chore: import upstream snapshot with attribution

tools/Polygraphy/tests/backend/tf/test_loader.py

@@ -0,0 +1,81 @@
+#
+# SPDX-FileCopyrightText: Copyright (c) 1993-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+import os
+import tempfile
+
+import pytest
+from polygraphy import constants, util
+from polygraphy.backend.tf import (
+    GraphFromFrozen,
+    ModifyGraphOutputs,
+    SaveGraph,
+    graph_from_frozen,
+)
+from polygraphy.logger import G_LOGGER
+from tests.helper import is_file_non_empty
+from tests.models.meta import TF_MODELS
+
+tf = pytest.importorskip("tensorflow")
+
+
+class TestLoggerCallbacks:
+    @pytest.mark.parametrize("sev", G_LOGGER.SEVERITY_LETTER_MAPPING.keys())
+    def test_set_severity(self, sev):
+        G_LOGGER.module_severity = sev
+
+
+class TestFrozenGraphLoader:
+    def test_load_graph(self):
+        with tf.compat.v1.Graph().as_default() as graph:
+            inp = tf.placeholder(shape=(1, 1, 1, 1), dtype=tf.float32)
+            out = tf.identity(inp)
+
+        graph, outputs = graph_from_frozen(graph)
+        assert graph
+        assert outputs
+
+    def test_load_pb(self):
+        tf_loader = GraphFromFrozen(TF_MODELS["identity"].path)
+        tf_loader()
+
+
+class TestModifyGraph:
+    def test_layerwise(self):
+        load_frozen = GraphFromFrozen(TF_MODELS["identity"].path)
+        modify_tf = ModifyGraphOutputs(load_frozen, outputs=constants.MARK_ALL)
+
+        graph, outputs = modify_tf()
+        assert graph
+        assert outputs
+
+
+class TestSaveGraph:
+    def test_save_pb(self):
+        with util.NamedTemporaryFile() as outpath:
+            tf_loader = SaveGraph(
+                GraphFromFrozen(TF_MODELS["identity"].path), path=outpath.name
+            )
+            tf_loader()
+            assert is_file_non_empty(outpath.name)
+
+    def test_save_tensorboard(self):
+        with tempfile.TemporaryDirectory() as outdir:
+            tf_loader = SaveGraph(
+                GraphFromFrozen(TF_MODELS["identity"].path), tensorboard_dir=outdir
+            )
+            tf_loader()
+            assert os.path.exists(tf_loader.tensorboard_dir)

tools/Polygraphy/tests/backend/tf/test_runner.py

@@ -0,0 +1,93 @@
+#
+# SPDX-FileCopyrightText: Copyright (c) 1993-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+import numpy as np
+import pytest
+from polygraphy import util
+from polygraphy.backend.tf import SessionFromGraph, TfRunner
+from polygraphy.exception import PolygraphyException
+from tests.helper import is_file_non_empty
+from tests.models.meta import TF_MODELS
+
+pytest.importorskip("tensorflow")
+
+
+class TestTfRunner:
+    def test_can_name_runner(self):
+        NAME = "runner"
+        runner = TfRunner(None, name=NAME)
+        assert runner.name == NAME
+
+    def test_basic(self):
+        model = TF_MODELS["identity"]
+        with TfRunner(SessionFromGraph(model.loader)) as runner:
+            assert runner.is_active
+            model.check_runner(runner)
+            assert runner.last_inference_time() is not None
+        assert not runner.is_active
+
+    @pytest.mark.serial
+    def test_warn_if_impl_methods_called(self, check_warnings_on_runner_impl_methods):
+        model = TF_MODELS["identity"]
+        runner = TfRunner(SessionFromGraph(model.loader))
+        check_warnings_on_runner_impl_methods(runner)
+
+    @pytest.mark.skip(reason="Non-trivial to set up - requires CUPTI")
+    def test_save_timeline(self):
+        model = TF_MODELS["identity"]
+        with util.NamedTemporaryFile() as outpath:
+            with TfRunner(
+                SessionFromGraph(model.loader),
+                allow_growth=True,
+                save_timeline=outpath.name,
+            ) as runner:
+                model.check_runner(runner)
+                assert is_file_non_empty(outpath.name)
+
+    @pytest.mark.parametrize(
+        "names, err",
+        [
+            (["fake-input", "Input:0"], "Extra inputs in"),
+            (["fake-input"], "The following inputs were not found"),
+            ([], "The following inputs were not found"),
+        ],
+    )
+    def test_error_on_wrong_name_feed_dict(self, names, err):
+        model = TF_MODELS["identity"]
+        with TfRunner(SessionFromGraph(model.loader)) as runner:
+            with pytest.raises(PolygraphyException, match=err):
+                runner.infer(
+                    {
+                        name: np.ones(shape=(1, 15, 25, 30), dtype=np.float32)
+                        for name in names
+                    }
+                )
+
+    def test_error_on_wrong_dtype_feed_dict(self):
+        model = TF_MODELS["identity"]
+        with TfRunner(SessionFromGraph(model.loader)) as runner:
+            with pytest.raises(PolygraphyException, match="unexpected dtype."):
+                runner.infer(
+                    {"Input:0": np.ones(shape=(1, 15, 25, 30), dtype=np.int32)}
+                )
+
+    def test_error_on_wrong_shape_feed_dict(self):
+        model = TF_MODELS["identity"]
+        with TfRunner(SessionFromGraph(model.loader)) as runner:
+            with pytest.raises(PolygraphyException, match="incompatible shape."):
+                runner.infer(
+                    {"Input:0": np.ones(shape=(1, 1, 25, 30), dtype=np.float32)}
+                )