diff --git a/mlpp_lib/models.py b/mlpp_lib/models.py index 7bb3142..e756b8b 100644 --- a/mlpp_lib/models.py +++ b/mlpp_lib/models.py @@ -1,6 +1,8 @@ -import tensorflow as tf +import logging from typing import Optional, Union, Any +import numpy as np +import tensorflow as tf from tensorflow.keras.layers import ( Add, Dense, @@ -8,14 +10,11 @@ BatchNormalization, Activation, ) - from tensorflow.keras import Model, initializers from mlpp_lib.physical_layers import * from mlpp_lib.probabilistic_layers import * -import numpy as np - try: import tcn # type: ignore except ImportError: @@ -24,6 +23,10 @@ TCN_IMPORTED = True +_LOGGER = logging.getLogger(__name__) + + +@tf.keras.utils.register_keras_serializable() class MonteCarloDropout(Dropout): def call(self, inputs): return super().call(inputs, training=True) @@ -39,6 +42,9 @@ def _build_fcn_block( skip_connection, idx=0, ): + if mc_dropout and dropout is None: + _LOGGER.warning("dropout=None, hence I will ignore mc_dropout=True") + x = inputs for i, units in enumerate(hidden_layers): x = Dense(units, name=f"dense_{idx}_{i}")(x) diff --git a/poetry.lock b/poetry.lock index 307d514..37c667f 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,20 +1,42 @@ -# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand. 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"2.0" python-versions = ">=3.9, <3.11" -content-hash = "9cce460b750325558ffb24a1d41aa331c1781c8231327dcd28c92485bff85091" +content-hash = "41877e4ee5d60174c62336ef24536fab4e2db1e201f096c72a64bedda93a49e9" diff --git a/pyproject.toml b/pyproject.toml index 79bd128..501048e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -24,10 +24,11 @@ tensorflow = ["tensorflow"] tensorflow-cpu = ["tensorflow-cpu"] extended = ["zarr", "numba", "tensorflow"] -[tool.poetry.dev-dependencies] +[tool.poetry.group.dev.dependencies] tensorflow = "~2.9.3" pytest = "^7" black = "^22.1.0" +mlflow = "<2" [build-system] requires = ["poetry-core>=1.0.8"] diff --git a/tests/test_save_model.py b/tests/test_save_model.py index e0a68c3..a2235a2 100644 --- a/tests/test_save_model.py +++ b/tests/test_save_model.py @@ -9,7 +9,7 @@ from mlpp_lib import models from mlpp_lib import losses, metrics from mlpp_lib import probabilistic_layers -from mlpp_lib.utils import get_loss, get_metric +from mlpp_lib.utils import get_loss, get_metric, get_optimizer def _belongs_here(obj, module): @@ -63,7 +63,11 @@ def test_save_model(save_format, loss, prob_layer, tmp_path): save_traces = False model = models.fully_connected_network( - (5,), 2, hidden_layers=[3], probabilistic_layer=prob_layer + (5,), + 2, + hidden_layers=[3], + probabilistic_layer=prob_layer, + mc_dropout=True, ) assert isinstance(model.from_config(model.get_config()), Functional) loss = get_loss(loss) @@ -105,3 +109,31 @@ def test_save_model(save_format, loss, prob_layer, tmp_path): model = tf.keras.models.load_model(tmp_path, compile=False) assert isinstance(model, Functional) np.testing.assert_allclose(model(input_arr).mean(), outputs) + + +def test_save_model_mlflow(tmp_path): + """Test model save/load""" + pytest.importorskip("mlflow") + + import mlflow + + mlflow_uri = f"file://{tmp_path.absolute()}/mlruns" + mlflow.set_tracking_uri(mlflow_uri) + + model = models.fully_connected_network( + (5,), 2, hidden_layers=[3, 3], dropout=0.5, mc_dropout=True + ) + optimizer = get_optimizer("Adam") + model.compile(optimizer=optimizer, loss=None, metrics=None) + custom_objects = tf.keras.layers.serialize(model) + + model_info = mlflow.keras.log_model( + model, + "model_save", + custom_objects=custom_objects, + save_format="h5", + ) + + tf.keras.backend.clear_session() + model = mlflow.keras.load_model(model_info.model_uri) + assert isinstance(model, Functional)