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improve examples
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DaStoll committed Nov 14, 2024
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2 changes: 1 addition & 1 deletion docs/index.md
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Expand Up @@ -32,7 +32,7 @@ In addition to the features offered by traditional HPO and NAS libraries, NePS s
* [Reference documentation](./reference/neps_run.md) for a quick overview.
* [API](./api/neps/api.md) for a more detailed reference.
* [Colab Tutorial](https://colab.research.google.com/drive/11IOhkmMKsIUhWbHyMYzT0v786O9TPWlH?usp=sharing) walking through NePS's main features.
* [Examples](./examples/template/basic_template.md) for copy-pastable code to get started.
* [Examples](./examples) for basic code snippets to get started.

## Installation

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12 changes: 3 additions & 9 deletions neps_examples/README.md
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1. **Basic usage examples** demonstrate fundamental usage.
Learn how to perform Hyperparameter Optimization (HPO), Neural Architecture Search (NAS), and Joint Architecture and Hyperparameter Search (JAHS).
Understand how to analyze runs on a basic level, emphasizing that no neural network training is involved at this stage; the search is performed on functions to introduce NePS.
Understand how to analyze runs on a basic level.

2. **Efficiency examples** showcase how to enhance efficiency in NePS.
Learn about expert priors, multi-fidelity, and parallelization to streamline your pipeline and optimize search processes.

3. **Convenience examples** show tensorboard compatibility and its integration, explore the compatibility with PyTorch Lightning, and understand file management within the run pipeline function used in NePS.
3. **Convenience examples** show tensorboard compatibility and its integration, explore the compatibility with PyTorch Lightning, see the declarative API, understand file management within the run pipeline function used in NePS.

4. **Experimental examples** tailored for NePS contributors.
These examples provide insights and practices for experimental scenarios.

5. **Templates** to find a basic fill-in template to kickstart your hyperparameter search with NePS.
Use this template as a foundation for your projects, saving time and ensuring a structured starting point.

6. **YAML usage examples** to define NePS configurations and search spaces with YAML files, streamlining the setup and execution of experiments.
4. **Experimental examples** tailored for NePS contributors. These examples provide insights and practices for experimental scenarios.
2 changes: 1 addition & 1 deletion neps_examples/__init__.py
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"analyse",
"architecture",
"architecture_and_hyperparameters",
"hpo_usage_example",
"hyperparameters",
],
"convenience": [
"logging_additional_info",
"neps_tblogger_tutorial",
"running_on_slurm_scripts",
"neps_x_lightning",
"running_on_slurm_scripts",
"working_directory_per_pipeline",
],
"efficiency": [
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35 changes: 0 additions & 35 deletions neps_examples/basic_usage/hpo_usage_example.py

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3 changes: 1 addition & 2 deletions neps_examples/basic_usage/hyperparameters.py
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import logging
import time

import numpy as np

import neps


def run_pipeline(float1, float2, categorical, integer1, integer2):
# In this example we maximize an arbitrary sum for demonstration purposes
loss = -float(np.sum([float1, float2, int(categorical), integer1, integer2]))
# time.sleep(0.7) # For demonstration purposes
return loss


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41 changes: 0 additions & 41 deletions neps_examples/experimental/cost_aware.py

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91 changes: 0 additions & 91 deletions neps_examples/experimental/fault_tolerance.py

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81 changes: 0 additions & 81 deletions neps_examples/template/basic_template.py

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37 changes: 0 additions & 37 deletions neps_examples/template/ifbo_template.py

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