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MAC_scheduling

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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    ArrowInvalid
Message:      Float value 0.195830 was truncated converting to int64
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2303, in cast_table_to_schema
                  cast_array_to_feature(
                  ~~~~~~~~~~~~~~~~~~~~~^
                      table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                      feature,
                      ^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1852, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ~~~~^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2143, in cast_array_to_feature
                  return array_cast(
                      array,
                  ...<2 lines>...
                      allow_decimal_to_str=allow_decimal_to_str,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1854, in wrapper
                  return func(array, *args, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2006, in array_cast
                  return array.cast(pa_type)
                         ~~~~~~~~~~^^^^^^^^^
                File "pyarrow/array.pxi", line 1147, in pyarrow.lib.Array.cast
                File "/usr/local/lib/python3.14/site-packages/pyarrow/compute.py", line 412, in cast
                  return call_function("cast", [arr], options, memory_pool)
                File "pyarrow/_compute.pyx", line 604, in pyarrow._compute.call_function
                File "pyarrow/_compute.pyx", line 399, in pyarrow._compute.Function.call
                  result = GetResultValue(
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                  return check_status(status)
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: Float value 0.195830 was truncated converting to int64
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1869, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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mcs_0
int64
mcs_1
int64
mcs_2
int64
mcs_3
int64
q_0
int64
q_1
int64
q_2
int64
q_3
int64
g_0
int64
g_1
int64
g_2
int64
g_3
int64
obs_0
int64
obs_1
int64
obs_2
int64
obs_3
int64
raw_mcs_0
int64
raw_mcs_1
int64
raw_mcs_2
int64
raw_mcs_3
int64
raw_q_0
float64
raw_q_1
float64
raw_q_2
float64
raw_q_3
float64
raw_g_0
float64
raw_g_1
float64
raw_g_2
float64
raw_g_3
float64
thput_0
float64
thput_1
float64
thput_2
float64
thput_3
float64
gfbr_0
float64
gfbr_1
float64
gfbr_2
float64
gfbr_3
float64
action_v
int64
action_wq_0
int64
action_wq_1
int64
action_wq_2
int64
action_wq_3
int64
action_wg_0
int64
action_wg_1
int64
action_wg_2
int64
action_wg_3
int64
reward
float64
reward_thput
float64
reward_rbs
float64
next_mcs_0
int64
next_mcs_1
int64
next_mcs_2
int64
next_mcs_3
int64
next_q_0
int64
next_q_1
int64
next_q_2
int64
next_q_3
int64
next_g_0
int64
next_g_1
int64
next_g_2
int64
next_g_3
int64
next_obs_0
int64
next_obs_1
int64
next_obs_2
int64
next_obs_3
int64
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5,999,900
5,999,900
5,999,900
5,999,900
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28
13,168.8
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1
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26
14,576.5
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28
13,450.8
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28
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13,384.7
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13,248.5
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25
542,855
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24
1,407,050
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420,106
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1
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28
28
16,917.9
14,675.1
11,597.3
7,914.7
3,497,270
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5,142,860
9,999,840
9,999,840
9,999,840
9,999,840
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17,003.4
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5,176,470
5,142,860
9,999,840
9,999,840
9,999,840
9,999,840
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28
16,878.3
14,623.4
11,553.5
7,960.47
3,484,570
2,344,440
5,215,780
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9,999,840
9,999,840
9,999,840
9,999,840
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1
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
1
0
28
28
28
28
13,882.1
15,525.5
11,973
8,741.04
3,037,300
2,854,720
5,722,270
5,489,260
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.706904
1
0.413807
2
1
1
2
0
0
0
0
1
1
1
1
0
1
1
0
2
1
1
2
0
0
0
0
1
1
1
1
0
1
1
0
28
22
24
28
13,223.3
16,222.7
12,082.8
9,025.22
3,318,720
3,012,600
6,216,560
5,684,540
9,999,840
9,833,180
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.692186
1
0.384372
2
1
2
2
0
0
0
0
1
1
1
1
0
0
1
0
2
1
2
2
0
0
0
0
1
1
1
1
0
0
1
0
28
24
25
28
13,337.2
16,175.2
12,154.4
9,025.12
3,375,680
2,904,110
6,368,030
5,722,490
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
7
0
1
1
0
0
3
0
2
0.690289
1
0.380579
2
1
1
2
0
0
0
0
1
1
1
1
0
0
0
1
2
1
1
2
0
0
0
0
1
1
1
1
0
0
0
1
28
24
24
28
11,721.4
18,097.8
11,654.5
9,107.72
4,227,040
3,717,270
8,329,110
7,342,730
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
6
0
3
1
1
2
3
2
3
0.718047
1
0.436094
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
1
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
1
28
28
28
28
12,469.9
14,168.1
10,584.4
9,083.9
3,610,000
3,324,440
7,533,330
6,304,760
9,999,840
10,166,500
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.732816
1
0.465633
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
1
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
1
28
28
28
28
16,932.5
14,826
11,660.1
7,846.03
3,522,940
2,300,000
5,201,880
5,161,900
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.732806
1
0.465612
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
1
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
1
28
28
28
28
16,339
14,362.8
11,625.7
8,048.73
3,317,220
2,392,660
5,239,930
5,178,790
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
8
3
3
2
0
0
1
1
2
0.730849
1
0.461698
2
2
1
2
0
0
0
0
1
1
2
1
0
0
0
1
2
2
1
2
0
0
0
0
1
1
2
1
0
0
0
1
28
28
24
28
12,419
11,165.6
10,674
9,061.7
4,057,610
5,095,270
11,249,500
8,475,060
9,833,180
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
2
2
3
3
3
0
3
3
0.732345
1
0.464689
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
1
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
1
28
28
28
28
16,999.2
14,763.2
11,647
7,853.67
3,522,940
2,322,220
5,277,000
5,200,000
10,166,500
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.708515
1
0.41703
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
28
28
28
28
16,995.1
14,784.6
11,682.5
7,823.15
3,522,940
2,277,780
5,176,470
5,142,860
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.732806
1
0.465612
2
2
2
2
0
0
0
0
1
1
1
1
1
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
1
0
0
0
28
28
28
28
16,650.9
13,466.7
10,655.4
8,986.62
3,216,080
2,844,440
5,495,800
5,142,860
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
9
0
3
0
0
1
2
0
3
0.718675
1
0.437349
1
2
2
2
0
0
0
0
1
1
1
1
1
0
0
0
1
2
2
2
0
0
0
0
1
1
1
1
1
0
0
0
22
28
28
28
72,241.3
11,617.8
10,214.2
9,679.36
4,584,730
5,206,270
9,951,470
9,238,700
8,999,860
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
4
1
1
2
0
0
0
2
3
0.724368
1
0.448736
1
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
1
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
22
28
28
28
28,423.3
12,833.6
9,501.3
10,372.4
3,368,400
4,488,660
7,560,640
7,884,520
10,833,200
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.683417
1
0.366834
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
26
28
28
28
16,533.6
13,338.8
9,084.53
10,601.9
3,209,070
2,944,440
5,206,650
5,596,670
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
2
0
0
0
0
1
2
3
3
0.718877
1
0.437755
1
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
1
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
23
28
28
28
16,929
11,754.4
10,461.1
9,347.29
3,926,220
4,663,420
9,723,300
8,046,190
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.727347
1
0.454693
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
28
28
28
28
16,999.1
14,758.8
11,660.1
7,846.03
3,522,940
2,311,110
5,239,440
5,180,950
10,166,500
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.732806
1
0.465612
2
2
2
2
0
0
0
0
1
1
1
1
0
1
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
1
0
0
28
28
28
28
14,067.3
13,419.4
9,963.62
12,529
3,432,390
2,940,030
5,741,790
4,602,000
9,999,840
9,999,840
9,999,840
9,833,180
2,000,000
2,000,000
4,000,000
4,000,000
5
3
3
3
2
2
0
2
3
0.701225
1
0.40245
2
2
2
1
0
0
0
0
1
1
1
1
0
1
0
0
2
2
2
1
0
0
0
0
1
1
1
1
0
1
0
0
28
26
28
22
11,730.6
11,739.8
9,157.26
15,169.2
4,765,460
4,603,150
7,622,740
5,679,980
9,833,180
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
8
0
2
2
2
1
2
1
0
0.681945
1
0.363891
2
2
2
1
0
0
0
0
2
2
2
2
0
1
0
0
2
2
2
1
0
0
0
0
2
2
2
2
0
1
0
0
28
28
28
23
539,464
540,049
415,033
437,754
76,090,500
84,734,100
79,618,300
230,803,000
1,833,300
1,833,300
3,666,610
3,666,610
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.18333
0.916652
0
2
2
2
0
0
0
0
0
1
1
1
1
1
1
0
0
2
2
2
0
0
0
0
0
1
1
1
1
1
1
0
0
28
28
28
16
646,861
710,966
290,570
977,780
3,634,160
3,605,770
6,417,690
8,829,920
17,166,400
16,333,100
16,333,100
7,999,870
2,000,000
2,000,000
4,000,000
4,000,000
6
0
2
3
3
2
0
1
0
0.530458
1
0.060917
2
2
2
0
0
0
0
1
2
2
2
2
1
1
0
1
2
2
2
0
0
0
0
1
2
2
2
2
1
1
0
1
26
28
28
14
661,285
747,348
405,975
1,499,370
58,334,200
56,916,400
51,233,000
207,916,000
1,999,970
1,833,300
3,666,610
3,666,610
2,000,000
2,000,000
4,000,000
4,000,000
4
0
3
0
1
2
1
0
3
0.187497
0.937485
0
2
1
2
0
0
0
0
1
1
1
1
1
1
1
0
1
2
1
2
0
0
0
0
1
1
1
1
1
1
1
0
1
26
22
28
16
792,982
864,320
266,907
1,993,230
3,362,610
3,599,350
6,060,120
7,721,000
16,999,700
17,499,700
16,333,100
9,666,510
2,000,000
2,000,000
4,000,000
4,000,000
9
1
0
1
2
3
0
3
3
0.518958
1
0.037917
2
2
2
0
0
0
0
1
1
1
1
1
1
1
0
1
2
2
2
0
0
0
0
1
1
1
1
1
1
1
0
1
26
27
28
19
78,928
120,117
9,136.12
2,063,590
3,738,310
3,656,700
7,720,530
6,649,960
12,166,500
12,499,800
9,999,840
7,999,870
2,000,000
2,000,000
4,000,000
4,000,000
3
1
2
0
1
0
0
1
1
0.660794
1
0.321589
2
2
2
0
0
0
0
1
2
2
2
2
0
1
0
0
2
2
2
0
0
0
0
1
2
2
2
2
0
1
0
0
27
28
28
18
519,242
508,108
361,286
2,606,870
31,060,800
33,353,100
30,236,900
111,376,000
1,999,970
2,166,630
4,333,260
3,666,610
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.195832
0.979159
0
2
1
2
0
0
0
0
1
1
1
1
1
0
1
0
0
2
1
2
0
0
0
0
1
1
1
1
1
0
1
0
0
26
23
28
16
691,483
651,310
225,500
3,090,520
3,274,690
3,420,110
5,664,560
6,088,340
15,499,800
15,833,100
15,666,400
12,333,100
2,000,000
2,000,000
4,000,000
4,000,000
1
2
3
2
1
0
1
2
0
0.536917
1
0.073833
2
2
2
2
0
0
0
1
2
2
2
2
0
0
0
0
2
2
2
2
0
0
0
1
2
2
2
2
0
0
0
0
28
26
28
28
820,462
758,189
401,249
3,108,120
36,129,000
43,673,700
36,217,100
36,118,000
1,999,970
2,166,630
3,833,270
3,833,270
2,000,000
2,000,000
4,000,000
4,000,000
4
0
1
3
3
1
2
1
3
0.195831
0.979155
0
2
2
2
2
1
1
0
1
1
1
1
1
0
0
1
0
2
2
2
2
1
1
0
1
1
1
1
1
0
0
1
0
28
28
28
28
1,112,670
1,120,200
257,972
2,447,570
4,227,460
4,275,150
5,894,060
3,487,700
14,499,800
12,833,100
16,166,400
27,666,200
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.515042
1
0.030083
2
2
2
2
0
0
0
0
1
1
1
1
0
0
1
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
1
0
28
27
28
28
387,099
566,035
10,197.2
417,393
3,428,820
2,925,230
8,458,430
4,416,360
15,999,700
16,999,700
9,999,840
19,666,400
2,000,000
2,000,000
4,000,000
4,000,000
1
1
3
0
2
0
1
1
2
0.574597
1
0.149195
2
2
2
2
0
0
0
0
1
1
1
1
0
0
1
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
1
0
28
26
26
28
11,863.6
14,668
10,770.3
9,119.34
4,627,350
3,791,110
9,809,920
7,630,330
9,999,840
9,833,180
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
2
3
3
0
1
0
0
3
1
0.726288
1
0.452576
2
2
2
2
0
0
0
0
1
1
1
2
0
0
1
0
2
2
2
2
0
0
0
0
1
1
1
2
0
0
1
0
28
28
28
28
146,209
201,024
8,825.61
79,541.9
7,436,920
8,058,580
9,250,960
10,332,400
7,666,540
6,999,890
9,999,840
8,999,860
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.752853
1
0.505707
2
2
2
1
0
0
0
0
1
1
1
1
0
0
0
1
2
2
2
1
0
0
0
0
1
1
1
1
0
0
0
1
26
28
28
23
78,772
104,441
9,126.42
28,021.2
2,980,880
2,777,110
6,298,510
5,302,330
12,333,100
13,166,500
9,999,840
10,999,800
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.662286
1
0.324572
2
2
2
2
0
0
0
0
1
1
1
1
1
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
1
0
0
0
26
28
28
28
15,106.6
12,585
9,085.15
12,551.8
3,134,560
2,862,680
5,543,530
4,827,110
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
7
3
3
3
3
3
0
1
3
0.706695
1
0.413389
2
2
2
1
0
0
0
0
1
1
1
1
0
0
1
1
2
2
2
1
0
0
0
0
1
1
1
1
0
0
1
1
26
28
28
22
13,649.5
12,190.2
9,671.9
12,109.4
3,626,000
3,856,860
7,022,680
6,886,260
9,833,180
9,833,180
9,999,840
9,833,180
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.682437
1
0.364874
1
0
2
1
0
0
0
0
1
1
1
1
0
1
1
1
1
0
2
1
0
0
0
0
1
1
1
1
0
1
1
1
24
14
26
23
12,798.8
214,434
10,259.1
12,323.6
3,768,170
4,001,650
6,801,750
6,600,020
10,166,500
6,833,220
9,999,840
10,166,500
2,000,000
2,000,000
4,000,000
4,000,000
3
3
0
3
1
0
3
2
2
0.645285
1
0.290571
2
0
2
2
0
0
0
0
2
2
2
2
0
1
1
1
2
0
2
2
0
0
0
0
2
2
2
2
0
1
1
1
26
11
26
27
419,976
940,991
191,491
261,510
16,775,400
93,447,900
16,292,000
19,623,000
3,499,940
1,999,970
7,166,550
5,833,240
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.199999
0.999996
0
2
0
2
2
0
1
0
0
1
1
1
1
0
1
1
1
2
0
2
2
0
1
0
0
1
1
1
1
0
1
1
1
26
13
26
28
468,785
1,792,880
85,703.8
157,114
3,096,090
6,317,010
6,540,490
6,291,580
16,499,700
5,833,240
12,833,100
14,166,400
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.572792
1
0.145583
2
0
2
2
0
1
0
0
1
1
1
1
0
1
1
1
2
0
2
2
0
1
0
0
1
1
1
1
0
1
1
1
28
16
26
28
12,781.8
2,010,320
10,812
11,137.7
5,311,010
3,251,950
8,333,210
7,588,460
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.598292
1
0.196584
2
0
2
2
0
1
0
0
1
1
1
1
0
1
0
0
2
0
2
2
0
1
0
0
1
1
1
1
0
1
0
0
28
14
26
28
13,162.8
1,987,960
10,864.5
10,846
5,030,710
3,266,580
8,011,290
7,648,120
9,999,840
9,666,510
9,999,840
9,833,180
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.608167
1
0.216333
2
0
1
1
0
1
0
0
1
1
1
1
0
1
0
0
2
0
1
1
0
1
0
0
1
1
1
1
0
1
0
0
28
16
24
23
13,207.6
2,030,070
10,027.8
11,424.1
5,518,370
3,082,480
8,179,880
8,833,140
9,999,840
10,333,200
9,999,840
10,166,500
2,000,000
2,000,000
4,000,000
4,000,000
1
3
1
2
3
2
2
1
3
0.554001
1
0.108002
2
0
2
2
0
1
0
0
1
1
1
1
0
0
0
0
2
0
2
2
0
1
0
0
1
1
1
1
0
0
0
0
28
15
28
28
12,491.6
2,285,130
10,553.6
10,137.1
5,463,040
6,464,200
9,830,040
9,103,480
9,999,840
4,833,260
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
8
2
3
2
3
1
0
2
3
0.728971
1
0.457943
2
0
2
2
0
1
0
0
1
1
2
1
0
0
0
0
2
0
2
2
0
1
0
0
1
1
2
1
0
0
0
0
28
14
28
28
12,473.4
2,938,220
10,732.9
9,908.6
5,473,300
7,573,670
10,226,200
8,889,950
9,999,840
4,166,600
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.739397
1
0.478795
2
0
2
2
0
1
0
0
1
1
1
2
0
0
0
0
2
0
2
2
0
1
0
0
1
1
1
2
0
0
0
0
28
15
28
28
14,107.4
1,490,500
9,626.2
10,154
6,428,840
2,053,150
8,142,180
10,696,300
9,999,840
35,666,100
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.557837
1
0.115674
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
28
28
28
28
16,995.2
14,789
11,669.3
7,830.78
3,522,940
2,277,780
5,176,470
5,142,860
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.708515
1
0.41703
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
28
28
28
28
16,995.1
14,784.6
11,682.5
7,823.15
3,522,940
2,277,780
5,176,470
5,142,860
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
6
2
2
0
0
1
3
3
1
0.732806
1
0.465612
2
2
2
2
0
0
0
0
1
1
2
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
2
1
0
0
0
0
28
28
28
28
14,375.1
13,350.2
9,896.49
8,646.52
5,629,240
5,734,090
10,187,800
8,561,920
9,833,180
9,833,180
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.708557
1
0.417113
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
28
28
28
28
16,999.1
14,758.8
11,660.1
7,846.03
3,522,940
2,288,890
5,239,440
5,180,950
10,166,500
10,166,500
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
7
0
3
3
0
1
0
2
1
0.732806
1
0.465612
2
2
2
2
0
0
0
0
1
1
1
1
0
0
1
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
1
0
28
28
28
28
23,452.6
16,752.4
11,521.1
8,640.27
5,736,980
5,849,740
9,529,770
8,365,690
9,833,180
9,833,180
9,833,180
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.721358
1
0.442715
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
28
28
27
28
15,252
13,348.4
12,099
8,375.86
3,128,540
2,556,530
4,933,730
5,480,380
10,166,500
10,166,500
10,166,500
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
8
1
2
3
3
1
2
2
1
0.719281
1
0.438561
2
2
2
2
0
0
0
0
1
1
2
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
2
1
0
0
0
0
28
28
28
28
81,236.7
76,883
9,887.47
8,646.52
7,244,030
7,303,180
10,464,700
8,695,010
8,833,190
8,833,190
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.746932
1
0.493864
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
28
28
28
28
24,085
22,705.6
11,573.9
7,946.66
3,412,590
2,366,200
5,726,220
5,425,180
11,166,500
11,166,500
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.718932
1
0.437865
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
28
28
28
28
16,995.2
14,789
11,669.3
7,830.78
3,522,940
2,277,780
5,176,470
5,142,860
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
5
2
3
0
2
2
1
1
1
0.708515
1
0.41703
2
2
2
2
0
0
0
0
1
1
2
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
2
1
0
0
0
0
28
28
28
28
11,237.7
12,403.5
10,599.5
9,061.7
4,868,900
4,243,600
11,400,000
8,503,560
9,999,840
9,833,180
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
1
0
3
0
0
1
3
2
3
0.732813
1
0.465626
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
28
28
28
28
12,469.9
14,168.1
10,584.4
9,083.9
3,610,000
3,324,440
7,566,670
6,323,810
9,999,840
10,166,500
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
10
0
3
2
1
1
1
0
0
0.732816
1
0.465633
2
2
2
2
0
0
0
0
2
2
2
2
0
0
0
0
2
2
2
2
0
0
0
0
2
2
2
2
0
0
0
0
28
28
28
28
539,818
540,204
413,762
413,348
104,049,000
103,141,000
106,601,000
107,264,000
1,833,300
1,833,300
3,666,610
3,666,610
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.18333
0.916652
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
28
28
28
28
656,990
659,378
262,472
254,566
3,933,530
3,875,460
5,775,930
6,948,840
18,166,400
18,166,400
16,333,100
16,333,100
2,000,000
2,000,000
4,000,000
4,000,000
10
3
1
2
2
3
1
3
3
0.50072
1
0.00144
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
28
28
28
28
13,125.2
11,757.6
10,599.5
9,061.7
3,621,020
4,332,720
9,450,000
7,391,920
9,833,180
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.732829
1
0.465659
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
28
28
28
28
16,999.2
14,763.2
11,647
7,853.67
3,522,940
2,311,110
5,239,440
5,180,950
10,166,500
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.708515
1
0.41703
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
28
28
28
28
16,995.1
14,784.6
11,682.5
7,823.15
3,522,940
2,277,780
5,176,470
5,142,860
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.732806
1
0.465612
2
2
2
2
0
0
0
0
1
1
1
1
0
0
1
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
1
0
28
28
28
28
14,734.2
12,439.9
12,845.7
8,683.69
3,323,020
2,723,780
4,468,730
5,562,350
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.707614
1
0.415228
2
2
1
2
0
0
0
0
1
1
1
1
0
0
1
0
2
2
1
2
0
0
0
0
1
1
1
1
0
0
1
0
28
28
22
28
13,639.2
11,165.1
14,078.8
8,995.65
3,361,260
2,978,420
4,400,620
5,862,080
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
7
2
2
1
0
3
3
0
2
0.697414
1
0.394828
2
2
1
2
0
0
0
0
1
1
1
1
0
0
1
0
2
2
1
2
0
0
0
0
1
1
1
1
0
0
1
0
28
28
24
28
12,007.8
10,543.5
12,853.2
9,170.21
4,374,190
4,434,500
6,698,460
7,716,420
9,999,840
9,999,840
9,833,180
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.703832
1
0.407663
2
2
0
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
0
2
0
0
0
0
1
1
1
1
0
0
0
0
28
28
21
28
13,872.9
11,387.4
14,124.9
9,030.58
3,372,410
2,971,530
4,438,320
5,827,270
9,999,840
9,999,840
10,166,500
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.697306
1
0.394612
2
2
0
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
0
2
0
0
0
0
1
1
1
1
0
0
0
0
28
28
20
28
13,587.8
11,118.2
14,312.4
8,977.61
3,362,520
2,951,530
4,398,530
5,856,820
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
5
0
0
2
2
2
1
2
1
0.696054
1
0.392108
2
2
0
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
0
2
0
0
0
0
1
1
1
1
0
0
0
0
28
28
20
28
12,310.9
48,092
13,341.5
9,114.84
4,933,970
5,297,800
9,684,870
8,300,840
9,999,840
9,333,180
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.723203
1
0.446406
2
2
2
2
0
0
0
0
1
1
1
1
0
1
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
1
0
0
28
27
28
28
14,240
17,586.8
10,825.4
8,810.53
2,985,610
3,140,050
5,705,510
5,311,160
9,999,840
10,666,500
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
9
0
2
3
2
1
1
2
1
0.721774
1
0.443547
2
2
2
2
0
0
0
0
1
1
2
1
0
1
0
0
2
2
2
2
0
0
0
0
1
1
2
1
0
1
0
0
28
26
28
28
143,024
228,155
9,456.17
8,414.43
7,231,510
8,184,830
10,184,400
9,400,490
7,833,210
6,666,560
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.762487
1
0.524975
2
2
2
2
0
0
0
0
1
1
1
1
0
1
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
1
0
0
28
27
28
28
45,346.4
93,143.7
10,779.2
8,897.61
3,037,640
2,875,680
6,569,310
6,060,740
12,166,500
13,333,100
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
10
3
2
2
3
3
3
0
1
0.68889
1
0.37778
2
2
2
2
0
0
0
0
1
1
2
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
2
1
0
0
0
0
28
25
28
28
182,338
240,459
9,556.64
8,416.45
8,477,920
9,018,150
10,124,900
9,324,750
7,166,550
6,333,230
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.769986
1
0.539972
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
28
27
28
28
66,134.4
109,539
10,848.9
8,766.76
2,937,800
2,822,090
6,920,460
5,944,340
12,833,100
13,666,400
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.681994
1
0.363987
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
28
26
28
28
16,901
14,701.8
11,573.5
7,945.22
3,497,270
2,325,430
5,190,700
5,142,860
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
0
0
0
0
0
0
0
0
0
0.732282
1
0.464564
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
2
2
2
2
0
0
0
0
1
1
1
1
0
0
0
0
28
28
28
28
16,995.2
14,789
11,669.3
7,830.78
3,522,940
2,277,780
5,176,470
5,142,860
9,999,840
9,999,840
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
3
0
2
2
0
1
0
1
0
0.708515
1
0.41703
2
2
2
2
0
0
0
0
2
2
2
2
0
0
1
0
2
2
2
2
0
0
0
0
2
2
2
2
0
0
1
0
28
28
28
28
586,086
586,068
487,329
466,528
460,764,000
460,619,000
665,477,000
499,270,000
1,333,310
1,333,310
2,999,950
3,166,620
2,000,000
2,000,000
4,000,000
4,000,000
1
0
0
2
1
3
3
0
3
0.143748
0.718738
0
2
2
1
2
0
0
0
0
2
2
2
2
0
0
0
1
2
2
1
2
0
0
0
0
2
2
2
2
0
0
0
1
28
28
23
28
741,019
745,696
535,451
392,998
13,361,900
14,031,300
17,774,800
15,346,600
15,499,800
15,499,800
16,499,700
16,666,400
2,000,000
2,000,000
4,000,000
4,000,000
8
3
2
1
0
0
3
1
2
0.488409
1
-0.023182
2
2
2
1
0
0
0
0
1
1
1
1
1
0
0
1
2
2
2
1
0
0
0
0
1
1
1
1
1
0
0
1
28
28
28
22
265,384
217,177
10,885.5
11,596.3
4,133,820
4,098,970
7,766,740
8,646,110
11,666,500
12,499,800
10,499,800
10,166,500
2,000,000
2,000,000
4,000,000
4,000,000
10
0
2
3
1
0
0
1
2
0.678464
1
0.356928
2
2
2
1
0
0
0
0
1
1
1
1
1
0
0
1
2
2
2
1
0
0
0
0
1
1
1
1
1
0
0
1
26
28
28
24
211,658
31,503.6
8,997
11,501.6
4,960,470
4,722,310
8,000,000
8,595,750
9,499,850
10,499,800
9,999,840
9,833,180
2,000,000
2,000,000
4,000,000
4,000,000
0
3
1
1
3
1
0
2
2
0.680467
1
0.360933
2
2
2
1
0
0
0
0
1
1
1
1
1
0
0
0
2
2
2
1
0
0
0
0
1
1
1
1
1
0
0
0
27
28
28
22
33,176.1
12,923.3
8,408.69
12,619.3
2,752,570
2,703,520
5,866,670
5,776,740
11,999,800
10,166,500
9,999,840
10,166,500
2,000,000
2,000,000
4,000,000
4,000,000
10
0
3
3
0
0
0
0
1
0.694077
1
0.388153
2
2
2
1
0
0
0
0
1
1
1
2
0
0
0
0
2
2
2
1
0
0
0
0
1
1
1
2
0
0
0
0
26
28
28
24
274,619
170,780
8,343.14
19,589.4
9,453,190
8,403,020
9,515,260
10,192,100
5,666,580
7,499,880
9,999,840
9,999,840
2,000,000
2,000,000
4,000,000
4,000,000
4
2
3
3
1
1
1
1
3
0.765443
1
0.530885
1
2
2
2
0
0
0
0
1
1
1
1
1
0
0
0
End of preview.

5G NR ISAC DRL-assisted MAC Scheduling Dataset

Overview

This dataset was generated as part of the 6G-SENSES project. It contains simulation traces that capture the network state and resulting performance metrics (rewards) in an environment that integrates communications and sensing (ISAC).

The goal of this dataset is to facilitate research and development of RL agents and other ML techniques for intelligent decision-making in the MAC scheduler of 5G networks.

The data comes from simulations performed in the ns-3 5g-LENA simulator, using the implementation available in the RBIS repository. This implementation includes a drift-plus-penalty scheduler for ns-3 5G-LENA responsible for the RB allocation among UEs, and an emulated xApp in which a DRL agent periodically adjusts the drift-plus-penalty weights to enhance performance and adaptability. For additional details about the scheduler implementation and its operation, readers are referred to this repository.

Simulation Context

The scenario simulates a single cell under realistic channel conditions, incorporating fast fading and 3GPP propagation models in an urban environment with buildings (UMa_Buildings scenario).

Specifically, the dataset was generated using the following configuration:

  • Network setup: 20 MHz bandwidth, 5G NR numerology 0, and 6 GHz carrier frequency.
  • User Equipments (UEs): 4 active UEs in total.
    • 2 Virtual Reality (VR) UEs.
    • 2 Cloud Gaming (CG) UEs.
  • Mobility: UEs are moving at a constant speed of 2 m/s using a Random Walk 2D mobility model (ns3::RandomWalk2dMobilityModel).
  • Traffic Models: 3GPP-compliant traffic models are used to generate application-layer traffic.
    • VR UEs: 10 Mbps data rate, 60 FPS, with a Guaranteed Flow Bit Rate (GFBR) of 2 Mbps.
    • CG UEs: 10 Mbps data rate, 60 FPS, with a GFBR of 4 Mbps.

Dataset Structure

The dataset contains tabular information where each row represents a simulation step (timestep) and contains the full RL environment transition: current state, action taken, reward obtained, and the next state.

The CSV columns are divided into the following categories:

1. Current State

The state of the network before taking the action. For each of the 4 UEs (i from 0 to 3), the following variables are categorized into 3 levels for simplicity:

  • mcs_i: Modulation and Coding Scheme (MCS).
  • q_i: Transmission buffer/queue occupancy level.
  • g_i: Virtual queue occupancy level.
  • obs_i: Binary indicator of obstacle presence that is expected to degrade the signal quality of UE i in the near future.

2. Throughput metrics

  • thput_i: Throughput obtained by the UE.
  • gfbr_i: GFBR required by the UE.

3. Actions

The decisions taken by the agent to adjust the scheduler weights.

  • action_v: Weight assigned to the reduction of Resource Block (RB) usage.
  • action_wq_i: Weight assigned to the queue of UE i.
  • action_wg_i: Weight assigned to the virtual queue of UE i.

4. Rewards

Feedback signals received after applying the action.

  • reward: Total aggregated reward calculated by the environment.
  • reward_thput: Reward component based on the obtained throughput.
  • reward_rbs: Reward component based on the assigned RBs.

5. Next State

The resulting state after applying the action. It follows the same structure as the current state:

  • next_mcs_i, next_q_i, next_g_i, next_obs_i (for i from 0 to 3).
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