Provide tiny wrapper over pytorch ThroughputBenchmark

🚀 Feature

PyTorch utils module provides ThroughputBenchmark since 1.2.0

 >>> from torch.utils import ThroughputBenchmark
>>> bench = ThroughputBenchmark(my_module)
>>> # Pre-populate benchmark's data set with the inputs
>>> for input in inputs:
    # Both args and kwargs work, same as any PyTorch Module / ScriptModule
    bench.add_input(input[0], x2=input[1])
>>> # Inputs supplied above are randomly used during the execution
>>> stats = bench.benchmark(
                num_calling_threads=4,
                num_warmup_iters = 100,
                num_iters = 1000,
            )
>>> print("Avg latency (ms): {}".format(stats.latency_avg_ms))
>>> print("Number of iterations: {}".format(stats.num_iters))

It would be interesting to provide a tiny wrapper over this to simplify usage with ignite.

Start by reading PyTorch's linked torch.utils ThroughputBenchmark API and compare it with Ignite's existing utility or metric entry points. Define the smallest wrapper interface that fits Ignite usage, then verify that it supports the benchmark inputs and returns latency and iteration statistics as shown; the issue does not name a target file or test.