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# Copyright 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of NVIDIA CORPORATION nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
name: "tensorrt_llm"
backend: "tensorrtllm"
max_batch_size: 128
model_transaction_policy {
decoupled: True
}
input [
{
name: "input_ids"
data_type: TYPE_INT32
dims: [ -1 ]
},
{
name: "input_lengths"
data_type: TYPE_INT32
dims: [ 1 ]
reshape: { shape: [ ] }
},
{
name: "request_output_len"
data_type: TYPE_UINT32
dims: [ 1 ]
},
{
name: "end_id"
data_type: TYPE_UINT32
dims: [ 1 ]
reshape: { shape: [ ] }
optional: true
},
{
name: "pad_id"
data_type: TYPE_UINT32
dims: [ 1 ]
reshape: { shape: [ ] }
optional: true
},
{
name: "beam_width"
data_type: TYPE_UINT32
dims: [ 1 ]
reshape: { shape: [ ] }
optional: true
},
{
name: "temperature"
data_type: TYPE_FP32
dims: [ 1 ]
reshape: { shape: [ ] }
optional: true
},
{
name: "runtime_top_k"
data_type: TYPE_UINT32
dims: [ 1 ]
reshape: { shape: [ ] }
optional: true
},
{
name: "runtime_top_p"
data_type: TYPE_FP32
dims: [ 1 ]
reshape: { shape: [ ] }
optional: true
},
{
name: "len_penalty"
data_type: TYPE_FP32
dims: [ 1 ]
reshape: { shape: [ ] }
optional: true
},
{
name: "repetition_penalty"
data_type: TYPE_FP32
dims: [ 1 ]
reshape: { shape: [ ] }
optional: true
},
{
name: "min_length"
data_type: TYPE_UINT32
dims: [ 1 ]
reshape: { shape: [ ] }
optional: true
},
{
name: "presence_penalty"
data_type: TYPE_FP32
dims: [ 1 ]
reshape: { shape: [ ] }
optional: true
},
{
name: "random_seed"
data_type: TYPE_UINT64
dims: [ 1 ]
reshape: { shape: [ ] }
optional: true
},
{
name: "stop"
data_type: TYPE_BOOL
dims: [ 1 ]
optional: true
},
{
name: "streaming"
data_type: TYPE_BOOL
dims: [ 1 ]
optional: true
}
]
output [
{
name: "output_ids"
data_type: TYPE_INT32
dims: [ -1, -1 ]
}
]
instance_group [
{
count: 1
kind : KIND_CPU
}
]
parameters: {
key: "max_beam_width"
value: {
string_value: "1"
}
}
parameters: {
key: "FORCE_CPU_ONLY_INPUT_TENSORS"
value: {
string_value: "no"
}
}
parameters: {
key: "gpt_model_type"
value: {
string_value: "inflight_fused_batching"
}
}
parameters: {
key: "gpt_model_path"
value: {
string_value: "${gpt_model_path}"
}
}
parameters: {
key: "max_tokens_in_paged_kv_cache"
value: {
string_value: "${max_tokens_in_paged_kv_cache}"
}
}
parameters: {
key: "batch_scheduler_policy"
value: {
string_value: "max_utilization"
}
}
parameters: {
key: "kv_cache_free_gpu_mem_fraction"
value: {
string_value: "0.9"
}
}
parameters: {
key: "exclude_input_in_output"
value: {
string_value: "true"
}
}
parameters: {
key: "max_num_sequences"
value: {
string_value: "${max_num_sequences}"
}
}
parameters: {
key: "enable_trt_overlap"
value: {
string_value: "${enable_trt_overlap}"
}
}
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