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Bump OSS LLVM to 37ac1c19bed7b7d22e9312dfa61e7a4506ed4e49

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PiperOrigin-RevId: 306409008
Change-Id: I206b6f3f2df5a3c42b2f4b6ad89b48dfc7240a7f
This commit is contained in:
Benjamin Kramer 2020-04-14 03:41:29 -07:00 committed by TensorFlower Gardener
parent 02b3bc3c0d
commit 6b6736c316
22 changed files with 22 additions and 42 deletions
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5
tensorflow/compiler/mlir/lite/flatbuffer_import.cc
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@ -59,7 +59,6 @@ limitations under the License.
#include "mlir/IR/StandardTypes.h" // from @llvm-project
#include "mlir/IR/Types.h" // from @llvm-project
#include "mlir/IR/Value.h" // from @llvm-project
#include "mlir/Support/Functional.h" // from @llvm-project
#include "mlir/Support/LLVM.h" // from @llvm-project
#include "mlir/Translation.h" // from @llvm-project
#include "tensorflow/compiler/mlir/lite/flatbuffer_operator.h"
@ -676,8 +675,8 @@ template <typename ContainerType>
mlir::NamedAttribute BuildTFEntryFunctionAttribute(
const tflite::SubGraphT& subgraph, Builder* builder, const std::string name,
const ContainerType indices) {
llvm::SmallVector<std::string, 8> tensor_names = mlir::functional::map(
[&](int i) { return subgraph.tensors.at(i)->name; }, indices);
auto tensor_names = llvm::map_range(
indices, [&](int i) { return subgraph.tensors.at(i)->name; });
return builder->getNamedAttr(
name, builder->getStringAttr(llvm::join(tensor_names, ",")));
}

1
tensorflow/compiler/mlir/lite/ir/tfl_ops.h
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@ -28,7 +28,6 @@ limitations under the License.
#include "mlir/Interfaces/DerivedAttributeOpInterface.h" // from @llvm-project
#include "mlir/Interfaces/LoopLikeInterface.h" // from @llvm-project
#include "mlir/Interfaces/SideEffects.h" // from @llvm-project
#include "mlir/Support/Functional.h" // from @llvm-project
#include "mlir/Support/LLVM.h" // from @llvm-project
#include "tensorflow/compiler/mlir/lite/quantization/quantization_traits.h"
#include "tensorflow/lite/schema/schema_generated.h"

1
tensorflow/compiler/mlir/lite/quantization/import_quant_stats_pass.cc
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@ -33,7 +33,6 @@ limitations under the License.
#include "mlir/IR/PatternMatch.h" // from @llvm-project
#include "mlir/IR/StandardTypes.h" // from @llvm-project
#include "mlir/Pass/Pass.h" // from @llvm-project
#include "mlir/Support/Functional.h" // from @llvm-project
#include "mlir/Support/LLVM.h" // from @llvm-project
#include "tensorflow/compiler/mlir/lite/quantization/quantization_info.pb.h"
#include "tensorflow/compiler/mlir/lite/quantization/quantization_passes.h"

1
tensorflow/compiler/mlir/lite/transforms/default_quant_params.cc
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@ -20,7 +20,6 @@ limitations under the License.
#include "mlir/IR/PatternMatch.h"
#include "mlir/IR/StandardTypes.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Support/Functional.h"
#include "mlir/Support/LLVM.h"
#include "absl/memory/memory.h"
#include "llvm/ADT/STLExtras.h"

1
tensorflow/compiler/mlir/lite/transforms/extract_ophint.cc
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@ -38,7 +38,6 @@ limitations under the License.
#include "mlir/IR/Value.h" // from @llvm-project
#include "mlir/Pass/Pass.h" // from @llvm-project
#include "mlir/Pass/PassRegistry.h" // from @llvm-project
#include "mlir/Support/Functional.h" // from @llvm-project
#include "mlir/Support/LLVM.h" // from @llvm-project
#include "mlir/Support/LogicalResult.h" // from @llvm-project
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"

16
tensorflow/compiler/mlir/lite/transforms/legalize_tf.cc
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@ -36,7 +36,6 @@ limitations under the License.
#include "mlir/IR/PatternMatch.h" // from @llvm-project
#include "mlir/IR/StandardTypes.h" // from @llvm-project
#include "mlir/Pass/Pass.h" // from @llvm-project
#include "mlir/Support/Functional.h" // from @llvm-project
#include "mlir/Support/LLVM.h" // from @llvm-project
#include "mlir/Transforms/DialectConversion.h" // from @llvm-project
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"
@ -288,12 +287,10 @@ LogicalResult ConvertTFSplitOp::matchAndRewrite(
Operation* op, PatternRewriter& rewriter) const {
auto tf_split_op = cast<TF::SplitOp>(op);
auto output_types = functional::map([](Value v) { return v.getType(); },
tf_split_op.output());
// Number of splits cannot be negative.
auto num_split = rewriter.getI32IntegerAttr(tf_split_op.num_split());
rewriter.replaceOpWithNewOp<TFL::SplitOp>(op, output_types,
rewriter.replaceOpWithNewOp<TFL::SplitOp>(op, tf_split_op.output().getTypes(),
tf_split_op.split_dim(),
tf_split_op.value(), num_split);
return success();
@ -303,14 +300,12 @@ LogicalResult ConvertTFSplitVOp::matchAndRewrite(
Operation* op, PatternRewriter& rewriter) const {
auto tf_splitv_op = cast<TF::SplitVOp>(op);
auto output_types = functional::map([](Value v) { return v.getType(); },
tf_splitv_op.output());
// Number of splits cannot be negative.
auto num_split = rewriter.getI32IntegerAttr(tf_splitv_op.num_split());
rewriter.replaceOpWithNewOp<TFL::SplitVOp>(
op, output_types, tf_splitv_op.value(), tf_splitv_op.size_splits(),
tf_splitv_op.split_dim(), num_split);
op, tf_splitv_op.output().getTypes(), tf_splitv_op.value(),
tf_splitv_op.size_splits(), tf_splitv_op.split_dim(), num_split);
return success();
}
@ -402,13 +397,12 @@ LogicalResult ConvertTFUnpackOp::matchAndRewrite(
auto tf_unpack_op = cast<TF::UnpackOp>(op);
auto input = tf_unpack_op.value();
auto output_types = functional::map([](Value v) { return v.getType(); },
tf_unpack_op.output());
auto num = rewriter.getI32IntegerAttr(tf_unpack_op.num());
// Axis can be negative.
auto axis = rewriter.getI32IntegerAttr(tf_unpack_op.axis().getSExtValue());
rewriter.replaceOpWithNewOp<UnpackOp>(op, output_types, input, num, axis);
rewriter.replaceOpWithNewOp<UnpackOp>(op, tf_unpack_op.output().getTypes(),
input, num, axis);
return success();
}

1
tensorflow/compiler/mlir/lite/transforms/lower_static_tensor_list.cc
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@ -49,7 +49,6 @@ limitations under the License.
#include "mlir/IR/Value.h" // from @llvm-project
#include "mlir/Pass/Pass.h" // from @llvm-project
#include "mlir/Pass/PassRegistry.h" // from @llvm-project
#include "mlir/Support/Functional.h" // from @llvm-project
#include "mlir/Support/LLVM.h" // from @llvm-project
#include "mlir/Support/LogicalResult.h" // from @llvm-project
#include "mlir/Transforms/DialectConversion.h" // from @llvm-project

1
tensorflow/compiler/mlir/lite/transforms/optimize.cc
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@ -37,7 +37,6 @@ limitations under the License.
#include "mlir/IR/PatternMatch.h" // from @llvm-project
#include "mlir/IR/StandardTypes.h" // from @llvm-project
#include "mlir/Pass/Pass.h" // from @llvm-project
#include "mlir/Support/Functional.h" // from @llvm-project
#include "mlir/Support/LLVM.h" // from @llvm-project
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"
#include "tensorflow/compiler/mlir/lite/quantization/quantization_utils.h"

8
tensorflow/compiler/mlir/lite/transforms/prepare_tf.cc
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@ -46,7 +46,6 @@ limitations under the License.
#include "mlir/IR/PatternMatch.h" // from @llvm-project
#include "mlir/IR/StandardTypes.h" // from @llvm-project
#include "mlir/Pass/Pass.h" // from @llvm-project
#include "mlir/Support/Functional.h" // from @llvm-project
#include "mlir/Support/LLVM.h" // from @llvm-project
#include "mlir/Support/LogicalResult.h" // from @llvm-project
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"
@ -322,9 +321,10 @@ class ConvertTFConv2D : public ConvertTFConvOp<ConvertTFConv2D, TF::Conv2DOp> {
// Create tensor type for the transpose result.
auto filter_type = filter.getType().cast<RankedTensorType>();
auto result_shape = functional::map(
[filter_type](int64_t dim) { return filter_type.getDimSize(dim); },
perm);
auto result_shape =
llvm::to_vector<4>(llvm::map_range(perm, [filter_type](int64_t dim) {
return filter_type.getDimSize(dim);
}));
auto elem_type = filter_type.getElementType();
auto result_type = RankedTensorType::get(result_shape, elem_type);

1
tensorflow/compiler/mlir/lite/transforms/quantize.cc
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@ -29,7 +29,6 @@ limitations under the License.
#include "mlir/IR/OperationSupport.h" // from @llvm-project
#include "mlir/IR/PatternMatch.h" // from @llvm-project
#include "mlir/Pass/Pass.h" // from @llvm-project
#include "mlir/Support/Functional.h" // from @llvm-project
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"
#include "tensorflow/compiler/mlir/lite/quantization/quantization_utils.h"
#include "tensorflow/compiler/mlir/lite/transforms/passes.h"

7
tensorflow/compiler/mlir/lite/utils/lstm_utils.cc
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@ -94,9 +94,10 @@ Value Transpose(OpBuilder* builder, Value value_to_transpose,
// Create tensor type for the transpose result.
auto transpose_type = original_type;
auto transpose_shape = functional::map(
[transpose_type](int32_t dim) { return transpose_type.getDimSize(dim); },
perm);
auto transpose_shape =
llvm::to_vector<8>(llvm::map_range(perm, [transpose_type](int32_t dim) {
return transpose_type.getDimSize(dim);
}));
auto elem_type = transpose_type.getElementType();
auto result_type = RankedTensorType::get(transpose_shape, elem_type);

1
tensorflow/compiler/mlir/tensorflow/transforms/batchmatmul_to_einsum.cc
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@ -32,7 +32,6 @@ limitations under the License.
#include "mlir/IR/PatternMatch.h" // from @llvm-project
#include "mlir/IR/StandardTypes.h" // from @llvm-project
#include "mlir/Pass/Pass.h" // from @llvm-project
#include "mlir/Support/Functional.h" // from @llvm-project
#include "mlir/Support/LLVM.h" // from @llvm-project
#include "mlir/Support/LogicalResult.h" // from @llvm-project
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

1
tensorflow/compiler/mlir/tensorflow/transforms/einsum.cc
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@ -33,7 +33,6 @@ limitations under the License.
#include "mlir/IR/PatternMatch.h" // from @llvm-project
#include "mlir/IR/StandardTypes.h" // from @llvm-project
#include "mlir/Pass/Pass.h" // from @llvm-project
#include "mlir/Support/Functional.h" // from @llvm-project
#include "mlir/Support/LLVM.h" // from @llvm-project
#include "mlir/Support/LogicalResult.h" // from @llvm-project
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

1
tensorflow/compiler/mlir/tensorflow/transforms/fold_switch.cc
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@ -45,7 +45,6 @@ limitations under the License.
#include "mlir/IR/Visitors.h" // from @llvm-project
#include "mlir/Pass/Pass.h" // from @llvm-project
#include "mlir/Pass/PassRegistry.h" // from @llvm-project
#include "mlir/Support/Functional.h" // from @llvm-project
#include "mlir/Support/LLVM.h" // from @llvm-project
#include "mlir/Support/LogicalResult.h" // from @llvm-project
#include "tensorflow/compiler/mlir/tensorflow/ir/control_flow_ops.h"

1
tensorflow/compiler/mlir/tensorflow/transforms/unroll_batch_matmul.cc
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@ -31,7 +31,6 @@ limitations under the License.
#include "mlir/IR/PatternMatch.h" // from @llvm-project
#include "mlir/IR/StandardTypes.h" // from @llvm-project
#include "mlir/Pass/Pass.h" // from @llvm-project
#include "mlir/Support/Functional.h" // from @llvm-project
#include "mlir/Support/LLVM.h" // from @llvm-project
#include "mlir/Support/LogicalResult.h" // from @llvm-project
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

1
tensorflow/compiler/mlir/tfjs/ir/tfjs_ops.h
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@ -27,7 +27,6 @@ limitations under the License.
#include "mlir/IR/OpImplementation.h" // from @llvm-project
#include "mlir/IR/StandardTypes.h" // from @llvm-project
#include "mlir/Interfaces/SideEffects.h" // from @llvm-project
#include "mlir/Support/Functional.h" // from @llvm-project
#include "mlir/Support/LLVM.h" // from @llvm-project
namespace mlir {
namespace tfjs {

1
tensorflow/compiler/mlir/xla/ir/hlo_ops.h
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@ -30,7 +30,6 @@ limitations under the License.
#include "mlir/IR/Types.h" // from @llvm-project
#include "mlir/Interfaces/InferTypeOpInterface.h" // from @llvm-project
#include "mlir/Interfaces/SideEffects.h" // from @llvm-project
#include "mlir/Support/Functional.h" // from @llvm-project
namespace mlir {
class OpBuilder;

1
tensorflow/compiler/mlir/xla/ir/lhlo_ops.h
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@ -28,7 +28,6 @@ limitations under the License.
#include "mlir/IR/StandardTypes.h" // from @llvm-project
#include "mlir/IR/Types.h" // from @llvm-project
#include "mlir/Interfaces/SideEffects.h" // from @llvm-project
#include "mlir/Support/Functional.h" // from @llvm-project
namespace mlir {
class OpBuilder;

4
tensorflow/compiler/xla/service/cpu/llvm_ir_runtime.cc
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@ -142,8 +142,8 @@ void RewriteCalls(
}
for (auto* call_to_inline : calls_to_inline) {
llvm::InlineFunctionInfo inline_function_info;
CHECK(
llvm::InlineFunction(call_to_inline, inline_function_info).isSuccess());
CHECK(llvm::InlineFunction(*call_to_inline, inline_function_info)
.isSuccess());
}
// LLVM's InjectTLIMappings adds functions that might be used for
// vectorization to 'llvm.compiler.used'. Remove it before deleting the

2
tensorflow/compiler/xla/service/gpu/tests/gpu_noalias_test.cc
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@ -58,7 +58,7 @@ TEST_F(GpuNoAliasTest, Concat) {
; CHECK: load float, float* %[[y_gep]], {{.*}}, !noalias ![[param_noalias]]
; CHECK: %[[result_ptr:.*]] = bitcast [2 x [6 x float]]* %fusion{{.*}} to float*
; CHECK: %[[result_gep:.*]] = getelementptr inbounds float, float* %[[result_ptr]]
; CHECK: store float {{.*}}, float* %[[result_gep]], !alias.scope ![[param_noalias]]
; CHECK: store float {{.*}}, float* %[[result_gep]], align 4, !alias.scope ![[param_noalias]]
; CHECK: ![[param_noalias]] = !{![[retval_buffer:.*]]}
)",
/*match_optimized_ir=*/false);

4
tensorflow/compiler/xla/service/llvm_ir/alias_analysis_test.cc
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@ -59,13 +59,13 @@ ENTRY while3 {
CompileAndVerifyIr(hlo_string, R"(
; CHECK-LABEL: @body(i8* %retval
; CHECK: %[[add_result:.*]] = fadd fast float %[[fadd_lhs:.*]], %[[fadd_rhs:.*]]
; CHECK: store float %[[add_result]], float* %[[store_dest:.*]], !alias.scope ![[alias_scope_md_for_store:[0-9]+]]
; CHECK: store float %[[add_result]], float* %[[store_dest:.*]], align 4, !alias.scope ![[alias_scope_md_for_store:[0-9]+]]
;
; CHECK-LABEL: @condition(i8* %retval, i8* noalias %run_options, i8** noalias %params
; CHECK: %[[cond_state_buf_ptr:.*]] = getelementptr inbounds i8*, i8** %buffer_table, i64 0
; CHECK: %[[cond_state_buf_untyped:.*]] = load i8*, i8** %[[cond_state_buf_ptr]]
; CHECK: %[[cond_state_buf_typed:.*]] = bitcast i8* %[[cond_state_buf_untyped]] to float*
; CHECK: load float, float* %[[cond_state_buf_typed]], !alias.scope ![[alias_scope_md_for_store]], !noalias ![[noalias_md_for_load:.*]]
; CHECK: load float, float* %[[cond_state_buf_typed]], align 4, !alias.scope ![[alias_scope_md_for_store]], !noalias ![[noalias_md_for_load:.*]]
;
; CHECK-LABEL: @while3(

4
tensorflow/workspace.bzl
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@ -658,8 +658,8 @@ def tf_repositories(path_prefix = "", tf_repo_name = ""):
)
# Check out LLVM and MLIR from llvm-project.
LLVM_COMMIT = "813f438baaa9638529023b2218875e01ea037735"
LLVM_SHA256 = "d264734ecd31d6d3d16b6a0c10eeb2b43a9ba8ddc9a79db6256847b91c956aa9"
LLVM_COMMIT = "37ac1c19bed7b7d22e9312dfa61e7a4506ed4e49"
LLVM_SHA256 = "b694cd7ed85cbc938f11534d56a326126015de21a5fec3c073dc6125bec1fc24"
LLVM_URLS = [
"https://storage.googleapis.com/mirror.tensorflow.org/github.com/llvm/llvm-project/archive/{commit}.tar.gz".format(commit = LLVM_COMMIT),
"https://github.com/llvm/llvm-project/archive/{commit}.tar.gz".format(commit = LLVM_COMMIT),