chore(deps): bump ray from 2.52.1 to 2.54.0

[dependabot]

Bumps ray from 2.52.1 to 2.54.0.

Release notes

Sourced from ray's releases.

Ray-2.54.0

Ray Data

🎉 New Features

• Add checkpointing support to Ray Data (#59409)
• Compute Expressions: list operations (#59346), fixed-size arrays (#58741), string padding (#59552), logarithmic (#59549), trigonometric (#59712), arithmetic (#59678), and rounding (#59295)
• Add sql_params support to read_sql (#60030)
• Add AsList aggregation (#59920)
• Support CountDistinct aggregate (#59030)
• Add credential provider abstraction for Databricks UC datasource (#60457)
• Support callable classes for UDFExpr (#56725)
• Add autoscaler metrics to Data Dashboard (#60472)
• Add optional filesystem parameter to download expression (#60677)
• Allow specifying partitioning style or flavor in write_parquet() (#59102)
• New cluster autoscaler enabled by default (#60474)

💫 Enhancements

• Improve numerical stability in scalers by handling near-zero values (#60488)
• Export dataset operator output schema to event logger (#60086)
• Iceberg: add retry policy for Storage + Catalog writes (#60620)
• Iceberg: remove calls to Catalog Table in write tasks (#60476)
• Expose logical operators and rules via package exports (#60297, #60296)
• Demote Sort from requiring preserve_order (#60555)
• Improve appearance of repr(dataset) (#59631)
• Allow configuring DefaultClusterAutoscalerV2 thresholds via env vars (#60133)
• Use Arrow IPC for Arrow Schema serialization/deserialization (#60195)
• Store _source_paths in object store to prevent excessive spilling during read task serialization (#59999)
• Add more shuffle fusion rules (#59985)
• Enable and tune DownstreamCapacityBackpressurePolicy (#59753)
• Enable concurrency cap backpressure with tuning (#59392)
• Set default actor pool scale up threshold to 1.75 (#59512)
• Don't downscale actors if the operator hasn't received any inputs (#59883)
• Don't reserve GPU budget for non-GPU tasks (#59789)
• Only return selected data columns in hive-partitioned Parquet files (#60236)
• Ordered + FIFO bundle queue (#60228)
• Add node_id, pid, attempt number for hanging tasks (#59793)
• Revise resource allocator task scheduling to factor in pending task outputs (#60639)
• Track block serialization time (#60574)
• Use metrics from OpRuntimeMetrics for progress (#60304)
• Tabular form for streaming executor op metrics (#59774)
• Info-log cluster scale-up decisions (#60357)
• Use plain mode instead of grid mode for OpMetrics logging (#59907)
• Progress reporting refactors (#59350, #59629, #59880)
• Remove deprecated TENSOR_COLUMN_NAME constant (#60573)
• Remove meta_provider parameter (#60379)
• Decouple Ray Train from Ray Data by removing top-level ray.data imports (#60292)
• Move extension types to ray.data (#59420)
• Skip upscaling validation warning for fixed-size actor pools (#60569)

... (truncated)

Commits

• 48bd1f8 [data] revert "continue grabbing task state until response is not None" (#61066)
• 165b4aa [Data][Cherry-pick] Fixed min_scheduling_resources to fallback to incremental...
• 6835277 [rllib] disable failing tests that are not release blocking (#60933)
• f8e1102 [Core] Fix test_failed_task_runtime_env_setup failure on windows (#60852) (#6...
• 620214f [RLlib] Fix _test_dependency_torch (#60742) (#60888)
• 5d2115c cherrypick part of #60887 (#60897)
• e94871d [Data][Cherry-pick] Prevent Limit from getting pushed past map_groups (#6...
• a77457b [Data] Fixing ReservationOpResourceAllocator to properly borrow resources f...
• 0f27a3a [Serve] Video analysis example fix (#60784) (#60871)
• 1b1a9bd [Data] Fixing output backpressure unblocking sequence to properly handle term...
• Additional commits viewable in compare view

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[github-actions]

Experiment Results

Experiment 1: air-passengers

Description:

variable	experiment
h	12
season_length	12
freq	MS
level	None
n_windows	1

Results:

metric	timegpt-1	timegpt-1-long-horizon	SeasonalNaive	Naive
mae	12.6793	11.0623	47.8333	76
mape	0.027	0.0232	0.0999	0.1425
mse	213.936	199.132	2571.33	10604.2
total_time	18.7936	1.5242	0.0044	0.0036

Plot:

Experiment 2: air-passengers

Description:

variable	experiment
h	24
season_length	12
freq	MS
level	None
n_windows	1

Results:

metric	timegpt-1	timegpt-1-long-horizon	SeasonalNaive	Naive
mae	58.1031	58.4587	71.25	115.25
mape	0.1257	0.1267	0.1552	0.2358
mse	4040.21	4110.79	5928.17	18859.2
total_time	0.8439	0.8787	0.0039	0.0034

Plot:

Experiment 3: electricity-multiple-series

Description:

variable	experiment
h	24
season_length	24
freq	H
level	None
n_windows	1

Results:

metric	timegpt-1	timegpt-1-long-horizon	SeasonalNaive	Naive
mae	178.293	268.13	269.23	1331.02
mape	0.0234	0.0311	0.0304	0.1692
mse	121589	219485	213677	4.68961e+06
total_time	1.2722	1.3935	0.0048	0.0042

Plot:

Experiment 4: electricity-multiple-series

Description:

variable	experiment
h	168
season_length	24
freq	H
level	None
n_windows	1

Results:

metric	timegpt-1	timegpt-1-long-horizon	SeasonalNaive	Naive
mae	465.497	346.978	398.956	1119.26
mape	0.062	0.0436	0.0512	0.1583
mse	835021	403769	656723	3.17316e+06
total_time	0.7321	1.8215	0.005	0.0043

Plot:

Experiment 5: electricity-multiple-series

Description:

variable	experiment
h	336
season_length	24
freq	H
level	None
n_windows	1

Results:

metric	timegpt-1	timegpt-1-long-horizon	SeasonalNaive	Naive
mae	558.702	459.769	602.926	1340.95
mape	0.0697	0.0565	0.0787	0.17
mse	1.22728e+06	739162	1.61572e+06	6.04619e+06
total_time	1.454	0.9357	0.0051	0.0045

Plot:

[rogeliomj]

approved