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TempusBench Docs

Guides

Time Series Forecasting Benchmarking Pipeline (`tempus_bench`)
Tempus Bench — library documentation
TODO - Benchmarking Pipeline Improvements
Chronos-2 Covariate Data Flow
Covariate Testing Guide
Foundation Models: Covariate Support Reference
Config Module Coverage Summary
Models Served in Chronax
Model Set Comparison: (Tempus Bench ∪ Chronax) vs StatsForecast
Models Served in StatsForecast
Models Served in Tempus Bench
Model capabilities (`settings.yaml`)
Forecasting Model Implementations & Explanations
Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
TimesFM
TimesFM 2.5
TimesFM
Welcome
Toto - Time Series Optimized Transformer for Observability
BOOM (Benchmark of Observability Metrics) Evaluations
Time Series Tasks

API Reference

tempus_bench
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- models
  - chronos_tiny
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    chronos_tiny_model
  - lafn
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  - moirai_base
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  - moment_large
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  - tiny_time_mixer_r1
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  - base_model
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  - timesfm_model
  - timesfm2_model
  - timesfm_500m_model
  - timesnet_model
  - tiny_time_mixer_model
  - tiny_time_mixer_r2_model
  - tiny_time_mixer_r2_1_model
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- pipeline
- utils
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- utils
- compat.lightning_pytree
test_metric_registry_init

`MAPE`

chronax.metrics.mape.MAPE · inherits BaseMetric

Calculates Mean Absolute Percentage Error.

`init(self)`

Initializes the MAPE metric.

On this page

MAPE
__init__(self)