#!/usr/bin/env python # Copyright (c) 2020, NVIDIA CORPORATION. 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. import argparse import sys import numpy as np import tritonclient.grpc as grpcclient if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument( "-v", "--verbose", action="store_true", required=False, default=False, help="Enable verbose output", ) parser.add_argument( "-u", "--url", type=str, required=False, default="10.95.163.43:8001", help="Inference server URL. Default is localhost:8001.", ) parser.add_argument( "-s", "--ssl", action="store_true", required=False, default=False, help="Enable SSL encrypted channel to the server", ) parser.add_argument( "-t", "--client-timeout", type=float, required=False, default=None, help="Client timeout in seconds. Default is None.", ) parser.add_argument( "-r", "--root-certificates", type=str, required=False, default=None, help="File holding PEM-encoded root certificates. Default is None.", ) parser.add_argument( "-p", "--private-key", type=str, required=False, default=None, help="File holding PEM-encoded private key. Default is None.", ) parser.add_argument( "-x", "--certificate-chain", type=str, required=False, default=None, help="File holding PEM-encoded certificate chain. Default is None.", ) parser.add_argument( "-C", "--grpc-compression-algorithm", type=str, required=False, default=None, help="The compression algorithm to be used when sending request to server. Default is None.", ) FLAGS = parser.parse_args() try: # triton_client = grpcclient.InferenceServerClient( # url=FLAGS.url, # verbose=FLAGS.verbose, # ssl=FLAGS.ssl, # root_certificates=FLAGS.root_certificates, # private_key=FLAGS.private_key, # certificate_chain=FLAGS.certificate_chain, # ) triton_client = grpcclient.InferenceServerClient( url=FLAGS.url, # verbose=FLAGS.verbose, verbose = True, ssl=FLAGS.ssl, root_certificates=None, private_key=None, certificate_chain=None, ) except Exception as e: print("channel creation failed: " + str(e)) sys.exit() model_name = "ensemble_mllm" img_url = f"https://s3plus.sankuai.com/automl-pkgs/0000.jpeg" # img_url = f"https://s3plus.sankuai.com/automl-pkgs/0003.jpeg" text = f"详细描述一下这张图片" # Infer inputs = [] img_url_bytes = img_url.encode("utf-8") img_url_bytes = np.array(img_url_bytes, dtype=bytes) img_url_bytes = img_url_bytes.reshape([1, -1]) inputs.append(grpcclient.InferInput('IMAGE_URL', img_url_bytes.shape, "BYTES")) inputs[0].set_data_from_numpy(img_url_bytes) text_bytes = text.encode("utf-8") text_bytes = np.array(text_bytes, dtype=bytes) text_bytes = text_bytes.reshape([1, -1]) # text_input = np.expand_dims(text_bytes, axis=0) text_input = text_bytes inputs.append(grpcclient.InferInput('TEXT', text_input.shape, "BYTES")) inputs[1].set_data_from_numpy(text_input) outputs = [] outputs.append(grpcclient.InferRequestedOutput("OUTPUT")) # Test with outputs results = triton_client.infer( model_name=model_name, inputs=inputs, outputs=outputs, client_timeout=None, #FLAGS.client_timeout, # headers={"test": "1"}, compression_algorithm=None, #FLAGS.grpc_compression_algorithm, ) statistics = triton_client.get_inference_statistics(model_name=model_name) print(statistics) if len(statistics.model_stats) != 1: print("FAILED: Inference Statistics") sys.exit(1) # Get the output arrays from the results output_data = results.as_numpy("OUTPUT") result_str = output_data[0][0].decode('utf-8') print("OUTPUT: "+ result_str) # # Test with no outputs # results = triton_client.infer( # model_name=model_name, # inputs=inputs, # outputs=None, # compression_algorithm=FLAGS.grpc_compression_algorithm, # ) # # Get the output arrays from the results # output0_data = results.as_numpy("OUTPUT0") # output1_data = results.as_numpy("OUTPUT1") # for i in range(16): # print( # str(input0_data[0][i]) # + " + " # + str(input1_data[0][i]) # + " = " # + str(output0_data[0][i]) # ) # print( # str(input0_data[0][i]) # + " - " # + str(input1_data[0][i]) # + " = " # + str(output1_data[0][i]) # ) # if (input0_data[0][i] + input1_data[0][i]) != output0_data[0][i]: # print("sync infer error: incorrect sum") # sys.exit(1) # if (input0_data[0][i] - input1_data[0][i]) != output1_data[0][i]: # print("sync infer error: incorrect difference") # sys.exit(1) print("PASS: infer")