forked from owulveryck/onnx-go
/
onnx_test_scan9_sum.go
63 lines (50 loc) · 3.62 KB
/
onnx_test_scan9_sum.go
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package onnxtest
// this file is auto-generated... DO NOT EDIT
import (
"github.com/owulveryck/onnx-go/backend/testbackend"
"gorgonia.org/tensor"
)
func init() {
testbackend.Register("Scan", "TestScan9Sum", NewTestScan9Sum)
}
// NewTestScan9Sum version: 3.
func NewTestScan9Sum() *testbackend.TestCase {
return &testbackend.TestCase{
OpType: "Scan",
Title: "TestScan9Sum",
ModelB: []byte{0x8, 0x3, 0x12, 0xc, 0x62, 0x61, 0x63, 0x6b, 0x65, 0x6e, 0x64, 0x2d, 0x74, 0x65, 0x73, 0x74, 0x3a, 0xc5, 0x2, 0xa, 0xe0, 0x1, 0xa, 0x7, 0x69, 0x6e, 0x69, 0x74, 0x69, 0x61, 0x6c, 0xa, 0x1, 0x78, 0x12, 0x1, 0x79, 0x12, 0x1, 0x7a, 0x22, 0x4, 0x53, 0x63, 0x61, 0x6e, 0x2a, 0xad, 0x1, 0xa, 0x4, 0x62, 0x6f, 0x64, 0x79, 0x32, 0xa1, 0x1, 0xa, 0x1c, 0xa, 0x6, 0x73, 0x75, 0x6d, 0x5f, 0x69, 0x6e, 0xa, 0x4, 0x6e, 0x65, 0x78, 0x74, 0x12, 0x7, 0x73, 0x75, 0x6d, 0x5f, 0x6f, 0x75, 0x74, 0x22, 0x3, 0x41, 0x64, 0x64, 0xa, 0x1d, 0xa, 0x7, 0x73, 0x75, 0x6d, 0x5f, 0x6f, 0x75, 0x74, 0x12, 0x8, 0x73, 0x63, 0x61, 0x6e, 0x5f, 0x6f, 0x75, 0x74, 0x22, 0x8, 0x49, 0x64, 0x65, 0x6e, 0x74, 0x69, 0x74, 0x79, 0x12, 0x9, 0x73, 0x63, 0x61, 0x6e, 0x5f, 0x62, 0x6f, 0x64, 0x79, 0x5a, 0x14, 0xa, 0x6, 0x73, 0x75, 0x6d, 0x5f, 0x69, 0x6e, 0x12, 0xa, 0xa, 0x8, 0x8, 0x1, 0x12, 0x4, 0xa, 0x2, 0x8, 0x2, 0x5a, 0x12, 0xa, 0x4, 0x6e, 0x65, 0x78, 0x74, 0x12, 0xa, 0xa, 0x8, 0x8, 0x1, 0x12, 0x4, 0xa, 0x2, 0x8, 0x2, 0x62, 0x15, 0xa, 0x7, 0x73, 0x75, 0x6d, 0x5f, 0x6f, 0x75, 0x74, 0x12, 0xa, 0xa, 0x8, 0x8, 0x1, 0x12, 0x4, 0xa, 0x2, 0x8, 0x2, 0x62, 0x16, 0xa, 0x8, 0x73, 0x63, 0x61, 0x6e, 0x5f, 0x6f, 0x75, 0x74, 0x12, 0xa, 0xa, 0x8, 0x8, 0x1, 0x12, 0x4, 0xa, 0x2, 0x8, 0x2, 0xa0, 0x1, 0x5, 0x2a, 0x16, 0xa, 0xf, 0x6e, 0x75, 0x6d, 0x5f, 0x73, 0x63, 0x61, 0x6e, 0x5f, 0x69, 0x6e, 0x70, 0x75, 0x74, 0x73, 0x18, 0x1, 0xa0, 0x1, 0x2, 0x12, 0xe, 0x74, 0x65, 0x73, 0x74, 0x5f, 0x73, 0x63, 0x61, 0x6e, 0x39, 0x5f, 0x73, 0x75, 0x6d, 0x5a, 0x15, 0xa, 0x7, 0x69, 0x6e, 0x69, 0x74, 0x69, 0x61, 0x6c, 0x12, 0xa, 0xa, 0x8, 0x8, 0x1, 0x12, 0x4, 0xa, 0x2, 0x8, 0x2, 0x5a, 0x13, 0xa, 0x1, 0x78, 0x12, 0xe, 0xa, 0xc, 0x8, 0x1, 0x12, 0x8, 0xa, 0x2, 0x8, 0x3, 0xa, 0x2, 0x8, 0x2, 0x62, 0xf, 0xa, 0x1, 0x79, 0x12, 0xa, 0xa, 0x8, 0x8, 0x1, 0x12, 0x4, 0xa, 0x2, 0x8, 0x2, 0x62, 0x13, 0xa, 0x1, 0x7a, 0x12, 0xe, 0xa, 0xc, 0x8, 0x1, 0x12, 0x8, 0xa, 0x2, 0x8, 0x3, 0xa, 0x2, 0x8, 0x2, 0x42, 0x4, 0xa, 0x0, 0x10, 0x9},
/*
&ir.NodeProto{
Input: []string{"initial", "x"},
Output: []string{"y", "z"},
Name: "",
OpType: "Scan",
Attributes: ([]*ir.AttributeProto) (len=2 cap=2) {
(*ir.AttributeProto)(0xc000359500)(name:"body" type:GRAPH g:<node:<input:"sum_in" input:"next" output:"sum_out" op_type:"Add" > node:<input:"sum_out" output:"scan_out" op_type:"Identity" > name:"scan_body" input:<name:"sum_in" type:<tensor_type:<elem_type:1 shape:<dim:<dim_value:2 > > > > > input:<name:"next" type:<tensor_type:<elem_type:1 shape:<dim:<dim_value:2 > > > > > output:<name:"sum_out" type:<tensor_type:<elem_type:1 shape:<dim:<dim_value:2 > > > > > output:<name:"scan_out" type:<tensor_type:<elem_type:1 shape:<dim:<dim_value:2 > > > > > > ),
(*ir.AttributeProto)(0xc000359600)(name:"num_scan_inputs" type:INT i:1 )
}
,
},
*/
Input: []tensor.Tensor{
tensor.New(
tensor.WithShape(2),
tensor.WithBacking([]float32{0, 0}),
),
tensor.New(
tensor.WithShape(3, 2),
tensor.WithBacking([]float32{1, 2, 3, 4, 5, 6}),
),
},
ExpectedOutput: []tensor.Tensor{
tensor.New(
tensor.WithShape(2),
tensor.WithBacking([]float32{9, 12}),
),
tensor.New(
tensor.WithShape(3, 2),
tensor.WithBacking([]float32{1, 2, 4, 6, 9, 12}),
),
},
}
}