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test: add tests for sparsity #2316
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Codecov Report
@@ Coverage Diff @@
## master #2316 +/- ##
==========================================
+ Coverage 90.91% 90.94% +0.02%
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Files 222 222
Lines 11792 11792
==========================================
+ Hits 10721 10724 +3
+ Misses 1071 1068 -3
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There are errors in https://github.com/jina-ai/jina/pull/2316/checks?check_run_id=2380856819 |
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tests/unit/drivers/test_vector_index_driver.py::test_vector_index_driver_add_bad_docs[tf] FAILED
Latency summaryCurrent PR yields:
Breakdown
Backed by latency-tracking. Further commits will update this comment. |
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jina/drivers/search.py
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@@ -139,6 +139,8 @@ def _get_documents_embeddings(self, docs: 'DocumentSet'): | |||
scipy_cls_type = embedding_cls_type.split('_')[1] | |||
embedding_cls_type = 'scipy' | |||
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print(f'scipy_cls_type {scipy_cls_type} ') |
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should we use print or logger?
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oh, my bad
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@@ -155,12 +155,12 @@ def _fill_matches(self, doc, op_name, topks, scores, topk_embed): | |||
else: | |||
for idx, (numpy_match_id, score) in enumerate(zip(topks, scores)): | |||
vector = None | |||
if topk_embed is not None: | |||
if topk_embed[idx] is not None: |
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I wonder if this could work if topk_embed is none
?
Will it get this?
TypeError: 'NoneType' object is not subscriptable
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it seems not to be the case, as it is not considerrd in the case with dense embeddings
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So this won't happen? topk_embed won't be None but the elements could be None
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yes, see the caller
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LGTM!
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