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Integrate LLVM at llvm/llvm-project@6ce76ff7eb 

Updates LLVM usage to match
[6ce76ff7eb76](https://github.com/llvm/llvm-project/commit/6ce76ff7eb76)

PiperOrigin-RevId: 367678843
This commit is contained in:
Alexander Belyaev 2021-04-09 12:10:47 -07:00 committed by TensorFlow MLIR Team
parent 6d2209e301
commit 8a9bf05d78
3 changed files with 10 additions and 6 deletions
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4
WORKSPACE
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@ -15,9 +15,9 @@
load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive") load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
LLVM_COMMIT = "39ae25fb8c648b0e710ba2d2d46e7a5b7fafff19" LLVM_COMMIT = "6ce76ff7eb7640e53b65f0473848ce7d08165c98"
LLVM_SHA256 = "909ea626e84624fb428fdd6557bf35818b875dfd3ec72dfad810923c0662adf0" LLVM_SHA256 = "7f881381d7fd99216716416d9c98de36d47bebb433881fa54dd43b981163664f"
LLVM_BAZEL_TAG = "llvm-project-{commit}".format(commit = LLVM_COMMIT) LLVM_BAZEL_TAG = "llvm-project-{commit}".format(commit = LLVM_COMMIT)

2
build_tools/llvm_version.txt
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@ -1,2 +1,2 @@
39ae25fb8c648b0e710ba2d2d46e7a5b7fafff19 6ce76ff7eb7640e53b65f0473848ce7d08165c98

10
tests/move_up_dynamic_broadcasts_for_fusion.mlir
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@ -129,6 +129,7 @@ func @move_shape_of_into_assuming(%arg0 : !shape.witness,
shape.assuming_yield %arg1, %1 : tensor<?x32xf32>, tensor<?x32xf32> shape.assuming_yield %arg1, %1 : tensor<?x32xf32>, tensor<?x32xf32>
} }
%2 = shape.shape_of %0#1 : tensor<?x32xf32> -> tensor<3xindex> %2 = shape.shape_of %0#1 : tensor<?x32xf32> -> tensor<3xindex>
"use"(%0#0, %0#1) : (tensor<?x32xf32>, tensor<?x32xf32>) -> ()
return %2 : tensor<3xindex> return %2 : tensor<3xindex>
} }
@ -150,6 +151,7 @@ func @move_cstr_broadcastable_into_assuming(%arg0 : !shape.witness,
shape.assuming_yield %arg1, %1 : tensor<2xindex>, tensor<3xindex> shape.assuming_yield %arg1, %1 : tensor<2xindex>, tensor<3xindex>
} }
%1 = shape.cstr_broadcastable %arg1, %0#1 : tensor<2xindex>, tensor<3xindex> %1 = shape.cstr_broadcastable %arg1, %0#1 : tensor<2xindex>, tensor<3xindex>
"use"(%0#0, %0#1) : (tensor<2xindex>, tensor<3xindex>) -> ()
return %1 : !shape.witness return %1 : !shape.witness
} }
@ -223,6 +225,7 @@ func @move_shape_of_out_of_assuming(%arg0 : !shape.witness,
%2 = shape.shape_of %arg1 : tensor<2x?xf32> -> tensor<2xindex> %2 = shape.shape_of %arg1 : tensor<2x?xf32> -> tensor<2xindex>
shape.assuming_yield %1, %2 : tensor<2x?xf32>, tensor<2xindex> shape.assuming_yield %1, %2 : tensor<2x?xf32>, tensor<2xindex>
} }
"use"(%0#0, %0#1) : (tensor<2x?xf32>, tensor<2xindex>) -> ()
return %0#1 : tensor<2xindex> return %0#1 : tensor<2xindex>
} }
@ -283,6 +286,7 @@ func @merge_assuming_ops(%arg0: tensor<?x32xf16>, %arg1 : tensor<?x32xf16>,
%8 = "another.producer"() : () -> tensor<?x?x32xf16> %8 = "another.producer"() : () -> tensor<?x?x32xf16>
shape.assuming_yield %8 : tensor<?x?x32xf16> shape.assuming_yield %8 : tensor<?x?x32xf16>
} }
"use"(%5, %7) : (tensor<?x32xf16>, tensor<?x?x32xf16>) -> ()
return %7 : tensor<?x?x32xf16> return %7 : tensor<?x?x32xf16>
} }
@ -297,7 +301,7 @@ func @sub_sub(%arg0: tensor<?x32xf16>, %arg1 : tensor<?x32xf16>,
// CHECK: %[[SHAPE1:.*]] = shape.shape_of %[[ARG1]] // CHECK: %[[SHAPE1:.*]] = shape.shape_of %[[ARG1]]
// CHECK: %[[SHAPE2:.*]] = shape.shape_of %[[ARG2]] // CHECK: %[[SHAPE2:.*]] = shape.shape_of %[[ARG2]]
// CHECK: %[[WITNESS:.*]] = shape.cstr_broadcastable %[[SHAPE2]], %[[SHAPE0]], %[[SHAPE1]], %[[SHAPE0]], %[[SHAPE1]] // CHECK: %[[WITNESS:.*]] = shape.cstr_broadcastable %[[SHAPE2]], %[[SHAPE0]], %[[SHAPE1]], %[[SHAPE0]], %[[SHAPE1]]
// CHECK: %[[ASSUMING_RESULTS:.*]]:4 = shape.assuming %[[WITNESS]] // CHECK: %[[ASSUMING_RESULT:.*]] = shape.assuming %[[WITNESS]]
// CHECK-SAME: { // CHECK-SAME: {
// CHECK: %[[BCASTED_SHAPE01:.*]] = shape.broadcast %[[SHAPE0]], %[[SHAPE1]] // CHECK: %[[BCASTED_SHAPE01:.*]] = shape.broadcast %[[SHAPE0]], %[[SHAPE1]]
// CHECK: %[[BCASTED_SHAPE012:.*]] = shape.broadcast %[[SHAPE2]], %[[BCASTED_SHAPE01]] // CHECK: %[[BCASTED_SHAPE012:.*]] = shape.broadcast %[[SHAPE2]], %[[BCASTED_SHAPE01]]
@ -306,9 +310,9 @@ func @sub_sub(%arg0: tensor<?x32xf16>, %arg1 : tensor<?x32xf16>,
// CHECK: %[[BCASTED_ARG1:.*]] = "mhlo.dynamic_broadcast_in_dim"(%[[ARG1]], %[[BCASTED_SHAPE012]]) {broadcast_dimensions = dense<[1, 2]> : tensor<2xi64>} // CHECK: %[[BCASTED_ARG1:.*]] = "mhlo.dynamic_broadcast_in_dim"(%[[ARG1]], %[[BCASTED_SHAPE012]]) {broadcast_dimensions = dense<[1, 2]> : tensor<2xi64>}
// CHECK: %[[TMP:.*]] = mhlo.subtract %[[BCASTED_ARG0]], %[[BCASTED_ARG1]] // CHECK: %[[TMP:.*]] = mhlo.subtract %[[BCASTED_ARG0]], %[[BCASTED_ARG1]]
// CHECK: %[[RESULT:.*]] = mhlo.subtract %[[BCASTED_ARG2]], %[[TMP]] // CHECK: %[[RESULT:.*]] = mhlo.subtract %[[BCASTED_ARG2]], %[[TMP]]
// CHECK: shape.assuming_yield %{{.*}}, %{{.*}}, %{{.*}}, %[[RESULT]] // CHECK: shape.assuming_yield %[[RESULT]]
// CHECK: } // CHECK: }
// CHECK: return %[[ASSUMING_RESULTS]]#3 // CHECK: return %[[ASSUMING_RESULT]]
%0 = shape.shape_of %arg0 : tensor<?x32xf16> -> tensor<2xindex> %0 = shape.shape_of %arg0 : tensor<?x32xf16> -> tensor<2xindex>
%1 = shape.shape_of %arg1 : tensor<?x32xf16> -> tensor<2xindex> %1 = shape.shape_of %arg1 : tensor<?x32xf16> -> tensor<2xindex>
%2 = shape.cstr_broadcastable %0, %1 : tensor<2xindex>, tensor<2xindex> %2 = shape.cstr_broadcastable %0, %1 : tensor<2xindex>, tensor<2xindex>