@@ -58,9 +58,14 @@ val imageTensDefaultDenotations = Tensor(data,shape)
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Note that ONNX Tensor content is in row-major order.
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``` scala
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- val out = squeezenet.fullModel[Float , " ImageNetClassification" ," Batch" ##: " Class" ##: TSNil ,1 #: 1000 #: SNil ](Tuple (imageTens))
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+ val out = squeezenet.fullModel[Float ,
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+ " ImageNetClassification" ,
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+ " Batch" ##: " Class" ##: TSNil ,
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+ 1 #: 1000 #: SNil ](Tuple (imageTens))
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// val out:
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- // org.emergentorder.onnx.Tensors.Tensor[Float, ("ImageNetClassification", "Batch" ##: "Class" ##:
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+ // org.emergentorder.onnx.Tensors.Tensor[Float,
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+ // ("ImageNetClassification",
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+ // "Batch" ##: "Class" ##:
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// org.emergentorder.compiletime.TSNil
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// , 1 #: 1000 #: io.kjaer.compiletime.SNil)] = (Array(0.8230729,
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// ...
@@ -96,7 +101,9 @@ val onnxBackend = new ORTOperatorBackendAll()
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val longTens = Tensor (Array .fill(1 * 3 * 224 * 224 ){- 42l },tensorDenotation,tensorShapeDenotation,shape)
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// longTens:
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- // org.emergentorder.onnx.Tensors.Tensor[Float, ("Image", "Batch" ##: "Channel" ##: "Height" ##: "Width" ##:
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+ // org.emergentorder.onnx.Tensors.Tensor[Float,
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+ // ("Image",
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+ // "Batch" ##: "Channel" ##: "Height" ##: "Width" ##:
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// org.emergentorder.compiletime.TSNil
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// , 1 #: 1000 #: io.kjaer.compiletime.SNil)] = (
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// Array(
@@ -106,7 +113,9 @@ val longTens = Tensor(Array.fill(1*3*224*224){-42l},tensorDenotation,tensorShape
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onnxBackend.AbsV6 (" abs" , longTens)
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// res2:
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- // org.emergentorder.onnx.Tensors.Tensor[Float, ("Image", "Batch" ##: "Channel" ##: "Height" ##: "Width" ##:
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+ // org.emergentorder.onnx.Tensors.Tensor[Float,
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+ // ("Image",
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+ // "Batch" ##: "Channel" ##: "Height" ##: "Width" ##:
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// org.emergentorder.compiletime.TSNil
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// , 1 #: 1000 #: io.kjaer.compiletime.SNil)] = (
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// Array(
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