# 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}" } }