experiments/STT-tensorflow
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Integrate LLVM at llvm/llvm-project@c907681b07

Browse Source 
Updates LLVM usage to match
[c907681b077c](https://github.com/llvm/llvm-project/commit/c907681b077c)

PiperOrigin-RevId: 360891677
Change-Id: Iaaf934b70f5b064ad3796d08abd887c53e3b1d41
This commit is contained in:
Benjamin Kramer 2021-03-04 05:21:32 -08:00 committed by TensorFlower Gardener
parent a5629c8368
commit 503babe90b
27 changed files with 224 additions and 157 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
tensorflow/compiler/mlir/hlo/include/mlir-hlo/Dialect/mhlo/IR/chlo_ops.td
View File

@ -90,7 +90,7 @@ class HLOClient_BroadcastBinaryElementwiseOp<
);
let builders = [
OpBuilderDAG<(ins "Value":$left, "Value":$right,
OpBuilder<(ins "Value":$left, "Value":$right,
"DenseIntElementsAttr":$broadcast_dimensions)>];
let results = (outs HLO_Tensor);
@ -673,7 +673,7 @@ def HLOClient_BroadcastCompareOp : HLOClient_BroadcastBinaryElementwiseOp<
let results = (outs HLO_PredTensor);
let builders = [
OpBuilderDAG<(ins "Value":$lhs, "Value":$rhs,
OpBuilder<(ins "Value":$lhs, "Value":$rhs,
"DenseIntElementsAttr":$broadcast_dimensions,
"StringAttr":$comparison_direction, CArg<"StringAttr", "{}">:$compare_type)>];
}

16
tensorflow/compiler/mlir/hlo/include/mlir-hlo/Dialect/mhlo/IR/hlo_ops.td
View File

@ -61,7 +61,7 @@ def HLO_ConstOp : HLO_Op<"constant",
);
let builders = [
OpBuilderDAG<(ins "Attribute":$value)>];
OpBuilder<(ins "Attribute":$value)>];
let assemblyFormat = "attr-dict $value";
@ -163,7 +163,7 @@ def HLO_ConvertOp : HLO_UnaryElementwiseOp<"convert",
[NoSideEffect, SameOperandsAndResultShape], HLO_Tensor>,
BASE_HLO_ConvertOp {
let builders = [
OpBuilderDAG<(ins "Value":$operand, "Type":$result_element_ty)>];
OpBuilder<(ins "Value":$operand, "Type":$result_element_ty)>];
let hasFolder = 1;
@ -624,7 +624,7 @@ def HLO_ReduceOp: HLO_Op<"reduce", [
let results = (outs Variadic<HLO_TensorOrTuple>);
let builders = [
OpBuilderDAG<(ins "ValueRange":$operands, "ValueRange":$init_values,
OpBuilder<(ins "ValueRange":$operands, "ValueRange":$init_values,
"DenseIntElementsAttr":$dimensions)>];
let extraClassDeclaration = [{
@ -662,7 +662,7 @@ def HLO_GetTupleElementOp: HLO_Op<"get_tuple_element", [NoSideEffect]>, BASE_HLO
let hasFolder = 1;
let builders = [
OpBuilderDAG<(ins "Value":$value, "int32_t":$index)>];
OpBuilder<(ins "Value":$value, "int32_t":$index)>];
}
def HLO_TupleOp : HLO_Op<"tuple", [NoSideEffect]>, BASE_HLO_TupleOp {
@ -670,7 +670,7 @@ def HLO_TupleOp : HLO_Op<"tuple", [NoSideEffect]>, BASE_HLO_TupleOp {
let results = (outs HLO_Tuple);
let builders = [
OpBuilderDAG<(ins "ValueRange":$values)>];
OpBuilder<(ins "ValueRange":$values)>];
let hasCanonicalizer = 1;
}
@ -690,7 +690,7 @@ def HLO_CompareOp: HLO_Op<"compare", [NoSideEffect, SameTypeOperands,
let hasFolder = 1;
let builders = [
OpBuilderDAG<(ins "Value":$lhs, "Value":$rhs,
OpBuilder<(ins "Value":$lhs, "Value":$rhs,
"StringAttr":$comparison_direction, CArg<"StringAttr", "{}">:$compare_type)>,
];
@ -889,7 +889,7 @@ def HLO_ConcatenateOp : HLO_Op<"concatenate",
let hasFolder = 1;
let extraClassDeclaration = [{
static bool isCompatibleReturnTypes(ArrayRef<Type> l, ArrayRef<Type> r) {
static bool isCompatibleReturnTypes(TypeRange l, TypeRange r) {
return succeeded(mlir::verifyCompatibleShapes(l, r));
}
}];
@ -1170,7 +1170,7 @@ def HLO_SortOp : HLO_Op<"sort", [RecursiveSideEffects,
let regions = (region SizedRegion<1>:$comparator);
let builders = [
OpBuilderDAG<(ins "ValueRange":$operands, CArg<"int64_t", "-1">:$dimension,
OpBuilder<(ins "ValueRange":$operands, CArg<"int64_t", "-1">:$dimension,
CArg<"bool", "false">:$is_stable)>];
// TODO(b/129422361): SortOp has special conversion logic to HLO.

4
tensorflow/compiler/mlir/hlo/include/mlir-hlo/Dialect/mhlo/IR/lhlo_ops.td
View File

@ -691,7 +691,7 @@ def FusionOp : LHLO_Op<"fusion", [SingleBlockImplicitTerminator<"TerminatorOp">]
let skipDefaultBuilders = 1;
let builders = [
OpBuilderDAG<(ins CArg<"ArrayRef<NamedAttribute>", "{}">:$attributes)>
OpBuilder<(ins CArg<"ArrayRef<NamedAttribute>", "{}">:$attributes)>
];
let extraClassDeclaration = [{
@ -740,7 +740,7 @@ def TerminatorOp :
Terminator operation for the LHLO dialect.
}];
let builders = [
OpBuilderDAG<(ins "ValueRange":$operands),
OpBuilder<(ins "ValueRange":$operands),
[{ build($_builder, $_state, llvm::None, operands, llvm::None); }]>];
}

8
tensorflow/compiler/mlir/lite/ir/tfl_ops.cc
View File

@ -1045,7 +1045,7 @@ LogicalResult Conv2DOp::inferReturnTypes(
return success();
}
bool Conv2DOp::isCompatibleReturnTypes(ArrayRef<Type> lhs, ArrayRef<Type> rhs) {
bool Conv2DOp::isCompatibleReturnTypes(TypeRange lhs, TypeRange rhs) {
if (lhs.size() != rhs.size() || lhs.size() != 1) return false;
if (failed(mlir::verifyCompatibleShape(lhs[0], rhs[0]))) return false;
return true;
@ -1917,7 +1917,7 @@ LogicalResult UnpackOp::inferReturnTypes(
return success();
}
bool UnpackOp::isCompatibleReturnTypes(ArrayRef<Type> lhs, ArrayRef<Type> rhs) {
bool UnpackOp::isCompatibleReturnTypes(TypeRange lhs, TypeRange rhs) {
if (lhs.size() != rhs.size()) return false;
for (auto pair : llvm::zip(lhs, rhs)) {
if (failed(
@ -2267,8 +2267,8 @@ LogicalResult UnidirectionalSequenceLSTMOp::inferReturnTypes(
return success();
}
bool UnidirectionalSequenceLSTMOp::isCompatibleReturnTypes(ArrayRef<Type> lhs,
ArrayRef<Type> rhs) {
bool UnidirectionalSequenceLSTMOp::isCompatibleReturnTypes(TypeRange lhs,
TypeRange rhs) {
if (lhs.size() != rhs.size() || lhs.size() != 1) return false;
if (failed(mlir::verifyCompatibleShape(lhs[0], rhs[0]))) return false;
return true;

40
tensorflow/compiler/mlir/lite/ir/tfl_ops.td
View File

@ -428,7 +428,7 @@ def ComparisonOpSameElementTypeConstraint :
//===----------------------------------------------------------------------===//
def TFL_BroadcastableBinaryBuilder :
OpBuilderDAG<(ins "Value":$lhs, "Value":$rhs),
OpBuilder<(ins "Value":$lhs, "Value":$rhs),
[{
auto resultType =
OpTrait::util::getBroadcastedType(lhs.getType(), rhs.getType());
@ -439,7 +439,7 @@ def TFL_BroadcastableBinaryBuilder :
}]>;
def TFL_FusedBroadcastableBinaryBuilder :
OpBuilderDAG<(ins "Value":$lhs, "Value":$rhs,
OpBuilder<(ins "Value":$lhs, "Value":$rhs,
"StringAttr":$fusedActivationFunction),
[{
buildFusedBroadcastableBinOp(
@ -447,7 +447,7 @@ def TFL_FusedBroadcastableBinaryBuilder :
}]>;
def TFL_ComparisonBinaryBuilder :
OpBuilderDAG<(ins "Value":$lhs, "Value":$rhs),
OpBuilder<(ins "Value":$lhs, "Value":$rhs),
[{
buildComparisonBinOp(&$_builder, $_state, lhs, rhs);
}]>;
@ -818,7 +818,7 @@ def TFL_ConstOp : Op<TFL_Dialect, "pseudo_const", [ConstantLike, NoSideEffect,
let hasFolder = 1;
let builders = [
OpBuilderDAG<(ins "Attribute":$value),
OpBuilder<(ins "Attribute":$value),
[{
$_state.addAttribute("value", value);
$_state.addTypes(value.getType());
@ -843,7 +843,7 @@ def TFL_SparseConstOp : Op<TFL_Dialect, "pseudo_sparse_const", [
let results = (outs AnyTensor:$output);
let builders = [
OpBuilderDAG<(ins "Attribute":$value, "SparsityParameterAttr":$s_param,
OpBuilder<(ins "Attribute":$value, "SparsityParameterAttr":$s_param,
"Attribute":$compressed_data),
[{
$_state.addTypes(value.getType());
@ -881,7 +881,7 @@ def TFL_Conv2DOp : TFL_ConvOp<"conv_2d", "Convolution", 0,
std::vector<std::vector<int>> GetQuantizedBlockSize() { return {}; }
// Returns whether the return types are compatible.
static bool isCompatibleReturnTypes(ArrayRef<Type> l, ArrayRef<Type> r);
static bool isCompatibleReturnTypes(TypeRange l, TypeRange r);
}];
}
@ -1062,7 +1062,7 @@ def TFL_GatherOp : TFL_Op<"gather", [
let builders =
[
OpBuilderDAG<(ins "Value":$params, "Value":$indices, "IntegerAttr":$axis),
OpBuilder<(ins "Value":$params, "Value":$indices, "IntegerAttr":$axis),
[{ BuildGatherOp(&$_builder, $_state, params, indices, axis); }]>
];
@ -1399,7 +1399,7 @@ def TFL_NotEqualOp : TFL_Op<"not_equal", [
let builders =
[
OpBuilderDAG<(ins "Value":$lhs, "Value":$rhs),
OpBuilder<(ins "Value":$lhs, "Value":$rhs),
[{
buildComparisonBinOp(&$_builder, $_state, lhs, rhs);
}]>
@ -1901,7 +1901,7 @@ def TFL_LogisticOp: TFL_Op<"logistic", [
// non-quantization tablegen patterns. Currently, it is used by the
// elementwise-move reordering pattern in the optimize_patterns.td
let builders = [
OpBuilderDAG<(ins "Value":$input),
OpBuilder<(ins "Value":$input),
[{
$_state.addOperands({input});
$_state.addTypes(input.getType());
@ -2554,7 +2554,7 @@ def TFL_ReluOp: TFL_Op<"relu", [
// non-quantization tablegen patterns. Currently, it is used by the
// elementwise-move reordering pattern in the optimize_patterns.td
let builders = [
OpBuilderDAG<(ins "Value":$input),
OpBuilder<(ins "Value":$input),
[{
$_state.addOperands({input});
$_state.addTypes(input.getType());
@ -2582,7 +2582,7 @@ def TFL_Relu6Op: TFL_Op<"relu6", [
// non-quantization tablegen patterns. Currently, it is used by the
// elementwise-move reordering pattern in the optimize_patterns.td
let builders = [
OpBuilderDAG<(ins "Value":$input),
OpBuilder<(ins "Value":$input),
[{
$_state.addOperands({input});
$_state.addTypes(input.getType());
@ -2610,7 +2610,7 @@ def TFL_Relu1Op: TFL_Op<"relu_n1_to_1", [
// non-quantization tablegen patterns. Currently, it is used by the
// elementwise-move reordering pattern in the optimize_patterns.td
let builders = [
OpBuilderDAG<(ins "Value":$input),
OpBuilder<(ins "Value":$input),
[{
$_state.addOperands({input});
$_state.addTypes(input.getType());
@ -2795,7 +2795,7 @@ def TFL_SelectOp : TFL_Op<"select", [
// TODO(jpienaar): autogenerate this.
let builders = [
OpBuilderDAG<(ins "Value":$condition, "Value":$x, "Value":$y),
OpBuilder<(ins "Value":$condition, "Value":$x, "Value":$y),
[{
auto resultType = x.getType();
$_state.addOperands({condition, x, y});
@ -2832,7 +2832,7 @@ def TFL_SelectV2Op : TFL_Op<"select_v2", [
TFL_TensorOf<[F32, I1, I8, I16, I32, I64, QI8, QUI8, QI16, TFL_Quint8]>:$output);
let builders = [
OpBuilderDAG<(ins "Value":$cond, "Value":$x, "Value":$y),
OpBuilder<(ins "Value":$cond, "Value":$x, "Value":$y),
[{
BuildSelectV2Op(&$_builder, $_state, cond, x, y);
}]>];
@ -3009,7 +3009,7 @@ def TFL_TanhOp: TFL_Op<"tanh", [
// non-quantization tablegen patterns. Currently, it is used by the
// elementwise-move reordering pattern in the optimize_patterns.td
let builders = [
OpBuilderDAG<(ins "Value":$input),
OpBuilder<(ins "Value":$input),
[{
$_state.addOperands({input});
$_state.addTypes(input.getType());
@ -3083,7 +3083,7 @@ def TFL_TopKV2Op: TFL_Op<"topk_v2", [
TFL_I32Tensor:$indices);
let builders = [
OpBuilderDAG<(ins "Value":$input, "Value":$k),
OpBuilder<(ins "Value":$input, "Value":$k),
[{ BuildTopKOp(&$_builder, $_state, input, k); }]>];
let hasOptions = 1;
@ -3152,7 +3152,7 @@ def TFL_UnpackOp : TFL_Op<"unpack", [
);
let extraClassDeclaration = [{
static bool isCompatibleReturnTypes(ArrayRef<Type> l, ArrayRef<Type> r);
static bool isCompatibleReturnTypes(TypeRange l, TypeRange r);
}];
let hasOptions = 1;
@ -3628,7 +3628,7 @@ def TFL_QConstOp : Op<TFL_Dialect, "pseudo_qconst", [
let results = (outs TFL_TensorOf<[QUI8, QI8, QI16, QUI16, TFL_Quint8]>:$output);
let builders = [
OpBuilderDAG<(ins "TypeAttr":$qtype, "Attribute":$value),
OpBuilder<(ins "TypeAttr":$qtype, "Attribute":$value),
[{
$_state.addAttribute("qtype", qtype);
$_state.addAttribute("value", value);
@ -3657,7 +3657,7 @@ def TFL_SparseQConstOp : Op<TFL_Dialect, "pseudo_sparse_qconst", [
let results = (outs TFL_TensorOf<[QUI8, QI8, QI16, QUI16, TFL_Quint8]>:$output);
let builders = [
OpBuilderDAG<(ins "TypeAttr":$qtype, "Attribute":$value,
OpBuilder<(ins "TypeAttr":$qtype, "Attribute":$value,
"SparsityParameterAttr":$s_param, "Attribute":$compressed_data),
[{
$_state.addTypes(qtype.getValue());
@ -4046,7 +4046,7 @@ def TFL_UnidirectionalSequenceLSTMOp :
std::vector<int> GetStatefulOperands() { return {18, 19}; }
// Compatiable return types check
static bool isCompatibleReturnTypes(ArrayRef<Type> l, ArrayRef<Type> r);
static bool isCompatibleReturnTypes(TypeRange l, TypeRange r);
}];
}

8
tensorflow/compiler/mlir/tensorflow/ir/tf_device.cc
View File

@ -179,8 +179,7 @@ LogicalResult Verify(ParallelExecuteOp op) {
// static
void ParallelExecuteOp::build(OpBuilder& builder, OperationState& state,
int num_regions,
llvm::ArrayRef<Type> output_types) {
int num_regions, TypeRange output_types) {
DCHECK_GE(num_regions, 2);
for (int i = 0; i < num_regions; ++i) {
Region* region = state.addRegion();
@ -203,10 +202,7 @@ Operation::result_range ParallelExecuteOp::GetRegionOutputs(
return_value_offset +=
GetRegionBlockWithIndex(region_id).getTerminator()->getNumOperands();
Operation::result_range region_results(getOperation(),
/*startIndex=*/return_value_offset,
/*count=*/num_region_results);
return region_results;
return getResults().slice(return_value_offset, num_region_results);
}
bool ParallelExecuteOp::RegionWrapsSingleOp(unsigned index) {

12
tensorflow/compiler/mlir/tensorflow/ir/tf_device_ops.td
View File

@ -76,7 +76,7 @@ This op captures all needed live-in values.
}];
let builders = [
OpBuilderDAG<(ins "StringAttr":$device, "ArrayRef<Type>":$result_types),
OpBuilder<(ins "StringAttr":$device, "TypeRange":$result_types),
[{
$_state.addAttribute("device", device);
$_state.addTypes(result_types);
@ -98,7 +98,7 @@ The `tf_device.return` operation terminates and returns values from a
);
let builders = [
OpBuilderDAG<(ins),
OpBuilder<(ins),
[{
build($_builder, $_state, {});
}]>
@ -169,7 +169,7 @@ def TfDevice_ParallelExecuteOp : TfDevice_Op<"parallel_execute",
}];
let builders = [
OpBuilderDAG<(ins "int":$num_regions, "llvm::ArrayRef<Type>":$output_types)>,
OpBuilder<(ins "int":$num_regions, "TypeRange":$output_types)>,
];
let verifier = [{ return Verify(*this); }];
@ -294,11 +294,11 @@ For example:
}];
let builders = [
OpBuilderDAG<(ins "int":$n,
OpBuilder<(ins "int":$n,
"const llvm::SmallDenseMap<StringRef, llvm::SmallVector<StringRef, 4>>&":$devices,
"llvm::ArrayRef<std::pair<ValueRange, Type>>":$replicated_inputs,
"ValueRange":$packed_inputs, "TypeRange":$replica_output_types)>,
OpBuilderDAG<(ins "int":$n, "llvm::Optional<DictionaryAttr>":$devices,
OpBuilder<(ins "int":$n, "llvm::Optional<DictionaryAttr>":$devices,
"llvm::ArrayRef<std::pair<ValueRange, Type>>":$replicated_inputs,
"ValueRange":$packed_inputs, "TypeRange":$replica_output_types)>,
];
@ -330,7 +330,7 @@ used to form the cluster.
let regions = (region SizedRegion<1>:$body);
let builders = [
OpBuilderDAG<(ins "ArrayRef<Type>":$resultTypes),
OpBuilder<(ins "TypeRange":$resultTypes),
[{
build($_builder, $_state, resultTypes, mlir::StringAttr {});
}]>

10
tensorflow/compiler/mlir/tensorflow/ir/tf_executor_ops.td
View File

@ -144,7 +144,7 @@ def TfExecutor_FetchOp : TfExecutor_Op<"fetch",
);
let builders = [
OpBuilderDAG<(ins),
OpBuilder<(ins),
[{
build($_builder, $_state, {});
}]>
@ -229,7 +229,7 @@ def TfExecutor_YieldOp : TfExecutor_Op<"yield",
);
let builders = [
OpBuilderDAG<(ins),
OpBuilder<(ins),
[{
build($_builder, $_state, {});
}]>
@ -460,7 +460,7 @@ def TfExecutor_NextIterationSourceOp : TfExecutor_Op<"NextIteration.Source",
);
let builders = [
OpBuilderDAG<(ins "Type":$result_type,
OpBuilder<(ins "Type":$result_type,
CArg<"ArrayRef<NamedAttribute>", "{}">:$attributes),
[{
Type token_type = TokenType::get($_builder.getContext());
@ -530,7 +530,7 @@ def TfExecutor_NextIterationSinkOp : TfExecutor_Op<"NextIteration.Sink",
);
let builders = [
OpBuilderDAG<(ins "Value":$token, "ArrayRef<Value>":$operands,
OpBuilder<(ins "Value":$token, "ArrayRef<Value>":$operands,
CArg<"ArrayRef<NamedAttribute>", "{}">:$attributes),
[{
assert(operands.size() >= 1 && "tf_executor.NextIteration.Sink builder "
@ -618,7 +618,7 @@ def TfExecutor_ControlTriggerOp : TfExecutor_Op<"ControlTrigger",
let hasCanonicalizer = 1;
let builders = [
OpBuilderDAG<(ins "ArrayRef<Value>":$operands,
OpBuilder<(ins "ArrayRef<Value>":$operands,
CArg<"ArrayRef<NamedAttribute>", "{}">:$attributes),
[{
assert(operands.size() >= 1 && "tf_executor.ControlTrigger builder "

36
tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
View File

@ -2227,7 +2227,7 @@ of `data_format`, see below for details.}]>:$input,
StringRef GetOptimalLayout(const RuntimeDevices& devices);
LogicalResult UpdateDataFormat(StringRef data_format);
// InferTypeOpInterface:
static bool isCompatibleReturnTypes(ArrayRef<Type> l, ArrayRef<Type> r) {
static bool isCompatibleReturnTypes(TypeRange l, TypeRange r) {
return ArraysAreCastCompatible(l, r);
}
}];
@ -2348,7 +2348,7 @@ out_channels]`. `in_channels` must match between `input` and `filter`.}]>:$filte
let extraClassDeclaration = [{
// InferTypeOpInterface:
static bool isCompatibleReturnTypes(ArrayRef<Type> l, ArrayRef<Type> r) {
static bool isCompatibleReturnTypes(TypeRange l, TypeRange r) {
return ArraysAreCastCompatible(l, r);
}
}];
@ -3923,7 +3923,7 @@ tf.math.equal(x, y) ==> array([True, True])
TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
let builders = [
OpBuilderDAG<(ins "Value":$x, "Value":$y,
OpBuilder<(ins "Value":$x, "Value":$y,
"BoolAttr":$incompatible_shape_error)>
];
@ -4073,7 +4073,7 @@ dimension of size 1 added.}]>:$output
TF_DerivedOperandTypeAttr Tdim = TF_DerivedOperandTypeAttr<1>;
let builders = [
OpBuilderDAG<(ins "Value":$condition, "Value":$dim)>
OpBuilder<(ins "Value":$condition, "Value":$dim)>
];
}
@ -4460,7 +4460,7 @@ Equivalent to np.full
let hasFolder = 1;
let builders = [
OpBuilderDAG<(ins "Value":$dims, "Value":$value)>
OpBuilder<(ins "Value":$dims, "Value":$value)>
];
}
@ -8042,7 +8042,7 @@ retained with length 1.
TF_DerivedOperandTypeAttr Tidx = TF_DerivedOperandTypeAttr<1>;
let builders = [
OpBuilderDAG<(ins "Value":$input, "Value":$reduction_indices,
OpBuilder<(ins "Value":$input, "Value":$reduction_indices,
"BoolAttr":$keep_dims)>
];
}
@ -9060,7 +9060,7 @@ def TF_NotEqualOp : TF_Op<"NotEqual", [Commutative, NoSideEffect]> {
TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
let builders = [
OpBuilderDAG<(ins "Value":$x, "Value":$y,
OpBuilder<(ins "Value":$x, "Value":$y,
"BoolAttr":$incompatible_shape_error)>
];
@ -9179,7 +9179,7 @@ output =
TF_DerivedOperandTypeAttr TI = TF_DerivedOperandTypeAttr<0>;
let builders = [
OpBuilderDAG<(ins "Value":$indices, "Value":$depth, "Value":$on_value,
OpBuilder<(ins "Value":$indices, "Value":$depth, "Value":$on_value,
"Value":$off_value, "IntegerAttr":$axis)>
];
@ -10394,7 +10394,7 @@ tf.range(start, limit, delta) ==> [3, 6, 9, 12, 15]
TF_DerivedOperandTypeAttr Tidx = TF_DerivedOperandTypeAttr<0>;
let builders = [
OpBuilderDAG<(ins "Value":$start, "Value":$limit, "Value":$delta)>
OpBuilder<(ins "Value":$start, "Value":$limit, "Value":$delta)>
];
}
@ -10447,7 +10447,7 @@ of the tensor. Rank is also known as "order", "degree", or "ndims."
TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
let builders = [
OpBuilderDAG<(ins "Value":$input)>
OpBuilder<(ins "Value":$input)>
];
let hasFolder = 1;
@ -10796,7 +10796,7 @@ reshape(t, []) ==> 7
TF_DerivedOperandTypeAttr Tshape = TF_DerivedOperandTypeAttr<1>;
let builders = [
OpBuilderDAG<(ins "Value":$tensor, "Value":$shape)>
OpBuilder<(ins "Value":$tensor, "Value":$shape)>
];
let verifier = [{
@ -13298,7 +13298,7 @@ def TF_SelectV2Op : TF_Op<"SelectV2", [NoSideEffect, ResultsBroadcastableShape]>
TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<1>;
let builders = [
OpBuilderDAG<(ins "Value":$condition, "Value":$e, "Value":$t)>
OpBuilder<(ins "Value":$condition, "Value":$e, "Value":$t)>
];
}
@ -13461,7 +13461,7 @@ shape(t) ==> [2, 2, 3]
}];
let builders = [
OpBuilderDAG<(ins "Value":$input, "BoolAttr":$use32Bit)>
OpBuilder<(ins "Value":$input, "BoolAttr":$use32Bit)>
];
let hasFolder = 1;
@ -14137,7 +14137,7 @@ regular convolution.}]>:$paddings
let verifier = [{ return Verify(*this); }];
let extraClassDeclaration = [{
static bool isCompatibleReturnTypes(ArrayRef<Type> l, ArrayRef<Type> r) {
static bool isCompatibleReturnTypes(TypeRange l, TypeRange r) {
return ArraysAreCastCompatible(l, r);
}
}];
@ -15608,7 +15608,7 @@ retained with length 1.
TF_DerivedOperandTypeAttr Tidx = TF_DerivedOperandTypeAttr<1>;
let builders = [
OpBuilderDAG<(ins "Value":$input, "Value":$reduction_indices,
OpBuilder<(ins "Value":$input, "Value":$reduction_indices,
"BoolAttr":$keep_dims)>
];
@ -16801,7 +16801,7 @@ to the indices.}]>:$output
let verifier = [{ return Verify(*this); }];
let builders = [
OpBuilderDAG<(ins "Value":$tensor, "Value":$indices, "Value":$updates),
OpBuilder<(ins "Value":$tensor, "Value":$indices, "Value":$updates),
[{build($_builder, $_state, tensor.getType(), tensor, indices, updates);}]>
];
}
@ -16999,7 +16999,7 @@ The output `y` has the same rank as `x`. The shapes of `x` and `y` satisfy:
TF_DerivedOperandTypeAttr Tperm = TF_DerivedOperandTypeAttr<1>;
let builders = [
OpBuilderDAG<(ins "Value":$x, "Value":$perm)>
OpBuilder<(ins "Value":$x, "Value":$perm)>
];
let verifier = [{
@ -17670,7 +17670,7 @@ for binary operators.
let extraClassDeclaration = [{
// InferTypeOpInterface:
static bool isCompatibleReturnTypes(ArrayRef<Type> l, ArrayRef<Type> r) {
static bool isCompatibleReturnTypes(TypeRange l, TypeRange r) {
return ArraysAreCastCompatible(l, r);
}
}];

8
tensorflow/compiler/mlir/tensorflow/ir/tf_op_base.td
View File

@ -579,8 +579,8 @@ def TF_IntTypeAttr : TypeAttrBase<"IntegerType", "integer type"> {
// Mixin class defining a builder for binary ops supporting broadcast
// behavior. The result type has the same element type as both operands.
class WithBroadcastableBinOpBuilder {
list<OpBuilderDAG> builders = [
OpBuilderDAG<(ins "Value":$x, "Value":$y),
list<OpBuilder> builders = [
OpBuilder<(ins "Value":$x, "Value":$y),
[{
auto resultType =
OpTrait::util::getBroadcastedType(x.getType(), y.getType());
@ -593,8 +593,8 @@ class WithBroadcastableBinOpBuilder {
// Mixin class defining a builder for comparison ops supporting broadcast
// behavior. The result type has bool element type.
class WithBroadcastableCmpOpBuilder {
list<OpBuilderDAG> builders = [
OpBuilderDAG<(ins "Value":$x, "Value":$y),
list<OpBuilder> builders = [
OpBuilder<(ins "Value":$x, "Value":$y),
[{
Type resultType;
if (x.getType().isa<UnrankedTensorType>() ||

10
tensorflow/compiler/mlir/tensorflow/ir/tf_ops.td
View File

@ -203,14 +203,14 @@ def TF_ConstOp : TF_Op<"Const", [ConstantLike, NoSideEffect,
TF_DerivedResultTypeAttr dtype = TF_DerivedResultTypeAttr<0>;
let builders = [
OpBuilderDAG<(ins "Attribute":$value)>,
OpBuilderDAG<(ins "Type":$type, "Attribute":$value)>,
OpBuilder<(ins "Attribute":$value)>,
OpBuilder<(ins "Type":$type, "Attribute":$value)>,
];
let hasFolder = 1;
let extraClassDeclaration = [{
static bool isCompatibleReturnTypes(ArrayRef<Type> l, ArrayRef<Type> r) {
static bool isCompatibleReturnTypes(TypeRange l, TypeRange r) {
return BroadcastCompatible(l, r);
}
}];
@ -410,7 +410,7 @@ else_branch: A region that computes the outputs of the op if cond = false.
}];
let builders = [
OpBuilderDAG<(ins "TypeRange":$resultTypes, "ValueRange":$operands,
OpBuilder<(ins "TypeRange":$resultTypes, "ValueRange":$operands,
"llvm::ArrayRef<::mlir::NamedAttribute>":$attributes,
"unsigned":$numRegions),
[{
@ -1213,7 +1213,7 @@ as true/false for a branch condition.
TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
let builders = [
OpBuilderDAG<(ins "Value":$value),
OpBuilder<(ins "Value":$value),
[{
build($_builder, $_state, RankedTensorType::get({}, $_builder.getI1Type()),
value);

6
tensorflow/compiler/mlir/tensorflow/ir/tf_types.cc
View File

@ -198,7 +198,7 @@ ArrayRef<TensorType> TensorFlowTypeWithSubtype::GetSubtypes() {
// TODO(jpienaar): BroadcastCompatible and HasCompatibleElementTypes have
// similar structure that could be extracted into helper method.
bool BroadcastCompatible(ArrayRef<Type> lhs, ArrayRef<Type> rhs) {
bool BroadcastCompatible(TypeRange lhs, TypeRange rhs) {
if (lhs.size() != rhs.size()) return false;
for (auto types : llvm::zip(lhs, rhs)) {
// Drop ref types because they don't affect broadcast compatibility. E.g.,
@ -349,7 +349,7 @@ bool HasCompatibleElementTypes(Type lhs, Type rhs,
return GetCastCompatibleType(lhs, rhs, may_ignore_ref_type_lhs) != nullptr;
}
bool AreCastCompatible(ArrayRef<Type> types) {
bool AreCastCompatible(TypeRange types) {
Type common = types.front();
for (auto type : types.drop_front()) {
Type refined_type =
@ -360,7 +360,7 @@ bool AreCastCompatible(ArrayRef<Type> types) {
return true;
}
bool ArraysAreCastCompatible(ArrayRef<Type> lhs, ArrayRef<Type> rhs) {
bool ArraysAreCastCompatible(TypeRange lhs, TypeRange rhs) {
if (lhs.size() != rhs.size()) return false;
for (auto pair : llvm::zip(lhs, rhs)) {
auto lhs_i = std::get<0>(pair);

6
tensorflow/compiler/mlir/tensorflow/ir/tf_types.h
View File

@ -287,7 +287,7 @@ mlir::Type GetCastCompatibleType(mlir::Type a, mlir::Type b,
bool may_ignore_ref_type_a);
// Returns whether two arrays of Type are broadcast compatible.
bool BroadcastCompatible(ArrayRef<Type> lhs, ArrayRef<Type> rhs);
bool BroadcastCompatible(TypeRange lhs, TypeRange rhs);
// Returns whether the two elemental types are compatible. Shapes are compatible
// if:
@ -305,11 +305,11 @@ bool HasCompatibleElementTypes(Type lhs, Type rhs,
// another. In other words, a single run-time value is legal for both the types.
// For example, tensor<*xf32>, tensor<?xf32> and tensor<3xf32> are cast
// compatible.
bool AreCastCompatible(ArrayRef<Type> types);
bool AreCastCompatible(TypeRange types);
// Returns true if corresponding elements of lhs and rhs AreCastCompatible and
// lhs and rhs are the same length.
bool ArraysAreCastCompatible(ArrayRef<Type> lhs, ArrayRef<Type> rhs);
bool ArraysAreCastCompatible(TypeRange lhs, TypeRange rhs);
// If `ty` is a tensor type and its element type has subtypes, then returns a
// new type of same shape but dropped subtypes for the element type.

2
tensorflow/compiler/mlir/tensorflow/transforms/constant_fold.cc
View File

@ -80,7 +80,7 @@ LogicalResult ConstantFoldFallbackHook(
// If any of the result types are variants, don't try to constant fold them.
// This creates opaque variant constants which lose information and would
// require "raising" later.
for (auto& type : inst->getResultTypes()) {
for (auto type : inst->getResultTypes()) {
if (auto tensor_type = type.dyn_cast<TensorType>()) {
if (tensor_type.getElementType().isa<VariantType>()) {
return failure();

4
tensorflow/compiler/mlir/tensorflow/transforms/shape_inference.cc
View File

@ -890,7 +890,7 @@ bool ShapeInference::RefineTypeForPassThroughOperands(Operation* op,
OperandRange operands,
ResultRange results) {
bool changed = false;
for (auto entry : zip(operands, results)) {
for (auto entry : llvm::zip(operands, results)) {
Type operand_type = std::get<0>(entry).getType();
Value result = std::get<1>(entry);
TensorType result_type = result.getType().cast<TensorType>();
@ -925,7 +925,7 @@ bool ShapeInference::RefineShapeForPassThroughOps(Operation* op) {
};
bool changed = false;
for (auto entry : zip(op->getOperands(), op->getResults())) {
for (auto entry : llvm::zip(op->getOperands(), op->getResults())) {
TensorType operand_type = std::get<0>(entry).getType().cast<TensorType>();
Value result = std::get<1>(entry);
TensorType result_type = result.getType().cast<TensorType>();

4
tensorflow/compiler/mlir/tfr/ir/tfr_ops.td
View File

@ -267,7 +267,7 @@ def TFR_ConstOp : TFR_Op<"constant", [ConstantLike, NoSideEffect]> {
let hasFolder = 1;
let builders = [
OpBuilderDAG<(ins "Attribute":$value),
OpBuilder<(ins "Attribute":$value),
[{
auto* ctx = value.getContext();
$_state.addAttribute("value", value);
@ -425,7 +425,7 @@ def TFR_TFRFuncOp : TFR_Op<"func", [HasParent<"ModuleOp">,
let skipDefaultBuilders = 1;
let builders = [
OpBuilderDAG<(ins "StringRef":$name, "FunctionType":$type,
OpBuilder<(ins "StringRef":$name, "FunctionType":$type,
CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs)>
];

7
tensorflow/compiler/mlir/tools/kernel_gen/BUILD
View File

@ -68,6 +68,7 @@ cc_library(
"@llvm-project//mlir:GPUTransforms",
"@llvm-project//mlir:IR",
"@llvm-project//mlir:LLVMDialect",
"@llvm-project//mlir:LLVMToLLVMIRTranslation",
"@llvm-project//mlir:LinalgOps",
"@llvm-project//mlir:LinalgTransforms",
"@llvm-project//mlir:NVVMDialect",
@ -86,7 +87,7 @@ cc_library(
"@llvm-project//mlir:StandardOps",
"@llvm-project//mlir:StandardOpsTransforms",
"@llvm-project//mlir:Support",
"@llvm-project//mlir:TargetLLVMIR",
"@llvm-project//mlir:ToLLVMIRTranslation",
"@llvm-project//mlir:Transforms",
],
)
@ -117,8 +118,8 @@ tf_cc_binary(
"@llvm-project//llvm:X86Disassembler", # fixdeps: keep
"@llvm-project//mlir:ExecutionEngineUtils",
"@llvm-project//mlir:Pass",
"@llvm-project//mlir:TargetLLVMIR",
"@llvm-project//mlir:TargetLLVMIRModuleTranslation",
"@llvm-project//mlir:LLVMToLLVMIRTranslation",
"@llvm-project//mlir:ToLLVMIRTranslation",
] + if_llvm_system_z_available([
"@llvm-project//llvm:SystemZCodeGen", # fixdeps: keep
]) + if_llvm_aarch64_available([

4
tensorflow/compiler/mlir/tools/kernel_gen/ir/tf_framework_ops.td
View File

@ -80,12 +80,12 @@ def TFFramework_TFAllocOp : TFFramework_Op<"alloc",
let results = (outs Res<AnyMemRef, "", [MemAlloc<DefaultResource>]>:$result);
let builders = [
OpBuilderDAG<(ins "MemRefType":$memref_type, "Value":$ctx),
OpBuilder<(ins "MemRefType":$memref_type, "Value":$ctx),
[{
$_state.addOperands(ctx);
$_state.types.push_back(memref_type);
}]>,
OpBuilderDAG<(ins "MemRefType":$memref_type, "Value":$ctx,
OpBuilder<(ins "MemRefType":$memref_type, "Value":$ctx,
"ValueRange":$dyn_sizes),
[{
build($_builder, $_state, memref_type, ctx);

11
tensorflow/compiler/mlir/tools/kernel_gen/kernel_creator.cc
View File

@ -31,8 +31,6 @@ limitations under the License.
#include "mlir/Dialect/GPU/ParallelLoopMapper.h" // from @llvm-project
#include "mlir/Dialect/GPU/Passes.h" // from @llvm-project
#include "mlir/Dialect/LLVMIR/LLVMDialect.h" // from @llvm-project
#include "mlir/Dialect/LLVMIR/NVVMDialect.h" // from @llvm-project
#include "mlir/Dialect/LLVMIR/ROCDLDialect.h" // from @llvm-project
#include "mlir/Dialect/Linalg/Passes.h" // from @llvm-project
#include "mlir/Dialect/Linalg/Transforms/Transforms.h" // from @llvm-project
#include "mlir/Dialect/SCF/Passes.h" // from @llvm-project
@ -46,7 +44,7 @@ limitations under the License.
#include "mlir/Parser.h" // from @llvm-project
#include "mlir/Pass/Pass.h" // from @llvm-project
#include "mlir/Pass/PassManager.h" // from @llvm-project
#include "mlir/Target/LLVMIR.h" // from @llvm-project
#include "mlir/Target/LLVMIR/Dialect/LLVMIR/LLVMToLLVMIRTranslation.h" // from @llvm-project
#include "mlir/Target/LLVMIR/Dialect/NVVM/NVVMToLLVMIRTranslation.h" // from @llvm-project
#include "mlir/Target/LLVMIR/Dialect/ROCDL/ROCDLToLLVMIRTranslation.h" // from @llvm-project
#include "mlir/Transforms/Bufferize.h" // from @llvm-project
@ -435,12 +433,9 @@ StatusOr<mlir::OwningModuleRef> GenerateKernelForTfCode(
mlir::DialectRegistry registry;
mlir::RegisterAllTensorFlowDialects(registry);
registry.insert<mlir::chlo::HloClientDialect, mlir::mhlo::MhloDialect>();
registry.insert<mlir::NVVM::NVVMDialect, mlir::ROCDL::ROCDLDialect>();
registry.addDialectInterface<mlir::NVVM::NVVMDialect,
mlir::NVVMDialectLLVMIRTranslationInterface>();
registry.addDialectInterface<mlir::ROCDL::ROCDLDialect,
mlir::ROCDLDialectLLVMIRTranslationInterface>();
mlir::registerLLVMDialectTranslation(registry);
mlir::registerNVVMDialectTranslation(registry);
mlir::registerROCDLDialectTranslation(registry);
context.appendDialectRegistry(registry);
mlir::OwningModuleRef module = mlir::parseSourceString(tf_code, &context);

2
tensorflow/compiler/mlir/tools/kernel_gen/tf_to_kernel.cc
View File

@ -34,7 +34,7 @@
#include "llvm/Target/TargetMachine.h"
#include "mlir/ExecutionEngine/OptUtils.h" // from @llvm-project
#include "mlir/Pass/PassManager.h" // from @llvm-project
#include "mlir/Target/LLVMIR.h" // from @llvm-project
#include "mlir/Target/LLVMIR/Dialect/LLVMIR/LLVMToLLVMIRTranslation.h" // from @llvm-project
#include "mlir/Target/LLVMIR/Export.h" // from @llvm-project
#include "tensorflow/compiler/mlir/init_mlir.h"
#include "tensorflow/compiler/mlir/tools/kernel_gen/kernel_creator.h"

6
tensorflow/compiler/mlir/tools/kernel_gen/transforms/BUILD
View File

@ -126,8 +126,10 @@ cc_library(
"@llvm-project//mlir:StandardOps",
"@llvm-project//mlir:StandardOpsTransforms",
"@llvm-project//mlir:Support",
"@llvm-project//mlir:TargetLLVMIR",
"@llvm-project//mlir:TargetLLVMIRModuleTranslation",
"@llvm-project//mlir:LLVMToLLVMIRTranslation",
"@llvm-project//mlir:NVVMToLLVMIRTranslation",
"@llvm-project//mlir:ROCDLToLLVMIRTranslation",
"@llvm-project//mlir:ToLLVMIRTranslation",
"@llvm-project//mlir:TensorDialect",
"@llvm-project//mlir:TensorTransforms",
"@llvm-project//mlir:Transforms",

1
tensorflow/compiler/mlir/tools/kernel_gen/transforms/gpu_kernel_to_blob_pass.cc
View File

@ -15,7 +15,6 @@ limitations under the License.
#include "llvm/Transforms/Utils/Cloning.h"
#include "mlir/Dialect/StandardOps/IR/Ops.h" // from @llvm-project
#include "mlir/Target/LLVMIR.h" // from @llvm-project
#include "mlir/Target/LLVMIR/Export.h" // from @llvm-project
#include "mlir/Transforms/DialectConversion.h" // from @llvm-project
#include "tensorflow/compiler/mlir/hlo/include/mlir-hlo/Dialect/mhlo/IR/hlo_ops.h"

4
tensorflow/compiler/xla/service/cpu/BUILD
View File

@ -1162,10 +1162,10 @@ cc_library(
"@llvm-project//llvm:Linker",
"@llvm-project//mlir:CFGTransforms",
"@llvm-project//mlir:IR",
"@llvm-project//mlir:LLVMToLLVMIRTranslation",
"@llvm-project//mlir:LinalgTransforms",
"@llvm-project//mlir:Pass",
"@llvm-project//mlir:TargetLLVMIR",
"@llvm-project//mlir:TargetLLVMIRModuleTranslation",
"@llvm-project//mlir:ToLLVMIRTranslation",
"@llvm-project//mlir:Transforms",
"@llvm-project//mlir:VectorToLLVM",
],

1
tensorflow/compiler/xla/service/cpu/mlir_emitter.cc
View File

@ -23,7 +23,6 @@ limitations under the License.
#include "mlir/IR/BuiltinOps.h" // from @llvm-project
#include "mlir/Pass/Pass.h" // from @llvm-project
#include "mlir/Pass/PassManager.h" // from @llvm-project
#include "mlir/Target/LLVMIR.h" // from @llvm-project
#include "mlir/Target/LLVMIR/Export.h" // from @llvm-project
#include "mlir/Transforms/Passes.h" // from @llvm-project
#include "tensorflow/compiler/mlir/xla/hlo_utils.h"

4
third_party/llvm/workspace.bzl vendored
View File

@ -4,8 +4,8 @@ load("//third_party:repo.bzl", "tf_http_archive")
def repo(name):
"""Imports LLVM."""
LLVM_COMMIT = "5d7e0a23c6f2051d4caf8f8c8821790c40b584be"
LLVM_SHA256 = "dc100f5eddb35b694454ecc8cbf654b238f2e2684784d33d40536500297e9212"
LLVM_COMMIT = "c907681b077c6acf95c3ddca6611639c29559e40"
LLVM_SHA256 = "2929f1730e9ba4fea489400d81e5da21a4e79c94fea9dd3fd12e042350ff19ea"
tf_http_archive(
name = name,

135
third_party/mlir/BUILD vendored
View File

@ -201,6 +201,7 @@ cc_library(
"include/mlir-c/BuiltinTypes.h",
"include/mlir-c/Diagnostics.h",
"include/mlir-c/Dialect/Standard.h",
"include/mlir-c/ExecutionEngine.h",
"include/mlir-c/IR.h",
"include/mlir-c/IntegerSet.h",
"include/mlir-c/Pass.h",
@ -219,6 +220,7 @@ cc_library(
],
includes = ["include"],
deps = [
":ConversionPassIncGen",
":IR",
":InferTypeOpInterface",
":Parser",
@ -229,6 +231,35 @@ cc_library(
],
)
cc_library(
name = "CAPIConversion",
srcs = ["lib/CAPI/Conversion/Passes.cpp"],
hdrs = ["include/mlir-c/Conversion.h"],
includes = ["include"],
deps = [
":CAPIIR",
":ConversionPassIncGen",
":ConversionPasses",
":Pass",
],
)
cc_library(
name = "CAPIExecutionEngine",
srcs = ["lib/CAPI/ExecutionEngine/ExecutionEngine.cpp"],
hdrs = [
"include/mlir-c/ExecutionEngine.h",
"include/mlir/CAPI/ExecutionEngine.h",
],
includes = ["include"],
deps = [
":CAPIIR",
":ExecutionEngine",
":LLVMToLLVMIRTranslation",
"@llvm-project//llvm:Support",
],
)
cc_library(
name = "CAPITransforms",
srcs = ["lib/CAPI/Transforms/Passes.cpp"],
@ -259,6 +290,7 @@ cc_library(
deps = [
":AllPassesAndDialectsNoRegistration",
":CAPIIR",
":LLVMToLLVMIRTranslation",
],
)
@ -1130,6 +1162,14 @@ gentbl(
"-gen-pass-decls -name Conversion",
"include/mlir/Conversion/Passes.h.inc",
),
(
"-gen-pass-capi-header --prefix Conversion",
"include/mlir/Conversion/Passes.capi.h.inc",
),
(
"-gen-pass-capi-impl --prefix Conversion",
"include/mlir/Conversion/Passes.capi.cpp.inc",
),
],
tblgen = ":mlir-tblgen",
td_file = "include/mlir/Conversion/Passes.td",
@ -3535,7 +3575,7 @@ cc_library(
)
cc_library(
name = "TargetLLVMIRModuleTranslation",
name = "ToLLVMIRTranslation",
srcs = [
"lib/Target/LLVMIR/DebugTranslation.cpp",
"lib/Target/LLVMIR/DebugTranslation.h",
@ -3573,7 +3613,7 @@ cc_library(
":LLVMAVX512",
":LLVMAVX512ConversionIncGen",
":Support",
":TargetLLVMIRModuleTranslation",
":ToLLVMIRTranslation",
"@llvm-project//llvm:Core",
"@llvm-project//llvm:Support",
],
@ -3590,7 +3630,7 @@ cc_library(
":LLVMArmNeonConversionIncGen",
":LLVMArmNeonIncGen",
":Support",
":TargetLLVMIRModuleTranslation",
":ToLLVMIRTranslation",
"@llvm-project//llvm:Core",
"@llvm-project//llvm:Support",
],
@ -3606,7 +3646,7 @@ cc_library(
":LLVMArmSVE",
":LLVMArmSVEConversionIncGen",
":Support",
":TargetLLVMIRModuleTranslation",
":ToLLVMIRTranslation",
"@llvm-project//llvm:Core",
"@llvm-project//llvm:Support",
],
@ -3622,7 +3662,7 @@ cc_library(
":NVVMConversionIncGen",
":NVVMDialect",
":Support",
":TargetLLVMIRModuleTranslation",
":ToLLVMIRTranslation",
"@llvm-project//llvm:Core",
"@llvm-project//llvm:Support",
],
@ -3638,7 +3678,7 @@ cc_library(
":ROCDLConversionIncGen",
":ROCDLDialect",
":Support",
":TargetLLVMIRModuleTranslation",
":ToLLVMIRTranslation",
"@llvm-project//llvm:Core",
"@llvm-project//llvm:Support",
],
@ -3654,7 +3694,7 @@ cc_library(
":LLVMConversionIncGen",
":LLVMDialect",
":Support",
":TargetLLVMIRModuleTranslation",
":ToLLVMIRTranslation",
"@llvm-project//llvm:Core",
"@llvm-project//llvm:Support",
],
@ -3669,7 +3709,7 @@ cc_library(
":IR",
":OpenMPDialect",
":Support",
":TargetLLVMIRModuleTranslation",
":ToLLVMIRTranslation",
"@llvm-project//llvm:Core",
"@llvm-project//llvm:FrontendOpenMP",
"@llvm-project//llvm:Support",
@ -3677,32 +3717,46 @@ cc_library(
)
cc_library(
name = "TargetLLVMIR",
name = "AllToLLVMIRTranslations",
hdrs = ["include/mlir/Target/LLVMIR/Dialect/All.h"],
includes = ["include"],
deps = [
":LLVMAVX512ToLLVMIRTranslation",
":LLVMArmNeonToLLVMIRTranslation",
":LLVMArmSVEToLLVMIRTranslation",
":LLVMToLLVMIRTranslation",
":NVVMToLLVMIRTranslation",
":OpenMPToLLVMIRTranslation",
":ROCDLToLLVMIRTranslation",
],
)
cc_library(
name = "ToLLVMIRTranslationRegistration",
srcs = ["lib/Target/LLVMIR/ConvertToLLVMIR.cpp"],
includes = ["include"],
deps = [
":AllToLLVMIRTranslations",
":IR",
":ToLLVMIRTranslation",
":Translation",
"@llvm-project//llvm:Core",
"@llvm-project//llvm:Support",
],
)
cc_library(
name = "FromLLVMIRTranslation",
srcs = [
"lib/Target/LLVMIR/ConvertFromLLVMIR.cpp",
"lib/Target/LLVMIR/ConvertToLLVMIR.cpp",
],
hdrs = ["include/mlir/Target/LLVMIR.h"],
includes = ["include"],
deps = [
":IR",
":LLVMAVX512",
":LLVMAVX512ToLLVMIRTranslation",
":LLVMArmNeon",
":LLVMArmNeonToLLVMIRTranslation",
":LLVMArmSVE",
":LLVMArmSVEToLLVMIRTranslation",
":LLVMConversionIncGen",
":LLVMDialect",
":LLVMToLLVMIRTranslation",
":NVVMDialect",
":NVVMToLLVMIRTranslation",
":OpenMPDialect",
":OpenMPToLLVMIRTranslation",
":ROCDLDialect",
":ROCDLToLLVMIRTranslation",
":Support",
":TargetLLVMIRModuleTranslation",
":Translation",
"@llvm-project//llvm:Core",
"@llvm-project//llvm:IRReader",
@ -3722,11 +3776,11 @@ cc_library(
],
includes = ["include"],
deps = [
":AllToLLVMIRTranslations",
":IR",
":LLVMDialect",
":Support",
":TargetLLVMIR",
":TargetLLVMIRModuleTranslation",
":ToLLVMIRTranslation",
":Translation",
"@llvm-project//llvm:BitReader",
"@llvm-project//llvm:BitWriter",
@ -3789,14 +3843,9 @@ cc_library(
name = "AllTranslations",
hdrs = ["include/mlir/InitAllTranslations.h"],
deps = [
":LLVMAVX512ToLLVMIRTranslation",
":LLVMArmNeonToLLVMIRTranslation",
":LLVMArmSVEToLLVMIRTranslation",
":LLVMToLLVMIRTranslation",
":NVVMToLLVMIRTranslation",
":ROCDLToLLVMIRTranslation",
":FromLLVMIRTranslation",
":SPIRVTranslateRegistration",
":TargetLLVMIR",
":ToLLVMIRTranslationRegistration",
],
)
@ -4011,13 +4060,14 @@ cc_binary(
srcs = ["tools/mlir-cpu-runner/mlir-cpu-runner.cpp"],
linkopts = ["-ldl"],
deps = [
":AllToLLVMIRTranslations",
":ExecutionEngineUtils",
":IR",
":LLVMDialect",
":LLVMToLLVMIRTranslation",
":MlirJitRunner",
":OpenMPDialect",
":OpenMPToLLVMIRTranslation",
":TargetLLVMIR",
":ToLLVMIRTranslation",
"@llvm-project//llvm:AsmParser",
"@llvm-project//llvm:Support",
"@llvm-project//llvm:X86AsmParser",
@ -4094,13 +4144,14 @@ cc_binary(
":GPUTransforms",
":IR",
":LLVMDialect",
":LLVMToLLVMIRTranslation",
":MlirJitRunner",
":NVVMDialect",
":NVVMToLLVMIRTranslation",
":Pass",
":StandardOps",
":TargetLLVMIR",
":TargetLLVMIRModuleTranslation",
":StandardToLLVM",
":ToLLVMIRTranslation",
":Transforms",
"//devtools/build/runtime:get_runfiles_dir",
"//third_party/gpus/cuda:cuda_headers",
@ -4120,6 +4171,7 @@ cc_binary(
":GPUToVulkanTransforms",
":GPUTransforms",
":LLVMDialect",
":LLVMToLLVMIRTranslation",
":MlirJitRunner",
":Pass",
":SPIRVDialect",
@ -4127,8 +4179,7 @@ cc_binary(
":StandardOps",
":StandardToLLVM",
":StandardToSPIRV",
":TargetLLVMIR",
":TargetLLVMIRModuleTranslation",
":ToLLVMIRTranslation",
"@llvm-project//llvm:Support",
],
)
@ -4143,6 +4194,7 @@ cc_binary(
":GPUTransforms",
":IR",
":LLVMDialect",
":LLVMToLLVMIRTranslation",
":MlirJitRunner",
":Pass",
":SPIRVConversion",
@ -4151,8 +4203,7 @@ cc_binary(
":SPIRVTransforms",
":StandardOps",
":StandardToLLVM",
":TargetLLVMIR",
":TargetLLVMIRModuleTranslation",
":ToLLVMIRTranslation",
"@llvm-project//llvm:Core",
"@llvm-project//llvm:Linker",
"@llvm-project//llvm:Support",
@ -4940,7 +4991,7 @@ cc_library(
":StandardOps",
":StandardToLLVM",
":Support",
":TargetLLVMIRModuleTranslation",
":ToLLVMIRTranslation",
":Transforms",
":VectorOps",
"@llvm-project//llvm:Core",

28
third_party/mlir/test.BUILD vendored
View File

@ -124,6 +124,27 @@ gentbl(
test = True,
)
gentbl(
name = "TestAttrDefsIncGen",
strip_include_prefix = "lib/Dialect/Test",
tbl_outs = [
(
"-gen-attrdef-decls",
"lib/Dialect/Test/TestAttrDefs.h.inc",
),
(
"-gen-attrdef-defs",
"lib/Dialect/Test/TestAttrDefs.cpp.inc",
),
],
tblgen = "@llvm-project//mlir:mlir-tblgen",
td_file = "lib/Dialect/Test/TestAttrDefs.td",
td_srcs = [
":TestOpTdFiles",
],
test = True,
)
gentbl(
name = "TestTypeDefsIncGen",
strip_include_prefix = "lib/Dialect/Test",
@ -148,6 +169,7 @@ gentbl(
cc_library(
name = "TestDialect",
srcs = [
"lib/Dialect/Test/TestAttributes.cpp",
"lib/Dialect/Test/TestDialect.cpp",
"lib/Dialect/Test/TestInterfaces.cpp",
"lib/Dialect/Test/TestPatterns.cpp",
@ -155,6 +177,7 @@ cc_library(
"lib/Dialect/Test/TestTypes.cpp",
],
hdrs = [
"lib/Dialect/Test/TestAttributes.h",
"lib/Dialect/Test/TestDialect.h",
"lib/Dialect/Test/TestInterfaces.h",
"lib/Dialect/Test/TestTypes.h",
@ -163,6 +186,7 @@ cc_library(
"lib/Dialect/Test",
],
deps = [
":TestAttrDefsIncGen",
":TestInterfacesIncGen",
":TestOpsIncGen",
":TestTypeDefsIncGen",
@ -262,6 +286,7 @@ cc_library(
"@llvm-project//mlir:GPUTransforms",
"@llvm-project//mlir:IR",
"@llvm-project//mlir:LLVMDialect",
"@llvm-project//mlir:LLVMToLLVMIRTranslation",
"@llvm-project//mlir:LLVMTransforms",
"@llvm-project//mlir:LinalgOps",
"@llvm-project//mlir:LinalgTransforms",
@ -277,8 +302,7 @@ cc_library(
"@llvm-project//mlir:StandardOps",
"@llvm-project//mlir:StandardOpsTransforms",
"@llvm-project//mlir:Support",
"@llvm-project//mlir:TargetLLVMIR",
"@llvm-project//mlir:TargetLLVMIRModuleTranslation",
"@llvm-project//mlir:ToLLVMIRTranslation",
"@llvm-project//mlir:TransformUtils",
"@llvm-project//mlir:Transforms",
"@llvm-project//mlir:VectorOps",