-
Notifications
You must be signed in to change notification settings - Fork 126
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Merge pull request #714 from roboflow/multi-label-classification-oper…
…ations Multi-Label Classification UQL Operations
- Loading branch information
Showing
5 changed files
with
207 additions
and
1 deletion.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Empty file.
172 changes: 172 additions & 0 deletions
172
tests/workflows/unit_tests/core_steps/control_flow/test_control_flow.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,172 @@ | ||
| import pytest | ||
| from inference.core.workflows.core_steps.common.query_language.evaluation_engine.core import ( | ||
| build_eval_function, | ||
| ) | ||
| from inference.core.workflows.core_steps.common.query_language.entities.operations import ( | ||
| StatementGroup, | ||
| ) | ||
|
|
||
| CONTINUE_IF_MULTI_LABEL_EXACT_MATCH_PASS = { | ||
| "type": "roboflow_core/continue_if@v1", | ||
| "name": "exact_match", | ||
| "condition_statement": { | ||
| "type": "StatementGroup", | ||
| "statements": [ | ||
| { | ||
| "type": "BinaryStatement", | ||
| "left_operand": {"type": "StaticOperand", "value": ["lion", "zebra"]}, | ||
| "comparator": {"type": "=="}, | ||
| "right_operand": {"type": "StaticOperand", "value": ["lion", "zebra"]}, | ||
| } | ||
| ], | ||
| }, | ||
| "next_steps": ["$steps.flip"], | ||
| "evaluation_parameters": {}, | ||
| } | ||
|
|
||
| CONTINUE_IF_MULTI_LABEL_EXACT_MATCH_FAIL = { | ||
| "type": "roboflow_core/continue_if@v1", | ||
| "name": "exact_match", | ||
| "condition_statement": { | ||
| "type": "StatementGroup", | ||
| "statements": [ | ||
| { | ||
| "type": "BinaryStatement", | ||
| "left_operand": {"type": "StaticOperand", "value": ["lion", "zebra"]}, | ||
| "comparator": {"type": "=="}, | ||
| "right_operand": { | ||
| "type": "StaticOperand", | ||
| "value": ["lion", "zebra", "elephant"], | ||
| }, | ||
| } | ||
| ], | ||
| }, | ||
| "next_steps": ["$steps.flip"], | ||
| "evaluation_parameters": {}, | ||
| } | ||
|
|
||
|
|
||
| CONTINUE_IF_MULTI_LABEL_ANY_MATCH_PASS = { | ||
| "type": "roboflow_core/continue_if@v1", | ||
| "name": "any_in", | ||
| "condition_statement": { | ||
| "type": "StatementGroup", | ||
| "statements": [ | ||
| { | ||
| "type": "BinaryStatement", | ||
| "left_operand": {"type": "StaticOperand", "value": ["lion", "zebra"]}, | ||
| "comparator": {"type": "any in (Sequence)"}, | ||
| "right_operand": { | ||
| "type": "StaticOperand", | ||
| "value": ["cat", "zebra", "dog"], | ||
| }, | ||
| } | ||
| ], | ||
| }, | ||
| "next_steps": ["$steps.flip"], | ||
| "evaluation_parameters": {}, | ||
| } | ||
|
|
||
| CONTINUE_IF_MULTI_LABEL_ANY_MATCH_FAIL = { | ||
| "type": "roboflow_core/continue_if@v1", | ||
| "name": "any_in", | ||
| "condition_statement": { | ||
| "type": "StatementGroup", | ||
| "statements": [ | ||
| { | ||
| "type": "BinaryStatement", | ||
| "left_operand": {"type": "StaticOperand", "value": ["lion", "zebra"]}, | ||
| "comparator": {"type": "any in (Sequence)"}, | ||
| "right_operand": { | ||
| "type": "StaticOperand", | ||
| "value": ["cat", "elephant", "dog"], | ||
| }, | ||
| } | ||
| ], | ||
| }, | ||
| "next_steps": ["$steps.flip"], | ||
| "evaluation_parameters": {}, | ||
| } | ||
|
|
||
|
|
||
| CONTINUE_IF_MULTI_LABEL_ALL_MATCH_PASS = { | ||
| "type": "roboflow_core/continue_if@v1", | ||
| "name": "all_in", | ||
| "condition_statement": { | ||
| "type": "StatementGroup", | ||
| "statements": [ | ||
| { | ||
| "type": "BinaryStatement", | ||
| "left_operand": {"type": "StaticOperand", "value": ["lion", "zebra"]}, | ||
| "comparator": {"type": "all in (Sequence)"}, | ||
| "right_operand": {"type": "StaticOperand", "value": ["zebra", "lion"]}, | ||
| } | ||
| ], | ||
| }, | ||
| "next_steps": ["$steps.flip"], | ||
| "evaluation_parameters": {"left": "$steps.multi_label_classes.predictions"}, | ||
| } | ||
|
|
||
| CONTINUE_IF_MULTI_LABEL_ALL_MATCH_FAIL = { | ||
| "type": "roboflow_core/continue_if@v1", | ||
| "name": "all_in", | ||
| "condition_statement": { | ||
| "type": "StatementGroup", | ||
| "statements": [ | ||
| { | ||
| "type": "BinaryStatement", | ||
| "left_operand": {"type": "StaticOperand", "value": ["lion", "dog"]}, | ||
| "comparator": {"type": "all in (Sequence)"}, | ||
| "right_operand": {"type": "StaticOperand", "value": ["zebra", "lion"]}, | ||
| } | ||
| ], | ||
| }, | ||
| "next_steps": ["$steps.flip"], | ||
| "evaluation_parameters": {"left": "$steps.multi_label_classes.predictions"}, | ||
| } | ||
|
|
||
|
|
||
| @pytest.mark.parametrize( | ||
| "condition_statement, evaluation_parameters, expected_result", | ||
| [ | ||
| ( | ||
| CONTINUE_IF_MULTI_LABEL_EXACT_MATCH_PASS["condition_statement"], | ||
| CONTINUE_IF_MULTI_LABEL_EXACT_MATCH_PASS["evaluation_parameters"], | ||
| True, | ||
| ), | ||
| ( | ||
| CONTINUE_IF_MULTI_LABEL_EXACT_MATCH_FAIL["condition_statement"], | ||
| CONTINUE_IF_MULTI_LABEL_EXACT_MATCH_FAIL["evaluation_parameters"], | ||
| False, | ||
| ), | ||
| ( | ||
| CONTINUE_IF_MULTI_LABEL_ANY_MATCH_PASS["condition_statement"], | ||
| CONTINUE_IF_MULTI_LABEL_ANY_MATCH_PASS["evaluation_parameters"], | ||
| True, | ||
| ), | ||
| ( | ||
| CONTINUE_IF_MULTI_LABEL_ANY_MATCH_FAIL["condition_statement"], | ||
| CONTINUE_IF_MULTI_LABEL_ANY_MATCH_FAIL["evaluation_parameters"], | ||
| False, | ||
| ), | ||
| ( | ||
| CONTINUE_IF_MULTI_LABEL_ALL_MATCH_PASS["condition_statement"], | ||
| CONTINUE_IF_MULTI_LABEL_ALL_MATCH_PASS["evaluation_parameters"], | ||
| True, | ||
| ), | ||
| ( | ||
| CONTINUE_IF_MULTI_LABEL_ALL_MATCH_FAIL["condition_statement"], | ||
| CONTINUE_IF_MULTI_LABEL_ALL_MATCH_FAIL["evaluation_parameters"], | ||
| False, | ||
| ), | ||
| ], | ||
| ) | ||
| def test_continue_if_evaluation( | ||
| condition_statement, evaluation_parameters, expected_result | ||
| ): | ||
| parsed_definition = StatementGroup.model_validate(condition_statement) | ||
| evaluation_function = build_eval_function(definition=parsed_definition) | ||
| evaluation_result = evaluation_function(evaluation_parameters) | ||
| assert ( | ||
| evaluation_result == expected_result | ||
| ), f"Expected {expected_result} for condition {condition_statement} with parameters {evaluation_parameters}, but got {evaluation_result}" |