ensemble/config.pbtxt

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name: "ensemble"
platform: "ensemble"
max_batch_size: 16
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 ]
    optional: true
  },
  {
    name: "return_context_logits"
    data_type: TYPE_BOOL
    dims: [ 1 ]
    optional: true
  },
  {
    name: "return_generation_logits"
    data_type: TYPE_BOOL
    dims: [ 1 ]
    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
  }
]
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 ]
  }
]
ensemble_scheduling {
  step [
    {
      model_name: "preprocessing"
      model_version: -1
      input_map {
        key: "QUERY"
        value: "text_input"
      }
      input_map {
        key: "DECODER_QUERY"
        value: "decoder_text_input"
      }
      input_map {
        key: "REQUEST_OUTPUT_LEN"
        value: "max_tokens"
      }
      input_map {
        key: "BAD_WORDS_DICT"
        value: "bad_words"
      }
      input_map {
        key: "STOP_WORDS_DICT"
        value: "stop_words"
      }
      input_map {
        key: "EMBEDDING_BIAS_WORDS"
        value: "embedding_bias_words"
      }
      input_map {
        key: "EMBEDDING_BIAS_WEIGHTS"
        value: "embedding_bias_weights"
      }
      input_map {
        key: "END_ID"
        value: "end_id"
      }
      input_map {
        key: "PAD_ID"
        value: "pad_id"
      }
      output_map {
        key: "REQUEST_INPUT_LEN"
        value: "_REQUEST_INPUT_LEN"
      }
      output_map {
        key: "INPUT_ID"
        value: "_INPUT_ID"
      }
      output_map {
        key: "REQUEST_DECODER_INPUT_LEN"
        value: "_REQUEST_DECODER_INPUT_LEN"
      }
      output_map {
        key: "DECODER_INPUT_ID"
        value: "_DECODER_INPUT_ID"
      }
      output_map {
        key: "REQUEST_OUTPUT_LEN"
        value: "_REQUEST_OUTPUT_LEN"
      }
      output_map {
        key: "STOP_WORDS_IDS"
        value: "_STOP_WORDS_IDS"
      }
      output_map {
        key: "BAD_WORDS_IDS"
        value: "_BAD_WORDS_IDS"
      }
      output_map {
        key: "EMBEDDING_BIAS"
        value: "_EMBEDDING_BIAS"
      }
      output_map {
        key: "OUT_END_ID"
        value: "_PREPROCESSOR_END_ID"
      }
      output_map {
        key: "OUT_PAD_ID"
        value: "_PREPROCESSOR_PAD_ID"
      }
    },
    {
      model_name: "tensorrt_llm"
      model_version: -1
      input_map {
        key: "input_ids"
        value: "_INPUT_ID"
      }
      input_map {
        key: "decoder_input_ids"
        value: "_DECODER_INPUT_ID"
      }
      input_map {
        key: "input_lengths"
        value: "_REQUEST_INPUT_LEN"
      }
      input_map {
        key: "decoder_input_lengths"
        value: "_REQUEST_DECODER_INPUT_LEN"
      }
      input_map {
        key: "request_output_len"
        value: "_REQUEST_OUTPUT_LEN"
      }
      input_map {
          key: "end_id"
          value: "_PREPROCESSOR_END_ID"
      }
      input_map {
          key: "pad_id"
          value: "_PREPROCESSOR_PAD_ID"
      }
      input_map {
          key: "embedding_bias"
          value: "_EMBEDDING_BIAS"
      }
      input_map {
          key: "runtime_top_k"
          value: "top_k"
      }
      input_map {
          key: "runtime_top_p"
          value: "top_p"
      }
      input_map {
          key: "temperature"
          value: "temperature"
      }
      input_map {
          key: "len_penalty"
          value: "length_penalty"
      }
      input_map {
          key: "repetition_penalty"
          value: "repetition_penalty"
      }
      input_map {
          key: "min_length"
          value: "min_length"
      }
      input_map {
          key: "presence_penalty"
          value: "presence_penalty"
      }
      input_map {
          key: "frequency_penalty"
          value: "frequency_penalty"
      }
      input_map {
          key: "random_seed"
          value: "random_seed"
      }
      input_map {
          key: "return_log_probs"
          value: "return_log_probs"
      }
      input_map {
          key: "return_context_logits"
          value: "return_context_logits"
      }
      input_map {
          key: "return_generation_logits"
          value: "return_generation_logits"
      }
      input_map {
          key: "beam_width"
          value: "beam_width"
      }
      input_map {
          key: "streaming"
          value: "stream"
      }
      input_map {
        key: "prompt_embedding_table"
        value: "prompt_embedding_table"
      }
      input_map {
        key: "prompt_vocab_size"
        value: "prompt_vocab_size"
      }
      input_map {
        key: "stop_words_list"
        value: "_STOP_WORDS_IDS"
      }
      input_map {
        key: "bad_words_list"
        value: "_BAD_WORDS_IDS"
      }
      output_map {
        key: "output_ids"
        value: "_TOKENS_BATCH"
      }
      output_map {
        key: "sequence_length"
        value: "_SEQUENCE_LENGTH"
      },
      output_map {
        key: "cum_log_probs"
        value: "_CUM_LOG_PROBS"
      }
      output_map {
        key: "output_log_probs"
        value: "_OUTPUT_LOG_PROBS"
      },
      output_map {
        key: "context_logits"
        value: "_CONTEXT_LOGITS"
      },
      output_map {
        key: "generation_logits"
        value: "_GENERATION_LOGITS"
      }
    },
    {
      model_name: "postprocessing"
      model_version: -1
      input_map {
        key: "TOKENS_BATCH"
        value: "_TOKENS_BATCH"
      }
      input_map {
        key: "CUM_LOG_PROBS"
        value: "_CUM_LOG_PROBS"
      }
      input_map {
        key: "OUTPUT_LOG_PROBS"
        value: "_OUTPUT_LOG_PROBS"
      }
      input_map {
        key: "CONTEXT_LOGITS"
        value: "_CONTEXT_LOGITS"
      }
      input_map {
        key: "GENERATION_LOGITS"
        value: "_GENERATION_LOGITS"
      }
      input_map {
        key: "SEQUENCE_LENGTH"
        value: "_SEQUENCE_LENGTH"
      }
      output_map {
        key: "OUTPUT"
        value: "text_output"
      }
      output_map {
        key: "OUT_OUTPUT_LOG_PROBS"
        value: "output_log_probs"
      }
      output_map {
        key: "OUT_CUM_LOG_PROBS"
        value: "cum_log_probs"
      }
      output_map {
        key: "OUT_CONTEXT_LOGITS"
        value: "context_logits"
      }
      output_map {
        key: "OUT_GENERATION_LOGITS"
        value: "generation_logits"
      }
    }
  ]
}