chore: import upstream snapshot with attribution
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#
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# SPDX-FileCopyrightText: Copyright (c) 2022-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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---
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name: GroupNormalizationPlugin
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interface: "IPluginV2DynamicExt"
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versions:
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"1":
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inputs:
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- input
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- scale
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- bias
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outputs:
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- output
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input_dims:
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input: 4
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scale: 1
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bias: 1
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input_dim_constraints:
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- "input_1 MULTIPLE_OF num_groups_0"
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- "scale_0 == input_1"
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- "bias_0 == scale_0"
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input_dim_range:
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input:
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min: "=1, =1, =1, =1"
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max: "=pinf, =pinf, =pinf, =pinf"
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scale:
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min: "=1"
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max: "=pinf"
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bias:
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min: "=1"
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max: "=pinf"
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supported_input_types:
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- combination1:
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input: float32
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scale: float32
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bias: float32
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output_dims:
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output: "input_0, input_1, input_2, input_3"
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attributes:
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- eps
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- num_groups
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attribute_types:
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eps: float32
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num_groups: int32
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attribute_length:
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eps: 1
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num_groups: 1
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attribute_dim_range:
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eps:
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min: "=1"
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max: "=1"
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num_groups:
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min: "=1"
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max: "=1"
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attribute_options:
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eps:
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min: "0"
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max: "=pinf"
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num_groups:
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min: "=1"
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max: "=pinf"
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attributes_required: []
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abs_tol: 1e-2
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rel_tol: 1e-2
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golden_reference_script: "plugin/GroupNormalizationPlugin_PluginReference.py"
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configs:
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config1:
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input_types:
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input: float32
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scale: float32
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bias: float32
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attribute_options:
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eps:
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value: 0.0001
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num_groups:
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value: 1
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config2:
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input_types:
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input: float32
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scale: float32
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bias: float32
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attribute_options:
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eps:
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value: 0.001
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num_groups:
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value: 2
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config3:
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input_types:
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input: float32
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scale: float32
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bias: float32
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attribute_options:
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eps:
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value: 0.01
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num_groups:
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value: 3
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...
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