[Feature](bangc-ops):voxelization support voxels largetensor.

[mahxn0]

Thanks for your contribution and we appreciate it a lot.

1. Motivation

output voxels support largetensor case.

2. Modification

bangc-ops/kernel_depends.toml
bangc-ops/kernels/voxelization/voxelization.cpp

3. Test Report

If you want to know how to do operator testing, you can see GTest-User-Guide-zh.

3.1 Modification Details

3.1.1 Accuracy Acceptance Standard

For static threshold standard details, see: MLU-OPS Accuracy Acceptance Standard.

• diff1: diff1 <= 3e-3
• diff2: diff2 <= 3e-3

3.1.2 Operator Scheme checklist

No.	Details	Check Results
1	Supported hardware	MLU370 MLU590
2	Job types	block U1 U4
3	Layouts	NHWC 、NCHW、ARRAY etc
4	Whether multi-dimensions are supported
5	Whether element zero is supported
6	Data type(half/float)	half / float etc
7	Whether there is size limit

3.1.3 New Feature Test

If you have checked the following items, please tick the relevant box.

• Data type test
• Multi-dimensional tensor test
• Layout test
• Different size/integer remainder end segment/alignment misalignment test
• Zero dimensional tensor test/zero element test
• stability test
• Multiple platform test
• Gen_case module test
• Nan/INF tests
• Bug fix tests
• For memory leak check details, seeGTest-User-Guide-zh.
• For code coverage check details, see: GTest-User-Guide-zh.
• For I/O calculation efficiency check details, see: MLU-OPS Performance Acceptance Standard.

3.1.4 Parameter Check

When a new operator is submitted, the test points are given and the test results are stated.

Test Point	Acceptance Standard	Test Result (Error Message)
Whether it conforms to the operator restriction	Normal error
Whether illegal parameters are passed	Normal error

3.2 Accuracy Test

For the cases used in the New Feature Test section, the features and the number of cases are recorded here. When multiple operations are tested, multiple tables are needed to include details of these operations.

Operation:

Test Point	Description	Quantity	Comment
Data type test	half/float/int8
Mult-tensor test	Supports 1-8 dims
Layout test	Supports NCHW/NHWC
Zero element test	Whether to support this test
Stability test	--gtest_repeat=NUM --thread=NUM
mlu-only mode test	--mlu-only,see MLU-OPS Performance Acceptance Standard
Mult-platform test	MLU370/MLU590
Nan/INF test	Whether to support this test
Memory leak check	Test result
Code coverage check	Test result

3.3 Performance Test

See MLU-OPS Performance Acceptance Standard for details.

Platform：MLU370

Operation	Mlu_hardware_time(us)	Mlu_interface_time(us)	Mlu_io_efficiency	Mlu_compute_efficiency	Mlu_workwpace_size(Bytes)	Data_type	Shape
op_name
op_name

Platform：MLU590

Operation	Mlu_hardware_time(us)	Mlu_interface_time(us)	Mlu_io_efficiency	Mlu_compute_efficiency	Mlu_workwpace_size(Bytes)	Data_type	Shape
op_name
op_name

3.4 Summary Analysis

Please give a brief overview here, if you want to note and summarize the content.