chore: import upstream snapshot with attribution

python/paddle/tensorrt/impls/stat.py

@@ -0,0 +1,34 @@
+# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved
+#
+# 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 tensorrt as trt
+
+# from paddle.tensorrt.converter_utils import get_axes_for_reduce_op, set_layer_name
+# from paddle.tensorrt.register import converter_registry
+
+
+# @converter_registry.register("pd_op.mean")
+# def mean_converter(network, paddle_op, inputs):
+#     input_tensor = inputs[0]
+#     keep_dim = paddle_op.attrs().get("keepdim")
+#     dim = paddle_op.attrs().get("axis")
+
+#     mean_layer = network.add_reduce(
+#         input_tensor,
+#         trt.ReduceOperation.AVG,
+#         axes=get_axes_for_reduce_op(dim, network.has_implicit_batch_dimension),
+#         keep_dims=keep_dim,
+#     )
+#     set_layer_name(mean_layer, paddle_op)
+#     return mean_layer.get_output(0)