-P flag appears to be broken in example README command

[jharlow-intel]

Summary:

It seems as though the -P flag and it's other synonyms break the fft_bench.py script for a particular command given in the README
python fft_bench.py -P -r -t 1 -d float32 -o 5 100000000

Output:

(fft-bench) harlowjo@harlowjo-mobl:~/repositories/IntelPython/fft_benchmark$ python fft_bench.py -P -r -t 1 -d float32 -o 5 100000000
/home/harlowjo/miniconda3/envs/fft-bench/lib/python3.10/site-packages/scipy/__init__.py:146: UserWarning: A NumPy version >=1.16.5 and <1.23.0 is required for this version of SciPy (detected version 1.23.5
  warnings.warn(f"A NumPy version >={np_minversion} and <{np_maxversion}"
TAG: CONDA_DEFAULT_ENV = fft-bench
TAG: numpy.__mkl_version__ = 2023.0.1

prefix,module,function,threads,dtype,size,place,time
Traceback (most recent call last):
  File "/home/harlowjo/repositories/IntelPython/fft_benchmark/fft_bench.py", line 169, in <module>
    perf_times = perf.time_func(func, arr, kwargs, **time_kwargs)
  File "/home/harlowjo/repositories/IntelPython/fft_benchmark/perf.py", line 161, in time_func
    res = func(buf, **kwargs)
  File "/home/harlowjo/miniconda3/envs/fft-bench/lib/python3.10/site-packages/mkl_fft/_scipy_fft_backend.py", line 113, in __ua_function__
    return fn(*args, **kwargs)
TypeError: rfft() got an unexpected keyword argument 'overwrite_x'

Steps to reproduce:

I followed the README instructions nearly identically

1. conda create -n fft-bench -c intel numpy scipy
2. conda activate fft-bench
3. python fft_bench.py -P -r -t 1 -d float32 -o 5 100000000

I noticed I can run the same command without -P and it works.
Running it with --overwrite-x and --in-place caused the same error as above.

Please let me know if I did something wrong with my setup or if you need more info

More info:

    scipy-1.7.3                |  py310h77d8492_8        22.9 MB  intel
    numpy-1.23.5               |  py310h52df89b_7           4 KB  intel
    mkl-2023.1.0               |      intel_46342       197.2 MB  intel
    mkl-service-2.4.0          | py310h75d02e3_15          58 KB  intel
    mkl_fft-1.3.5              | py310h28f0b46_11         260 KB  intel
    mkl_random-1.2.2           | py310h0b06908_51         375 KB  intel
    mkl_umath-0.1.1            | py310h450dca2_61         296 KB  intel

[oleksandr-pavlyk]

The rfft does not provide in-place operation mode. Please do not use -P when compute FFT of real-value floating-point type datasets.