# Copyright 2024, 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_bls" backend: "python" max_batch_size: 16 model_transaction_policy { decoupled: true } input [ { name: "text_input" data_type: TYPE_STRING dims: [ -1 ] }, { name: "decoder_text_input" data_type: TYPE_STRING dims: [ -1 ] optional: true }, { name: "max_tokens" data_type: TYPE_INT32 dims: [ -1 ] }, { name: "bad_words" data_type: TYPE_STRING dims: [ -1 ] optional: true }, { name: "stop_words" data_type: TYPE_STRING dims: [ -1 ] optional: true }, { name: "end_id" data_type: TYPE_INT32 dims: [ 1 ] optional: true }, { name: "pad_id" data_type: TYPE_INT32 dims: [ 1 ] optional: true }, { name: "top_k" data_type: TYPE_INT32 dims: [ 1 ] optional: true }, { name: "top_p" data_type: TYPE_FP32 dims: [ 1 ] optional: true }, { name: "temperature" data_type: TYPE_FP32 dims: [ 1 ] optional: true }, { name: "length_penalty" data_type: TYPE_FP32 dims: [ 1 ] optional: true }, { name: "repetition_penalty" data_type: TYPE_FP32 dims: [ 1 ] optional: true }, { name: "min_length" data_type: TYPE_INT32 dims: [ 1 ] optional: true }, { name: "presence_penalty" data_type: TYPE_FP32 dims: [ 1 ] optional: true }, { name: "frequency_penalty" data_type: TYPE_FP32 dims: [ 1 ] optional: true }, { name: "random_seed" data_type: TYPE_UINT64 dims: [ 1 ] optional: true }, { name: "return_log_probs" data_type: TYPE_BOOL dims: [ 1 ] reshape: { shape: [ ] } optional: true }, { name: "return_context_logits" data_type: TYPE_BOOL dims: [ 1 ] reshape: { shape: [ ] } optional: true }, { name: "return_generation_logits" data_type: TYPE_BOOL dims: [ 1 ] reshape: { shape: [ ] } optional: true }, { name: "beam_width" data_type: TYPE_INT32 dims: [ 1 ] optional: true }, { name: "stream" data_type: TYPE_BOOL dims: [ 1 ] optional: true }, { name: "prompt_embedding_table" data_type: TYPE_FP16 dims: [ -1, -1 ] optional: true }, { name: "prompt_vocab_size" data_type: TYPE_INT32 dims: [ 1 ] optional: true }, { name: "embedding_bias_words" data_type: TYPE_STRING dims: [ -1 ] optional: true }, { name: "embedding_bias_weights" data_type: TYPE_FP32 dims: [ -1 ] optional: true }, { name: "num_draft_tokens", data_type: TYPE_INT32, dims: [ 1 ] optional: true }, { name: "use_draft_logits", data_type: TYPE_BOOL, dims: [ 1 ] reshape: { shape: [ ] } optional: true } ] output [ { name: "text_output" data_type: TYPE_STRING dims: [ -1 ] }, { name: "cum_log_probs" data_type: TYPE_FP32 dims: [ -1 ] }, { name: "output_log_probs" data_type: TYPE_FP32 dims: [ -1, -1 ] }, { name: "context_logits" data_type: TYPE_FP32 dims: [ -1, -1 ] }, { name: "generation_logits" data_type: TYPE_FP32 dims: [ -1, -1, -1 ] } ] parameters: { key: "accumulate_tokens" value: { string_value: "${accumulate_tokens}" } } parameters: { key: "tensorrt_llm_model_name" value: { string_value: "${tensorrt_llm_model_name}" } } parameters: { key: "tensorrt_llm_draft_model_name" value: { string_value: "${tensorrt_llm_draft_model_name}" } } instance_group [ { count: 1 kind : KIND_CPU } ]