o }oi@s\dZzddlmZddlmZmZWn eydZYnwddlmZGdddeZ dS) T) ModelConfig)Triton TritonConfigF) DeployBasec sreZdZdZ          dd ed ed edededef fdd ZddZddZddZ ddZ Z S)DeployPyTritona Deploys any models to Triton Inference Server that implements ITritonDeployable interface in nemo.deploy. Example: from nemo.deploy import DeployPyTriton, NemoQueryLLM from nemo.export.tensorrt_llm import TensorRTLLM trt_llm_exporter = TensorRTLLM(model_dir="/path/for/model/files") trt_llm_exporter.export( nemo_checkpoint_path="/path/for/nemo/checkpoint", model_type="llama", tensor_parallelism_size=1, ) nm = DeployPyTriton(model=trt_llm_exporter, triton_model_name="model_name", http_port=8000) nm.deploy() nm.run() nq = NemoQueryLLM(url="localhost", model_name="model_name") prompts = ["hello, testing GPT inference", "another GPT inference test?"] output = nq.query_llm(prompts=prompts, max_output_len=100) print("prompts: ", prompts) print("") print("output: ", output) print("") prompts = ["Give me some info about Paris", "Do you think Londan is a good city to visit?", "What do you think about Rome?"] output = nq.query_llm(prompts=prompts, max_output_len=250) print("prompts: ", prompts) print("") print("output: ", output) print("") N@A0.0.0.0TFrtriton_model_nametriton_model_versioncheckpoint_pathmax_batch_size http_port grpc_portc s(tj||||||||| | | | d dS)aH A nemo checkpoint or model is expected for serving on Triton Inference Server. Args: triton_model_name (str): Name for the service triton_model_version(int): Version for the service checkpoint_path (str): path of the nemo file model (ITritonDeployable): A model that implements the ITritonDeployable from nemo.deploy import ITritonDeployable max_batch_size (int): max batch size port (int) : port for the Triton server address (str): http address for Triton server to bind. ) r r rmodelrrraddress allow_grpc allow_http streamingpytriton_log_verboseN)super__init__) selfr r rrrrrrrrrr __class__O/home/ubuntu/.local/lib/python3.10/site-packages/nemo/deploy/deploy_pytriton.pyr>s zDeployPyTriton.__init__c Cs|z`|jr4t|j|j|j|jd}t|d|_|jj |j |j |j j |j j|j jtdddWdSt|j|j|j|j|j|jd}t|d|_|jj |j |j |j j|j j|j jt|jddWdSty~}zd|_t|WYd}~dSd}~ww) z@ Deploys any models to Triton Inference Server. ) log_verboserr grpc_address)configT) decoupled) model_name model_version infer_funcinputsoutputsr!) http_addressrr rrr)rN)_init_nemo_modelrrrrrrrtritonbindr r rtriton_infer_fn_streamingget_triton_inputget_triton_outputrrrtriton_infer_fnr Exceptionprint)r triton_configerrrdeployisP      zDeployPyTriton.deployc CsX|jdur tdz|jWdSty+}zd|_t|WYd}~dSd}~ww)zE Starts serving the model and waits for the requests Ndeploy should be called first.)r*r0server1)rr3rrrr6s zDeployPyTriton.servecC |jdur td|jdS)z: Starts serving the model asynchronously. Nr5)r*r0runrrrrr8 zDeployPyTriton.runcCr7)z* Stops serving the model. Nr5)r*r0stopr9rrrr;r:zDeployPyTriton.stop) rNNrr r r TTFr) __name__ __module__ __qualname____doc__strintrr4r6r8r; __classcell__rrrrrs<&+/ rN) use_pytritonpytriton.model_configrpytriton.tritonrrr0nemo.deploy.deploy_baserrrrrrs