Handle 0 dimension output for generate endpoint

[krishung5]

For the TRT-LLM backend, it is possible that the output tensor has the 0 dim shape if the end token is predicted at the first step. This PR fixed the handle for 0 dim output, and added test case for it.

Before the fix, when using generate/generate_stream endpoint for zero dim tensors:
generate

root@a2826b5-lcedt:/opt/tritonserver/tensorrtllm_backend# curl -X POST localhost:8000/v2/models/ensemble/generate --data-binary @sample.txt
{"error":"attempt to access non-existing array index '0'"}

generate_stream

root@a2826b5-lcedt:/opt/tritonserver/tensorrtllm_backend# curl -X POST localhost:8000/v2/models/ensemble/generate_stream --data-binary @sample
.txt
data: {"error":"attempt to access non-existing array index '0'"}

After the fix:
generate

root@a2826b5-lcedt:/opt/tritonserver/tensorrtllm_backend# curl -X POST localhost:8000/v2/models/ensemble/generate --data-binary @sample.txt
{"context_logits":0.0,"cum_log_probs":0.0,"generation_logits":0.0,"model_name":"ensemble","model_version":"1","output_log_probs":[],"sequence_end":false,"sequence_id":0,"sequence_start":false,"text_output":[]}

generate_stream

root@a2826b5-lcedt:/opt/tritonserver/tensorrtllm_backend# curl -X POST localhost:8000/v2/models/ensemble/generate_stream --data-binary @sample
.txt
data: {"context_logits":0.0,"cum_log_probs":0.0,"generation_logits":0.0,"model_name":"ensemble","model_version":"1","output_log_probs":[],"sequence_end":false,"sequence_id":0,"sequence_start":false,"text_output":[]}

sample.txt looks like this:

{
  "text_input": "I have to work on an AI project. So now, I will explain the project I have to do first :The data is divided into three parts. \n\n1. Training data: train.csv \n2. Test data: test.csv \n3. Submission file: sample\\_submission.csv \n\nThe train.csv file consists of 3 columns of id, text and label, and the test.csv file consists of 2 columns of id and text. The sample\\_submission.csv file consists of id and label columns second: There are 8 labels in total. The data is news article. I want to make a model to classify this. First of all, I want to know the number of classes in the train.csv file. I mean, I want to make sure the class is in balance. I'm talking about EDA. Can you make this code first? and at this code please add about Visualization and also printing each class count.",
  "max_tokens": 1024,
  "bad_words": "",
  "stop_words": "",
  "end_id": 40
}