tff.learning.programs.extract_and_rewrap_metrics
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Extracts a sub-structure and re-wraps it with a new prefix.
tff.learning.programs.extract_and_rewrap_metrics(
metrics_structure: Mapping[str, Any], *, path: Sequence[str]
) -> Mapping[str, Any]
This is used to normalize outputs from the training and evaluation
computations. For example, we are interested in the following substructure
from the evaluation and training tasks:
client_work/eval/current_round_metrics/...
client_work/eval/total_rounds_metrics/...
client_work/train/...
And we like to "re-home" these structures under:
model_metrics/...
while leaving all the other metrics alone. This can be thought of as a
"subtree promotion" method.
This is used for grouping metrics so that they appear aligned in
http://tensorboard/ in a uniform way. TensorBoard uses the name up to the
first / as a tab separator in the UI.
Args |
|---|
metrics_structure
|
The nested structure of tensor-like metric values.
|
path
|
A sequence of strings that will be used to traverse the keys of
metrics_structure and identify the substructure of interest.
|
Returns |
|---|
A structure of metrics of metrics_substructure.
|
Raises |
|---|
ValueError
|
If path is empty.
|
KeyError
|
If any key in path sequence does not exist in the
metrics_structure.
|
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Last updated 2024-09-20 UTC.
[null,null,["Last updated 2024-09-20 UTC."],[],[],null,["# tff.learning.programs.extract_and_rewrap_metrics\n\n\u003cbr /\u003e\n\n|-------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/federated/blob/v0.87.0 Version 2.0, January 2004 Licensed under the Apache License, Version 2.0 (the) |\n\nExtracts a sub-structure and re-wraps it with a new prefix. \n\n tff.learning.programs.extract_and_rewrap_metrics(\n metrics_structure: Mapping[str, Any], *, path: Sequence[str]\n ) -\u003e Mapping[str, Any]\n\nThis is used to normalize outputs from the training and evaluation\ncomputations. For example, we are interested in the following substructure\nfrom the evaluation and training tasks: \n\n client_work/eval/current_round_metrics/...\n client_work/eval/total_rounds_metrics/...\n client_work/train/...\n\nAnd we like to \"re-home\" these structures under: \n\n model_metrics/...\n\nwhile leaving all the other metrics alone. This can be thought of as a\n\"subtree promotion\" method.\n\nThis is used for grouping metrics so that they appear aligned in\n\u003chttp://tensorboard/\u003e in a uniform way. TensorBoard uses the name up to the\nfirst `/` as a tab separator in the UI.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|---------------------|--------------------------------------------------------------------------------------------------------------------------------|\n| `metrics_structure` | The nested structure of tensor-like metric values. |\n| `path` | A sequence of strings that will be used to traverse the keys of `metrics_structure` and identify the substructure of interest. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A structure of metrics of `metrics_substructure`. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|--------------|--------------------------------------------------------------------------|\n| `ValueError` | If `path` is empty. |\n| `KeyError` | If any key in `path` sequence does not exist in the `metrics_structure`. |\n\n\u003cbr /\u003e"]]
View source on GitHub