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Set batch sizes in unit tests to powers of 2 at least 16 #1054

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Apr 12, 2023
Merged

Set batch sizes in unit tests to powers of 2 at least 16 #1054

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4 changes: 2 additions & 2 deletions tests/unit/tf/models/test_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -923,11 +923,11 @@ def test_retrieval_model_query_candidate(ecommerce_data: Dataset, run_eagerly=Tr
assert isinstance(reloaded_model.query_encoder, mm.EmbeddingEncoder)
assert isinstance(reloaded_model.candidate_encoder, mm.EmbeddingEncoder)

queries = model.query_embeddings(ecommerce_data, batch_size=10, index=Tags.USER_ID).compute()
queries = model.query_embeddings(ecommerce_data, batch_size=16, index=Tags.USER_ID).compute()
_check_embeddings(queries, 100, "user_id")

candidates = model.candidate_embeddings(
ecommerce_data, batch_size=10, index=candidate
ecommerce_data, batch_size=16, index=candidate
).compute()
_check_embeddings(candidates, 100, "item_id")

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8 changes: 4 additions & 4 deletions tests/unit/tf/models/test_retrieval.py
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Expand Up @@ -898,11 +898,11 @@ def test_two_tower_v2_export_embeddings(

model, _ = testing_utils.model_test(model, ecommerce_data, reload_model=False)

queries = model.query_embeddings(ecommerce_data, batch_size=10, index=Tags.USER_ID).compute()
queries = model.query_embeddings(ecommerce_data, batch_size=16, index=Tags.USER_ID).compute()
_check_embeddings(queries, 100, 8, "user_id")

candidates = model.candidate_embeddings(
ecommerce_data, batch_size=10, index=Tags.ITEM_ID
ecommerce_data, batch_size=16, index=Tags.ITEM_ID
).compute()
_check_embeddings(candidates, 100, 8, "item_id")

Expand All @@ -918,11 +918,11 @@ def test_mf_v2_export_embeddings(

model, _ = testing_utils.model_test(model, ecommerce_data, reload_model=False)

queries = model.query_embeddings(ecommerce_data, batch_size=10, index=Tags.USER_ID).compute()
queries = model.query_embeddings(ecommerce_data, batch_size=16, index=Tags.USER_ID).compute()
_check_embeddings(queries, 100, 8, "user_id")

candidates = model.candidate_embeddings(
ecommerce_data, batch_size=10, index=Tags.ITEM_ID
ecommerce_data, batch_size=16, index=Tags.ITEM_ID
).compute()
_check_embeddings(candidates, 100, 8, "item_id")

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4 changes: 2 additions & 2 deletions tests/unit/tf/transformers/test_block.py
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Expand Up @@ -182,7 +182,7 @@ def test_transformer_as_classification_model(sequence_testing_data: Dataset, run
batch = loader.peek()[0]

outputs = model(batch)
assert list(outputs.shape) == [50, 63]
assert list(outputs.shape) == [64, 63]
testing_utils.model_test(model, loader, run_eagerly=run_eagerly)


Expand Down Expand Up @@ -223,7 +223,7 @@ def classification_loader(sequence_testing_data: Dataset):
sequence_testing_data.schema = schema
dataloader = mm.Loader(
sequence_testing_data,
batch_size=50,
batch_size=64,
).map(mm.ToTarget(schema, "user_country", one_hot=True))
return dataloader, dataloader.output_schema

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