.
This should be canonicalized to a single dimensional iota followed
by a broadcast. Changing iota to on a single dimension  and a broadcast
substantially simplifies implementing iota operations.

PiperOrigin-RevId: 320095470
 2020-07-30 22:32:54 +00:00
Mehdi Amini 8900222fed Rename `xla_hlo` dialect to `mhlo` 
This is part of the current refactoring of the HLO related dialect.
`xla_hlo` will be reintroduced in a new form later.

PiperOrigin-RevId: 319916753
 2020-07-30 22:32:50 +00:00
Mehdi Amini fcf3df1541 Move the HLO/LHLO dialects to a new directory: tensorflow/compiler/mlir/hlo 
We're preparing to restructure the MLIR HLO ecosystem with 5 dialects:

- chlo: client dialect with explicit broadcast and multiple composite operations
- mhlo: hlo with dynamic shape, decouple from XLA for evolution purpose
- lmhlo: same as above, but after buffer assignment.
- xla_hlo: mapping 1:1 to the XLA HloInstruction class.
- xla_lhlo: same as above, but after buffer assignment.

The first three dialects are intended to live in the new tensorflow/compiler/mlir/hlo
path, the latter two will be created in tensorflow/compiler/mlir/xla.

This patch only moves the directory, will followup with other transformations and tests.

The structure of the new directory follows: https://llvm.discourse.group/t/rfc-canonical-file-paths-to-dialects/621 as we intend to make it a standalone buildable component (see also https://github.com/google/mlir-npcomp as another example).

PiperOrigin-RevId: 319273229
 2020-07-30 22:32:32 +00:00