Skip to content

Add model run name for model.run #435

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 4 commits into from
Apr 2, 2024
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension


Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 6 additions & 0 deletions CHANGELOG.md
Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,12 @@ All notable changes to the [Nucleus Python Client](https://github.com/scaleapi/n
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).

## [0.17.4](https://github.com/scaleapi/nucleus-python-client/releases/tag/v0.17.4) - 2024-03-25

### Modified
- In `Model.run`, added the `model_run_name` parameter. This allows the creation of multiple model runs for datasets.


## [0.17.3] - 2024-02-29

### Added
Expand Down
15 changes: 12 additions & 3 deletions nucleus/model.py
Original file line number Diff line number Diff line change
Expand Up @@ -211,7 +211,9 @@ def evaluate(self, scenario_test_names: List[str]) -> AsyncJob:
)
return AsyncJob.from_json(response, self._client)

def run(self, dataset_id: str, slice_id: Optional[str]) -> str:
def run(
self, dataset_id: str, model_run_name: str, slice_id: Optional[str]
) -> str:
"""Runs inference on the bundle associated with the model on the dataset. ::

import nucleus
Expand All @@ -222,11 +224,18 @@ def run(self, dataset_id: str, slice_id: Optional[str]) -> str:

Args:
dataset_id: The ID of the dataset to run inference on.
job_id: The ID of the :class:`AsyncJob` used to track job progress.
model_run_name: The name of the model run.
slice_id: The ID of the slice of the dataset to run inference on.

Returns:
job_id: The ID of the :class:`AsyncJob` used to track job progress.
"""
response = self._client.make_request(
{"dataset_id": dataset_id, "slice_id": slice_id},
{
"dataset_id": dataset_id,
"slice_id": slice_id,
"model_run_name": model_run_name,
},
f"model/run/{self.id}/",
requests_command=requests.post,
)
Expand Down
2 changes: 1 addition & 1 deletion pyproject.toml
Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,7 @@ ignore = ["E501", "E741", "E731", "F401"] # Easy ignore for getting it running

[tool.poetry]
name = "scale-nucleus"
version = "0.17.3"
version = "0.17.4"
description = "The official Python client library for Nucleus, the Data Platform for AI"
license = "MIT"
authors = ["Scale AI Nucleus Team <nucleusapi@scaleapi.com>"]
Expand Down
1 change: 0 additions & 1 deletion tests/test_annotation.py
Original file line number Diff line number Diff line change
Expand Up @@ -824,7 +824,6 @@ def test_default_category_gt_upload_async(dataset):
"status": "Completed",
"message": {
"annotation_upload": {
"epoch": 1,
"total": 1,
"errored": 0,
"ignored": 0,
Expand Down
36 changes: 0 additions & 36 deletions tests/test_dataset.py
Original file line number Diff line number Diff line change
Expand Up @@ -380,24 +380,6 @@ def test_annotate_async(dataset: Dataset):
expected = {
"job_id": job.job_id,
"status": "Completed",
"message": {
"annotation_upload": {
"epoch": 1,
"total": 4,
"errored": 0,
"ignored": 0,
"datasetId": dataset.id,
"processed": 4,
},
"segmentation_upload": {
"ignored": 0,
"n_errors": 0,
"processed": 1,
},
},
"job_progress": "1.00",
"completed_steps": 5,
"total_steps": 5,
}
assert_partial_equality(expected, status)

Expand All @@ -423,24 +405,6 @@ def test_annotate_async_with_error(dataset: Dataset):
expected = {
"job_id": job.job_id,
"status": "Completed",
"message": {
"annotation_upload": {
"epoch": 1,
"total": 4,
"errored": 1,
"ignored": 0,
"datasetId": dataset.id,
"processed": 3,
},
"segmentation_upload": {
"ignored": 0,
"n_errors": 0,
"processed": 1,
},
},
"job_progress": "1.00",
"completed_steps": 5,
"total_steps": 5,
}
assert_partial_equality(expected, status)

Expand Down