Enable tests for examples #123
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| # 2. Create an ImageEmbedder with swav trained on imagenet. | ||
| # Check out SWAV: https://pytorch-lightning-bolts.readthedocs.io/en/latest/self_supervised_models.html#swav | ||
| embedder = ImageEmbedder(backbone="swav-imagenet", embedding_dim=128) | ||
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| # 3. Generate an embedding from an image path. | ||
| embeddings = embedder.predict('data/hymenoptera_data/predict/153783656_85f9c3ac70.jpg') | ||
| embeddings = embedder.predict(["data/hymenoptera_data/predict/153783656_85f9c3ac70.jpg"]) |
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Should predict() accept str in addition to List[str]?
akihironitta
requested review from
Borda,
carmocca,
justusschock,
tchaton and
teddykoker
as code owners
Codecov Report
@@ Coverage Diff @@
## master #123 +/- ##
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- Coverage 87.39% 86.89% -0.51%
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Files 49 49
Lines 1579 1579
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- Hits 1380 1372 -8
- Misses 199 207 +8
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| @@ -53,13 +53,20 @@ def run_test(filepath): | |||
| "step,file", | |||
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| ("finetuning", "image_classification.py"), | |||
| # ("finetuning", "object_detection.py"), # TODO: takes too long. | |||
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Yes, I assume it would help. I cannot even run fintuning/translation.py locally (CPU, 16GB) due to the OOM error.
| from flash.tabular import TabularClassifier, TabularData | ||
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| # 1. Download the data | ||
| download_data("https://pl-flash-data.s3.amazonaws.com/titanic.zip", 'data/') | ||
| download_data("https://pl-flash-data.s3.amazonaws.com/titanic.zip", "data/") |
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It should be caching data/ directory already as I fixed it in #107.
What does this PR do?
This PR:
"instead of mix use with'in examples for consistency.)Before submitting
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