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Use jax.block_until_ready in benchmarks #344

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merged 2 commits into from
Jan 15, 2025
Merged

Use jax.block_until_ready in benchmarks #344

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df81dfa
Update test_benchmark.py to use different data for batch processing
xela-95 Jan 15, 2025
709ceed
Update `test_benchmark.py` to use jax.block_until_ready for more accu…
xela-95 Jan 15, 2025
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8 changes: 6 additions & 2 deletions tests/test_benchmark.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,13 +9,14 @@

def vectorize_data(model: js.model.JaxSimModel, batch_size: int):
key = jax.random.PRNGKey(seed=0)
keys = jax.random.split(key, num=batch_size)

return jax.vmap(
lambda key: js.data.random_model_data(
model=model,
key=key,
)
)(jax.numpy.repeat(key[None, :], repeats=batch_size, axis=0))
)(keys)


def benchmark_test_function(
Expand All @@ -26,7 +27,10 @@ def benchmark_test_function(

# Warm-up call to avoid including compilation time
jax.vmap(func, in_axes=(None, 0))(model, data)
benchmark(jax.vmap(func, in_axes=(None, 0)), model, data)

# Benchmark the function call
# Note: jax.block_until_ready is used to ensure that the benchmark is not measuring only the asynchronous dispatch
benchmark(jax.block_until_ready(jax.vmap(func, in_axes=(None, 0))), model, data)


@pytest.mark.benchmark
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