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Add Constant, Inverse ops
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@EmergentOrder
EmergentOrder committed Apr 2, 2021
1 parent 62c80bc commit 41b9c00
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Showing 2 changed files with 8 additions and 3 deletions.
9 changes: 6 additions & 3 deletions ONNXScala/src/main/scala/ndscala/ONNXScalaOps.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -26,7 +26,7 @@ object ONNXScalaOps {
//
// }
val onnx = new ORTOperatorBackendAll()
// def fuseOps = onnx.fuseOps
def fuseOps = onnx.fuseOps
}

//TODO: Stricter type bounds because ORT doesn't implement them all
Expand Down Expand Up @@ -113,6 +113,7 @@ given NDArrayOps[Tensor] with {
val rng = spire.random.rng.Cmwc5()

//Nullary / factory ops

def zeros[DType <: NumericSupported : ClassTag: Numeric : IsNumericSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape](using tt: ValueOf[Tt], td: TensorShapeDenotationOf[Td], s: ShapeOf[S]): Tensor[DType, (Tt,Td,S)] = Tensor(Array.fill(s.value.toSeq.foldLeft(1)(_*_))(implicitly[Numeric[DType]].zero),tt.value,td.value, s.value)
def ones[DType <: NumericSupported : ClassTag: Numeric : IsNumericSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape](shape: Array[Int])(using tt: ValueOf[Tt], td: TensorShapeDenotationOf[Td], s: ShapeOf[S]): Tensor[DType, (Tt,Td,S)] = Tensor(Array.fill(shape.foldLeft(1)(_*_))(implicitly[Numeric[DType]].one), tt.value, td.value,s.value)
def full[DType <: NumericSupported : ClassTag: Numeric : IsNumericSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape](shape: Array[Int], value: DType)(using tt: ValueOf[Tt], td: TensorShapeDenotationOf[Td], s: ShapeOf[S]): Tensor[DType, (Tt,Td,S)] = Tensor(Array.fill(shape.foldLeft(1)(_*_))(value), tt.value, td.value, s.value)
Expand All @@ -134,7 +135,7 @@ given NDArrayOps[Tensor] with {
extension[DType <: Supported : ClassTag : IsSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape] (arr: Tensor[DType, (Tt,Td,S)]) def slice[Tt2 <: TensorTypeDenotation, AxesStart <: Indices, AxesEnd <: Indices](using tt: ValueOf[Tt2], td: TensorShapeDenotationOf[Td], s2: ShapeOf[SlicedShape[AxesStart,AxesEnd]], i: IndicesOf[AxesStart], i2: IndicesOf[AxesEnd]): Tensor[DType, (Tt2,Td,SlicedShape[AxesStart,AxesEnd])] = onnx.SliceV11("slice", arr, indicesOf[AxesStart], indicesOf[AxesEnd]) //wrong denotations

//currently can't infer return type
extension[DType <: Supported : ClassTag : IsSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape] (arr: Tensor[DType, (Tt,Td,S)]) def squeeze[Tt1 <: TensorTypeDenotation, Axes <: Indices](using tt: ValueOf[Tt1], td: TensorShapeDenotationOf[KeepOrReduceDimDenotations[Td,Axes,false]], s: ShapeOf[KeepOrReduceDims[S,Axes,false]], i: IndicesOf[Axes]): Tensor[DType, Tuple3[Tt1,KeepOrReduceDimDenotations[Td,Axes,false],KeepOrReduceDims[S,Axes,false]]] = onnx.SqueezeV11("squeeze",Some(indicesOf[Axes]),arr)
extension[DType <: Supported : ClassTag : IsSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape] (arr: Tensor[DType, (Tt,Td,S)]) def squeeze[Tt1 <: TensorTypeDenotation, Axes <: Indices](using tt: ValueOf[Tt1], td: TensorShapeDenotationOf[KeepOrReduceDimDenotations[Td,Axes,false]], s: ShapeOf[KeepOrReduceDims[S,Axes,false]], i: IndicesOf[Axes]): Tensor[DType, Tuple3[Tt1,KeepOrReduceDimDenotations[Td,Axes,false],KeepOrReduceDims[S,Axes,false]]] = onnx.SqueezeV13("squeeze",Some(indicesOf[Axes]),arr)
extension[DType <: Supported : ClassTag : IsSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape] (arr: Tensor[DType, (Tt,Td,S)]) def rank: Int = arr.shape.size

//extension[DType <: FloatSupported : ClassTag: Numeric] (arr: Tensor[DType]) def clip(min: DType, max: DType)(using tt: ValueOf[Tt], td: TensorShapeDenotationOf[Td], s: ShapeOf[S]): Tensor[DType] = onnx.ClipV11("clip", arr,None, None)
Expand All @@ -143,7 +144,7 @@ given NDArrayOps[Tensor] with {


//TODO: rest of Reduction ops:
extension[DType <: NumericSupported : ClassTag : Numeric : IsNumericSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape] (arr: Tensor[DType, (Tt,Td,S)]) def reduceSum[Tt1 <: TensorTypeDenotation, Axes <: Indices, KeepDims <: (Boolean&Singleton)] (using tt: ValueOf[Tt1], td: TensorShapeDenotationOf[KeepOrReduceDimDenotations[Td,Axes,KeepDims]], s: ShapeOf[KeepOrReduceDims[S,Axes,KeepDims]], i: IndicesOf[Axes], k: ValueOf[KeepDims]): Tensor[DType, Tuple3[Tt1,KeepOrReduceDimDenotations[Td,Axes,KeepDims],KeepOrReduceDims[S,Axes,KeepDims]]] = onnx.ReduceSumV11[DType, Tt, Td, S, Tt1, Axes, KeepDims ]("reduceSum", Some(indicesOf[Axes]), valueOf[KeepDims], arr )
extension[DType <: NumericSupported : ClassTag : Numeric : IsNumericSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape] (arr: Tensor[DType, (Tt,Td,S)]) def reduceSum[Tt1 <: TensorTypeDenotation, Axes <: Indices, KeepDims <: (Boolean&Singleton)] (using tt: ValueOf[Tt1], td: TensorShapeDenotationOf[KeepOrReduceDimDenotations[Td,Axes,KeepDims]], s: ShapeOf[KeepOrReduceDims[S,Axes,KeepDims]], i: IndicesOf[Axes], k: ValueOf[KeepDims]): Tensor[DType, Tuple3[Tt1,KeepOrReduceDimDenotations[Td,Axes,KeepDims],KeepOrReduceDims[S,Axes,KeepDims]]] = onnx.ReduceSumV13[DType, Tt, Td, S, Tt1, Axes, KeepDims ]("reduceSum", Some(indicesOf[Axes]), valueOf[KeepDims], arr )



Expand All @@ -169,6 +170,8 @@ given NDArrayOps[Tensor] with {
extension[DType <: FloatSupported : ClassTag: Numeric : IsFloatSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape] (arr: Tensor[DType, (Tt,Td,S)]) def atanh()(using tt: ValueOf[Tt], td: TensorShapeDenotationOf[Td], s: ShapeOf[S]): Tensor[DType, (Tt,Td,S)] = onnx.AtanhV9("atanh", arr)
extension[DType <: FloatSupported : ClassTag: Numeric : IsFloatSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape] (arr: Tensor[DType, (Tt,Td,S)]) def sigmoid()(using tt: ValueOf[Tt], td: TensorShapeDenotationOf[Td], s: ShapeOf[S]): Tensor[DType, (Tt,Td,S)] = onnx.SigmoidV6("sig", arr)
extension[DType <: FloatSupported : ClassTag: Numeric : IsFloatSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape] (arr: Tensor[DType, (Tt,Td,S)]) def relu()(using tt: ValueOf[Tt], td: TensorShapeDenotationOf[Td], s: ShapeOf[S]): Tensor[DType, (Tt,Td,S)] = onnx.ReluV6("relu", arr)
extension[DType <: FloatSupported : ClassTag: Numeric : IsFloatSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape] (arr: Tensor[DType, (Tt,Td,S)]) def inverse()(using tt: ValueOf[Tt], td: TensorShapeDenotationOf[Td], s: ShapeOf[S]): Tensor[DType, (Tt,Td,S)] = onnx.InverseV1Contrib("inverse", arr)
extension[DType <: FloatSupported : ClassTag: Numeric : IsFloatSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape] (arr: Tensor[DType, (Tt,Td,S)]) def constant()(using tt: ValueOf[Tt], td: TensorShapeDenotationOf[Td], s: ShapeOf[S]): Tensor[DType, (Tt,Td,S)] = onnx.ConstantV12("constant", value = Some(arr))


//Binary Tensor ops
Expand Down
2 changes: 2 additions & 0 deletions core/src/main/scala/ndscala/NDArrayOps.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -96,6 +96,8 @@ trait NDArrayOps[SomeNDArray[_ <: AllSupported, _ <: Axes]] {
extension[DType <: FloatSupported : ClassTag: Numeric : IsFloatSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape] (arr: SomeNDArray[DType, (Tt,Td,S)]) def sigmoid()(using tt: ValueOf[Tt], td: TensorShapeDenotationOf[Td], s: ShapeOf[S]): SomeNDArray[DType, (Tt,Td,S)]
extension[DType <: FloatSupported : ClassTag: Numeric : IsFloatSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape] (arr: SomeNDArray[DType, (Tt,Td,S)]) def relu()(using tt: ValueOf[Tt], td: TensorShapeDenotationOf[Td], s: ShapeOf[S]): SomeNDArray[DType, (Tt,Td,S)]

extension[DType <: FloatSupported : ClassTag: Numeric : IsFloatSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape] (arr: SomeNDArray[DType, (Tt,Td,S)]) def inverse()(using tt: ValueOf[Tt], td: TensorShapeDenotationOf[Td], s: ShapeOf[S]): SomeNDArray[DType, (Tt,Td,S)]
extension[DType <: FloatSupported : ClassTag: Numeric : IsFloatSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape] (arr: SomeNDArray[DType, (Tt,Td,S)]) def constant()(using tt: ValueOf[Tt], td: TensorShapeDenotationOf[Td], s: ShapeOf[S]): SomeNDArray[DType, (Tt,Td,S)]

//Binary NDArray ops
extension[DType <: NumericSupported : ClassTag: Numeric : IsNumericSupported, Tt <: TensorTypeDenotation, Td <: TensorShapeDenotation, S <: Shape] (arr: SomeNDArray[DType, (Tt,Td,S)]) def +(other: SomeNDArray[DType, (Tt,Td,S)])(using tt: ValueOf[Tt], td: TensorShapeDenotationOf[Td], s: ShapeOf[S]): SomeNDArray[DType, (Tt,Td,S)]
Expand Down

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