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| from caffe2.python import core |
| from hypothesis import given |
| import caffe2.python.hypothesis_test_util as hu |
| import hypothesis.strategies as st |
| import numpy as np |
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| def calculate_ap(predictions, labels): |
| N, D = predictions.shape |
| ap = np.zeros(D) |
| num_range = np.arange((N), dtype=np.float32) + 1 |
| for k in range(D): |
| scores = predictions[:N, k] |
| label = labels[:N, k] |
| sortind = np.argsort(-scores, kind='mergesort') |
| truth = label[sortind] |
| precision = np.cumsum(truth) / num_range |
| ap[k] = precision[truth.astype(np.bool)].sum() / max(1, truth.sum()) |
| return ap |
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|
| class TestAPMeterOps(hu.HypothesisTestCase): |
| @given(predictions=hu.arrays(dims=[10, 3], |
| elements=hu.floats(allow_nan=False, |
| allow_infinity=False, |
| min_value=0.1, |
| max_value=1)), |
| labels=hu.arrays(dims=[10, 3], |
| dtype=np.int32, |
| elements=st.integers(min_value=0, |
| max_value=1)), |
| **hu.gcs_cpu_only) |
| def test_average_precision(self, predictions, labels, gc, dc): |
| op = core.CreateOperator( |
| "APMeter", |
| ["predictions", "labels"], |
| ["AP"], |
| buffer_size=10, |
| ) |
|
|
| def op_ref(predictions, labels): |
| ap = calculate_ap(predictions, labels) |
| return (ap, ) |
|
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| self.assertReferenceChecks( |
| device_option=gc, |
| op=op, |
| inputs=[predictions, labels], |
| reference=op_ref) |
|
|
| @given(predictions=hu.arrays(dims=[10, 3], |
| elements=hu.floats(allow_nan=False, |
| allow_infinity=False, |
| min_value=0.1, |
| max_value=1)), |
| labels=hu.arrays(dims=[10, 3], |
| dtype=np.int32, |
| elements=st.integers(min_value=0, |
| max_value=1)), |
| **hu.gcs_cpu_only) |
| def test_average_precision_small_buffer(self, predictions, labels, gc, dc): |
| op_small_buffer = core.CreateOperator( |
| "APMeter", |
| ["predictions", "labels"], |
| ["AP"], |
| buffer_size=5, |
| ) |
|
|
| def op_ref(predictions, labels): |
| |
| ap = calculate_ap(predictions[5:], labels[5:]) |
| return (ap, ) |
|
|
| self.assertReferenceChecks( |
| device_option=gc, |
| op=op_small_buffer, |
| inputs=[predictions, labels], |
| reference=op_ref |
| ) |
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|
