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Merged
ramiro050 merged 1 commit into from
Sep 28, 2023
Merged

add e2e support for torch.log10 #2479

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45 changes: 45 additions & 0 deletions include/torch-mlir/Dialect/Torch/IR/GeneratedTorchOps.td
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Original file line number Diff line number Diff line change
Expand Up @@ -2527,6 +2527,51 @@ def Torch_AtenLog2_Op : Torch_Op<"aten.log2_", [
}];
}

def Torch_AtenLog10Op : Torch_Op<"aten.log10", [
AllowsTypeRefinement,
HasValueSemantics,
ReadOnly
]> {
let summary = "Generated op for `aten::log10 : (Tensor) -> (Tensor)`";
let arguments = (ins
AnyTorchTensorType:$self
);
let results = (outs
AnyTorchTensorType:$result
);
let hasCustomAssemblyFormat = 1;
let extraClassDefinition = [{
ParseResult AtenLog10Op::parse(OpAsmParser &parser, OperationState &result) {
return parseDefaultTorchOp(parser, result, 1, 1);
}
void AtenLog10Op::print(OpAsmPrinter &printer) {
printDefaultTorchOp(printer, *this, 1, 1);
}
}];
}

def Torch_AtenLog10_Op : Torch_Op<"aten.log10_", [
IsTrailingUnderscoreInplaceVariant,
AllowsTypeRefinement
]> {
let summary = "Generated op for `aten::log10_ : (Tensor) -> (Tensor)`";
let arguments = (ins
AnyTorchTensorType:$self
);
let results = (outs
AnyTorchTensorType:$result
);
let hasCustomAssemblyFormat = 1;
let extraClassDefinition = [{
ParseResult AtenLog10_Op::parse(OpAsmParser &parser, OperationState &result) {
return parseDefaultTorchOp(parser, result, 1, 1);
}
void AtenLog10_Op::print(OpAsmPrinter &printer) {
printDefaultTorchOp(printer, *this, 1, 1);
}
}];
}

def Torch_AtenSqrtOp : Torch_Op<"aten.sqrt", [
AllowsTypeRefinement,
HasValueSemantics,
Expand Down
8 changes: 6 additions & 2 deletions lib/Conversion/TorchToLinalg/Uncategorized.cpp
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Expand Up @@ -235,6 +235,10 @@ static Value createLinalgPayloadCalculationForElementwiseOp(
return createCalculationForMathOpWithDtypeConversion<math::Log2Op>(
b, converter, payloadArgs[0], op);
}
if (isa<AtenLog10Op>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::Log10Op>(
b, converter, payloadArgs[0], op);
}
if (isa<AtenLog1pOp>(op)) {
return createCalculationForMathOpWithDtypeConversion<math::Log1pOp>(
b, converter, payloadArgs[0], op);
Expand Down Expand Up @@ -1177,7 +1181,7 @@ class ConvertElementwiseOp : public ConversionPattern {
AtenMinimumOp, AtenMaximumOp, AtenToDtypeOp, AtenClampOp,
AtenRsubScalarOp, AtenMulScalarOp, AtenLogOp, AtenErfOp,
AtenSqrtOp, AtenFloorOp, AtenPowScalarOp, AtenPowTensorScalarOp,
AtenPowTensorTensorOp, AtenLog2Op, AtenLog1pOp, AtenRsqrtOp,
AtenPowTensorTensorOp, AtenLog2Op, AtenLog10Op, AtenLog1pOp, AtenRsqrtOp,
AtenDivScalarOp, AtenRemainderScalarOp, AtenAbsOp,
AtenReciprocalOp, AtenBitwiseAndTensorOp, AtenBitwiseOrTensorOp,
AtenBitwiseXorTensorOp, AtenGtScalarOp, AtenGeScalarOp,
Expand Down Expand Up @@ -1712,7 +1716,7 @@ void mlir::torch::torch_to_linalg::populateUncategorizedPatternsAndLegality(
AtenMaximumOp, AtenToDtypeOp, AtenClampOp, AtenRsubScalarOp, AtenLogOp,
AtenErfOp, AtenSqrtOp, AtenFloorOp, AtenCeilOp, AtenPreluOp,
AtenPowScalarOp, AtenPowTensorScalarOp, AtenPowTensorTensorOp, AtenLog2Op,
AtenLog1pOp, AtenRsqrtOp, AtenAbsOp, AtenReciprocalOp,
AtenLog10Op, AtenLog1pOp, AtenRsqrtOp, AtenAbsOp, AtenReciprocalOp,
AtenBitwiseAndTensorOp, AtenBitwiseOrTensorOp, AtenBitwiseXorTensorOp,
AtenGtScalarOp, AtenGeScalarOp, AtenEqScalarOp, AtenLtScalarOp,
AtenLeScalarOp, AtenWhereSelfOp, AtenGtTensorOp, AtenGeTensorOp,
Expand Down
9 changes: 9 additions & 0 deletions lib/Dialect/Torch/Transforms/AbstractInterpLibrary.cpp
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Expand Up @@ -6322,6 +6322,10 @@ StringRef mlir::torch::Torch::getAbstractInterpLibrary() {
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_shape_fn.aten.log10\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
" }\n"
" func.func @\"__torch_mlir_shape_fn.aten.log1p\"(%arg0: !torch.list<int>) -> !torch.list<int> {\n"
" %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>\n"
" return %0 : !torch.list<int>\n"
Expand Down Expand Up @@ -8291,6 +8295,11 @@ StringRef mlir::torch::Torch::getAbstractInterpLibrary() {
" %1 = call @__torch__._get_dtype_of_floating_point_op(%0#1) : (!torch.int) -> !torch.int\n"
" return %1 : !torch.int\n"
" }\n"
" func.func @\"__torch_mlir_dtype_fn.aten.log10\"(%arg0: !torch.tuple<int, int>) -> !torch.int {\n"
" %0:2 = torch.prim.TupleUnpack %arg0 : !torch.tuple<int, int> -> !torch.int, !torch.int\n"
" %1 = call @__torch__._get_dtype_of_floating_point_op(%0#1) : (!torch.int) -> !torch.int\n"
" return %1 : !torch.int\n"
" }\n"
" func.func @\"__torch_mlir_dtype_fn.aten.log1p\"(%arg0: !torch.tuple<int, int>) -> !torch.int {\n"
" %0:2 = torch.prim.TupleUnpack %arg0 : !torch.tuple<int, int> -> !torch.int, !torch.int\n"
" %1 = call @__torch__._get_dtype_of_floating_point_op(%0#1) : (!torch.int) -> !torch.int\n"
Expand Down
8 changes: 8 additions & 0 deletions python/torch_mlir/dialects/torch/importer/jit_ir/build_tools/abstract_interp_lib_gen.py
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Expand Up @@ -122,6 +122,9 @@ def aten〇detach〡shape(self: List[int]) -> List[int]:
def aten〇log2〡shape(self: List[int]) -> List[int]:
return upstream_shape_functions.unary(self)

def aten〇log10〡shape(self: List[int]) -> List[int]:
return upstream_shape_functions.unary(self)

def aten〇log1p〡shape(self: List[int]) -> List[int]:
return upstream_shape_functions.unary(self)

Expand Down Expand Up @@ -1438,6 +1441,11 @@ def aten〇log2〡dtype(self_rank_dtype: Tuple[int, int]) -> int:
self_rank, self_dtype = self_rank_dtype
return _get_dtype_of_floating_point_op(self_dtype)

@check_dtype_function(_check_tensors_with_the_same_dtype(num_of_tensors=1))
def aten〇log10〡dtype(self_rank_dtype: Tuple[int, int]) -> int:
self_rank, self_dtype = self_rank_dtype
return _get_dtype_of_floating_point_op(self_dtype)

@check_dtype_function(_check_tensors_with_the_same_dtype(num_of_tensors=1))
def aten〇log1p〡dtype(self_rank_dtype: Tuple[int, int]) -> int:
self_rank, self_dtype = self_rank_dtype
Expand Down
1 change: 1 addition & 0 deletions python/torch_mlir/dialects/torch/importer/jit_ir/build_tools/torch_ods_gen.py
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Expand Up @@ -294,6 +294,7 @@ def emit_with_mutating_variants(key, **kwargs):
"aten::clamp_max : (Tensor, Scalar) -> (Tensor)",
"aten::clamp_max.Tensor : (Tensor, Tensor) -> (Tensor)",
"aten::log2 : (Tensor) -> (Tensor)",
"aten::log10 : (Tensor) -> (Tensor)",
"aten::sqrt : (Tensor) -> (Tensor)",
"aten::log1p : (Tensor) -> (Tensor)",
"aten::rsqrt : (Tensor) -> (Tensor)",
Expand Down
42 changes: 42 additions & 0 deletions python/torch_mlir_e2e_test/test_suite/elementwise.py
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Expand Up @@ -1683,6 +1683,48 @@ def ElementwiseLog2IntModule_basic(module, tu: TestUtils):
module.forward(tu.randint(3, 4, low=1, high=10).to(torch.int32))


# ==============================================================================

class ElementwiseLog10Module(torch.nn.Module):

def __init__(self):
super().__init__()

@export
@annotate_args([
None,
([-1, -1], torch.float32, True),
])
def forward(self, a):
return torch.log10(a)


@register_test_case(module_factory=lambda: ElementwiseLog10Module())
def ElementwiseLog10Module_basic(module, tu: TestUtils):
module.forward(tu.rand(3, 4))


# ==============================================================================

class ElementwiseLog10IntModule(torch.nn.Module):

def __init__(self):
super().__init__()

@export
@annotate_args([
None,
([-1, -1], torch.int32, True),
])
def forward(self, a):
return torch.log10(a)


@register_test_case(module_factory=lambda: ElementwiseLog10IntModule())
def ElementwiseLog10IntModule_basic(module, tu: TestUtils):
module.forward(tu.randint(3, 4, low=1, high=10).to(torch.int32))


# ==============================================================================


Expand Down