tfl.test_utils.sample_uniformly
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Deterministically generates num_point random points within bounds.
tfl.test_utils.sample_uniformly(
num_points, lower_bounds, upper_bounds
)
Points will be such that:
lower_bounds[i] <= p[i] <= upper_bounds[i]
Number of dimensions is defined by lengths of lower_bounds list.
Args |
num_points
|
number of points to generate.
|
lower_bounds
|
list or tuple of lower bounds.
|
upper_bounds
|
list or tuple of upper bounds.
|
Returns |
List of generated points.
|
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Last updated 2024-08-02 UTC.
[null,null,["Last updated 2024-08-02 UTC."],[],[],null,["# tfl.test_utils.sample_uniformly\n\n\u003cbr /\u003e\n\n|------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/lattice/blob/v2.1.1/tensorflow_lattice/python/test_utils.py#L158-L186) |\n\nDeterministically generates num_point random points within bounds. \n\n tfl.test_utils.sample_uniformly(\n num_points, lower_bounds, upper_bounds\n )\n\nPoints will be such that:\nlower_bounds\\[i\\] \\\u003c= p\\[i\\] \\\u003c= upper_bounds\\[i\\]\n\nNumber of dimensions is defined by lengths of lower_bounds list.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------------|--------------------------------|\n| `num_points` | number of points to generate. |\n| `lower_bounds` | list or tuple of lower bounds. |\n| `upper_bounds` | list or tuple of upper bounds. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| List of generated points. ||\n\n\u003cbr /\u003e"]]