From e2f68fc27627e9d85c9eb8182a899e6201ef965e Mon Sep 17 00:00:00 2001 From: Benjie Genchel Date: Thu, 15 Aug 2024 11:17:42 -0400 Subject: [PATCH] convert tf.debugging.assert_none_equal to standard assert for single value checks, remove model train callback test bc basically duplicate with more work. --- .../data/tf_example_deserialization.py | 10 ++----- tests/test_callbacks.py | 26 ------------------- 2 files changed, 2 insertions(+), 34 deletions(-) diff --git a/basic_pitch/data/tf_example_deserialization.py b/basic_pitch/data/tf_example_deserialization.py index acb2f99..ffaeb73 100644 --- a/basic_pitch/data/tf_example_deserialization.py +++ b/basic_pitch/data/tf_example_deserialization.py @@ -73,10 +73,7 @@ def prepare_datasets( # check that the base dataset returned by ds_function is FINITE for ds in [ds_train, ds_validation]: - tf.debugging.assert_none_equal( - tf.cast(tf.data.experimental.cardinality(ds), tf.int32), - tf.data.experimental.INFINITE_CARDINALITY, - ) + assert tf.cast(tf.data.experimental.cardinality(ds), tf.int32) != tf.data.experimental.INFINITE_CARDINALITY # training dataset if training_shuffle_buffer_size > 0: @@ -137,10 +134,7 @@ def prepare_visualization_datasets( # check that the base dataset returned by ds_function is FINITE for ds in [ds_train, ds_validation]: - tf.debugging.assert_none_equal( - tf.cast(tf.data.experimental.cardinality(ds), tf.int32), - tf.data.experimental.INFINITE_CARDINALITY, - ) + assert tf.cast(tf.data.experimental.cardinality(ds), tf.int32) != tf.data.experimental.INFINITE_CARDINALITY # training dataset ds_train = ds_train.repeat().batch(batch_size).prefetch(tf.data.AUTOTUNE) diff --git a/tests/test_callbacks.py b/tests/test_callbacks.py index bf3929e..e5f5788 100644 --- a/tests/test_callbacks.py +++ b/tests/test_callbacks.py @@ -24,8 +24,6 @@ from basic_pitch.callbacks import VisualizeCallback from basic_pitch.constants import AUDIO_N_SAMPLES, ANNOTATIONS_N_SEMITONES, ANNOT_N_FRAMES -os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3" - class MockModel(tf.keras.Model): def __init__(self) -> None: @@ -62,27 +60,3 @@ def test_visualize_callback_on_epoch_end(tmpdir: str) -> None: vc.model = MockModel() vc.on_epoch_end(1, {"loss": np.random.random(), "val_loss": np.random.random()}) - - -def test_visualize_callback_on_epoch_end_with_model(tmpdir: str) -> None: - model = MockModel() - model.compile(optimizer="adam", loss="mse") - - batch_size = 2 # needs to be at least 2 bc validation_split required - - x_train = np.random.random((batch_size, AUDIO_N_SAMPLES, 1)) - y_train = { - key: np.random.random((batch_size, ANNOTATIONS_N_SEMITONES, ANNOT_N_FRAMES)) - for key in ["onset", "contour", "note"] - } - - vc = VisualizeCallback( - train_ds=create_mock_dataset(), - validation_ds=create_mock_dataset(), - tensorboard_dir=str(tmpdir), - original_validation_ds=create_mock_dataset(), - contours=True, - ) - - history = model.fit(x_train, y_train, epochs=1, validation_split=0.5, callbacks=[vc], verbose=0) - assert history