[mlir][spirv] Add Cast/Rescale ops in TOSA Ext Inst Set (#189028)
This patch introduces the following operators: spirv.Tosa.Cast spirv.Tosa.Rescale Also dialect and serialization round-trip tests have been added. Signed-off-by: Davide Grohmann <davide.grohmann@arm.com>
This commit is contained in:
Davide Grohmann
GitHub
parent
5d051f628c
commit
d5f7acdbc1
@ -4985,4 +4985,15 @@ def SPIRV_TosaExtNaNPropagationModeAttr : SPIRV_I32EnumAttr<
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I32EnumAttrCase<"Ignore", 2>,
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]>;
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// NOTE: This is an attribute in the SPIR-V *dialect* but a constant (<id>) in
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// SPIR-V proper.
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def SPIRV_TosaExtRoundingModeAttr : SPIRV_I32EnumAttr<
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"TosaExtRoundingModeType", "Tosa Ext Rounding Mode Type",
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"tosa_ext_rounding_mode_type",
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[
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I32EnumAttrCase<"SingleRound", 1>,
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I32EnumAttrCase<"InexactRound", 2>,
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I32EnumAttrCase<"DoubleRound", 3>,
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]>;
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#endif // MLIR_DIALECT_SPIRV_IR_BASE
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@ -2648,4 +2648,137 @@ def SPIRV_TosaResizeOp : SPIRV_TosaOpWithResult<"Resize", 63, [Pure,
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}
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def SPIRV_TosaCastOp : SPIRV_TosaOpWithResult<"Cast", 64, [Pure,
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AllShapesMatch<["input", "output"]>]> {
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let summary = "Cast operation.";
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let description = [{
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Casts a tensor from one data type to another.
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References:
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* https://github.khronos.org/SPIRV-Registry/extended/TOSA.001000.1.html#_cast
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* https://www.mlplatform.org/tosa/tosa_spec_1_0_1.html#_cast
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#### Example:
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```mlir
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%0 = spirv.Tosa.Cast %arg0 : !spirv.arm.tensor<1x65538x1x2xi8> -> !spirv.arm.tensor<1x65538x1x2xi32>
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%0 = spirv.Tosa.Cast %arg0 : !spirv.arm.tensor<11x5x14x4xf32> -> !spirv.arm.tensor<11x5x14x4xf16>
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```
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}];
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let arguments = (ins
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SPIRV_TosaAny_TensorArm: $input
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);
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let results = (outs
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SPIRV_TosaAny_TensorArm: $output
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);
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let assemblyFormat = [{
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$input
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attr-dict `:` type(operands) `->` type(results)
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}];
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let extraClassDeclaration = extraBaseClassDeclaration#[{
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::mlir::spirv::TensorArmType getInputType() {
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return cast<::mlir::spirv::TensorArmType>(getInput().getType());
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}
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}];
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}
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def SPIRV_TosaRescaleOp : SPIRV_TosaOpWithResult<"Rescale", 65, [NoMemoryEffect,
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AllShapesMatch<["input", "output"]>,
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AllElementTypesMatch<["input", "input_zp"]>,
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AllElementTypesMatch<["output", "output_zp"]>,
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ElementTypeMatchesScale32<"multiplier">,
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TensorLengthMatchesPerChannel<"multiplier">,
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TensorLengthMatchesPerChannel<"shift">,
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TypeConstraintImplicationOn<"input", I8, "output", [I8, I16, I32]>,
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TypeConstraintImplicationOn<"input", I16, "output", [I8, I16, I32]>,
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TypeConstraintImplicationOn<"input", I32, "output", [I8, I16, I32]>,
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TypeConstraintImplicationOn<"input", I64, "output", [I8, I16, I32]>,
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BoolAttrTypeConstraintImplicationOn<"input_unsigned", "input", [I8, I16]>,
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BoolAttrTypeConstraintImplicationOn<"output_unsigned", "input", [I8, I16]>,
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BoolAttrTypeConstraintImplicationOn<"input_unsigned", "output", [I8, I16]>,
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BoolAttrTypeConstraintImplicationOn<"output_unsigned", "output", [I8, I16]>]> {
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let summary = "Rescale operator.";
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let description = [{
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Rescale is defined using an integer multiply, add, and shift.
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Rescale supports two precisions of multiplier: 16-bit and 32-bit. The
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32-bit multiplier version supports two rounding modes to enable simpler
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lowering of existing frameworks that use two stage rounding. All arithmetic
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is designed so that it does not overflow a 64-bit accumulator and that the
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result fits in 32 bits. In particular, a 48-bit value (represented as a
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64-bit value in SPIR-V) cannot be scaled with the 32-bit multiplier because
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the accumulator would need to have 80 bits.
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The shift and value range are limited to allow a variety of implementations.
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The limit of 62 on shift allows the shift to be decomposed as two right
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shifts of 31.
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Unsigned 8- and 16-bit values are only allowed in the Rescale operation,
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to allow for compatibility with networks which expect unsigned 8-bit or
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16-bit tensors for input and output.
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Undefined behaviour may occur if the calculated result underflows or overflows
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their integer ranges.
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References:
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* https://github.khronos.org/SPIRV-Registry/extended/TOSA.001000.1.html#_rescale
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* https://www.mlplatform.org/tosa/tosa_spec_1_0_1.html#_rescale
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#### Example:
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```mlir
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%9 = spirv.Tosa.Rescale scale32 = true, rounding_mode = <DoubleRound>, per_channel = false, input_unsigned = false, output_unsigned = true, %arg0, %multiplier, %shift, %input_zp, %output_zp : !spirv.arm.tensor<17x29x19xi16>, !spirv.arm.tensor<1xi32>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi16> -> !spirv.arm.tensor<17x29x19xi16>
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```
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}];
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let arguments = (ins
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SPIRV_BoolConstAttr: $scale32,
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SPIRV_TosaExtRoundingModeAttr: $rounding_mode,
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SPIRV_BoolConstAttr: $per_channel,
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SPIRV_BoolConstAttr: $input_unsigned,
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SPIRV_BoolConstAttr: $output_unsigned,
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SPIRV_TosaInteger_TensorArm: $input,
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SPIRV_Int16OrInt32_TensorArm1D: $multiplier,
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SPIRV_Int8_TensorArm1D: $shift,
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SPIRV_TosaInteger_1DTensorArmOfLength1: $input_zp,
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SPIRV_TosaInteger_1DTensorArmOfLength1: $output_zp
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);
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let results = (outs
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SPIRV_TosaInteger_TensorArm: $output
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);
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let assemblyFormat = [{
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`scale32` `=` $scale32 `,`
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`rounding_mode` `=` $rounding_mode `,`
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`per_channel` `=` $per_channel `,`
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`input_unsigned` `=` $input_unsigned `,`
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`output_unsigned` `=` $output_unsigned `,`
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$input `,`
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$multiplier `,`
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$shift `,`
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$input_zp `,`
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$output_zp
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attr-dict `:` type(operands) `->` type(results)
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}];
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let extraClassDeclaration = extraBaseClassDeclaration#[{
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::mlir::spirv::TensorArmType getInputType() {
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return cast<::mlir::spirv::TensorArmType>(getInput().getType());
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}
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::mlir::spirv::TensorArmType getMultiplierType() {
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return cast<::mlir::spirv::TensorArmType>(getMultiplier().getType());
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}
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::mlir::spirv::TensorArmType getShiftType() {
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return cast<::mlir::spirv::TensorArmType>(getShift().getType());
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}
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}];
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}
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#endif // MLIR_DIALECT_SPIRV_IR_TOSA_OPS
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@ -38,6 +38,8 @@ class TensorArmRankOf<list<Type> allowedTypes, list<int> ranks>
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[HasAnyRankOfPred<ranks>],
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!interleave(!foreach(rank, ranks, rank # "D"), "/") # " tensorArm">;
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def SPIRV_Int8_TensorArm1D : TensorArmRankOf<[SPIRV_Int8], [1]>;
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def SPIRV_Int16OrInt32_TensorArm1D : TensorArmRankOf<[SPIRV_Int16, SPIRV_Int32], [1]>;
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def SPIRV_Int32_TensorArm2D : TensorArmRankOf<[SPIRV_Int32], [2]>;
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def SPIRV_Float32_TensorArm3D: TensorArmRankOf<[SPIRV_Float32], [3]>;
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def SPIRV_TosaInteger_TensorArm1D : TensorArmRankOf<[SPIRV_TosaInteger], [1]>;
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@ -92,6 +94,7 @@ def SPIRV_Int32_1DTensorArmOfLength1To6Attr : ConfinedAttr<
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I32ElementsAttr, [SPIRV_DenseElementAttrsWithTensorArmType, Is1DTensorArmAttrOfLength<[1, 2, 3, 4, 5, 6]>]>;
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def SPIRV_Int8_1DTensorArmOfLength1 : SPIRV_1DTensorArmOfLengthAndType<[1], [SPIRV_Int8]>;
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def SPIRV_TosaInteger_1DTensorArmOfLength1 : SPIRV_1DTensorArmOfLengthAndType<[1], [SPIRV_TosaInteger]>;
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def SPIRV_TosaNumerical_1DTensorArmOfLength1 : SPIRV_1DTensorArmOfLengthAndType<[1], [SPIRV_TosaNumerical]>;
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def SPIRV_TosaAny_1DTensorArmOfLength1 : SPIRV_1DTensorArmOfLengthAndType<[1], [SPIRV_TosaAny]>;
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@ -121,6 +124,13 @@ class TypeConstraintImplicationOn<string name, Type type, string other, list<Typ
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Implies<ElementTypeIsPred<name, type>,
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!foreach(allowedType, allowedTypes, ElementTypeIsPred<other, allowedType>)>>;
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class BoolAttrTypeConstraintImplicationOn<string boolAttr, string other, list<Type> allowedTypes>:
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PredOpTrait<"if " # boolAttr # " is true then " #
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other # " must have a type in [" #
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!interleave(!foreach(type, allowedTypes, type.summary), ",") # "]",
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Implies<CPred<"get" # snakeCaseToCamelCase<boolAttr>.ret # "()" >,
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!foreach(allowedType, allowedTypes, ElementTypeIsPred<other, allowedType>)>>;
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class AxisValueLessThanRankOf<string input>:
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PredOpTrait<"axis attribute value should be lower than rank(" # input # ")",
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Implies<CPred<HasRank<input>.result>, [CPred<"getAxis() < " # Rank<input>.result>]>>;
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@ -201,5 +211,16 @@ class VariadicInputAllSameRank<string reference, string input>:
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" && ::llvm::cast<::mlir::ShapedType>(t).getRank() == "
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# Rank<reference>.result # "; })">>;
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class ElementTypeMatchesScale32<string tensor> :
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PredOpTrait<tensor # " must have element type i32 when scale32 is true, otherwise i16",
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CPred<"::llvm::cast<::mlir::ShapedType>($" # tensor # ".getType()).getElementType()."
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"isInteger(getScale32() ? 32 : 16)">>;
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class TensorLengthMatchesPerChannel<string tensor> :
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PredOpTrait<tensor # " must have length rank(input) - 1 when per_channel is true, otherwise length 1",
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CPred<"::llvm::cast<::mlir::ShapedType>($" # tensor # ".getType()).getShape()[0] == "
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"(getPerChannel() ? "
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"::llvm::cast<::mlir::ShapedType>($input.getType()).getRank() - 1 : 1)">>;
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#endif // MLIR_DIALECT_SPIRV_IR_TOSA_TYPES
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@ -1940,3 +1940,187 @@ spirv.ARM.Graph @resize_bf16_input_output_element_type_must_be_bf16(%arg0: !spir
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%4 = spirv.Tosa.Resize mode = <Bilinear>, %arg0, %1, %2, %3 : !spirv.arm.tensor<1x48x33x63xbf16>, !spirv.arm.tensor<4xi32>, !spirv.arm.tensor<2xi32>, !spirv.arm.tensor<2xi32> -> !spirv.arm.tensor<1x753x297x63xf32>
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spirv.ARM.GraphOutputs %4 : !spirv.arm.tensor<1x753x297x63xf32>
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}
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//===----------------------------------------------------------------------===//
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// spirv.TOSA.Cast
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//===----------------------------------------------------------------------===//
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spirv.ARM.Graph @cast_input_output_shapes_not_matching(%arg0: !spirv.arm.tensor<2x3x4xi8>) -> (!spirv.arm.tensor<2x3x5xi32>) {
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// expected-error @+1 {{op failed to verify that all of {input, output} have same shape}}
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%0 = spirv.Tosa.Cast %arg0 : !spirv.arm.tensor<2x3x4xi8> -> !spirv.arm.tensor<2x3x5xi32>
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spirv.ARM.GraphOutputs %0 : !spirv.arm.tensor<2x3x5xi32>
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}
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//===----------------------------------------------------------------------===//
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// spirv.TOSA.Rescale
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//===----------------------------------------------------------------------===//
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spirv.ARM.Graph @rescale_input_output_shapes_not_matching(%arg0: !spirv.arm.tensor<2x3x4xi16>) -> (!spirv.arm.tensor<2x3x5xi16>) {
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%1 = spirv.Constant dense<1> : !spirv.arm.tensor<1xi16>
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%2 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi8>
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%3 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
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%4 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
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// expected-error @+1 {{op failed to verify that all of {input, output} have same shape}}
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%5 = spirv.Tosa.Rescale scale32 = false, rounding_mode = <SingleRound>, per_channel = false, input_unsigned = false, output_unsigned = false, %arg0, %1, %2, %3, %4 : !spirv.arm.tensor<2x3x4xi16>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi16> -> !spirv.arm.tensor<2x3x5xi16>
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spirv.ARM.GraphOutputs %5 : !spirv.arm.tensor<2x3x5xi16>
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}
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spirv.ARM.Graph @rescale_input_and_input_zp_element_types_not_matching(%arg0: !spirv.arm.tensor<2x3x4xi16>) -> (!spirv.arm.tensor<2x3x4xi16>) {
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%1 = spirv.Constant dense<1> : !spirv.arm.tensor<1xi16>
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%2 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi8>
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%3 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi8>
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%4 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
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// expected-error @+1 {{op failed to verify that all of {input, input_zp} have same element type}}
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%5 = spirv.Tosa.Rescale scale32 = false, rounding_mode = <SingleRound>, per_channel = false, input_unsigned = false, output_unsigned = false, %arg0, %1, %2, %3, %4 : !spirv.arm.tensor<2x3x4xi16>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi16> -> !spirv.arm.tensor<2x3x4xi16>
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spirv.ARM.GraphOutputs %5 : !spirv.arm.tensor<2x3x4xi16>
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}
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spirv.ARM.Graph @rescale_output_and_output_zp_element_types_not_matching(%arg0: !spirv.arm.tensor<2x3x4xi16>) -> (!spirv.arm.tensor<2x3x4xi16>) {
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%1 = spirv.Constant dense<1> : !spirv.arm.tensor<1xi16>
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%2 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi8>
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%3 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
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%4 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi8>
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// expected-error @+1 {{op failed to verify that all of {output, output_zp} have same element type}}
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%5 = spirv.Tosa.Rescale scale32 = false, rounding_mode = <SingleRound>, per_channel = false, input_unsigned = false, output_unsigned = false, %arg0, %1, %2, %3, %4 : !spirv.arm.tensor<2x3x4xi16>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi8> -> !spirv.arm.tensor<2x3x4xi16>
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spirv.ARM.GraphOutputs %5 : !spirv.arm.tensor<2x3x4xi16>
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}
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spirv.ARM.Graph @rescale_scale32_true_requires_i32_multiplier(%arg0: !spirv.arm.tensor<2x3x4xi16>) -> (!spirv.arm.tensor<2x3x4xi16>) {
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%1 = spirv.Constant dense<1> : !spirv.arm.tensor<1xi16>
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%2 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi8>
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%3 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
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%4 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
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// expected-error @+1 {{op failed to verify that multiplier must have element type i32 when scale32 is true, otherwise i16}}
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%5 = spirv.Tosa.Rescale scale32 = true, rounding_mode = <SingleRound>, per_channel = false, input_unsigned = false, output_unsigned = false, %arg0, %1, %2, %3, %4 : !spirv.arm.tensor<2x3x4xi16>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi16> -> !spirv.arm.tensor<2x3x4xi16>
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spirv.ARM.GraphOutputs %5 : !spirv.arm.tensor<2x3x4xi16>
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}
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spirv.ARM.Graph @rescale_scale32_false_requires_i16_multiplier(%arg0: !spirv.arm.tensor<2x3x4xi16>) -> (!spirv.arm.tensor<2x3x4xi16>) {
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%1 = spirv.Constant dense<1> : !spirv.arm.tensor<1xi32>
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%2 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi8>
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%3 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
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%4 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
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// expected-error @+1 {{op failed to verify that multiplier must have element type i32 when scale32 is true, otherwise i16}}
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%5 = spirv.Tosa.Rescale scale32 = false, rounding_mode = <SingleRound>, per_channel = false, input_unsigned = false, output_unsigned = false, %arg0, %1, %2, %3, %4 : !spirv.arm.tensor<2x3x4xi16>, !spirv.arm.tensor<1xi32>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi16> -> !spirv.arm.tensor<2x3x4xi16>
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spirv.ARM.GraphOutputs %5 : !spirv.arm.tensor<2x3x4xi16>
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}
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spirv.ARM.Graph @rescale_per_channel_true_requires_multiplier_length_rank_minus_one(%arg0: !spirv.arm.tensor<2x3x4xi16>) -> (!spirv.arm.tensor<2x3x4xi16>) {
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%1 = spirv.Constant dense<[1]> : !spirv.arm.tensor<1xi16>
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%2 = spirv.Constant dense<[0, 0]> : !spirv.arm.tensor<2xi8>
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%3 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
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%4 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
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// expected-error @+1 {{op failed to verify that multiplier must have length rank(input) - 1 when per_channel is true, otherwise length 1}}
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%5 = spirv.Tosa.Rescale scale32 = false, rounding_mode = <SingleRound>, per_channel = true, input_unsigned = false, output_unsigned = false, %arg0, %1, %2, %3, %4 : !spirv.arm.tensor<2x3x4xi16>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<2xi8>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi16> -> !spirv.arm.tensor<2x3x4xi16>
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spirv.ARM.GraphOutputs %5 : !spirv.arm.tensor<2x3x4xi16>
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}
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spirv.ARM.Graph @rescale_per_channel_true_requires_shift_length_rank_minus_one(%arg0: !spirv.arm.tensor<2x3x4xi16>) -> (!spirv.arm.tensor<2x3x4xi16>) {
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%1 = spirv.Constant dense<[1, 1]> : !spirv.arm.tensor<2xi16>
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%2 = spirv.Constant dense<[0]> : !spirv.arm.tensor<1xi8>
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%3 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
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%4 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
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// expected-error @+1 {{op failed to verify that shift must have length rank(input) - 1 when per_channel is true, otherwise length 1}}
|
||||
%5 = spirv.Tosa.Rescale scale32 = false, rounding_mode = <SingleRound>, per_channel = true, input_unsigned = false, output_unsigned = false, %arg0, %1, %2, %3, %4 : !spirv.arm.tensor<2x3x4xi16>, !spirv.arm.tensor<2xi16>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi16> -> !spirv.arm.tensor<2x3x4xi16>
|
||||
spirv.ARM.GraphOutputs %5 : !spirv.arm.tensor<2x3x4xi16>
|
||||
}
|
||||
|
||||
spirv.ARM.Graph @rescale_per_channel_false_requires_multiplier_length_one(%arg0: !spirv.arm.tensor<2x3x4xi16>) -> (!spirv.arm.tensor<2x3x4xi16>) {
|
||||
%1 = spirv.Constant dense<[1, 1]> : !spirv.arm.tensor<2xi16>
|
||||
%2 = spirv.Constant dense<[0]> : !spirv.arm.tensor<1xi8>
|
||||
%3 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
|
||||
%4 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
|
||||
// expected-error @+1 {{op failed to verify that multiplier must have length rank(input) - 1 when per_channel is true, otherwise length 1}}
|
||||
%5 = spirv.Tosa.Rescale scale32 = false, rounding_mode = <SingleRound>, per_channel = false, input_unsigned = false, output_unsigned = false, %arg0, %1, %2, %3, %4 : !spirv.arm.tensor<2x3x4xi16>, !spirv.arm.tensor<2xi16>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi16> -> !spirv.arm.tensor<2x3x4xi16>
|
||||
spirv.ARM.GraphOutputs %5 : !spirv.arm.tensor<2x3x4xi16>
|
||||
}
|
||||
|
||||
spirv.ARM.Graph @rescale_per_channel_false_requires_shift_length_one(%arg0: !spirv.arm.tensor<2x3x4xi16>) -> (!spirv.arm.tensor<2x3x4xi16>) {
|
||||
%1 = spirv.Constant dense<[1]> : !spirv.arm.tensor<1xi16>
|
||||
%2 = spirv.Constant dense<[0, 0]> : !spirv.arm.tensor<2xi8>
|
||||
%3 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
|
||||
%4 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
|
||||
// expected-error @+1 {{op failed to verify that shift must have length rank(input) - 1 when per_channel is true, otherwise length 1}}
|
||||
%5 = spirv.Tosa.Rescale scale32 = false, rounding_mode = <SingleRound>, per_channel = false, input_unsigned = false, output_unsigned = false, %arg0, %1, %2, %3, %4 : !spirv.arm.tensor<2x3x4xi16>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<2xi8>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi16> -> !spirv.arm.tensor<2x3x4xi16>
|
||||
spirv.ARM.GraphOutputs %5 : !spirv.arm.tensor<2x3x4xi16>
|
||||
}
|
||||
|
||||
spirv.ARM.Graph @rescale_i8_input_requires_i8_i16_or_i32_output(%arg0: !spirv.arm.tensor<2x3x4xi8>) -> (!spirv.arm.tensor<2x3x4xi64>) {
|
||||
%1 = spirv.Constant dense<1> : !spirv.arm.tensor<1xi16>
|
||||
%2 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi8>
|
||||
%3 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi8>
|
||||
%4 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi64>
|
||||
// expected-error @+1 {{op failed to verify that if input has type 8-bit signless integer then output must have a type in [8-bit signless integer,16-bit signless integer,32-bit signless integer]}}
|
||||
%5 = spirv.Tosa.Rescale scale32 = false, rounding_mode = <SingleRound>, per_channel = false, input_unsigned = false, output_unsigned = false, %arg0, %1, %2, %3, %4 : !spirv.arm.tensor<2x3x4xi8>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi64> -> !spirv.arm.tensor<2x3x4xi64>
|
||||
spirv.ARM.GraphOutputs %5 : !spirv.arm.tensor<2x3x4xi64>
|
||||
}
|
||||
|
||||
spirv.ARM.Graph @rescale_i16_input_requires_i8_i16_or_i32_output(%arg0: !spirv.arm.tensor<2x3x4xi16>) -> (!spirv.arm.tensor<2x3x4xi64>) {
|
||||
%1 = spirv.Constant dense<1> : !spirv.arm.tensor<1xi16>
|
||||
%2 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi8>
|
||||
%3 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
|
||||
%4 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi64>
|
||||
// expected-error @+1 {{op failed to verify that if input has type 16-bit signless integer then output must have a type in [8-bit signless integer,16-bit signless integer,32-bit signless integer]}}
|
||||
%5 = spirv.Tosa.Rescale scale32 = false, rounding_mode = <SingleRound>, per_channel = false, input_unsigned = false, output_unsigned = false, %arg0, %1, %2, %3, %4 : !spirv.arm.tensor<2x3x4xi16>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi64> -> !spirv.arm.tensor<2x3x4xi64>
|
||||
spirv.ARM.GraphOutputs %5 : !spirv.arm.tensor<2x3x4xi64>
|
||||
}
|
||||
|
||||
spirv.ARM.Graph @rescale_i32_input_requires_i8_i16_or_i32_output(%arg0: !spirv.arm.tensor<2x3x4xi32>) -> (!spirv.arm.tensor<2x3x4xi64>) {
|
||||
%1 = spirv.Constant dense<1> : !spirv.arm.tensor<1xi16>
|
||||
%2 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi8>
|
||||
%3 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi32>
|
||||
%4 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi64>
|
||||
// expected-error @+1 {{op failed to verify that if input has type 32-bit signless integer then output must have a type in [8-bit signless integer,16-bit signless integer,32-bit signless integer]}}
|
||||
%5 = spirv.Tosa.Rescale scale32 = false, rounding_mode = <SingleRound>, per_channel = false, input_unsigned = false, output_unsigned = false, %arg0, %1, %2, %3, %4 : !spirv.arm.tensor<2x3x4xi32>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi32>, !spirv.arm.tensor<1xi64> -> !spirv.arm.tensor<2x3x4xi64>
|
||||
spirv.ARM.GraphOutputs %5 : !spirv.arm.tensor<2x3x4xi64>
|
||||
}
|
||||
|
||||
spirv.ARM.Graph @rescale_i64_input_requires_i8_i16_or_i32_output(%arg0: !spirv.arm.tensor<2x3x4xi64>) -> (!spirv.arm.tensor<2x3x4xi64>) {
|
||||
%1 = spirv.Constant dense<1> : !spirv.arm.tensor<1xi16>
|
||||
%2 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi8>
|
||||
%3 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi64>
|
||||
%4 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi64>
|
||||
// expected-error @+1 {{op failed to verify that if input has type 64-bit signless integer then output must have a type in [8-bit signless integer,16-bit signless integer,32-bit signless integer]}}
|
||||
%5 = spirv.Tosa.Rescale scale32 = false, rounding_mode = <SingleRound>, per_channel = false, input_unsigned = false, output_unsigned = false, %arg0, %1, %2, %3, %4 : !spirv.arm.tensor<2x3x4xi64>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi64>, !spirv.arm.tensor<1xi64> -> !spirv.arm.tensor<2x3x4xi64>
|
||||
spirv.ARM.GraphOutputs %5 : !spirv.arm.tensor<2x3x4xi64>
|
||||
}
|
||||
|
||||
spirv.ARM.Graph @rescale_input_unsigned_true_requires_i8_or_i16_input(%arg0: !spirv.arm.tensor<2x3x4xi32>) -> (!spirv.arm.tensor<2x3x4xi16>) {
|
||||
%1 = spirv.Constant dense<1> : !spirv.arm.tensor<1xi16>
|
||||
%2 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi8>
|
||||
%3 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi32>
|
||||
%4 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
|
||||
// expected-error @+1 {{op failed to verify that if input_unsigned is true then input must have a type in [8-bit signless integer,16-bit signless integer]}}
|
||||
%5 = spirv.Tosa.Rescale scale32 = false, rounding_mode = <SingleRound>, per_channel = false, input_unsigned = true, output_unsigned = false, %arg0, %1, %2, %3, %4 : !spirv.arm.tensor<2x3x4xi32>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi32>, !spirv.arm.tensor<1xi16> -> !spirv.arm.tensor<2x3x4xi16>
|
||||
spirv.ARM.GraphOutputs %5 : !spirv.arm.tensor<2x3x4xi16>
|
||||
}
|
||||
|
||||
spirv.ARM.Graph @rescale_output_unsigned_true_requires_i8_or_i16_input(%arg0: !spirv.arm.tensor<2x3x4xi32>) -> (!spirv.arm.tensor<2x3x4xi16>) {
|
||||
%1 = spirv.Constant dense<1> : !spirv.arm.tensor<1xi16>
|
||||
%2 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi8>
|
||||
%3 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi32>
|
||||
%4 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
|
||||
// expected-error @+1 {{op failed to verify that if output_unsigned is true then input must have a type in [8-bit signless integer,16-bit signless integer]}}
|
||||
%5 = spirv.Tosa.Rescale scale32 = false, rounding_mode = <SingleRound>, per_channel = false, input_unsigned = false, output_unsigned = true, %arg0, %1, %2, %3, %4 : !spirv.arm.tensor<2x3x4xi32>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi32>, !spirv.arm.tensor<1xi16> -> !spirv.arm.tensor<2x3x4xi16>
|
||||
spirv.ARM.GraphOutputs %5 : !spirv.arm.tensor<2x3x4xi16>
|
||||
}
|
||||
|
||||
spirv.ARM.Graph @rescale_input_unsigned_true_requires_i8_or_i16_output(%arg0: !spirv.arm.tensor<2x3x4xi16>) -> (!spirv.arm.tensor<2x3x4xi32>) {
|
||||
%1 = spirv.Constant dense<1> : !spirv.arm.tensor<1xi16>
|
||||
%2 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi8>
|
||||
%3 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
|
||||
%4 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi32>
|
||||
// expected-error @+1 {{op failed to verify that if input_unsigned is true then output must have a type in [8-bit signless integer,16-bit signless integer]}}
|
||||
%5 = spirv.Tosa.Rescale scale32 = false, rounding_mode = <SingleRound>, per_channel = false, input_unsigned = true, output_unsigned = false, %arg0, %1, %2, %3, %4 : !spirv.arm.tensor<2x3x4xi16>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi32> -> !spirv.arm.tensor<2x3x4xi32>
|
||||
spirv.ARM.GraphOutputs %5 : !spirv.arm.tensor<2x3x4xi32>
|
||||
}
|
||||
|
||||
spirv.ARM.Graph @rescale_output_unsigned_true_requires_i8_or_i16_output(%arg0: !spirv.arm.tensor<2x3x4xi16>) -> (!spirv.arm.tensor<2x3x4xi32>) {
|
||||
%1 = spirv.Constant dense<1> : !spirv.arm.tensor<1xi16>
|
||||
%2 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi8>
|
||||
%3 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
|
||||
%4 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi32>
|
||||
// expected-error @+1 {{op failed to verify that if output_unsigned is true then output must have a type in [8-bit signless integer,16-bit signless integer]}}
|
||||
%5 = spirv.Tosa.Rescale scale32 = false, rounding_mode = <SingleRound>, per_channel = false, input_unsigned = false, output_unsigned = true, %arg0, %1, %2, %3, %4 : !spirv.arm.tensor<2x3x4xi16>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi32> -> !spirv.arm.tensor<2x3x4xi32>
|
||||
spirv.ARM.GraphOutputs %5 : !spirv.arm.tensor<2x3x4xi32>
|
||||
}
|
||||
|
||||
@ -1123,3 +1123,40 @@ spirv.ARM.Graph @resize_fp(%arg0: !spirv.arm.tensor<1x48x33x63xf32>) -> (!spirv.
|
||||
// CHECK: spirv.ARM.GraphOutputs {{%.*}} : !spirv.arm.tensor<1x753x297x63xf32>
|
||||
spirv.ARM.GraphOutputs %4 : !spirv.arm.tensor<1x753x297x63xf32>
|
||||
}
|
||||
|
||||
//===----------------------------------------------------------------------===//
|
||||
// spirv.TOSA.Cast - PRO-INT
|
||||
//===----------------------------------------------------------------------===//
|
||||
|
||||
spirv.ARM.Graph @cast_int(%arg0: !spirv.arm.tensor<1x65538x1x2xi8>) -> (!spirv.arm.tensor<1x65538x1x2xi32>) {
|
||||
// CHECK: {{%.*}} = spirv.Tosa.Cast %arg0 : !spirv.arm.tensor<1x65538x1x2xi8> -> !spirv.arm.tensor<1x65538x1x2xi32>
|
||||
%0 = spirv.Tosa.Cast %arg0 : !spirv.arm.tensor<1x65538x1x2xi8> -> !spirv.arm.tensor<1x65538x1x2xi32>
|
||||
// CHECK: spirv.ARM.GraphOutputs {{%.*}} : !spirv.arm.tensor<1x65538x1x2xi32>
|
||||
spirv.ARM.GraphOutputs %0 : !spirv.arm.tensor<1x65538x1x2xi32>
|
||||
}
|
||||
|
||||
//===----------------------------------------------------------------------===//
|
||||
// spirv.TOSA.Cast - PRO-FP
|
||||
//===----------------------------------------------------------------------===//
|
||||
|
||||
spirv.ARM.Graph @cast_fp(%arg0: !spirv.arm.tensor<11x5x14x4xf32>) -> (!spirv.arm.tensor<11x5x14x4xf16>) {
|
||||
// CHECK: {{%.*}} = spirv.Tosa.Cast %arg0 : !spirv.arm.tensor<11x5x14x4xf32> -> !spirv.arm.tensor<11x5x14x4xf16>
|
||||
%0 = spirv.Tosa.Cast %arg0 : !spirv.arm.tensor<11x5x14x4xf32> -> !spirv.arm.tensor<11x5x14x4xf16>
|
||||
// CHECK: spirv.ARM.GraphOutputs {{%.*}} : !spirv.arm.tensor<11x5x14x4xf16>
|
||||
spirv.ARM.GraphOutputs %0 : !spirv.arm.tensor<11x5x14x4xf16>
|
||||
}
|
||||
|
||||
//===----------------------------------------------------------------------===//
|
||||
// spirv.TOSA.Rescale - PRO-INT
|
||||
//===----------------------------------------------------------------------===//
|
||||
|
||||
spirv.ARM.Graph @rescale_int(%arg0: !spirv.arm.tensor<17x29x19xi16>) -> (!spirv.arm.tensor<17x29x19xi16>) {
|
||||
%5 = spirv.Constant dense<1866149760> : !spirv.arm.tensor<1xi32>
|
||||
%6 = spirv.Constant dense<31> : !spirv.arm.tensor<1xi8>
|
||||
%7 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
|
||||
%8 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
|
||||
// CHECK: {{%.*}} = spirv.Tosa.Rescale scale32 = true, rounding_mode = <DoubleRound>, per_channel = false, input_unsigned = false, output_unsigned = true, %arg0, {{%.*}}, {{%.*}}, {{%.*}}, {{%.*}} : !spirv.arm.tensor<17x29x19xi16>, !spirv.arm.tensor<1xi32>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi16> -> !spirv.arm.tensor<17x29x19xi16>
|
||||
%9 = spirv.Tosa.Rescale scale32 = true, rounding_mode = <DoubleRound>, per_channel = false, input_unsigned = false, output_unsigned = true, %arg0, %5, %6, %7, %8 : !spirv.arm.tensor<17x29x19xi16>, !spirv.arm.tensor<1xi32>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi16> -> !spirv.arm.tensor<17x29x19xi16>
|
||||
// CHECK: spirv.ARM.GraphOutputs {{%.*}} : !spirv.arm.tensor<17x29x19xi16>
|
||||
spirv.ARM.GraphOutputs %9 : !spirv.arm.tensor<17x29x19xi16>
|
||||
}
|
||||
|
||||
@ -1964,3 +1964,64 @@ spirv.module Logical Vulkan requires #spirv.vce<v1.3, [VulkanMemoryModel, Shader
|
||||
spirv.ARM.GraphOutputs %4 : !spirv.arm.tensor<1x753x297x63xf32>
|
||||
}
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
//===----------------------------------------------------------------------===//
|
||||
// spirv.TOSA.Cast - PRO-INT
|
||||
//===----------------------------------------------------------------------===//
|
||||
|
||||
// CHECK: spirv.module Logical Vulkan requires #spirv.vce<v1.3, [VulkanMemoryModel, Shader, Int8, Int16, Int64, Float16, TensorsARM, GraphARM], [SPV_ARM_tensors, SPV_ARM_graph, SPV_KHR_vulkan_memory_model]>
|
||||
spirv.module Logical Vulkan requires #spirv.vce<v1.3, [VulkanMemoryModel, Shader, Int8, Int16, Int64, Float16, TensorsARM, GraphARM], [SPV_ARM_tensors, SPV_ARM_graph, SPV_KHR_vulkan_memory_model]> {
|
||||
spirv.GlobalVariable @cast_int_arg_0 bind(0, 0) : !spirv.ptr<!spirv.arm.tensor<1x65538x1x2xi8>, UniformConstant>
|
||||
spirv.GlobalVariable @cast_int_res_0 bind(1, 0) : !spirv.ptr<!spirv.arm.tensor<1x65538x1x2xi32>, UniformConstant>
|
||||
spirv.ARM.GraphEntryPoint @cast_int, @cast_int_arg_0, @cast_int_res_0
|
||||
spirv.ARM.Graph @cast_int(%arg0: !spirv.arm.tensor<1x65538x1x2xi8>) -> (!spirv.arm.tensor<1x65538x1x2xi32>) {
|
||||
// CHECK: {{%.*}} = spirv.Tosa.Cast %arg0 : !spirv.arm.tensor<1x65538x1x2xi8> -> !spirv.arm.tensor<1x65538x1x2xi32>
|
||||
%0 = spirv.Tosa.Cast %arg0 : !spirv.arm.tensor<1x65538x1x2xi8> -> !spirv.arm.tensor<1x65538x1x2xi32>
|
||||
// CHECK: spirv.ARM.GraphOutputs {{%.*}} : !spirv.arm.tensor<1x65538x1x2xi32>
|
||||
spirv.ARM.GraphOutputs %0 : !spirv.arm.tensor<1x65538x1x2xi32>
|
||||
}
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
//===----------------------------------------------------------------------===//
|
||||
// spirv.TOSA.Cast - PRO-FP
|
||||
//===----------------------------------------------------------------------===//
|
||||
|
||||
// CHECK: spirv.module Logical Vulkan requires #spirv.vce<v1.3, [VulkanMemoryModel, Shader, Int8, Int16, Int64, Float16, TensorsARM, GraphARM], [SPV_ARM_tensors, SPV_ARM_graph, SPV_KHR_vulkan_memory_model]>
|
||||
spirv.module Logical Vulkan requires #spirv.vce<v1.3, [VulkanMemoryModel, Shader, Int8, Int16, Int64, Float16, TensorsARM, GraphARM], [SPV_ARM_tensors, SPV_ARM_graph, SPV_KHR_vulkan_memory_model]> {
|
||||
spirv.GlobalVariable @cast_fp_arg_0 bind(0, 0) : !spirv.ptr<!spirv.arm.tensor<11x5x14x4xf32>, UniformConstant>
|
||||
spirv.GlobalVariable @cast_fp_res_0 bind(1, 0) : !spirv.ptr<!spirv.arm.tensor<11x5x14x4xf16>, UniformConstant>
|
||||
spirv.ARM.GraphEntryPoint @cast_fp, @cast_fp_arg_0, @cast_fp_res_0
|
||||
spirv.ARM.Graph @cast_fp(%arg0: !spirv.arm.tensor<11x5x14x4xf32>) -> (!spirv.arm.tensor<11x5x14x4xf16>) {
|
||||
// CHECK: {{%.*}} = spirv.Tosa.Cast %arg0 : !spirv.arm.tensor<11x5x14x4xf32> -> !spirv.arm.tensor<11x5x14x4xf16>
|
||||
%0 = spirv.Tosa.Cast %arg0 : !spirv.arm.tensor<11x5x14x4xf32> -> !spirv.arm.tensor<11x5x14x4xf16>
|
||||
// CHECK: spirv.ARM.GraphOutputs {{%.*}} : !spirv.arm.tensor<11x5x14x4xf16>
|
||||
spirv.ARM.GraphOutputs %0 : !spirv.arm.tensor<11x5x14x4xf16>
|
||||
}
|
||||
}
|
||||
|
||||
// -----
|
||||
|
||||
//===----------------------------------------------------------------------===//
|
||||
// spirv.TOSA.Rescale - PRO-INT
|
||||
//===----------------------------------------------------------------------===//
|
||||
|
||||
// CHECK: spirv.module Logical Vulkan requires #spirv.vce<v1.3, [VulkanMemoryModel, Shader, Int8, Int16, Int64, Float16, TensorsARM, GraphARM], [SPV_ARM_tensors, SPV_ARM_graph, SPV_KHR_vulkan_memory_model]>
|
||||
spirv.module Logical Vulkan requires #spirv.vce<v1.3, [VulkanMemoryModel, Shader, Int8, Int16, Int64, Float16, TensorsARM, GraphARM], [SPV_ARM_tensors, SPV_ARM_graph, SPV_KHR_vulkan_memory_model]> {
|
||||
spirv.GlobalVariable @rescale_int_arg_0 bind(0, 0) : !spirv.ptr<!spirv.arm.tensor<17x29x19xi16>, UniformConstant>
|
||||
spirv.GlobalVariable @rescale_int_res_0 bind(1, 0) : !spirv.ptr<!spirv.arm.tensor<17x29x19xi16>, UniformConstant>
|
||||
spirv.ARM.GraphEntryPoint @rescale_int, @rescale_int_arg_0, @rescale_int_res_0
|
||||
spirv.ARM.Graph @rescale_int(%arg0: !spirv.arm.tensor<17x29x19xi16>) -> (!spirv.arm.tensor<17x29x19xi16>) {
|
||||
%5 = spirv.Constant dense<1866149760> : !spirv.arm.tensor<1xi32>
|
||||
%6 = spirv.Constant dense<31> : !spirv.arm.tensor<1xi8>
|
||||
%7 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
|
||||
%8 = spirv.Constant dense<0> : !spirv.arm.tensor<1xi16>
|
||||
// CHECK: {{%.*}} = spirv.Tosa.Rescale scale32 = true, rounding_mode = <DoubleRound>, per_channel = false, input_unsigned = false, output_unsigned = true, %arg0, {{%.*}}, {{%.*}}, {{%.*}}, {{%.*}} : !spirv.arm.tensor<17x29x19xi16>, !spirv.arm.tensor<1xi32>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi16> -> !spirv.arm.tensor<17x29x19xi16>
|
||||
%9 = spirv.Tosa.Rescale scale32 = true, rounding_mode = <DoubleRound>, per_channel = false, input_unsigned = false, output_unsigned = true, %arg0, %5, %6, %7, %8 : !spirv.arm.tensor<17x29x19xi16>, !spirv.arm.tensor<1xi32>, !spirv.arm.tensor<1xi8>, !spirv.arm.tensor<1xi16>, !spirv.arm.tensor<1xi16> -> !spirv.arm.tensor<17x29x19xi16>
|
||||
// CHECK: spirv.ARM.GraphOutputs {{%.*}} : !spirv.arm.tensor<17x29x19xi16>
|
||||
spirv.ARM.GraphOutputs %9 : !spirv.arm.tensor<17x29x19xi16>
|
||||
}
|
||||
}
|
||||
|
||||
@ -504,6 +504,7 @@ constexpr llvm::StringLiteral constantIdEnumAttrs[] = {
|
||||
"SPIRV_TosaExtAccTypeAttr",
|
||||
"SPIRV_TosaExtResizeModeAttr",
|
||||
"SPIRV_TosaExtNaNPropagationModeAttr",
|
||||
"SPIRV_TosaExtRoundingModeAttr",
|
||||
"SPIRV_QuadSwapDirectionAttr",
|
||||
};
|
||||
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user