colin
/
mlir-hlo
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Integrate LLVM at llvm/llvm-project@37e1458128 

Updates LLVM usage to match
[37e145812855](https://github.com/llvm/llvm-project/commit/37e145812855)

PiperOrigin-RevId: 370020161
This commit is contained in:
A. Unique TensorFlower 2021-04-22 22:55:48 -07:00 committed by TensorFlow MLIR Team
parent 49df46893c
commit 890a79641e
5 changed files with 7 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
WORKSPACE
View File

@ -15,9 +15,9 @@
load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
LLVM_COMMIT = "2f69975683f5b6ea7df79f335f96b889a4bddecd"
LLVM_COMMIT = "37e1458128556ae153313cdb7e085907dff5bb8b"
LLVM_SHA256 = "9949f5055db2b59306fb2be23487c782df4870329652bbd98d6e5a65e4600b70"
LLVM_SHA256 = "e71a7ebad47c739e0aac8c8f8aded78bdcccf3fdaf1ec04a2731554b997b758b"
LLVM_BAZEL_TAG = "llvm-project-{commit}".format(commit = LLVM_COMMIT)

2
build_tools/llvm_version.txt
View File

@ -1,2 +1,2 @@
2f69975683f5b6ea7df79f335f96b889a4bddecd
37e1458128556ae153313cdb7e085907dff5bb8b

1
lib/Dialect/mhlo/transforms/mhlo_control_flow_to_scf.cc
View File

@ -14,6 +14,7 @@ limitations under the License.
==============================================================================*/
#include "llvm/Support/Casting.h"
#include "llvm/Support/Debug.h"
#include "mlir-hlo/Dialect/mhlo/IR/hlo_ops.h"
#include "mlir-hlo/Dialect/mhlo/transforms/passes.h"
#include "mlir/Dialect/SCF/SCF.h"

1
lib/Dialect/mhlo/transforms/mhlo_fusion.cc
View File

@ -19,6 +19,7 @@ limitations under the License.
#include <vector>
#include "llvm/ADT/EquivalenceClasses.h"
#include "llvm/Support/Debug.h"
#include "mlir-hlo/Dialect/mhlo/IR/hlo_ops.h"
#include "mlir-hlo/utils/cycle_detector.h"
#include "mlir/Dialect/StandardOps/IR/Ops.h" // TF:llvm-project

3
tests/chlo_legalize_to_hlo_broadcasts.mlir
View File

@ -134,10 +134,11 @@ func @selectv2_broadcast_all(%arg0: tensor<8x1x1xi1>, %arg1: tensor<1x8x1xi32>,
func @selectv2_dynamic_ranked(%arg0: tensor<1xi1>, %arg1: tensor<2x?x8xi32>, %arg2: tensor<2x8x8xi32>) -> tensor<2x?x8xi32> {
// CHECK-NEXT: %[[SHAPE0:.*]] = shape.const_shape [1] : tensor<?xindex>
// CHECK-NEXT: %[[SHAPE2:.*]] = shape.const_shape [2, 8, 8] : tensor<?xindex>
// CHECK-NEXT: %[[PARTIALLY_FOLDED_BCAST:.*]] = constant dense<[2, 8, 8]> : tensor<3xindex>
// CHECK-NEXT: %[[SHAPE1:.*]] = shape.shape_of %arg1 : tensor<2x?x8xi32> -> tensor<?xindex>
// CHECK-NEXT: %[[CSTR:.*]] = shape.cstr_broadcastable %[[SHAPE1]], %[[SHAPE0]], %[[SHAPE2]] : tensor<?xindex>, tensor<?xindex>, tensor<?xindex>
// CHECK-NEXT: %[[ASSUME:.*]] = shape.assuming %[[CSTR]] -> (tensor<2x?x8xi32>) {
// CHECK-NEXT: %[[BCST_V:.*]] = shape.broadcast %[[SHAPE1]], %[[SHAPE0]], %[[SHAPE2]] : tensor<?xindex>, tensor<?xindex>, tensor<?xindex> -> tensor<?xindex>
// CHECK-NEXT: %[[BCST_V:.*]] = shape.broadcast %[[SHAPE1]], %[[PARTIALLY_FOLDED_BCAST]] : tensor<?xindex>, tensor<3xindex> -> tensor<?xindex>
// CHECK-NEXT: %[[BCST:.*]] = tensor.cast %[[BCST_V]] : tensor<?xindex> to tensor<3xindex>
// CHECK-NEXT: %[[BCST0:.*]] = "mhlo.dynamic_broadcast_in_dim"(%arg0, %[[BCST]]) {broadcast_dimensions = dense<2> : tensor<1xi64>} : (tensor<1xi1>, tensor<3xindex>) -> tensor<2x?x8xi1>
// CHECK-NEXT: %[[BCST1:.*]] = "mhlo.dynamic_broadcast_in_dim"(%arg1, %[[BCST]]) {broadcast_dimensions = dense<[0, 1, 2]> : tensor<3xi64>} : (tensor<2x?x8xi32>, tensor<3xindex>) -> tensor<2x?x8xi32>