RAM is not properly released by tf.reset_default_graph

Makefile

@@ -8,7 +8,7 @@
 FEEDSTOCK = spleeter-feedstock
 FEEDSTOCK_REPOSITORY = https://github.com/deezer/$(FEEDSTOCK)
 FEEDSTOCK_RECIPE = $(FEEDSTOCK)/recipe/spleeter/meta.yaml
-PYTEST_CMD = pytest -W ignore::FutureWarning -W ignore::DeprecationWarning -vv
+PYTEST_CMD = pytest -W ignore::FutureWarning -W ignore::DeprecationWarning -vv --forked
 
 all: clean build test deploy
 
@@ -27,7 +27,7 @@ build-gpu: clean
 	python3 setup.py sdist
 
 test:
-	$(foreach file, $(wildcard tests/test_*.py), $(PYTEST_CMD) $(file);)
+	$(PYTEST_CMD)
 
 
 deploy:

tests/test_separator.py

@@ -42,67 +42,67 @@
 @pytest.mark.parametrize('test_file, configuration, backend', TEST_CONFIGURATIONS)
 def test_separate(test_file, configuration, backend):
     """ Test separation from raw data. """
-    tf.reset_default_graph()
-    instruments = MODEL_TO_INST[configuration]
-    adapter = get_default_audio_adapter()
-    waveform, _ = adapter.load(test_file)
-    separator = Separator(configuration, stft_backend=backend)
-    prediction = separator.separate(waveform, test_file)
-    assert len(prediction) == len(instruments)
-    for instrument in instruments:
-        assert instrument in prediction
-    for instrument in instruments:
-        track = prediction[instrument]
-        assert waveform.shape[:-1] == track.shape[:-1]
-        assert not np.allclose(waveform, track)
-        for compared in instruments:
-            if instrument != compared:
-                assert not np.allclose(track, prediction[compared])
+    with tf.Session() as sess:
+        instruments = MODEL_TO_INST[configuration]
+        adapter = get_default_audio_adapter()
+        waveform, _ = adapter.load(test_file)
+        separator = Separator(configuration, stft_backend=backend)
+        prediction = separator.separate(waveform, test_file)
+        assert len(prediction) == len(instruments)
+        for instrument in instruments:
+            assert instrument in prediction
+        for instrument in instruments:
+            track = prediction[instrument]
+            assert waveform.shape[:-1] == track.shape[:-1]
+            assert not np.allclose(waveform, track)
+            for compared in instruments:
+                if instrument != compared:
+                    assert not np.allclose(track, prediction[compared])
 
 
 @pytest.mark.parametrize('test_file, configuration, backend', TEST_CONFIGURATIONS)
 def test_separate_to_file(test_file, configuration, backend):
     """ Test file based separation. """
-    tf.reset_default_graph()
-    instruments = MODEL_TO_INST[configuration]
-    separator = Separator(configuration, stft_backend=backend)
-    name = splitext(basename(test_file))[0]
-    with TemporaryDirectory() as directory:
-        separator.separate_to_file(
-            test_file,
-            directory)
-        for instrument in instruments:
-            assert exists(join(
-                directory,
-                '{}/{}.wav'.format(name, instrument)))
+    with tf.Session() as sess:
+        instruments = MODEL_TO_INST[configuration]
+        separator = Separator(configuration, stft_backend=backend)
+        name = splitext(basename(test_file))[0]
+        with TemporaryDirectory() as directory:
+            separator.separate_to_file(
+                test_file,
+                directory)
+            for instrument in instruments:
+                assert exists(join(
+                    directory,
+                    '{}/{}.wav'.format(name, instrument)))
 
 
 @pytest.mark.parametrize('test_file, configuration, backend', TEST_CONFIGURATIONS)
 def test_filename_format(test_file, configuration, backend):
     """ Test custom filename format. """
-    tf.reset_default_graph()
-    instruments = MODEL_TO_INST[configuration]
-    separator = Separator(configuration, stft_backend=backend)
-    name = splitext(basename(test_file))[0]
-    with TemporaryDirectory() as directory:
-        separator.separate_to_file(
-            test_file,
-            directory,
-            filename_format='export/{filename}/{instrument}.{codec}')
-        for instrument in instruments:
-            assert exists(join(
+    with tf.Session() as sess:
+        instruments = MODEL_TO_INST[configuration]
+        separator = Separator(configuration, stft_backend=backend)
+        name = splitext(basename(test_file))[0]
+        with TemporaryDirectory() as directory:
+            separator.separate_to_file(
+                test_file,
                 directory,
-                'export/{}/{}.wav'.format(name, instrument)))
+                filename_format='export/{filename}/{instrument}.{codec}')
+            for instrument in instruments:
+                assert exists(join(
+                    directory,
+                    'export/{}/{}.wav'.format(name, instrument)))
 
 
 @pytest.mark.parametrize('test_file, configuration', MODELS_AND_TEST_FILES)
 def test_filename_conflict(test_file, configuration):
     """ Test error handling with static pattern. """
-    tf.reset_default_graph()
-    separator = Separator(configuration)
-    with TemporaryDirectory() as directory:
-        with pytest.raises(SpleeterError):
-            separator.separate_to_file(
-                test_file,
-                directory,
-                filename_format='I wanna be your lover')
+    with tf.Session() as sess:
+        separator = Separator(configuration)
+        with TemporaryDirectory() as directory:
+            with pytest.raises(SpleeterError):
+                separator.separate_to_file(
+                    test_file,
+                    directory,
+                    filename_format='I wanna be your lover')