chore: import upstream snapshot with attribution

2026-07-13 13:36:55 +08:00
commit c8a779b1bb
1887 changed files with 3245738 additions and 0 deletions
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+#
+# 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 mod, util
+
+np = mod.lazy_import("numpy")
+
+
+@mod.export()
+class PostprocessFunc:
+    """
+    Provides functions that can apply post-processing to `IterationResult` s.
+    """
+
+    @staticmethod
+    # This function returns a top_k function that can be used as a postprocess_func.
+    def top_k(k=None):
+        """
+        Creates a function that applies a Top-K operation to a IterationResult.
+        Top-K will return the indices of the k largest values in the array.
+
+        Args:
+            k (Union[int, Tuple[int, int], Dict[str, int], Dict[str, Tuple[int, int]]]):
+                    The number of indices to keep and optionally the axis on which to operate.
+                    For example, a value of ``(5, 0)`` would keep the top 5 indices along axis 0.
+
+                    If this exceeds the axis length, it will be clamped.
+                    This can be specified on a per-output basis by providing a dictionary. In that case,
+                    use an empty string ("") as the key to specify default top-k value for outputs not explicitly listed.
+                    If no default is present, unspecified outputs will not be modified.
+                    Defaults to 10.
+
+        Returns:
+            Callable(IterationResult) -> IterationResult: The top-k function.
+        """
+        k = util.default(k, 10)
+        axis = -1
+
+        # Top-K implementation.
+        def top_k_impl(iter_result):
+            for name, output in iter_result.items():
+                k_val = util.value_or_from_dict(k, name)
+                if k_val:
+                    nonlocal axis
+                    if util.is_sequence(k_val):
+                        k_val, axis = k_val
+
+                    iter_result[name] = util.array.topk(output, k_val, axis)[1]
+            return iter_result
+
+        return top_k_impl