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Speedup end2end tests #552

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Oct 23, 2020
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Speedup end2end tests #552

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27 changes: 16 additions & 11 deletions larq_compute_engine/tests/end2end_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -139,19 +139,24 @@ def assert_model_output(model_lce, inputs, outputs, rtol, atol):
np.testing.assert_allclose(actual_outputs, outputs, rtol=rtol, atol=atol)


@pytest.mark.parametrize(
"model_cls",
[toy_model, toy_model_sequential, toy_model_int8, lqz.sota.QuickNetSmall],
)
def test_simple_model(model_cls):
# Test on the TF flowers dataset
dataset = (
@pytest.fixture(scope="module")
def dataset():
return (
tfds.load("tf_flowers", split="train", try_gcs=True)
.map(preprocess)
.map(preprocess, num_parallel_calls=2)
.take(100)
.cache()
.shuffle(100)
.batch(10)
.prefetch(1)
)


@pytest.mark.parametrize(
"model_cls",
[toy_model, toy_model_sequential, toy_model_int8, lqz.sota.QuickNetSmall],
)
def test_simple_model(dataset, model_cls):
model = model_cls(weights="imagenet")

# For the untrained models, do a very small amount of training so that the
Expand All @@ -162,7 +167,7 @@ def test_simple_model(model_cls):
optimizer=tf.keras.optimizers.Adam(1e-4),
loss="sparse_categorical_crossentropy",
)
model.fit(dataset, epochs=1, steps_per_epoch=10)
model.fit(dataset, epochs=1)

model_lce = convert_keras_model(
model, experimental_enable_bitpacked_activations=True
Expand All @@ -182,9 +187,9 @@ def test_simple_model(model_cls):
atol = 0.001

# Test on a single batch of images
inputs = next(dataset.map(lambda *data: data[0]).take(1).as_numpy_iterator())
inputs = next(iter(dataset.take(1)))[0]
outputs = model(inputs).numpy()
assert_model_output(model_lce, inputs, outputs, rtol, atol)
assert_model_output(model_lce, inputs.numpy(), outputs, rtol, atol)

# Test on some random inputs
input_shape = (10, *model.input.shape[1:])
Expand Down