onnx_test_reduce_l2_do_not_keepdims_random.go

package onnxtest

// this file is auto-generated... DO NOT EDIT

import (
	"github.com/godshen/onnx-go/backend/testbackend"
	"gorgonia.org/tensor"
)

func init() {
	testbackend.Register("ReduceL2", "TestReduceL2DoNotKeepdimsRandom", NewTestReduceL2DoNotKeepdimsRandom)
}

// NewTestReduceL2DoNotKeepdimsRandom version: 3.
func NewTestReduceL2DoNotKeepdimsRandom() *testbackend.TestCase {
	return &testbackend.TestCase{
		OpType: "ReduceL2",
		Title:  "TestReduceL2DoNotKeepdimsRandom",
		ModelB: []byte{0x8, 0x3, 0x12, 0xc, 0x62, 0x61, 0x63, 0x6b, 0x65, 0x6e, 0x64, 0x2d, 0x74, 0x65, 0x73, 0x74, 0x3a, 0x97, 0x1, 0xa, 0x37, 0xa, 0x4, 0x64, 0x61, 0x74, 0x61, 0x12, 0x7, 0x72, 0x65, 0x64, 0x75, 0x63, 0x65, 0x64, 0x22, 0x8, 0x52, 0x65, 0x64, 0x75, 0x63, 0x65, 0x4c, 0x32, 0x2a, 0xb, 0xa, 0x4, 0x61, 0x78, 0x65, 0x73, 0x40, 0x2, 0xa0, 0x1, 0x7, 0x2a, 0xf, 0xa, 0x8, 0x6b, 0x65, 0x65, 0x70, 0x64, 0x69, 0x6d, 0x73, 0x18, 0x0, 0xa0, 0x1, 0x2, 0x12, 0x25, 0x74, 0x65, 0x73, 0x74, 0x5f, 0x72, 0x65, 0x64, 0x75, 0x63, 0x65, 0x5f, 0x6c, 0x32, 0x5f, 0x64, 0x6f, 0x5f, 0x6e, 0x6f, 0x74, 0x5f, 0x6b, 0x65, 0x65, 0x70, 0x64, 0x69, 0x6d, 0x73, 0x5f, 0x72, 0x61, 0x6e, 0x64, 0x6f, 0x6d, 0x5a, 0x1a, 0xa, 0x4, 0x64, 0x61, 0x74, 0x61, 0x12, 0x12, 0xa, 0x10, 0x8, 0x1, 0x12, 0xc, 0xa, 0x2, 0x8, 0x3, 0xa, 0x2, 0x8, 0x2, 0xa, 0x2, 0x8, 0x2, 0x62, 0x19, 0xa, 0x7, 0x72, 0x65, 0x64, 0x75, 0x63, 0x65, 0x64, 0x12, 0xe, 0xa, 0xc, 0x8, 0x1, 0x12, 0x8, 0xa, 0x2, 0x8, 0x3, 0xa, 0x2, 0x8, 0x2, 0x42, 0x2, 0x10, 0x9},

		/*

		   &ir.NodeProto{
		     Input:     []string{"data"},
		     Output:    []string{"reduced"},
		     Name:      "",
		     OpType:    "ReduceL2",
		     Attributes: ([]*ir.AttributeProto) (len=2 cap=2) {
		    (*ir.AttributeProto)(0xc000119600)(name:"axes" type:INTS ints:2 ),
		    (*ir.AttributeProto)(0xc000119700)(name:"keepdims" type:INT )
		   }
		   ,
		   },


		*/

		Input: []tensor.Tensor{

			tensor.New(
				tensor.WithShape(3, 2, 2),
				tensor.WithBacking([]float32{0.9762701, 4.303787, 2.0552676, 0.89766365, -1.526904, 2.9178822, -1.2482557, 7.83546, 9.273255, -2.3311696, 5.834501, 0.5778984}),
			),
		},
		ExpectedOutput: []tensor.Tensor{

			tensor.New(
				tensor.WithShape(3, 2),
				tensor.WithBacking([]float32{4.413127, 2.2427495, 3.2932465, 7.934266, 9.561779, 5.863051}),
			),
		},
	}
}