[Feature Request]: Add metrics definitions to RunInference documentation

### What would you like to happen?

Add the following metrics definitions to RunInference documentation.

num_inferences
- The cumulative count of all samples being passed to RunInference. I.e. total sum of examples across all batches. This should increase monotonically.

inference_request_batch_size
- The number of samples in a particular batch of examples (created from beam.BatchElements) to be passed to run_inference(). This will vary over time depending on the dynamic batching decision of BatchElements().

inference_request_batch_byte_size
- The size, in bytes, of all elements for all samples in a particular batch of examples (created from beam.BatchElements) to be passed to run_inference(). This will vary over time depending on the dynamic batching decision of BatchElements(), and the particular values/dtypes of the elements.

inference_batch_latency_micro_secs
- The time, in microseconds, that it takes to perform the inference on the batch of examples. i.e. the time to call model_handler.run_inference(). This will vary over time depending on the dynamic batching decision of BatchElements(), and the particular values/dtypes of the elements.

model_byte_size
- The size, in bytes, of memory that the model takes for loading and initialization. i.e. the increase in memory usage from calling model_handler.load_model()

load_model_latency_milli_secs
- The time, in milliseconds, that it takes to load and initialize the model. i.e. the time it takes to call model_handler.load_model()

### Issue Priority

Priority: 2

### Issue Component

Component: run-inference