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EmergentOrderEmergentOrder
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Bump ONNX version to 1.6.0; format; Add full backend trait
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11 files changed

+1726
-248
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11 files changed

+1726
-248
lines changed

‎backends/src/main/scala/FullBackend.scala‎

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import org.emergentorder.onnx._
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trait FullBackend
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extends Abs
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with Acos
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with Acosh
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with Add
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with And
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with ArgMax
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with ArgMin
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with ArrayFeatureExtractor
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with Asin
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with Asinh
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with Atan
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with AveragePool
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with BatchNormalization
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with Binarizer
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with BitShift
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with Cast
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with CastMap
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with CategoryMapper
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with Ceil
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with Clip
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with Compress
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with Concat
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with ConcatFromSequence
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with Constant
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with ConstantOfShape
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with Conv
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with ConvInteger
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with ConvTranspose
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with Cos
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with Cosh
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with CumSum
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with DepthToSpace
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with DequantizeLinear
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with Det
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with DictVectorizer
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with Div
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with Dropout
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with DynamicQuantizeLinear
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with Elu
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with Equal
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with Erf
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with Exp
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with Expand
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with EyeLike
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with Flatten
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with Floor
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with GRU
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with Gather
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with GatherElements
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with GatherND
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with Gemm
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with GlobalAveragePool
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with GlobalLpPool
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with GlobalMaxPool
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with Greater
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with HardSigmoid
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with Hardmax
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with Identity
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with If
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with Imputer
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with InstanceNormalization
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with IsInf
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with IsNaN
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with LRN
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with LSTM
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with LabelEncoder
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with LeakyRelu
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with Less
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with LinearClassifier
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with LinearRegressor
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with Log
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with LogSoftmax
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with Loop
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with LpNormalization
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with LpPool
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with MatMul
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with MatMulInteger
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with Max
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with MaxPool
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with MaxRoiPool
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with MaxUnpool
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with Mean
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with MeanVarianceNormalization
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with Min
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with Mod
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with Mul
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with Multinomial
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with Neg
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with NonMaxSuppression
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with NonZero
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with Normalizer
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with Not
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with OneHot
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with OneHotEncoder
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with Or
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with PRelu
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with Pad
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with Pow
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with QLinearConv
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with QLinearMatMul
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with QuantizeLinear
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with RNN
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with RandomNormal
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with RandomNormalLike
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with RandomUniform
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with RandomUniformLike
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with Range
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with Reciprocal
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with ReduceL1
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with ReduceL2
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with ReduceLogSum
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with ReduceLogSumExp
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with ReduceMax
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with ReduceMean
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with ReduceMin
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with ReduceProd
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with ReduceSum
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with ReduceSumSquare
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with Relu
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with Reshape
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with Resize
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with ReverseSequence
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with RoiAlign
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with Round
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with SVMClassifier
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with SVMRegressor
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with Scaler
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with Scan
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with Scatter
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with ScatterElements
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with ScatterND
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with Selu
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with SequenceAt
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with SequenceConstruct
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with SequenceEmpty
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with SequenceErase
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with SequenceInsert
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with SequenceLength
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with Shape
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with Shrink
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with Sigmoid
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with Sign
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with Sin
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with Sinh
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with Size
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with Slice
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with Softmax
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with Softplus
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with Softsign
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with SpaceToDepth
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with Split
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with SplitToSequence
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with Sqrt
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with Squeeze
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with StringNormalizer
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with Sub
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with Sum
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with Tan
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with Tanh
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with TfIdfVectorizer
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with ThresholdedRelu
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with Tile
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with TopK
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with Transpose
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with TreeEnsembleClassifier
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with TreeEnsembleRegressor
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with Unique
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with Unsqueeze
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with Upsample
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with Where
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with Xor
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with ZipMap

‎backends/src/main/scala/NGraphBackend.scala‎

Lines changed: 9 additions & 11 deletions
Original file line numberDiff line numberDiff line change
@@ -39,7 +39,7 @@ import org.bytedeco.onnx.global.onnx.check_model
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//TODO: ONNX Runtime backend for JVM (and Native?)
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class NGraphBackend(onnxBytes: Array[Byte])
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extends Add
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// with DataSource
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with DataSource
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with Constant
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with ArgMin
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with ArgMax
@@ -62,29 +62,27 @@ class NGraphBackend(onnxBytes: Array[Byte])
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with AveragePool
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with Reshape
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with AutoCloseable {
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//with DataSource
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val scope = new PointerScope()
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val ngraphBackend = Backend.create("CPU")
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/*
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val onnxHelper = new ONNXHelper(onnxBytes)
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def paramsMap[T: spire.math.Numeric: ClassTag] =
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onnxHelper.params
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.map(x => x._1 -> (x._2, x._3.asInstanceOf[Array[T]], x._4))
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.toMap
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override def getParams[T: Numeric: ClassTag](name: String)(
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implicit ev: (UNil TypeOr Float16 TypeOr Float TypeOr Double TypeOr Byte TypeOr Short TypeOr Int TypeOr Long TypeOr UByte TypeOr UShort TypeOr UInt TypeOr ULong TypeOr Complex[
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Float
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] TypeOr Complex[Double])#check[T]
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): Tensor[T] = {
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override def getParams[T: Numeric: ClassTag](name: String): Tensor[T] = {
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val params = paramsMap.get(name)
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params match {
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case Some(x) => TensorFactory.getTensor(x._2, x._3.map(z => z: XInt))
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case None =>
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throw new Exception("No params found for param name: " + name)
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}
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}
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*/
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def Abs1[@sp T: Numeric: ClassTag](
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name: String,
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consumed_inputs: Option[(Array[Int])] = None,
@@ -207,8 +205,8 @@ class NGraphBackend(onnxBytes: Array[Byte])
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def Equal1[@sp T: Numeric: ClassTag, @sp T1: Numeric: ClassTag](
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name: String,
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axis: Option[(Int)] = None,
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broadcast: Option[(Int)] = None,
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axis: Option[(Int)],
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broadcast: Option[(Int)],
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A: Option[Tensor[T]],
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B: Option[Tensor[T]]
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)(

‎common/src/main/scala/UnionType.scala‎

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@@ -15,19 +15,19 @@
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package org.emergentorder
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package object union{
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package object union {
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type ![A] = A => Nothing
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type !![A] = ![![A]]
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type ![A] = A => Nothing
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type !![A] = ![![A]]
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trait Disjunction[T] {
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type or[S] = Disjunction[T with ![S]]
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type create = ![T]
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}
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trait Disjunction[T] {
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type or[S] = Disjunction[T with ![S]]
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type create = ![T]
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}
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type Union[T] = {
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type or[S] = Disjunction[![T]]#or[S]
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}
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type Union[T] = {
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type or[S] = Disjunction[![T]]#or[S]
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}
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32-
type Contains[S, T] = !![S] <:< T
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type Contains[S, T] = !![S] <:< T
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}

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