chore: import upstream snapshot with attribution
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#
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# SPDX-FileCopyrightText: Copyright (c) 1993-2026 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
|
||||
# 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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add_plugin_source(
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mhaRunner.cu
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mhaRunner.h
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qkvToContextInt8InterleavedPlugin.cpp
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qkvToContextInt8InterleavedPlugin.h
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qkvToContextInt8InterleavedPluginLegacy.cpp
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qkvToContextInt8InterleavedPluginLegacy.h
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qkvToContextPlugin.cpp
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qkvToContextPlugin.h
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qkvToContextPluginLegacy.cpp
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qkvToContextPluginLegacy.h
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zeroPadding2d.cu
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zeroPadding2d.h
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)
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set(BERT_QKV_SUPPORTED_SMS
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75
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80
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86
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87
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89
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90
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100
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120
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)
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add_subdirectory(fused_multihead_attention)
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add_subdirectory(fused_multihead_attention_v2)
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@@ -0,0 +1,216 @@
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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: CustomQKVToContextPluginDynamic
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interface: "IPluginV3"
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versions:
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"4":
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inputs:
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- input
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outputs:
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- output
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input_dims:
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input: 5
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output_dims:
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output: "input_0, input_1, hidden_size_0, 1, 1"
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attributes:
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- type_id
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- hidden_size
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- num_heads
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- has_mask
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- dq_probs
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attribute_types:
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type_id: int32
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hidden_size: int32
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num_heads: int32
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has_mask: int32
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dq_probs: float32
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attribute_length:
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type_id: 1
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hidden_size: 1
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num_heads: 1
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has_mask: 1
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dq_probs: 1
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attribute_options:
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type_id:
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- 0
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- 1
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- 2
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hidden_size:
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min: "0"
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max: "=pinf"
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num_heads:
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min: "0"
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max: "=pinf"
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has_mask:
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- 0
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- 1
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dq_probs:
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min: "0"
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max: "=pinf"
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attribute_constraints:
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- "num_heads * k == hidden_size"
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attributes_required:
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- type_id
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- hidden_size
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- num_heads
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- has_mask
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golden_io_path: "plugin/CustomQKVToContextPluginDynamic_PluginGoldenIO.json"
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abs_tol: 1e-5
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rel_tol: 1e-5
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fp16_atol: 1e-2
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fp16_rtol: 1e-2
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configs:
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config1:
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input_types:
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input: float16
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attribute_options:
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type_id:
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value: 1
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shape: "1"
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hidden_size:
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value: 768
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shape: "1"
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num_heads:
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value: 12
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shape: "1"
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has_mask:
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value: 0
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shape: "1"
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output_types:
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output: float16
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config2:
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input_types:
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input: float16
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attribute_options:
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type_id:
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value: 1
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shape: "1"
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hidden_size:
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value: 1024
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shape: "1"
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num_heads:
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value: 16
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shape: "1"
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has_mask:
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value: 0
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shape: "1"
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output_types:
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output: float16
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config5:
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input_types:
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input: float16
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attribute_options:
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type_id:
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value: 1
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shape: "1"
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hidden_size:
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value: 384
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shape: "1"
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num_heads:
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value: 12
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shape: "1"
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has_mask:
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value: 0
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shape: "1"
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output_types:
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output: float16
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has_mask:
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input_types:
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input: float32
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input_mask: int32
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attribute_options:
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type_id:
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value: 0
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shape: "1"
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hidden_size:
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value: 3
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shape: "1"
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num_heads:
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value: 3
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shape: "1"
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has_mask:
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value: 1
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shape: "1"
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output_types:
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output: float32
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"5":
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inputs:
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- input
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- input_mask
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outputs:
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- output
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input_dims:
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input: 5
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input_mask: 1
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output_dims:
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output: "input_0, input_mask_0, hidden_size_0, 1, 1"
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attributes:
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- type_id
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- hidden_size
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- num_heads
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- has_mask
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- dq_probs
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- var_seqlen
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- use_int8_scale_max
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attribute_types:
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type_id: int32
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hidden_size: int32
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||||
num_heads: int32
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has_mask: int32
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dq_probs: float32
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var_seqlen: int32
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use_int8_scale_max: int32
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attribute_length:
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type_id: 1
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hidden_size: 1
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num_heads: 1
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has_mask: 1
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dq_probs: 1
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var_seqlen: 1
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use_int8_scale_max: 1
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attribute_options:
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type_id:
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- 0
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- 1
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- 2
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hidden_size:
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min: "0"
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||||
max: "=pinf"
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||||
num_heads:
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min: "0"
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max: "=pinf"
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has_mask:
|
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- 0
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- 1
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||||
dq_probs:
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min: "0"
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||||
max: "=pinf"
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use_int8_scale_max:
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- 0
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- 1
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var_seqlen:
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- 0
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# - 1 # Disabled since SM specific tests are not supported yet
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attributes_required:
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||||
- type_id
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||||
- hidden_size
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- num_heads
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||||
- has_mask
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# "3": #version3 - Not supported yet
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...
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# bertQKVToContextPlugin [DEPRECATED]
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**This plugin has been deprecated since TensorRT 10.15 and will be removed in a future release. Use `IAttention` (via `INetworkDefinition::addAttention` / `addAttentionV2`) as the out-of-the-box replacement. See [Migration to IAttention](#migration-to-iattention) for the steps to adapt.**
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**Table Of Contents**
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- [Description](#description)
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||||
* [Structure](#structure)
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- [Migration to IAttention](#migration-to-iattention)
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- [Parameters](#parameters)
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- [Additional resources](#additional-resources)
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- [License](#license)
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||||
- [Changelog](#changelog)
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||||
- [Known issues](#known-issues)
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||||
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## Description
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Takes query, key and value tensors and computes scaled multi-head attention - computes scaled dot product attention scores `softmax(K'Q/sqrt(HeadSize))` and returns values weighted by these attention scores.
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### Structure
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The `bertQKVToContextPlugin` takes two inputs; `input`, and optionally `input_mask`.
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`input`
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input is a tensor with shape `[S, B, 3 * E, 1, 1]` where `B` is the batch size and `E` is the hidden size. The input has two trailing dimensions in order to generate an output with the same trailing dimensions for a FC optimiazation further down the network.
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This plugin makes strong assumptions about its input:
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- The input tensor contains all 3 matrices Q, K, V
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- This input tensor is computed by multiplying a tensor of size `[S, B, E]` with the weights `W_qkv` of size `[E, 3 * E]`
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- The weight matrix W_qkv is NOT just the vertical concatenation of individual matrices `W_tmp = [W_q', W_k', W_v']'`, but to start with `W_tmp`, reshaping it into `[E, 3, N, H]` (where `N * H = E` and `N` is number of heads, `H` is head size) transposing it into `[E, N, 3, H]` and reshaping it back to `[E, 3 * E]`. The interpretation is to layout the k-th heads of Q, K and V next to each other, instead of first all N heads of Q, then all N heads of K, then all heads of V
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`input_mask`
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The input mask is encoded in the `maskIdx` format described in `embLayerNormPlugin`, and contains the number of valid elements from the start of the sequence.
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If provided, the attention scores, i.e. the softmax distribution, are only computed over the elements designated as valid by the input mask
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The `bertQKVToContextPlugin` generates the following output:
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`output`
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output is a tensor with shape `[S, B, E, 1, 1]` where `B` is the batch size.
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## Migration to [IAttention](https://docs.nvidia.com/deeplearning/tensorrt/latest/_static/operators/Attention.html)
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|
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`IAttention` is the out-of-the-box attention layer in TensorRT and is functionally equivalent to this plugin for the multi-head attention computation, but it is not a drop-in replacement. Adapter steps:
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1. **Split the fused QKV input.** This plugin consumes one `[S, B, 3*E, 1, 1]` tensor with the K-th heads of Q, K, V interleaved. `IAttention` takes three separate tensors with shape `[B, N, S, H]`. Reshape the fused QKV to `[S, B, N, 3, H]`, slice along the size-3 axis, then transpose each slice to `[B, N, S, H]`. If the upstream FC weight `W_qkv` was packed using the head-interleaved layout described in the Structure section, no weight repacking is needed. Otherwise, repack `W_qkv` to produce three contiguous `[B, N, S, H]` tensors directly.
|
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```cpp
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// [S, B, 3*E, 1, 1] -> [B, N, S, 3, H], then slice axis 3.
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auto* shuf = network->addShuffle(*fusedQKV);
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shuf->setReshapeDimensions(Dims{5, {S, B, N, 3, H}});
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shuf->setSecondTranspose(Permutation{{1, 2, 0, 3, 4}});
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ITensor* t = shuf->getOutput(0);
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auto pick = [&](int32_t i) -> ITensor* {
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auto* sl = network->addSlice(*t, Dims{5, {0,0,0,i,0}},
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Dims{5, {B,N,S,1,H}}, Dims{5, {1,1,1,1,1}});
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auto* sq = network->addShuffle(*sl->getOutput(0));
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||||
sq->setReshapeDimensions(Dims{4, {B, N, S, H}});
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||||
return sq->getOutput(0);
|
||||
};
|
||||
ITensor *q = pick(0), *k = pick(1), *v = pick(2);
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||||
```
|
||||
|
||||
2. **Convert the mask.** This plugin uses the `maskIdx` format (count of valid tokens from the start of each sequence). `IAttention` takes a 4D boolean or additive mask of shape `[B, N, S_q, S_kv]` (broadcastable over `B` and `N`). For non-causal BERT-style self-attention, materialize a boolean mask from the valid-token counts. For causal generation, use `IAttention::setCausalKind(CausalMaskKind)` instead of a mask.
|
||||
|
||||
```cpp
|
||||
// Boolean mask from maskIdx ([B] int32). Broadcasts to [B, NQ, S_q, S_kv].
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||||
auto* idx = network->addFill(Dims{1, {S}}, FillOperation::kLINSPACE, DataType::kINT32);
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||||
idx->setAlpha(0.0); idx->setBeta(1.0);
|
||||
auto* less = network->addElementWise(*idx->getOutput(0), *maskIdx,
|
||||
ElementWiseOperation::kLESS);
|
||||
attn->setMask(*less->getOutput(0));
|
||||
|
||||
// For causal autoregressive decode, skip the mask and use:
|
||||
// attn->setCausalKind(CausalMaskKind::kLOWER_RIGHT);
|
||||
```
|
||||
|
||||
3. **Reshape the output.** This plugin produces `[S, B, E, 1, 1]`. `IAttention` produces `[B, N, S_q, H]`. Transpose and reshape as needed for downstream layers.
|
||||
|
||||
```cpp
|
||||
// [B, N, S_q, H] -> [S, B, E, 1, 1] for downstream layers expecting the plugin layout.
|
||||
auto* out = network->addShuffle(*attn->getOutput(0));
|
||||
out->setFirstTranspose(Permutation{{2, 0, 1, 3}}); // -> [S, B, N, H]
|
||||
out->setReshapeDimensions(Dims{5, {S, B, E, 1, 1}});
|
||||
```
|
||||
|
||||
4. **INT8/FP8 quantization.** The plugin folded the entire INT8 attention pipeline into a single op, exposing only `type_id==2` (implicit per-tensor scales) or the explicit-INT8 attribute set. With `IAttention`, you express the QDQ pattern in the network so the builder can fuse it into the FP8/INT8 attention kernel. See also [Explicit Quantization](https://docs.nvidia.com/deeplearning/tensorrt/latest/inference-library/work-quantized-types.html#explicit-quantization).
|
||||
|
||||
```cpp
|
||||
// QDQ Q, K, V (input_qkv_scale).
|
||||
auto qdq = [&](ITensor* x) -> ITensor* {
|
||||
auto* qn = network->addQuantize(*x, *qkvScale);
|
||||
qn->setOutputType(0, DataType::kINT8);
|
||||
auto* dq = network->addDequantize(*qn->getOutput(0), *qkvScale);
|
||||
return dq->getOutput(0);
|
||||
};
|
||||
ITensor *qq = qdq(q), *kq = qdq(k), *vq = qdq(v);
|
||||
|
||||
auto* attn = network->addAttentionV2(*qq, *kq, *vq,
|
||||
AttentionNormalizationOp::kSOFTMAX,
|
||||
CausalMaskKind::kNONE);
|
||||
// dq_probs -> NormalizationQuantizeScale.
|
||||
attn->setNormalizationQuantizeScale(*dqProbsScale);
|
||||
|
||||
// QDQ attention output (output_ctx_scale).
|
||||
auto* qOut = network->addQuantize(*attn->getOutput(0), *outScale);
|
||||
qOut->setOutputType(0, DataType::kINT8);
|
||||
auto* dqOut = network->addDequantize(*qOut->getOutput(0), *outScale);
|
||||
```
|
||||
|
||||
5. **Variable sequence length.** This plugin accepts a `cu_seqlen` packed layout. `IAttention` does not natively consume packed cu-seqlen input; users relying on this path must either pad to a fixed sequence length or implement their own packing/unpacking around `IAttention`. See below for an example.
|
||||
|
||||
```cpp
|
||||
// `scatterIdx`, `gatherIdx` are application-specific and are typically built from `cu_seqlen`
|
||||
|
||||
// Packed input: [total_tokens, E]; cu_seqlen: [B+1] int32 prefix sums.
|
||||
// Scatter packed -> padded [B, S, E] (pad slots are filled with zeros at a sentinel index).
|
||||
auto* padded = network->addGather(*packedInput, *scatterIdx, /*axis=*/0); // [B*S, E]
|
||||
auto* padBSE = network->addShuffle(*padded->getOutput(0));
|
||||
padBSE->setReshapeDimensions(Dims{3, {B, S, E}});
|
||||
// ...split into Q/K/V (step 1), build mask from validLen = cu_seqlen[b+1]-cu_seqlen[b] (step 2),
|
||||
// call addAttentionV2 (step 4 if quantized)...
|
||||
|
||||
// Gather attention output [B, N, S_q, H] -> [B, S, E] -> packed [total_tokens, E].
|
||||
auto* outBSE = network->addShuffle(*attn->getOutput(0));
|
||||
outBSE->setFirstTranspose(Permutation{{0, 2, 1, 3}});
|
||||
outBSE->setReshapeDimensions(Dims{2, {B * S, E}});
|
||||
auto* repacked = network->addGather(*outBSE->getOutput(0), *gatherIdx, /*axis=*/0);
|
||||
```
|
||||
|
||||
|
||||
## Parameters
|
||||
|
||||
`bertQKVToContextPlugin` has plugin creator class `QKVToContextPluginDynamicCreator` and plugin class `CustomQKVToContextPluginDynamic`.
|
||||
|
||||
The parameters are defined below and consists of the following attributes:
|
||||
|
||||
| Type | Parameter | Version | Description
|
||||
|----------|-----------------------------------------|-----------------------------------|-------------------------------------------------------------------
|
||||
|`int` |`type_id` | 1, 2, 4, 5 |Integer encoding the DataType (0: FP32, 1: FP16, 2: INT8)
|
||||
|`int` |`hidden_size` | 1, 2, 3, 4, 5, 6 |The hidden size, denoted by `E` above.
|
||||
|`int` |`num_heads` | 1, 2, 3, 4, 5, 6 |The number of self-attention heads.
|
||||
|`bool` |`has_mask` | 1, 2, 4, 5 |Whether to use the input_mask input.
|
||||
|`float` |`dq_probs` | 1, 2, 3, 4, 5, 6 |inner layer scale factor when run in int8 precision, default 1.f/127.f.
|
||||
|`int` |`var_seqlen` | 2, 5 |Whether to use variable sequence length (0: disable, 1: enable), default 0.
|
||||
|`int` |`use_int8_scale_max` | 2, 3, 5, 6 |Whether to use INT8 scale factors to optimize softmax MAX reduction. Only active when `type_id==2`. (0: disable, 1: enable), default 1.
|
||||
|`int` |`use_explicit_int8` | 3, 6 |Whether to use explicit INT8, (0: disable, 1: enable), default 0.
|
||||
|`float` |`input_qkv_scale` | 3, 6 |The int8 scale for the input qkv tensor when explicit precision is used, default 1.f.
|
||||
|`float` |`output_ctx_scale` | 3, 6 |The int8 scale for the output context tensor when explicit precision is used, default 1.f.
|
||||
|
||||
|
||||
## Additional resources
|
||||
|
||||
**Networks:**
|
||||
- [Transformer](https://arxiv.org/abs/1706.03762)
|
||||
|
||||
|
||||
## License
|
||||
|
||||
For terms and conditions for use, reproduction, and distribution, see the [TensorRT Software License Agreement](https://docs.nvidia.com/deeplearning/sdk/tensorrt-sla/index.html)
|
||||
documentation.
|
||||
|
||||
|
||||
## Changelog
|
||||
April 2026
|
||||
Provide `IAttention` as the out-of-the-box replacement.
|
||||
|
||||
Oct 2025
|
||||
Deprecated this plugin. No alternatives are planned to be provided.
|
||||
|
||||
Jan 2025
|
||||
Added precompiled kernel cubins for gb100 (compute capability 10.0) and gb20x (compute capability 12.0) platforms.
|
||||
|
||||
Aug 2024
|
||||
Ported v3 variant (IPluginV2 design) to v6 (IpluginV3 design), but preserves identical attributes and I/O to v3.
|
||||
Ported v2 variant (IPluginV2 design) to v5 (IpluginV3 design), but preserves identical attributes and I/O to v2.
|
||||
Ported v1 variant (IPluginV2 design) to v4 (IpluginV3 design), but preserves identical attributes and I/O to v1.
|
||||
|
||||
Feb 2024
|
||||
The issue of the V2 plugin not supporting head sizes of 32 or less and variable sequences of 64, 96, and 384 has been resolved.
|
||||
|
||||
Oct 2023
|
||||
Support explicit int8.
|
||||
|
||||
April 2023
|
||||
Optimize the GPU memory usage by using the cublas handle from attachToContext.
|
||||
|
||||
October 2022
|
||||
Add IGMMA/HGMMA sm90 fmha_v2 kernels
|
||||
|
||||
August 2022
|
||||
Expose `use_int8_scale_max` plugin attribute (for versions 2 and 3 of the plugin). This allows users to enable/disable the usage of INT8 scale factors to optimize softmax MAX reduction.
|
||||
This optimization is applied always when `type_id==2` by default.
|
||||
|
||||
September 2021
|
||||
Add sequence length 512 support in v2 plugin
|
||||
Add head size 32 support when sequence length is 128, 256 or 512 in v2 plugin
|
||||
|
||||
October 2020
|
||||
Add v2 plugin that supports variable sequence length.
|
||||
Add v3 plugin that supports int8 interleaved variable sequence length.
|
||||
|
||||
November 2019
|
||||
This is the first release of this `README.md` file.
|
||||
|
||||
|
||||
## Known issues
|
||||
|
||||
This plugin only supports GPUs with compute capability >= 7.0. For more information see the [CUDA GPU Compute Capability Support Matrix](https://developer.nvidia.com/cuda-gpus#compute)
|
||||
@@ -0,0 +1,54 @@
|
||||
#
|
||||
# SPDX-FileCopyrightText: Copyright (c) 1993-2025 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.
|
||||
#
|
||||
|
||||
# This folder contains a bunch of source files holding cubins. Since the files are huge, we only want to include and compile them if used.
|
||||
# Usage is indicated by the SM being set in CMAKE_CUDA_ARCHITECTURES.
|
||||
|
||||
function(add_plugin_source_if_exists)
|
||||
foreach(SRC_FILE IN LISTS ARGN)
|
||||
if(EXISTS ${CMAKE_CURRENT_LIST_DIR}/${SRC_FILE})
|
||||
add_plugin_source(${SRC_FILE})
|
||||
endif()
|
||||
endforeach()
|
||||
endfunction()
|
||||
|
||||
foreach(SM IN LISTS BERT_QKV_SUPPORTED_SMS)
|
||||
should_compile_kernel(${SM} SHOULD_COMPILE)
|
||||
if (${SHOULD_COMPILE})
|
||||
# Not every file exists for each SM, so we list all of the candidates and add them if present.
|
||||
add_plugin_source_if_exists(
|
||||
fused_multihead_attention_fp16_64_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_fp16_96_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_fp16_128_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_fp16_256_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_fp16_384_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_fp16_512_64_kernel.sm${SM}.cpp
|
||||
|
||||
fused_multihead_attention_int8_64_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_int8_96_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_int8_128_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_int8_192_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_int8_256_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_int8_384_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_int8_512_64_kernel.sm${SM}.cpp
|
||||
)
|
||||
endif()
|
||||
endforeach()
|
||||
|
||||
add_plugin_source(
|
||||
fused_multihead_attention_common.h
|
||||
)
|
||||
@@ -0,0 +1,652 @@
|
||||
/*
|
||||
* SPDX-FileCopyrightText: Copyright (c) 1993-2026 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.
|
||||
*/
|
||||
|
||||
#ifndef _BERT_FMHA_FMHA
|
||||
#define _BERT_FMHA_FMHA
|
||||
#include "common/bertCommon.h"
|
||||
#include "common/cudaDriverWrapper.h"
|
||||
#include "common/plugin.h"
|
||||
#include "cuda_runtime_api.h"
|
||||
#include "fused_multihead_attention_common.h"
|
||||
#include <memory>
|
||||
#include <mutex>
|
||||
#include <set>
|
||||
#include <stdint.h>
|
||||
#include <unordered_map>
|
||||
#include <unordered_set>
|
||||
#include <vector>
|
||||
|
||||
namespace nvinfer1
|
||||
{
|
||||
|
||||
namespace pluginInternal
|
||||
{
|
||||
template <typename TKernelMeta, typename TKernelParam>
|
||||
class TFusedMultiHeadAttentionXMMAKernel
|
||||
{
|
||||
public:
|
||||
using KernelMeta = TKernelMeta;
|
||||
using KernelParam = TKernelParam;
|
||||
inline uint64_t hashID(uint32_t s, uint32_t d) const
|
||||
{
|
||||
return (uint64_t) s << 32 | d;
|
||||
}
|
||||
virtual uint64_t hashID(const KernelMeta& kernelMeta) const
|
||||
{
|
||||
return hashID(kernelMeta.mS, kernelMeta.mD);
|
||||
}
|
||||
|
||||
TFusedMultiHeadAttentionXMMAKernel(
|
||||
const TKernelMeta* pMetaStart, uint32_t nMetaCount, plugin::bert::Data_type type, uint32_t sm)
|
||||
: mDataType(type)
|
||||
, mKernelMeta(pMetaStart)
|
||||
, mKernelMetaCount(nMetaCount)
|
||||
, mSM(sm)
|
||||
{
|
||||
PLUGIN_ASSERT(mKernelMetaCount && "No kernels were loaded correctly.");
|
||||
}
|
||||
|
||||
void loadXMMAKernels(uint32_t smVersion)
|
||||
{
|
||||
for (uint32_t i = 0; i < mKernelMetaCount; ++i)
|
||||
{
|
||||
const auto& kernelMeta = mKernelMeta[i];
|
||||
const auto kernelKey = hashID(kernelMeta);
|
||||
if (kernelMeta.mSM == smVersion && kernelMeta.mDataType == mDataType
|
||||
&& mFunctions.find(kernelKey) == mFunctions.end())
|
||||
{
|
||||
const uint32_t DEFAULT_SMEM_SIZE{48 * 1024};
|
||||
if (kernelMeta.mSharedMemBytes >= DEFAULT_SMEM_SIZE)
|
||||
{
|
||||
int32_t deviceID{0};
|
||||
cudaGetDevice(&deviceID);
|
||||
int32_t sharedMemPerMultiprocessor{0};
|
||||
if (cudaDeviceGetAttribute(
|
||||
&sharedMemPerMultiprocessor, cudaDevAttrMaxSharedMemoryPerBlockOptin, deviceID)
|
||||
!= cudaSuccess
|
||||
|| sharedMemPerMultiprocessor < static_cast<int32_t>(kernelMeta.mSharedMemBytes))
|
||||
{
|
||||
// skip load function because not enough shared memory to launch the kernel
|
||||
continue;
|
||||
}
|
||||
}
|
||||
|
||||
CUmodule hmod{0};
|
||||
auto findModuleIter = mModules.find(kernelMeta.mCubin);
|
||||
if (findModuleIter != mModules.end())
|
||||
{
|
||||
hmod = findModuleIter->second;
|
||||
}
|
||||
else
|
||||
{
|
||||
cuErrCheck(mDriver.cuModuleLoadData(&hmod, kernelMeta.mCubin), mDriver);
|
||||
mModules.insert(std::make_pair(kernelMeta.mCubin, hmod));
|
||||
}
|
||||
|
||||
FusedMultiHeadAttentionKernelInfo funcInfo;
|
||||
funcInfo.mMetaInfoIndex = i;
|
||||
cuErrCheck(mDriver.cuModuleGetFunction(&funcInfo.mDeviceFunction, hmod, kernelMeta.mFuncName), mDriver);
|
||||
if (kernelMeta.mSharedMemBytes >= DEFAULT_SMEM_SIZE)
|
||||
{
|
||||
if (mDriver.cuFuncSetAttribute(funcInfo.mDeviceFunction,
|
||||
CU_FUNC_ATTRIBUTE_MAX_DYNAMIC_SHARED_SIZE_BYTES, kernelMeta.mSharedMemBytes)
|
||||
!= CUDA_SUCCESS)
|
||||
{
|
||||
// some chip may not have enough shared memory to launch the kernel
|
||||
continue;
|
||||
}
|
||||
}
|
||||
mFunctions.insert({kernelKey, funcInfo});
|
||||
uint64_t const s = kernelMeta.mS;
|
||||
uint64_t const headSize = kernelMeta.mD;
|
||||
uint64_t key = (headSize << 32 | s);
|
||||
if (mValidSequences.find(key) == mValidSequences.end())
|
||||
{
|
||||
mValidSequences.insert(key);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
void loadXMMAKernels()
|
||||
{
|
||||
if (!mFunctions.empty())
|
||||
{
|
||||
return;
|
||||
}
|
||||
|
||||
loadXMMAKernels(mSM);
|
||||
|
||||
// sm_86 chips prefer sm_86 sass, but can also use sm_80 sass if sm_86 not exist.
|
||||
// sm_87 cannot run sm_80 sass
|
||||
if (mSM == kSM_86)
|
||||
{
|
||||
loadXMMAKernels(kSM_80);
|
||||
}
|
||||
|
||||
// sm_89 will reuse sm_80 and sm_86 kernels
|
||||
if (mSM == kSM_89)
|
||||
{
|
||||
loadXMMAKernels(kSM_86);
|
||||
loadXMMAKernels(kSM_80);
|
||||
}
|
||||
}
|
||||
|
||||
bool isValid(int32_t headSize, int32_t s) const
|
||||
{
|
||||
uint64_t key = (static_cast<uint64_t>(headSize) << 32 | static_cast<uint64_t>(s));
|
||||
return (mValidSequences.find(key) != mValidSequences.end());
|
||||
}
|
||||
|
||||
virtual void run(TKernelParam& params, cudaStream_t ss) const
|
||||
{
|
||||
const auto findIter = mFunctions.find(hashID(params.s, params.d));
|
||||
std::stringstream errMsg;
|
||||
errMsg << "Could not find kernel for:\n"
|
||||
<< "\t s: " << params.s << "\n"
|
||||
<< "\t d: " << params.d << "\n"
|
||||
<< "Was the plugin compiled on a compatible CUDA and SM version?\n"
|
||||
<< "\t Compiled on CUDA " << CUDA_VERSION << "\n"
|
||||
<< "\t Current SM version: " << mSM << "\n"
|
||||
<< "\t SM versions enabled during compilation: "
|
||||
#if defined(ENABLE_SM72)
|
||||
<< "72 "
|
||||
#endif
|
||||
#if defined(ENABLE_SM75)
|
||||
<< "75 "
|
||||
#endif
|
||||
#if defined(ENABLE_SM80)
|
||||
<< "80 "
|
||||
#endif
|
||||
#if defined(ENABLE_SM86)
|
||||
<< "86 "
|
||||
#endif
|
||||
#if defined(ENABLE_SM87)
|
||||
<< "87 "
|
||||
#endif
|
||||
#if defined(ENABLE_SM89)
|
||||
<< "89 "
|
||||
#endif
|
||||
#if defined(ENABLE_SM90)
|
||||
<< "90 "
|
||||
#endif
|
||||
<< "\n";
|
||||
PLUGIN_VALIDATE(findIter != mFunctions.end(), errMsg.str().c_str());
|
||||
|
||||
const auto& kernelMeta = mKernelMeta[findIter->second.mMetaInfoIndex];
|
||||
const CUfunction func = findIter->second.mDeviceFunction;
|
||||
|
||||
void* kernelParams[] = {¶ms, nullptr};
|
||||
cuErrCheck(mDriver.cuLaunchKernel(func, params.h, params.b, 1, kernelMeta.mThreadsPerCTA, 1, 1,
|
||||
kernelMeta.mSharedMemBytes, ss, kernelParams, nullptr),
|
||||
mDriver);
|
||||
}
|
||||
|
||||
virtual ~TFusedMultiHeadAttentionXMMAKernel() = default;
|
||||
|
||||
protected:
|
||||
nvinfer1::CUDADriverWrapper mDriver;
|
||||
|
||||
plugin::bert::Data_type mDataType;
|
||||
const TKernelMeta* mKernelMeta;
|
||||
uint32_t mKernelMetaCount;
|
||||
uint32_t mSM;
|
||||
std::unordered_map<const unsigned char*, CUmodule> mModules;
|
||||
struct FusedMultiHeadAttentionKernelInfo
|
||||
{
|
||||
uint32_t mMetaInfoIndex;
|
||||
CUfunction mDeviceFunction;
|
||||
};
|
||||
std::unordered_map<uint64_t, FusedMultiHeadAttentionKernelInfo> mFunctions;
|
||||
// Set of valid sequence and head size combination. We use (headSize << 32 | sequence) as key here.
|
||||
std::unordered_set<uint64_t> mValidSequences;
|
||||
};
|
||||
template <typename TFusedMHAKernelList>
|
||||
class TFusedMHAKernelFactory
|
||||
{
|
||||
public:
|
||||
TFusedMHAKernelList const* getXMMAKernels(typename TFusedMHAKernelList::KernelMeta const* pKernelList,
|
||||
uint32_t nbKernels, plugin::bert::Data_type type, uint32_t sm)
|
||||
{
|
||||
static std::mutex s_mutex;
|
||||
std::lock_guard<std::mutex> lg(s_mutex);
|
||||
|
||||
auto const id = hashID(type, sm);
|
||||
auto it = mKernels.find(id);
|
||||
if (it == mKernels.end())
|
||||
{
|
||||
auto newKernel = std::make_unique<TFusedMHAKernelList>(pKernelList, nbKernels, type, sm);
|
||||
newKernel->loadXMMAKernels();
|
||||
it = mKernels.emplace(id, std::move(newKernel)).first;
|
||||
}
|
||||
return it->second.get();
|
||||
}
|
||||
|
||||
static TFusedMHAKernelFactory<TFusedMHAKernelList>& Get()
|
||||
{
|
||||
static TFusedMHAKernelFactory<TFusedMHAKernelList> s_factory;
|
||||
return s_factory;
|
||||
}
|
||||
|
||||
private:
|
||||
TFusedMHAKernelFactory() = default;
|
||||
|
||||
inline uint64_t hashID(plugin::bert::Data_type type, uint32_t sm) const
|
||||
{
|
||||
// use deviceID in hasID for multi GPU support before driver support context-less loading of cubin
|
||||
int32_t deviceID{0};
|
||||
CSC(cudaGetDevice(&deviceID), STATUS_FAILURE);
|
||||
|
||||
PLUGIN_ASSERT((deviceID & 0xFFFF) == deviceID);
|
||||
PLUGIN_ASSERT((type & 0xFFFF) == type);
|
||||
PLUGIN_ASSERT((sm & 0xFFFFFFFF) == sm);
|
||||
return (uint64_t) type << 48 | (uint64_t) deviceID << 32 | sm;
|
||||
}
|
||||
|
||||
std::unordered_map<uint64_t, const std::unique_ptr<TFusedMHAKernelList>> mKernels;
|
||||
};
|
||||
} // namespace pluginInternal
|
||||
|
||||
namespace plugin
|
||||
{
|
||||
namespace bert
|
||||
{
|
||||
static inline size_t get_size_in_bytes(size_t n, Data_type dtype)
|
||||
{
|
||||
switch (dtype)
|
||||
{
|
||||
case DATA_TYPE_E8M10: return n * 4;
|
||||
case DATA_TYPE_FP32: return n * 4;
|
||||
case DATA_TYPE_FP16: return n * 2;
|
||||
case DATA_TYPE_INT32: return n * 4;
|
||||
case DATA_TYPE_INT8: return n;
|
||||
case DATA_TYPE_INT4: return n / 2U;
|
||||
case DATA_TYPE_BOOL: return n / 8U;
|
||||
case DATA_TYPE_E8M7: return n * 2;
|
||||
default: PLUGIN_ASSERT(false); return 0;
|
||||
}
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////////////////////////////////
|
||||
|
||||
struct Fused_multihead_attention_params
|
||||
{
|
||||
// The QKV matrices.
|
||||
void* qkv_ptr{};
|
||||
// The mask to implement drop-out.
|
||||
void* packed_mask_ptr{};
|
||||
// The O matrix (output).
|
||||
void* o_ptr{};
|
||||
|
||||
// The stride between rows of the Q, K and V matrices.
|
||||
int64_t qkv_stride_in_bytes{};
|
||||
// The stride between matrices of packed mask.
|
||||
int64_t packed_mask_stride_in_bytes{};
|
||||
// The stride between rows of O.
|
||||
int64_t o_stride_in_bytes{};
|
||||
|
||||
#if defined(STORE_P)
|
||||
// The pointer to the P matrix (for debugging).
|
||||
void* p_ptr{};
|
||||
// The stride between rows of the P matrix (for debugging).
|
||||
int64_t p_stride_in_bytes{};
|
||||
#endif // defined(STORE_P)
|
||||
|
||||
#if defined(STORE_S)
|
||||
// The pointer to the S matrix (for debugging).
|
||||
void* s_ptr{};
|
||||
// The stride between rows of the S matrix (for debugging).
|
||||
int64_t s_stride_in_bytes{};
|
||||
#endif // defined(STORE_S)
|
||||
|
||||
// The dimensions.
|
||||
int32_t b{};
|
||||
int32_t h{};
|
||||
int32_t s{};
|
||||
int32_t d{};
|
||||
// The scaling factors for the kernel.
|
||||
uint32_t scale_bmm1{};
|
||||
uint32_t scale_softmax{};
|
||||
uint32_t scale_bmm2{};
|
||||
|
||||
// Do we use Niall's trick to avoid I2F/F2I in the INT8 kernel.
|
||||
// See https://confluence.nvidia.com/pages/viewpage.action?pageId=302779721 for details.
|
||||
bool enable_i2f_trick{};
|
||||
|
||||
// The number of heads computed by one iteration of the wave.
|
||||
int32_t heads_per_wave{};
|
||||
// Buffers to perform a global sync and a critical section.
|
||||
int32_t* counters{};
|
||||
int32_t* max_barriers{};
|
||||
int32_t* sum_barriers{};
|
||||
int32_t* locks{};
|
||||
// Scratch buffers to finalize softmax.
|
||||
float* max_scratch_ptr{};
|
||||
float* sum_scratch_ptr{};
|
||||
// Scratch buffer to finalize the output (not needed for FP16).
|
||||
int32_t* o_scratch_ptr{};
|
||||
};
|
||||
|
||||
////////////////////////////////////////////////////////////////////////////////////////////////////
|
||||
#if defined(ENABLE_SM75)
|
||||
extern unsigned char fused_multihead_attention_fp16_64_64_kernel_sm75_cu_o[];
|
||||
extern unsigned char fused_multihead_attention_fp16_96_64_kernel_sm75_cu_o[];
|
||||
extern unsigned char fused_multihead_attention_fp16_128_64_kernel_sm75_cu_o[];
|
||||
extern unsigned char fused_multihead_attention_fp16_384_64_kernel_sm75_cu_o[];
|
||||
extern unsigned char fused_multihead_attention_int8_128_64_kernel_sm75_cu_o[];
|
||||
extern unsigned char fused_multihead_attention_int8_384_64_kernel_sm75_cu_o[];
|
||||
#endif // defined(ENABLE_SM75)
|
||||
|
||||
#if defined(ENABLE_SM80) || defined(ENABLE_SM86) || defined(ENABLE_SM89)
|
||||
extern unsigned char fused_multihead_attention_fp16_64_64_kernel_sm80_cu_o[];
|
||||
extern unsigned char fused_multihead_attention_fp16_96_64_kernel_sm80_cu_o[];
|
||||
extern unsigned char fused_multihead_attention_int8_384_64_kernel_sm80_cu_o[];
|
||||
extern unsigned char fused_multihead_attention_int8_128_64_kernel_sm80_cu_o[];
|
||||
extern unsigned char fused_multihead_attention_fp16_128_64_kernel_sm80_cu_o[];
|
||||
extern unsigned char fused_multihead_attention_fp16_384_64_kernel_sm80_cu_o[];
|
||||
|
||||
extern unsigned char cubin_fmha_v1_int8_64_64_sm80_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_int8_96_64_sm80_cu_cubin[];
|
||||
#endif // defined(ENABLE_SM80) || defined(SM86) || defined(ENABLE_SM89)
|
||||
|
||||
#if defined(ENABLE_SM86) || defined(ENABLE_SM89)
|
||||
extern unsigned char fused_multihead_attention_fp16_384_64_kernel_sm86_cu_o[];
|
||||
#endif // defined(ENABLE_SM86) || defined(ENABLE_SM89)
|
||||
|
||||
#if defined(ENABLE_SM87)
|
||||
extern unsigned char cubin_fmha_v1_int8_384_64_sm87_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_int8_128_64_sm87_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_384_64_sm87_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_128_64_sm87_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_96_64_sm87_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_64_64_sm87_cu_cubin[];
|
||||
#endif // defined(ENABLE_SM87)
|
||||
|
||||
#if defined(ENABLE_SM90)
|
||||
extern unsigned char cubin_fmha_v1_int8_512_64_sm90_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_int8_384_64_sm90_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_int8_128_64_sm90_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_512_64_sm90_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_384_64_sm90_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_128_64_sm90_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_96_64_sm90_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_64_64_sm90_cu_cubin[];
|
||||
#endif // defined(ENABLE_SM90)
|
||||
|
||||
#if defined(ENABLE_SM100)
|
||||
extern unsigned char cubin_fmha_v1_int8_512_64_sm100_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_int8_384_64_sm100_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_int8_128_64_sm100_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_512_64_sm100_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_384_64_sm100_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_128_64_sm100_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_96_64_sm100_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_64_64_sm100_cu_cubin[];
|
||||
#endif // defined(ENABLE_SM100)
|
||||
#if defined(ENABLE_SM120)
|
||||
extern unsigned char cubin_fmha_v1_int8_512_64_sm120_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_int8_384_64_sm120_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_int8_128_64_sm120_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_512_64_sm120_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_384_64_sm120_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_128_64_sm120_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_96_64_sm120_cu_cubin[];
|
||||
extern unsigned char cubin_fmha_v1_fp16_64_64_sm120_cu_cubin[];
|
||||
#endif // defined(ENABLE_SM120)
|
||||
|
||||
#if defined(ENABLE_SM75)
|
||||
extern uint32_t fused_multihead_attention_fp16_64_64_kernel_sm75_cu_o_len;
|
||||
extern uint32_t fused_multihead_attention_fp16_96_64_kernel_sm75_cu_o_len;
|
||||
extern uint32_t fused_multihead_attention_fp16_128_64_kernel_sm75_cu_o_len;
|
||||
extern uint32_t fused_multihead_attention_fp16_384_64_kernel_sm75_cu_o_len;
|
||||
extern uint32_t fused_multihead_attention_int8_128_64_kernel_sm75_cu_o_len;
|
||||
extern uint32_t fused_multihead_attention_int8_384_64_kernel_sm75_cu_o_len;
|
||||
#endif // defined(ENABLE_SM75)
|
||||
|
||||
#if defined(ENABLE_SM80) || defined(ENABLE_SM86) || defined(ENABLE_SM89)
|
||||
extern uint32_t fused_multihead_attention_fp16_64_64_kernel_sm80_cu_o_len;
|
||||
extern uint32_t fused_multihead_attention_fp16_96_64_kernel_sm80_cu_o_len;
|
||||
extern uint32_t fused_multihead_attention_int8_384_64_kernel_sm80_cu_o_len;
|
||||
extern uint32_t fused_multihead_attention_int8_128_64_kernel_sm80_cu_o_len;
|
||||
extern uint32_t fused_multihead_attention_fp16_128_64_kernel_sm80_cu_o_len;
|
||||
extern uint32_t fused_multihead_attention_fp16_384_64_kernel_sm80_cu_o_len;
|
||||
extern uint32_t cubin_fmha_v1_int8_64_64_sm80_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_int8_96_64_sm80_cu_cubin_len;
|
||||
#endif // defined(ENABLE_SM80) || defined(SM86) || defined(ENABLE_SM89)
|
||||
|
||||
#if defined(ENABLE_SM86) || defined(ENABLE_SM89)
|
||||
extern uint32_t fused_multihead_attention_fp16_384_64_kernel_sm86_cu_o_len;
|
||||
#endif // defined(ENABLE_SM86) || defined(ENABLE_SM89)
|
||||
|
||||
#if defined(ENABLE_SM87)
|
||||
extern uint32_t cubin_fmha_v1_int8_384_64_sm87_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_int8_128_64_sm87_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_384_64_sm87_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_128_64_sm87_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_96_64_sm87_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_64_64_sm87_cu_cubin_len;
|
||||
#endif // defined(ENABLE_SM87)
|
||||
|
||||
#if defined(ENABLE_SM90)
|
||||
extern uint32_t cubin_fmha_v1_int8_512_64_sm90_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_int8_384_64_sm90_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_int8_128_64_sm90_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_512_64_sm90_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_384_64_sm90_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_128_64_sm90_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_96_64_sm90_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_64_64_sm90_cu_cubin_len;
|
||||
#endif // defined(ENABLE_SM90)
|
||||
|
||||
#if defined(ENABLE_SM100)
|
||||
extern uint32_t cubin_fmha_v1_int8_512_64_sm100_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_int8_384_64_sm100_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_int8_128_64_sm100_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_512_64_sm100_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_384_64_sm100_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_128_64_sm100_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_96_64_sm100_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_64_64_sm100_cu_cubin_len;
|
||||
#endif // defined(ENABLE_SM100)
|
||||
#if defined(ENABLE_SM120)
|
||||
extern uint32_t cubin_fmha_v1_int8_512_64_sm120_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_int8_384_64_sm120_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_int8_128_64_sm120_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_512_64_sm120_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_384_64_sm120_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_128_64_sm120_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_96_64_sm120_cu_cubin_len;
|
||||
extern uint32_t cubin_fmha_v1_fp16_64_64_sm120_cu_cubin_len;
|
||||
#endif // defined(ENABLE_SM120)
|
||||
|
||||
#if !(defined(ENABLE_SM72) || defined(ENABLE_SM75) || defined(ENABLE_SM80) || defined(ENABLE_SM86) \
|
||||
|| defined(ENABLE_SM87) || defined(ENABLE_SM89) || defined(ENABLE_SM90) || defined(ENABLE_SM100) \
|
||||
|| defined(ENABLE_SM120))
|
||||
|
||||
#error This file can only be included if one of sm 72, 75, 80, 86, 87, 89, 90, 100 or 120 is defined.
|
||||
|
||||
#endif
|
||||
|
||||
static const struct FusedMultiHeadAttentionKernelMetaInfoV1
|
||||
{
|
||||
Data_type mDataType;
|
||||
uint32_t mS;
|
||||
uint32_t mD;
|
||||
uint32_t mSM;
|
||||
const unsigned char* mCubin;
|
||||
uint32_t mCubinSize;
|
||||
const char* mFuncName;
|
||||
uint32_t mSharedMemBytes;
|
||||
uint32_t mThreadsPerCTA;
|
||||
} sMhaKernelMetaInfos[] = {
|
||||
#if defined(ENABLE_SM75)
|
||||
// Turing
|
||||
{DATA_TYPE_FP16, 64, 64, kSM_75, fused_multihead_attention_fp16_64_64_kernel_sm75_cu_o,
|
||||
fused_multihead_attention_fp16_64_64_kernel_sm75_cu_o_len,
|
||||
"fused_multihead_attention_v2_fp16_64_64_kernel_sm75", 24576, 128},
|
||||
{DATA_TYPE_FP16, 96, 64, kSM_75, fused_multihead_attention_fp16_96_64_kernel_sm75_cu_o,
|
||||
fused_multihead_attention_fp16_96_64_kernel_sm75_cu_o_len,
|
||||
"fused_multihead_attention_v2_fp16_96_64_kernel_sm75", 24576, 128},
|
||||
{DATA_TYPE_FP16, 128, 64, kSM_75, fused_multihead_attention_fp16_128_64_kernel_sm75_cu_o,
|
||||
fused_multihead_attention_fp16_128_64_kernel_sm75_cu_o_len, "fused_multihead_attention_fp16_128_64_kernel_sm75",
|
||||
32768, 128},
|
||||
{DATA_TYPE_FP16, 384, 64, kSM_75, fused_multihead_attention_fp16_384_64_kernel_sm75_cu_o,
|
||||
fused_multihead_attention_fp16_384_64_kernel_sm75_cu_o_len, "fused_multihead_attention_fp16_384_64_kernel_sm75",
|
||||
57344, 256},
|
||||
{DATA_TYPE_INT8, 128, 64, kSM_75, fused_multihead_attention_int8_128_64_kernel_sm75_cu_o,
|
||||
fused_multihead_attention_int8_128_64_kernel_sm75_cu_o_len, "fused_multihead_attention_int8_128_64_kernel_sm75",
|
||||
16384, 128},
|
||||
{DATA_TYPE_INT8, 384, 64, kSM_75, fused_multihead_attention_int8_384_64_kernel_sm75_cu_o,
|
||||
fused_multihead_attention_int8_384_64_kernel_sm75_cu_o_len, "fused_multihead_attention_int8_384_64_kernel_sm75",
|
||||
53284, 256},
|
||||
#endif // defined(ENABLE_SM75)
|
||||
#if defined(ENABLE_SM80) || defined(ENABLE_SM86) || defined(ENABLE_SM89)
|
||||
// Ampere
|
||||
{DATA_TYPE_FP16, 64, 64, kSM_80, fused_multihead_attention_fp16_64_64_kernel_sm80_cu_o,
|
||||
fused_multihead_attention_fp16_64_64_kernel_sm80_cu_o_len,
|
||||
"fused_multihead_attention_v2_fp16_64_64_kernel_sm80", 32768, 128},
|
||||
{DATA_TYPE_FP16, 96, 64, kSM_80, fused_multihead_attention_fp16_96_64_kernel_sm80_cu_o,
|
||||
fused_multihead_attention_fp16_96_64_kernel_sm80_cu_o_len,
|
||||
"fused_multihead_attention_v2_fp16_96_64_kernel_sm80", 49152, 128},
|
||||
{DATA_TYPE_FP16, 128, 64, kSM_80, fused_multihead_attention_fp16_128_64_kernel_sm80_cu_o,
|
||||
fused_multihead_attention_fp16_128_64_kernel_sm80_cu_o_len, "fused_multihead_attention_fp16_128_64_kernel_sm80",
|
||||
49152, 128},
|
||||
{DATA_TYPE_FP16, 384, 64, kSM_80, fused_multihead_attention_fp16_384_64_kernel_sm80_cu_o,
|
||||
fused_multihead_attention_fp16_384_64_kernel_sm80_cu_o_len, "fused_multihead_attention_fp16_384_64_kernel_sm80",
|
||||
114688, 256},
|
||||
{DATA_TYPE_INT8, 64, 64, kSM_80, cubin_fmha_v1_int8_64_64_sm80_cu_cubin, cubin_fmha_v1_int8_64_64_sm80_cu_cubin_len,
|
||||
"fmha_v1_int8_64_64_sm80_kernel", 24576, 128},
|
||||
{DATA_TYPE_INT8, 96, 64, kSM_80, cubin_fmha_v1_int8_96_64_sm80_cu_cubin, cubin_fmha_v1_int8_96_64_sm80_cu_cubin_len,
|
||||
"fmha_v1_int8_96_64_sm80_kernel", 28672, 128},
|
||||
{DATA_TYPE_INT8, 128, 64, kSM_80, fused_multihead_attention_int8_128_64_kernel_sm80_cu_o,
|
||||
fused_multihead_attention_int8_128_64_kernel_sm80_cu_o_len, "fused_multihead_attention_int8_128_64_kernel_sm80",
|
||||
24576, 128},
|
||||
{DATA_TYPE_INT8, 384, 64, kSM_80, fused_multihead_attention_int8_384_64_kernel_sm80_cu_o,
|
||||
fused_multihead_attention_int8_384_64_kernel_sm80_cu_o_len, "fused_multihead_attention_int8_384_64_kernel_sm80",
|
||||
57344, 256},
|
||||
#endif // defined(ENABLE_SM80) || defined(SM86) || defined(ENABLE_SM89)
|
||||
#if defined(ENABLE_SM86) || defined(ENABLE_SM89)
|
||||
// GA10x
|
||||
// Note: For GA10X keep only kernels whose sharedMemBytes < 100KiB
|
||||
{DATA_TYPE_FP16, 64, 64, kSM_86, fused_multihead_attention_fp16_64_64_kernel_sm80_cu_o,
|
||||
fused_multihead_attention_fp16_64_64_kernel_sm80_cu_o_len,
|
||||
"fused_multihead_attention_v2_fp16_64_64_kernel_sm80", 32768, 128},
|
||||
{DATA_TYPE_FP16, 96, 64, kSM_86, fused_multihead_attention_fp16_96_64_kernel_sm80_cu_o,
|
||||
fused_multihead_attention_fp16_96_64_kernel_sm80_cu_o_len,
|
||||
"fused_multihead_attention_v2_fp16_96_64_kernel_sm80", 49152, 128},
|
||||
{DATA_TYPE_FP16, 128, 64, kSM_86, fused_multihead_attention_fp16_128_64_kernel_sm80_cu_o,
|
||||
fused_multihead_attention_fp16_128_64_kernel_sm80_cu_o_len, "fused_multihead_attention_fp16_128_64_kernel_sm80",
|
||||
49152, 128},
|
||||
{DATA_TYPE_FP16, 384, 64, kSM_86, fused_multihead_attention_fp16_384_64_kernel_sm86_cu_o,
|
||||
fused_multihead_attention_fp16_384_64_kernel_sm86_cu_o_len, "fused_multihead_attention_fp16_384_64_kernel_sm80",
|
||||
65536, 256},
|
||||
{DATA_TYPE_INT8, 128, 64, kSM_86, fused_multihead_attention_int8_128_64_kernel_sm80_cu_o,
|
||||
fused_multihead_attention_int8_128_64_kernel_sm80_cu_o_len, "fused_multihead_attention_int8_128_64_kernel_sm80",
|
||||
24576, 128},
|
||||
{DATA_TYPE_INT8, 384, 64, kSM_86, fused_multihead_attention_int8_384_64_kernel_sm80_cu_o,
|
||||
fused_multihead_attention_int8_384_64_kernel_sm80_cu_o_len, "fused_multihead_attention_int8_384_64_kernel_sm80",
|
||||
57344, 256},
|
||||
#endif // defined(ENABLE_SM86) || defined(ENABLE_SM89)
|
||||
#if defined(ENABLE_SM87)
|
||||
// GA10b (Orin-Auto)
|
||||
{DATA_TYPE_INT8, 384, 64, kSM_87, cubin_fmha_v1_int8_384_64_sm87_cu_cubin,
|
||||
cubin_fmha_v1_int8_384_64_sm87_cu_cubin_len, "fmha_v1_int8_384_64_sm87_kernel", 40960, 256},
|
||||
{DATA_TYPE_INT8, 128, 64, kSM_87, cubin_fmha_v1_int8_128_64_sm87_cu_cubin,
|
||||
cubin_fmha_v1_int8_128_64_sm87_cu_cubin_len, "fmha_v1_int8_128_64_sm87_kernel", 24576, 128},
|
||||
{DATA_TYPE_FP16, 384, 64, kSM_87, cubin_fmha_v1_fp16_384_64_sm87_cu_cubin,
|
||||
cubin_fmha_v1_fp16_384_64_sm87_cu_cubin_len, "fmha_v1_fp16_384_64_sm87_kernel", 65536, 256},
|
||||
{DATA_TYPE_FP16, 128, 64, kSM_87, cubin_fmha_v1_fp16_128_64_sm87_cu_cubin,
|
||||
cubin_fmha_v1_fp16_128_64_sm87_cu_cubin_len, "fmha_v1_fp16_128_64_sm87_kernel", 49152, 128},
|
||||
{DATA_TYPE_FP16, 96, 64, kSM_87, cubin_fmha_v1_fp16_96_64_sm87_cu_cubin, cubin_fmha_v1_fp16_96_64_sm87_cu_cubin_len,
|
||||
"fmha_v1_fp16_96_64_sm87_kernel", 49152, 128},
|
||||
{DATA_TYPE_FP16, 64, 64, kSM_87, cubin_fmha_v1_fp16_64_64_sm87_cu_cubin, cubin_fmha_v1_fp16_64_64_sm87_cu_cubin_len,
|
||||
"fmha_v1_fp16_64_64_sm87_kernel", 32768, 128},
|
||||
#endif // defined(ENABLE_SM87)
|
||||
#if defined(ENABLE_SM90)
|
||||
// GH100 hopper
|
||||
{DATA_TYPE_INT8, 512, 64, kSM_90, cubin_fmha_v1_int8_512_64_sm90_cu_cubin,
|
||||
cubin_fmha_v1_int8_512_64_sm90_cu_cubin_len, "fmha_v1_int8_512_64_sm90_kernel", 73728, 256},
|
||||
{DATA_TYPE_INT8, 384, 64, kSM_90, cubin_fmha_v1_int8_384_64_sm90_cu_cubin,
|
||||
cubin_fmha_v1_int8_384_64_sm90_cu_cubin_len, "fmha_v1_int8_384_64_sm90_kernel", 73728, 256},
|
||||
{DATA_TYPE_INT8, 128, 64, kSM_90, cubin_fmha_v1_int8_128_64_sm90_cu_cubin,
|
||||
cubin_fmha_v1_int8_128_64_sm90_cu_cubin_len, "fmha_v1_int8_128_64_sm90_kernel", 24576, 128},
|
||||
{DATA_TYPE_FP16, 512, 64, kSM_90, cubin_fmha_v1_fp16_512_64_sm90_cu_cubin,
|
||||
cubin_fmha_v1_fp16_512_64_sm90_cu_cubin_len, "fmha_v1_fp16_512_64_sm90_kernel", 73728, 256},
|
||||
{DATA_TYPE_FP16, 384, 64, kSM_90, cubin_fmha_v1_fp16_384_64_sm90_cu_cubin,
|
||||
cubin_fmha_v1_fp16_384_64_sm90_cu_cubin_len, "fmha_v1_fp16_384_64_sm90_kernel", 65536, 256},
|
||||
{DATA_TYPE_FP16, 128, 64, kSM_90, cubin_fmha_v1_fp16_128_64_sm90_cu_cubin,
|
||||
cubin_fmha_v1_fp16_128_64_sm90_cu_cubin_len, "fmha_v1_fp16_128_64_sm90_kernel", 65536, 128},
|
||||
{DATA_TYPE_FP16, 96, 64, kSM_90, cubin_fmha_v1_fp16_96_64_sm90_cu_cubin, cubin_fmha_v1_fp16_96_64_sm90_cu_cubin_len,
|
||||
"fmha_v1_fp16_96_64_sm90_kernel", 49152, 128},
|
||||
{DATA_TYPE_FP16, 64, 64, kSM_90, cubin_fmha_v1_fp16_64_64_sm90_cu_cubin, cubin_fmha_v1_fp16_64_64_sm90_cu_cubin_len,
|
||||
"fmha_v1_fp16_64_64_sm90_kernel", 32768, 128},
|
||||
#endif // defined(ENABLE_SM90)
|
||||
|
||||
#if defined(ENABLE_SM100)
|
||||
{DATA_TYPE_INT8, 512, 64, kSM_100, cubin_fmha_v1_int8_512_64_sm100_cu_cubin,
|
||||
cubin_fmha_v1_int8_512_64_sm100_cu_cubin_len, "fmha_v1_int8_512_64_sm100_kernel", 73728, 256},
|
||||
{DATA_TYPE_INT8, 384, 64, kSM_100, cubin_fmha_v1_int8_384_64_sm100_cu_cubin,
|
||||
cubin_fmha_v1_int8_384_64_sm100_cu_cubin_len, "fmha_v1_int8_384_64_sm100_kernel", 73728, 256},
|
||||
{DATA_TYPE_INT8, 128, 64, kSM_100, cubin_fmha_v1_int8_128_64_sm100_cu_cubin,
|
||||
cubin_fmha_v1_int8_128_64_sm100_cu_cubin_len, "fmha_v1_int8_128_64_sm100_kernel", 24576, 128},
|
||||
{DATA_TYPE_FP16, 512, 64, kSM_100, cubin_fmha_v1_fp16_512_64_sm100_cu_cubin,
|
||||
cubin_fmha_v1_fp16_512_64_sm100_cu_cubin_len, "fmha_v1_fp16_512_64_sm100_kernel", 73728, 256},
|
||||
{DATA_TYPE_FP16, 384, 64, kSM_100, cubin_fmha_v1_fp16_384_64_sm100_cu_cubin,
|
||||
cubin_fmha_v1_fp16_384_64_sm100_cu_cubin_len, "fmha_v1_fp16_384_64_sm100_kernel", 65536, 256},
|
||||
{DATA_TYPE_FP16, 128, 64, kSM_100, cubin_fmha_v1_fp16_128_64_sm100_cu_cubin,
|
||||
cubin_fmha_v1_fp16_128_64_sm100_cu_cubin_len, "fmha_v1_fp16_128_64_sm100_kernel", 65536, 128},
|
||||
{DATA_TYPE_FP16, 96, 64, kSM_100, cubin_fmha_v1_fp16_96_64_sm100_cu_cubin,
|
||||
cubin_fmha_v1_fp16_96_64_sm100_cu_cubin_len, "fmha_v1_fp16_96_64_sm100_kernel", 49152, 128},
|
||||
{DATA_TYPE_FP16, 64, 64, kSM_100, cubin_fmha_v1_fp16_64_64_sm100_cu_cubin,
|
||||
cubin_fmha_v1_fp16_64_64_sm100_cu_cubin_len, "fmha_v1_fp16_64_64_sm100_kernel", 32768, 128},
|
||||
#endif // defined(ENABLE_SM100)
|
||||
#if defined(ENABLE_SM120)
|
||||
{DATA_TYPE_INT8, 512, 64, kSM_120, cubin_fmha_v1_int8_512_64_sm120_cu_cubin,
|
||||
cubin_fmha_v1_int8_512_64_sm120_cu_cubin_len, "fmha_v1_int8_512_64_sm120_kernel", 73728, 256},
|
||||
{DATA_TYPE_INT8, 384, 64, kSM_120, cubin_fmha_v1_int8_384_64_sm120_cu_cubin,
|
||||
cubin_fmha_v1_int8_384_64_sm120_cu_cubin_len, "fmha_v1_int8_384_64_sm120_kernel", 73728, 256},
|
||||
{DATA_TYPE_INT8, 128, 64, kSM_120, cubin_fmha_v1_int8_128_64_sm120_cu_cubin,
|
||||
cubin_fmha_v1_int8_128_64_sm120_cu_cubin_len, "fmha_v1_int8_128_64_sm120_kernel", 24576, 128},
|
||||
{DATA_TYPE_FP16, 512, 64, kSM_120, cubin_fmha_v1_fp16_512_64_sm120_cu_cubin,
|
||||
cubin_fmha_v1_fp16_512_64_sm120_cu_cubin_len, "fmha_v1_fp16_512_64_sm120_kernel", 73728, 256},
|
||||
{DATA_TYPE_FP16, 384, 64, kSM_120, cubin_fmha_v1_fp16_384_64_sm120_cu_cubin,
|
||||
cubin_fmha_v1_fp16_384_64_sm120_cu_cubin_len, "fmha_v1_fp16_384_64_sm120_kernel", 65536, 256},
|
||||
{DATA_TYPE_FP16, 128, 64, kSM_120, cubin_fmha_v1_fp16_128_64_sm120_cu_cubin,
|
||||
cubin_fmha_v1_fp16_128_64_sm120_cu_cubin_len, "fmha_v1_fp16_128_64_sm120_kernel", 65536, 128},
|
||||
{DATA_TYPE_FP16, 96, 64, kSM_120, cubin_fmha_v1_fp16_96_64_sm120_cu_cubin,
|
||||
cubin_fmha_v1_fp16_96_64_sm120_cu_cubin_len, "fmha_v1_fp16_96_64_sm120_kernel", 49152, 128},
|
||||
{DATA_TYPE_FP16, 64, 64, kSM_120, cubin_fmha_v1_fp16_64_64_sm120_cu_cubin,
|
||||
cubin_fmha_v1_fp16_64_64_sm120_cu_cubin_len, "fmha_v1_fp16_64_64_sm120_kernel", 32768, 128},
|
||||
#endif // defined(ENABLE_SM120)
|
||||
|
||||
};
|
||||
|
||||
using FusedMultiHeadAttentionXMMAKernel
|
||||
= pluginInternal::TFusedMultiHeadAttentionXMMAKernel<FusedMultiHeadAttentionKernelMetaInfoV1,
|
||||
Fused_multihead_attention_params>;
|
||||
using FusedMHAKernelFactory = pluginInternal::TFusedMHAKernelFactory<FusedMultiHeadAttentionXMMAKernel>;
|
||||
|
||||
inline const FusedMultiHeadAttentionXMMAKernel* getXMMAKernels(Data_type type, uint32_t sm)
|
||||
{
|
||||
return FusedMHAKernelFactory::Get().getXMMAKernels(
|
||||
sMhaKernelMetaInfos, sizeof(sMhaKernelMetaInfos) / sizeof(sMhaKernelMetaInfos[0]), type, sm);
|
||||
}
|
||||
|
||||
} // namespace bert
|
||||
} // namespace plugin
|
||||
} // namespace nvinfer1
|
||||
#endif // _BERT_FMHA_FMHA
|
||||
+43
@@ -0,0 +1,43 @@
|
||||
/*
|
||||
* 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.
|
||||
*/
|
||||
#ifndef TRT_FUSED_MULTIHEAD_ATTENTION_COMMON_H
|
||||
#define TRT_FUSED_MULTIHEAD_ATTENTION_COMMON_H
|
||||
|
||||
#include "common/checkMacrosPlugin.h"
|
||||
#include "common/plugin.h"
|
||||
#include <cstdint>
|
||||
namespace nvinfer1
|
||||
{
|
||||
namespace plugin
|
||||
{
|
||||
namespace bert
|
||||
{
|
||||
enum Data_type
|
||||
{
|
||||
DATA_TYPE_BOOL,
|
||||
DATA_TYPE_E8M10,
|
||||
DATA_TYPE_E8M7,
|
||||
DATA_TYPE_FP16,
|
||||
DATA_TYPE_FP32,
|
||||
DATA_TYPE_INT4,
|
||||
DATA_TYPE_INT8,
|
||||
DATA_TYPE_INT32
|
||||
};
|
||||
} // namespace bert
|
||||
} // namespace plugin
|
||||
} // namespace nvinfer1
|
||||
#endif // TRT_FUSED_MULTIHEAD_ATTENTION_COMMON_H
|
||||
+32413
File diff suppressed because it is too large
Load Diff
+20539
File diff suppressed because it is too large
Load Diff
+2710
File diff suppressed because it is too large
Load Diff
+2285
File diff suppressed because it is too large
Load Diff
+19766
File diff suppressed because it is too large
Load Diff
+30448
File diff suppressed because it is too large
Load Diff
+24637
File diff suppressed because it is too large
Load Diff
+15567
File diff suppressed because it is too large
Load Diff
+25191
File diff suppressed because it is too large
Load Diff
+16019
File diff suppressed because it is too large
Load Diff
+1827
File diff suppressed because it is too large
Load Diff
+1666
File diff suppressed because it is too large
Load Diff
+2620
File diff suppressed because it is too large
Load Diff
+25729
File diff suppressed because it is too large
Load Diff
+24485
File diff suppressed because it is too large
Load Diff
+24029
File diff suppressed because it is too large
Load Diff
+15230
File diff suppressed because it is too large
Load Diff
+24485
File diff suppressed because it is too large
Load Diff
+14845
File diff suppressed because it is too large
Load Diff
+9376
File diff suppressed because it is too large
Load Diff
+924
@@ -0,0 +1,924 @@
|
||||
/*
|
||||
* 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.
|
||||
*/
|
||||
|
||||
namespace nvinfer1
|
||||
{
|
||||
namespace plugin
|
||||
{
|
||||
namespace bert
|
||||
{
|
||||
unsigned char fused_multihead_attention_fp16_64_64_kernel_sm75_cu_o[] = {0x7f, 0x45, 0x4c, 0x46, 0x02, 0x01, 0x01, 0x33,
|
||||
0x07, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0xbe, 0x00, 0x6e, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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0x00, 0x10, 0xaa, 0x06, 0x06, 0x00, 0x58, 0x00, 0x00, 0xff, 0xe0, 0xf3, 0x07, 0x00, 0xe4, 0x0f, 0x00, 0x19, 0x76,
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0xff, 0x00, 0x8e, 0x07, 0x00, 0xe2, 0x0f, 0x00, 0x10, 0xaa, 0x07, 0x07, 0x00, 0x59, 0x00, 0x00, 0x0b, 0xe4, 0xff,
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||||
0x78, 0x00, 0x3e, 0xff, 0x01, 0x00, 0x00, 0x70, 0x42, 0xf2, 0x03, 0x00, 0xe4, 0x0f, 0x00, 0x10, 0xba, 0x23, 0x05,
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0x01, 0x00, 0x00, 0xe2, 0x0f, 0x00, 0x05, 0x78, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xff, 0x01, 0x00, 0x00,
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0x10, 0x7a, 0x30, 0x34, 0x00, 0x58, 0x00, 0x00, 0x31, 0xe0, 0xd9, 0x07, 0x00, 0xe2, 0x0f, 0x00, 0x05, 0x78, 0x0a,
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0x14, 0x22, 0x00, 0x00, 0x00, 0x00, 0x00, 0xed, 0x1e, 0x00, 0x00, 0xe8, 0x08, 0x00, 0x81, 0x99, 0x0c, 0x34, 0x0a,
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0x00, 0x00, 0x00, 0x00, 0xed, 0x1e, 0x0c, 0x00, 0xe8, 0x0e, 0x00, 0x81, 0x83, 0x08, 0x30, 0x00, 0x00, 0x00, 0x00,
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0x00, 0xed, 0x1e, 0x00, 0x00, 0xe2, 0x0e, 0x00, 0x05, 0x78, 0x04, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xff, 0x01,
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||||
0x78, 0x22, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xff, 0x01, 0x00, 0x00, 0xcc, 0x0f, 0x00, 0x81, 0xb3, 0x04, 0x2a,
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0x00, 0x00, 0x00, 0x00, 0x00, 0xed, 0x1e, 0x00, 0x00, 0x28, 0x0f, 0x00, 0x81, 0xa3, 0x20, 0x28, 0x00, 0x00, 0x00,
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||||
0x00, 0x00, 0xed, 0x1e, 0x00, 0x00, 0x22, 0x0f, 0x00, 0x19, 0x78, 0x26, 0xff, 0x1f, 0x00, 0x00, 0x00, 0x25, 0x14,
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||||
0x01, 0x00, 0x00, 0xc8, 0x0f, 0x00, 0x11, 0x72, 0x26, 0x26, 0x25, 0x00, 0x00, 0x00, 0xff, 0x18, 0x8f, 0x07, 0x00,
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||||
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||||
0x12, 0x78, 0x3f, 0x3e, 0x40, 0x00, 0x00, 0x00, 0xff, 0xc0, 0x8e, 0x07, 0x00, 0xc6, 0x0f, 0x00, 0x24, 0x78, 0x2d,
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||||
0x25, 0x01, 0x00, 0x00, 0x00, 0x26, 0x0a, 0x8e, 0x07, 0x00, 0xe2, 0x0f, 0x00, 0x12, 0x78, 0x2e, 0x3e, 0x07, 0x00,
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||||
0x00, 0x00, 0xff, 0xc0, 0x8e, 0x07, 0x00, 0xe4, 0x0f, 0x04, 0x19, 0x78, 0x2f, 0xff, 0x03, 0x00, 0x00, 0x00, 0x3e,
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||||
0x16, 0x01, 0x00, 0x00, 0xe4, 0x0f, 0x00, 0x12, 0x72, 0x26, 0x2d, 0x40, 0x00, 0x00, 0x00, 0xff, 0x3c, 0x8e, 0x07,
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||||
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||||
0x00, 0x11, 0x72, 0x2d, 0x3f, 0x2e, 0x00, 0x00, 0x00, 0xff, 0xf0, 0x8f, 0x07, 0x00, 0xe4, 0x0f, 0x00, 0x1a, 0x78,
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||||
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||||
0x00, 0x00, 0x00, 0xff, 0xf8, 0x8f, 0x07, 0x00, 0xe4, 0x0f, 0x00, 0x12, 0x78, 0x2f, 0x2f, 0x07, 0x00, 0x00, 0x00,
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||||
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|
||||
0x07, 0x00, 0xe4, 0x0f, 0x00, 0x24, 0x78, 0x2c, 0x3e, 0x10, 0x00, 0x00, 0x00, 0xff, 0x00, 0x8e, 0x07, 0x00, 0xe2,
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||||
0x0f, 0x04, 0x12, 0x78, 0x32, 0x3e, 0x0f, 0x00, 0x00, 0x00, 0xff, 0xc0, 0x8e, 0x07, 0x00, 0xe4, 0x0f, 0x04, 0x12,
|
||||
0x78, 0x41, 0x3e, 0x20, 0x00, 0x00, 0x00, 0xff, 0xc0, 0x8e, 0x07, 0x00, 0xe4, 0x0f, 0x00, 0x12, 0x78, 0x33, 0x2c,
|
||||
0x70, 0x00, 0x00, 0x00, 0xff, 0xc0, 0x8e, 0x07, 0x00, 0xe4, 0x0f, 0x00, 0x11, 0x72, 0x2c, 0x41, 0x32, 0x00, 0x00,
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||||
0x00, 0xff, 0xf8, 0x8f, 0x07, 0x00, 0xe4, 0x0f, 0x00, 0x12, 0x78, 0x33, 0x33, 0x10, 0x00, 0x00, 0x00, 0x3e, 0x78,
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||||
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||||
0xc4, 0x0f, 0x00, 0x24, 0x78, 0x46, 0x2f, 0x10, 0x00, 0x00, 0x00, 0xff, 0x00, 0x8e, 0x07, 0x00, 0xe4, 0x0f, 0x00,
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||||
0x24, 0x78, 0x47, 0x2c, 0x80, 0x00, 0x00, 0x00, 0x33, 0x02, 0x8e, 0x07, 0x00, 0xe2, 0x0f, 0x00, 0x05, 0x78, 0x44,
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||||
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xff, 0x01, 0x00, 0x00, 0xe2, 0x0f, 0x00, 0x05, 0x78, 0x42, 0x00, 0x00, 0x00,
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||||
0x00, 0x00, 0x00, 0xff, 0x01, 0x00, 0x00, 0xe2, 0x0f, 0x00, 0x05, 0x78, 0x36, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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||||
0xff, 0x01, 0x00, 0x00, 0xe2, 0x0f, 0x00, 0x05, 0x78, 0x3a, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xff, 0x01, 0x00,
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||||
0x00, 0xe2, 0x0f, 0x00, 0x05, 0x78, 0x3c, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xff, 0x01, 0x00, 0x00, 0xe2, 0x0f,
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||||
0x00, 0x05, 0x78, 0x38, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xff, 0x01, 0x00, 0x00, 0xe2, 0x0f, 0x00, 0x99, 0x78,
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||||
0x04, 0x3f, 0x1f, 0x00, 0x00, 0x00, 0x07, 0x14, 0x01, 0x08, 0x00, 0xe4, 0x0f, 0x00, 0xb9, 0x7a, 0x05, 0x00, 0x00,
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||||
0x60, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0xc4, 0x0f, 0x00, 0xa4, 0x72, 0x08, 0x04, 0x05, 0x00, 0x00, 0x00,
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||||
0x3f, 0x02, 0x8e, 0x0f, 0x00, 0xe4, 0x0f, 0x00, 0xb9, 0x7a, 0x09, 0x00, 0x00, 0x61, 0x00, 0x00, 0x00, 0x08, 0x00,
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||||
0x00, 0x00, 0xe4, 0x0f, 0x00, 0xa5, 0x72, 0x04, 0x07, 0x05, 0x00, 0x00, 0x00, 0x3f, 0x00, 0x8e, 0x0f, 0x00, 0xe4,
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||||
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||||
0x72, 0x07, 0x05, 0x07, 0x00, 0x00, 0x00, 0x3f, 0xe0, 0xff, 0x0f, 0x00, 0xe2, 0x0f, 0x00, 0x88, 0x73, 0x00, 0x26,
|
||||
0x10, 0x00, 0x18, 0x00, 0x00, 0xcc, 0x00, 0x00, 0x00, 0xe8, 0x4f, 0x00, 0x88, 0x73, 0x00, 0x26, 0x1c, 0x00, 0x00,
|
||||
0x00, 0x00, 0xcc, 0x00, 0x00, 0x00, 0xe8, 0x8f, 0x00, 0x88, 0x73, 0x00, 0x26, 0x18, 0x00, 0x08, 0x00, 0x00, 0xcc,
|
||||
0x00, 0x00, 0x00, 0xe8, 0x0f, 0x00, 0x88, 0x73, 0x00, 0x26, 0x14, 0x00, 0x10, 0x00, 0x00, 0xcc, 0x00, 0x00, 0x00,
|
||||
0xe8, 0x0f, 0x00, 0x88, 0x73, 0x00, 0x26, 0x0c, 0x00, 0x20, 0x00, 0x00, 0xcc, 0x00, 0x00, 0x00, 0xe8, 0x0f, 0x00,
|
||||
0x88, 0x73, 0x00, 0x26, 0x08, 0x00, 0x28, 0x00, 0x00, 0xcc, 0x00, 0x00, 0x00, 0xe8, 0x0f, 0x00, 0x88, 0x73, 0x00,
|
||||
0x26, 0x04, 0x00, 0x30, 0x00, 0x00, 0xcc, 0x00, 0x00, 0x00, 0xe8, 0x0f, 0x01, 0x88, 0x73, 0x00, 0x26, 0x20, 0x00,
|
||||
0x38, 0x00, 0x00, 0xcc, 0x00, 0x00, 0x00, 0xe8, 0x0f, 0x00, 0x1d, 0x7b, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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||||
0x00, 0x00, 0x00, 0x00, 0xea, 0x0f, 0x00, 0x3b, 0x78, 0x2c, 0x47, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00,
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||||
0x00, 0xf0, 0x0f, 0x00, 0x3b, 0x78, 0x14, 0x46, 0x00, 0x00, 0x30, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x30, 0x0e,
|
||||
0x00, 0x3b, 0x78, 0x18, 0x46, 0x00, 0x00, 0x20, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x70, 0x0e, 0x00, 0x3b, 0x78,
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||||
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|
||||
0x00, 0x00, 0x00, 0xff, 0x3c, 0x8e, 0x07, 0x00, 0xc4, 0x0f, 0x00, 0x12, 0x78, 0x20, 0x46, 0x20, 0x00, 0x00, 0x00,
|
||||
0xff, 0x3c, 0x8e, 0x07, 0x00, 0xcc, 0x0f, 0x00, 0x3b, 0x78, 0x10, 0x21, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00,
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||||
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|
||||
0x0e, 0x00, 0x3b, 0x78, 0x08, 0x20, 0x00, 0x00, 0x20, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x30, 0x0f, 0x00, 0x3b,
|
||||
0x78, 0x0c, 0x21, 0x00, 0x00, 0x10, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0xe2, 0x04, 0x00, 0x3c, 0x72, 0x3a, 0x2c,
|
||||
0x16, 0x00, 0x00, 0x00, 0x3a, 0x08, 0x00, 0x00, 0x00, 0x5e, 0x1f, 0x00, 0x18, 0x79, 0x00, 0x00, 0x00, 0x00, 0x00,
|
||||
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xc2, 0x0f, 0x00, 0x3c, 0x72, 0x44, 0x2c, 0x18, 0x00, 0x00, 0x00, 0x44, 0x08,
|
||||
0x00, 0x00, 0x00, 0xde, 0x2f, 0x00, 0x18, 0x79, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
|
||||
0xc2, 0x0f, 0x00, 0x3c, 0x72, 0x3c, 0x1c, 0x18, 0x00, 0x00, 0x00, 0x3c, 0x08, 0x00, 0x00, 0x00, 0xda, 0x4b, 0x00,
|
||||
0x05, 0x78, 0x18, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xff, 0x01, 0x00, 0x00, 0xc6, 0x0f, 0x02, 0x3c, 0x72, 0x36,
|
||||
0x2c, 0x14, 0x00, 0x00, 0x00, 0x36, 0x08, 0x00, 0x00, 0x00, 0x62, 0x0f, 0x00, 0x05, 0x78, 0x20, 0x00, 0x00, 0x00,
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||||
0x00, 0x00, 0x00, 0xff, 0x01, 0x00, 0x00, 0xde, 0x0f, 0x00, 0x3c, 0x72, 0x42, 0x2c, 0x1a, 0x00, 0x00, 0x00, 0x42,
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||||
0x08, 0x00, 0x00, 0x00, 0x5e, 0x0f, 0x00, 0x18, 0x79, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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||||
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||||
0x00, 0x18, 0x79, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xc2, 0x0f, 0x00, 0x3c, 0x72,
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||||
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0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xc2, 0x0f, 0x00, 0x3c, 0x72, 0x2e, 0x10, 0x06, 0x00, 0x00, 0x00,
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||||
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|
||||
0x07, 0x00, 0xe4, 0x0f, 0x02, 0x12, 0x78, 0x3b, 0x46, 0x40, 0x00, 0x00, 0x00, 0xff, 0x3c, 0x8e, 0x07, 0x00, 0xe2,
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||||
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||||
0x78, 0x14, 0x3a, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0xe4, 0x0f, 0x02, 0x3c, 0x72, 0x1e, 0x10,
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||||
0x04, 0x00, 0x00, 0x00, 0x36, 0x08, 0x00, 0x00, 0x00, 0xde, 0x0f, 0x00, 0x18, 0x79, 0x00, 0x00, 0x00, 0x00, 0x00,
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||||
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0x00, 0x00, 0xa9, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
|
||||
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x3f, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
|
||||
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
|
||||
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0xc0, 0x41,
|
||||
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
|
||||
0x00, 0x00, 0x00, 0xa8, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xa8, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
|
||||
0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x38, 0x05, 0x00,
|
||||
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
|
||||
0x00, 0x00, 0xc8, 0x39, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xc8, 0x39, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08,
|
||||
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x00, 0x3f, 0x00, 0x00,
|
||||
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
|
||||
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00,
|
||||
0x00, 0x00, 0x00, 0x00, 0x00, 0x00};
|
||||
unsigned int fused_multihead_attention_fp16_64_64_kernel_sm75_cu_o_len = 17000;
|
||||
|
||||
} // namespace bert
|
||||
} // namespace plugin
|
||||
} // namespace nvinfer1
|
||||
+903
@@ -0,0 +1,903 @@
|
||||
/*
|
||||
* 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.
|
||||
*/
|
||||
|
||||
namespace nvinfer1::plugin::bert
|
||||
{
|
||||
unsigned char fused_multihead_attention_fp16_64_64_kernel_sm80_cu_o[] = {0x7f, 0x45, 0x4c, 0x46, 0x02, 0x01, 0x01, 0x33,
|
||||
0x07, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0xbe, 0x00, 0x6e, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
|
||||
0x00, 0x00, 0x00, 0x00, 0x00, 0xc0, 0x40, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x00, 0x00, 0x00,
|
||||
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|
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0x28, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0x03, 0x00, 0x04,
|
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0x7c, 0xff, 0xff, 0xff, 0xff, 0x0f, 0x0c, 0x81, 0x80, 0x80, 0x28, 0x00, 0x08, 0xff, 0x81, 0x80, 0x28, 0x08, 0x81,
|
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|
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0x81, 0x80, 0x80, 0x28, 0x00, 0x04, 0x8a, 0x0d, 0x00, 0x00, 0x00, 0x00, 0x00, 0x04, 0x2f, 0x08, 0x00, 0x04, 0x00,
|
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|
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|
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|
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|
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|
||||
0xa0, 0x19, 0x00, 0x00, 0xc0, 0x19, 0x00, 0x00, 0xd0, 0x19, 0x00, 0x00, 0xe0, 0x19, 0x00, 0x00, 0xf0, 0x19, 0x00,
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|
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|
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|
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|
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|
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0x80, 0x00, 0x00, 0x00, 0x10, 0x02, 0x8e, 0x07, 0x00, 0xc6, 0x0f, 0x00, 0x12, 0x78, 0x13, 0x13, 0xf8, 0xff, 0xff,
|
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0x8e, 0x07, 0x00, 0xe2, 0x0f, 0x00, 0x10, 0x7a, 0x10, 0x10, 0x00, 0x58, 0x00, 0x00, 0x03, 0xe0, 0xa3, 0x07, 0x00,
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||||
0xe4, 0x0f, 0x00, 0x0c, 0x78, 0x00, 0x24, 0x00, 0x02, 0x00, 0x00, 0x70, 0x62, 0xf0, 0x03, 0x00, 0xe4, 0x0f, 0x00,
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||||
0x12, 0x72, 0x13, 0x12, 0x25, 0x00, 0x00, 0x00, 0xff, 0x3c, 0x8e, 0x07, 0x00, 0xe4, 0x0f, 0x00, 0x10, 0x7a, 0x11,
|
||||
0x11, 0x00, 0x59, 0x00, 0x00, 0x02, 0x44, 0xfe, 0x00, 0x00, 0xe4, 0x0f, 0x00, 0x12, 0x78, 0x14, 0x24, 0x40, 0x00,
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||||
0x00, 0x00, 0xff, 0xc0, 0x8e, 0x07, 0x00, 0xe4, 0x0f, 0x04, 0x12, 0x78, 0x15, 0x24, 0x07, 0x00, 0x00, 0x00, 0xff,
|
||||
0xc0, 0x8e, 0x07, 0x00, 0xc4, 0x0f, 0x00, 0x0c, 0x78, 0x00, 0x39, 0x40, 0x00, 0x00, 0x00, 0x70, 0x62, 0xf2, 0x03,
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||||
0x00, 0xe2, 0x0f, 0x00, 0x24, 0x78, 0x36, 0x00, 0x08, 0x00, 0x00, 0x00, 0x13, 0x02, 0x8e, 0x07, 0x00, 0xe2, 0x0f,
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||||
0x00, 0x10, 0x72, 0x12, 0x1f, 0x10, 0x00, 0x00, 0x00, 0xff, 0xe0, 0xf5, 0x07, 0x00, 0xe4, 0x0f, 0x00, 0x11, 0x72,
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0x19, 0x14, 0x15, 0x00, 0x00, 0x00, 0xff, 0xf0, 0x8f, 0x07, 0x00, 0xe4, 0x0f, 0x00, 0x12, 0x78, 0x15, 0x24, 0x0f,
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0x00, 0x00, 0x00, 0xff, 0xc0, 0x8e, 0x07, 0x00, 0xe4, 0x0f, 0x04, 0x12, 0x78, 0x16, 0x24, 0x20, 0x00, 0x00, 0x00,
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0xff, 0xc0, 0x8e, 0x07, 0x00, 0xe2, 0x0f, 0x00, 0x24, 0x78, 0x1b, 0x36, 0x10, 0x00, 0x00, 0x00, 0xff, 0x00, 0x8e,
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||||
0x07, 0x00, 0xe2, 0x0f, 0x00, 0x12, 0x78, 0x14, 0x24, 0x10, 0x00, 0x00, 0x00, 0xff, 0xc0, 0x8e, 0x07, 0x00, 0xe2,
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||||
0x72, 0x16, 0x16, 0x15, 0x00, 0x00, 0x00, 0xff, 0xf8, 0x8f, 0x07, 0x00, 0xe2, 0x0f, 0x00, 0x24, 0x78, 0x15, 0x24,
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||||
0x10, 0x00, 0x00, 0x00, 0xff, 0x00, 0x8e, 0x07, 0x00, 0xe2, 0x0f, 0x00, 0x11, 0x72, 0x1a, 0x14, 0x19, 0x00, 0x00,
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||||
0x00, 0xff, 0xf8, 0x8f, 0x07, 0x00, 0xe2, 0x0f, 0x00, 0xae, 0x7f, 0x1b, 0x10, 0x00, 0x00, 0x00, 0x00, 0x4a, 0x1c,
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||||
0x14, 0x0c, 0x00, 0xe2, 0x03, 0x00, 0x19, 0x78, 0x1d, 0xff, 0x03, 0x00, 0x00, 0x00, 0x24, 0x16, 0x01, 0x00, 0x00,
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||||
0xc4, 0x0f, 0x00, 0x10, 0x72, 0x14, 0x12, 0x1f, 0x00, 0x00, 0x00, 0xff, 0xe0, 0xf5, 0x07, 0x00, 0xe2, 0x0f, 0x08,
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|
||||
0x07, 0x00, 0x00, 0x00, 0xff, 0xe0, 0xf1, 0x0f, 0x00, 0xe2, 0x0f, 0x00, 0x86, 0x79, 0x00, 0x18, 0x14, 0x00, 0x00,
|
||||
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|
||||
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|
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|
||||
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|
||||
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|
||||
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|
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|
||||
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|
||||
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|
||||
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xc0, 0x0f, 0x00, 0x18, 0x79, 0x00, 0x00, 0x00,
|
||||
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xc0, 0x0f, 0x00, 0x18, 0x79, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
|
||||
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|
||||
0x00, 0x00, 0xc0, 0x0f, 0x00, 0x18, 0x79, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xc0,
|
||||
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|
||||
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|
||||
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|
||||
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
|
||||
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|
||||
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
|
||||
0x48, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00,
|
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|
||||
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|
||||
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|
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|
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|
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|
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|
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|
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||||
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|
||||
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|
||||
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|
||||
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|
||||
0x00, 0x00, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x09, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x00, 0x00,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
0x00, 0xc8, 0x38, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00,
|
||||
0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x00, 0x3e, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
|
||||
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
|
||||
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00};
|
||||
unsigned int fused_multihead_attention_fp16_64_64_kernel_sm80_cu_o_len = 16744;
|
||||
} // namespace nvinfer1::plugin::bert
|
||||
+14166
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@@ -0,0 +1,68 @@
|
||||
#
|
||||
# SPDX-FileCopyrightText: Copyright (c) 1993-2025 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.
|
||||
#
|
||||
|
||||
# This folder contains a bunch of source files holding cubins. Since the files are huge, we only want to include and compile them if used.
|
||||
# Usage is indicated by the SM being set in CMAKE_CUDA_ARCHITECTURES.
|
||||
|
||||
function(add_plugin_source_if_exists)
|
||||
foreach(SRC_FILE IN LISTS ARGN)
|
||||
if(EXISTS ${CMAKE_CURRENT_LIST_DIR}/${SRC_FILE})
|
||||
add_plugin_source(${SRC_FILE})
|
||||
endif()
|
||||
endforeach()
|
||||
endfunction()
|
||||
|
||||
foreach(SM IN LISTS BERT_QKV_SUPPORTED_SMS)
|
||||
should_compile_kernel(${SM} SHOULD_COMPILE)
|
||||
if (${SHOULD_COMPILE})
|
||||
# Not every file exists for each SM, so we list all of the candidates and add them if present.
|
||||
add_plugin_source_if_exists(
|
||||
fused_multihead_attention_v2_fp16_64_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_fp16_96_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_fp16_128_32_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_fp16_128_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_fp16_256_32_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_fp16_256_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_fp16_384_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_fp16_512_32_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_fp16_512_64_kernel.sm${SM}.cpp
|
||||
|
||||
fused_multihead_attention_v2_il_int8_64_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_il_int8_96_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_il_int8_128_32_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_il_int8_128_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_il_int8_192_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_il_int8_256_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_il_int8_384_64_kernel.sm${SM}.cpp
|
||||
|
||||
fused_multihead_attention_v2_int8_64_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_int8_96_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_int8_128_32_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_int8_128_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_int8_192_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_int8_256_32_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_int8_256_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_int8_384_64_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_int8_512_32_kernel.sm${SM}.cpp
|
||||
fused_multihead_attention_v2_int8_512_64_kernel.sm${SM}.cpp
|
||||
)
|
||||
endif()
|
||||
endforeach()
|
||||
|
||||
add_plugin_source(
|
||||
fused_multihead_attention_v2.h
|
||||
)
|
||||
+1253
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+3847
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+6107
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+15045
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+3436
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+23828
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+15048
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+2983
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+3800
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+22932
File diff suppressed because it is too large
Load Diff
+14503
File diff suppressed because it is too large
Load Diff
+23281
File diff suppressed because it is too large
Load Diff
+19360
File diff suppressed because it is too large
Load Diff
+21883
File diff suppressed because it is too large
Load Diff
+13705
File diff suppressed because it is too large
Load Diff
+8675
File diff suppressed because it is too large
Load Diff
+1037
File diff suppressed because it is too large
Load Diff
+1053
File diff suppressed because it is too large
Load Diff
+1712
File diff suppressed because it is too large
Load Diff
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