File size: 1,744 Bytes
bbc9069 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 |
#!/bin/bash
# Stage-2: Prompt a pretrained language model to generate the corresponding response
# The input contains prompts, current dialogue context, and generated knowledge in Stage-1
# The output is the corresponding response.
# The size of the pretrained language model is 357M
WORLD_SIZE=8
DISTRIBUTED_ARGS="--nproc_per_node $WORLD_SIZE \
--nnodes 1 \
--node_rank 0 \
--master_addr localhost \
--master_port 6000"
CHECKPOINT_PATH=<PATH_OF_LANGUAGE_MODEL> (e.g., /357m)
VOCAB_PATH=<PATH_OF_VOCAB_FILE> (e.g., /gpt2-vocab.json)
MERGE_PATH=<PATH_OF_MERGE_FILE> (e.g., /gpt2-merges.txt)
INPUT_PATH=<PATH_OF_INPUT_TEST_DATA_FILE> (e.g., /testseen_processed.txt)
PROMPT_PATH=<PATH_OF_RESPONSE_GENERATION_PROMPTS> \
(e.g., /response_prompts.txt)
OUTPUT_PATH=<PATH_OF_OUTPUT_GENERATION_FILE> \
(e.g., /output_testseen_response_generations.txt)
python -m torch.distributed.launch $DISTRIBUTED_ARGS ./tasks/msdp/main.py \
--num-layers 24 \
--hidden-size 1024 \
--num-attention-heads 16 \
--seq-length 2048 \
--max-position-embeddings 2048 \
--micro-batch-size 1 \
--vocab-file ${VOCAB_PATH} \
--merge-file ${MERGE_PATH} \
--load ${CHECKPOINT_PATH} \
--fp16 \
--DDP-impl torch \
--tokenizer-type GPT2BPETokenizer \
--sample-input-file ${INPUT_PATH} \
--sample-output-file ${OUTPUT_PATH} \
--prompt-file ${PROMPT_PATH} \
--prompt-type response \
--num-prompt-examples 20 \
--task MSDP-PROMPT
# NOTE: If you use api for the model generation, please use
# the "--api-prompt" flag (setting this value as True).
|