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#include <torch/csrc/jit/tensorexpr/operators/misc.h>
#include <torch/csrc/jit/tensorexpr/operators/pointwise.h>
namespace torch::jit::tensorexpr {
using namespace torch::jit::tensorexpr;
Tensor computeSign(
const std::vector<ArgValue>& inputValues,
const std::vector<ExprHandle>& outputShape,
const std::optional<std::vector<ExprHandle>>& outputStrides) {
return Compute(
"aten_sign", outputShape, outputStrides, [&](ParameterList& axes) {
std::vector<ExprHandle> indices(axes.begin(), axes.end());
std::vector<ExprHandle> inputs = {
tensorOrConstant(inputValues[0], indices)};
auto inp = inputs[0];
auto zero = ExprHandle(immLike(inp, 0.0f));
auto res = (zero < inp) - (inp < zero);
return promoteToDtype(res, inp.dtype().scalar_type());
});
}
Tensor computeOneOperand(
const std::string& name,
const std::vector<ArgValue>& inputValues,
const std::vector<ExprHandle>& outputShape,
const std::vector<ExprHandle>& outputStrides,
const std::optional<ScalarType>& outputType,
const std::function<ExprHandle(const ExprHandle&)>& innerExpr,
const int checkParamTypes) {
return Compute(
name,
outputShape,
outputStrides,
[inputValues, outputType, innerExpr, checkParamTypes](
const std::vector<VarHandle>& axes) {
std::vector<ExprHandle> indices(axes.begin(), axes.end());
std::vector<ExprHandle> inputs = {
tensorOrConstant(inputValues[0], indices)};
promoteInputs(inputs, checkParamTypes);
ExprHandle compute = innerExpr(inputs[0]);
return demoteOutput(compute, outputType);
});
}
Tensor computeTwoOperand(
const std::string& name,
const std::vector<ArgValue>& inputValues,
const std::vector<ExprHandle>& outputShape,
const std::vector<ExprHandle>& outputStrides,
const std::optional<ScalarType>& outputType,
const std::function<ExprHandle(const ExprHandle&, const ExprHandle&)>&
innerExpr) {
return Compute(
name,
outputShape,
outputStrides,
[inputValues, outputType, innerExpr](const std::vector<VarHandle>& axes) {
std::vector<ExprHandle> indices(axes.begin(), axes.end());
std::vector<ExprHandle> inputs = {
tensorOrConstant(inputValues[0], indices),
tensorOrConstant(inputValues[1], indices),
};
promoteInputs(inputs);
ExprHandle compute = innerExpr(inputs[0], inputs[1]);
return demoteOutput(compute, outputType);
});
}
Tensor computeTwoOperandWithAlpha(
const std::string& name,
const std::vector<ArgValue>& inputValues,
const std::vector<ExprHandle>& outputShape,
const std::vector<ExprHandle>& outputStrides,
const std::optional<ScalarType>& outputType,
const std::function<ExprHandle(const ExprHandle&, const ExprHandle&)>&
innerExpr) {
return Compute(
name,
outputShape,
outputStrides,
[inputValues, outputType, innerExpr](const std::vector<VarHandle>& axes) {
std::vector<ExprHandle> indices(axes.begin(), axes.end());
std::vector<ExprHandle> inputs = {
tensorOrConstant(inputValues[0], indices),
tensorOrConstant(inputValues[1], indices),
tensorOrConstant(inputValues[2], indices),
};
promoteInputs(inputs);
ExprHandle compute = innerExpr(inputs[0], inputs[2] * inputs[1]);
return demoteOutput(compute, outputType);
});
}
Tensor computeConditionWithTwoOperand(
const std::string& name,
const std::vector<ArgValue>& inputValues,
const std::vector<ExprHandle>& outputShape,
const std::vector<ExprHandle>& outputStrides,
const std::optional<ScalarType>& outputType,
const std::function<
ExprHandle(const ExprHandle&, const ExprHandle&, const ExprHandle&)>&
innerExpr) {
return Compute(
name,
outputShape,
outputStrides,
[inputValues, outputType, innerExpr](const std::vector<VarHandle>& axes) {
std::vector<ExprHandle> indices(axes.begin(), axes.end());
std::vector<ExprHandle> inputs = {
tensorOrConstant(inputValues[1], indices),
tensorOrConstant(inputValues[2], indices),
};
promoteInputs(inputs);
// First expr is the condition, which we don't promote
inputs.emplace(
inputs.begin(), tensorOrConstant(inputValues[0], indices));
ExprHandle compute = innerExpr(inputs[0], inputs[1], inputs[2]);
return demoteOutput(compute, outputType);
});
}
Tensor computeThreeOperand(
const std::string& name,
const std::vector<ArgValue>& inputValues,
const std::vector<ExprHandle>& outputShape,
const std::vector<ExprHandle>& outputStrides,
const std::optional<ScalarType>& outputType,
const std::function<
ExprHandle(const ExprHandle&, const ExprHandle&, const ExprHandle&)>&
innerExpr,
bool promote_inputs) {
return Compute(
name,
outputShape,
outputStrides,
[inputValues, outputType, innerExpr, promote_inputs](
const std::vector<VarHandle>& axes) {
std::vector<ExprHandle> indices(axes.begin(), axes.end());
std::vector<ExprHandle> inputs = {
tensorOrConstant(inputValues[0], indices),
tensorOrConstant(inputValues[1], indices),
tensorOrConstant(inputValues[2], indices),
};
if (promote_inputs) {
promoteInputs(inputs);
}
ExprHandle compute = innerExpr(inputs[0], inputs[1], inputs[2]);
return demoteOutput(compute, outputType);
});
}
Tensor computeFourOperand(
const std::string& name,
const std::vector<ArgValue>& inputValues,
const std::vector<ExprHandle>& outputShape,
const std::vector<ExprHandle>& outputStrides,
const std::optional<ScalarType>& outputType,
const std::function<ExprHandle(
const ExprHandle&,
const ExprHandle&,
const ExprHandle&,
const ExprHandle&)>& innerExpr) {
return Compute(
name,
outputShape,
outputStrides,
[inputValues, outputType, innerExpr](const std::vector<VarHandle>& axes) {
std::vector<ExprHandle> indices(axes.begin(), axes.end());
std::vector<ExprHandle> inputs = {
tensorOrConstant(inputValues[0], indices),
tensorOrConstant(inputValues[1], indices),
tensorOrConstant(inputValues[2], indices),
tensorOrConstant(inputValues[3], indices),
};
promoteInputs(inputs);
ExprHandle compute =
innerExpr(inputs[0], inputs[1], inputs[2], inputs[3]);
return demoteOutput(compute, outputType);
});
}
Tensor computeNoop(
const std::vector<ArgValue>& inputValues,
const std::vector<ExprHandle>& outputShape,
const std::vector<ExprHandle>& outputStrides,
const std::optional<ScalarType>& outputType,
at::Device device) {
return computeOneOperand(
"copy",
inputValues,
outputShape,
outputStrides,
outputType,
[](const ExprHandle& a) { return a; });
}
Tensor computeScalar(
const std::string& name,
const std::vector<ArgValue>& inputValues,
const std::vector<ExprHandle>& outputShape,
const std::vector<ExprHandle>& outputStrides,
const std::optional<ScalarType>& outputType,
const std::function<ExprHandle(const ExprHandle&, const ExprHandle&)>&
innerExpr) {
auto dt = Dtype(*outputType);
VarPtr let_var = alloc<Var>(name + "_var", dt);
std::vector<ExprHandle> inputs = {
scalarOrConstant(inputValues[0]), scalarOrConstant(inputValues[1])};
promoteInputs(inputs);
ExprHandle compute = innerExpr(inputs[0], inputs[1]);
StmtPtr let_stmt =
Let::make(VarHandle(let_var), demoteOutput(compute, outputType));
std::vector<ExprPtr> dims;
BufPtr buf = alloc<Buf>(let_var, dims, dt);
return Tensor(buf, let_stmt);
}
} // namespace torch::jit::tensorexpr
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