chore: import upstream snapshot with attribution

tools/Polygraphy/polygraphy/backend/base/util.py

@@ -0,0 +1,53 @@
+#
+# 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.
+#
+
+from polygraphy import util
+from polygraphy.logger import G_LOGGER
+
+
+def check_inputs(feed_dict, input_metadata):
+    """
+    Checks the provided `feed_dict` against expected input metadata.
+
+    Args:
+        feed_dict (Dict[str, Union[DeviceView, numpy.ndarray, torch.Tensor]]):
+                A mapping of input names to arrays.
+        input_metadata (TensorMetadata):
+                The expected input metadata.
+    """
+    util.check_sequence_contains(
+        feed_dict.keys(), input_metadata.keys(), name="input data", items_name="inputs"
+    )
+
+    for name, inp in feed_dict.items():
+        meta = input_metadata[name]
+
+        # The "buffer" might just be a pointer, in which case we can't do any further checks with it, so we skip it.
+        if isinstance(inp, int):
+            continue
+
+        dtype = util.array.dtype(inp)
+        if dtype != meta.dtype:
+            G_LOGGER.critical(
+                f"Input tensor: {name} | Received unexpected dtype: {dtype}.\nNote: Expected type: {meta.dtype}"
+            )
+
+        shape = util.array.shape(inp)
+        if not util.is_valid_shape_override(shape, meta.shape):
+            G_LOGGER.critical(
+                f"Input tensor: {name} | Received incompatible shape: {shape}.\nNote: Expected a shape compatible with: {meta.shape}"
+            )