Add ChronosModel and ChronosBoltModel

CHANGELOG.md

@@ -10,8 +10,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Add `load_dataset` to public API ([#484](https://github.com/etna-team/etna/pull/484))
 - Add example of using custom pipeline pools in `Auto` ([#504](https://github.com/etna-team/etna/pull/504))
 - Add `MetricWithMissingHandling` base class, change signature of `etna.metrics.Metric` to return `None` values ([#514](https://github.com/etna-team/etna/pull/514))
-- 
-- 
+- Add `ChronosModel` ([#511](https://github.com/etna-team/etna/pull/511))
+- Add `ChronosBoltModel` ([#511](https://github.com/etna-team/etna/pull/511))
 - 
 - 
 - 

README.md

@@ -147,8 +147,9 @@ Available user extensions are the following:
 * `torch`: adds models based on neural nets,
 * `wandb`: adds wandb logger,
 * `auto`: adds AutoML functionality,
-* `statsforecast`: adds models from [statsforecast](https://nixtla.github.io/statsforecast/)
-* `classiciation`: adds time series classification functionality.
+* `statsforecast`: adds models from [statsforecast](https://nixtla.github.io/statsforecast/),
+* `classiciation`: adds time series classification functionality,
+* `chronos`: adds Chronos-like pretrained models.
 
 Install extension:
 ```bash

docs/source/api_reference/models.rst

@@ -114,3 +114,12 @@ Utilities for neural network models based on ``pytorch_forecasting``:
    :template: class.rst
 
    nn.PytorchForecastingDatasetBuilder
+
+Pretrained neural network models:
+
+.. autosummary::
+   :toctree: api/
+   :template: class.rst
+
+   nn.ChronosModel
+   nn.ChronosBoltModel

docs/source/installation.rst

@@ -23,7 +23,8 @@ Available user extensions are the following:
 - ``wandb``: adds wandb logger,
 - ``auto``: adds AutoML functionality,
 - ``statsforecast``: adds models from `statsforecast <https://nixtla.github.io/statsforecast/>`_,
-- ``classiciation``: adds time series classification functionality.
+- ``classiciation``: adds time series classification functionality,
+- ``chronos``: adds Chronos-like pretrained models.
 
 Install extension:
 

etna/libs/chronos/__init__.py

@@ -0,0 +1,178 @@
+"""
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+   5. Submission of Contributions. Unless You explicitly state otherwise,
+      any Contribution intentionally submitted for inclusion in the Work
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+      Notwithstanding the above, nothing herein shall supersede or modify
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+   8. Limitation of Liability. In no event and under no legal theory,
+      whether in tort (including negligence), contract, or otherwise,
+      unless required by applicable law (such as deliberate and grossly
+      negligent acts) or agreed to in writing, shall any Contributor be
+      liable to You for damages, including any direct, indirect, special,
+      incidental, or consequential damages of any character arising as a
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+   9. Accepting Warranty or Additional Liability. While redistributing
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+"""
+# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+# Note: Copied from chronos repository (https://github.com/amazon-science/chronos-forecasting/blob/47cac082c1848835db463bee1768bb355b26968f/src/chronos/__init__.py)
+
+from etna.libs.chronos.base import BaseChronosPipeline, ForecastType
+from etna.libs.chronos.chronos import (
+    ChronosConfig,
+    ChronosModelForForecasting,
+    ChronosPipeline,
+    ChronosTokenizer,
+    MeanScaleUniformBins,
+)
+from etna.libs.chronos.chronos_bolt import ChronosBoltConfig, ChronosBoltPipeline, ChronosBoltModelForForecasting
+
+__all__ = [
+    "BaseChronosPipeline",
+    "ForecastType",
+    "ChronosConfig",
+    "ChronosModelForForecasting",
+    "ChronosBoltModelForForecasting",
+    "ChronosPipeline",
+    "ChronosTokenizer",
+    "MeanScaleUniformBins",
+    "ChronosBoltConfig",
+    "ChronosBoltPipeline",
+]