GaP-NMF short benchmark scripts for Python and Julia.

gap_benchmark.jl

push!(LOAD_PATH, ".")
using BNMF
using PyCall

# bp_nmf のコードと比較するために、librosaを使う
@pyimport librosa

function spectrogram()
    x, ss = librosa.load("test.wav", sr=16000)
    X = abs(librosa.stft(x, n_fft=1024, hop_length=256))
    return X
end

function test_gap(X)
  srand(98765)
  p = GaPNMF(X, K=100)
  fit!(p, epochs=100, verbose=true)

  nothing
end

function benchmark(N)
    X = spectrogram()
    elapsed = Array(Float64, N)
    for i=1:N
        tic()
        test_gap(X)
        elapsed[i] = toc()
    end

    println("Mean elapsed time: $(mean(elapsed))")
end

benchmark(10)
versioninfo()

gap_benchmark.py

# -*- coding: utf-8 -*-
import gap_nmf
import librosa
import numpy as np
import scipy
import time


def spectrogram():
    x, _ = librosa.load('test.wav', sr=16000)
    X = np.abs(librosa.stft(x, n_fft=1024, hop_length=256))
    return X


def test_gap(X):
    obj = gap_nmf.GaP_NMF(X, K=100, seed=98765)
    score = -np.inf
    for i in range(100):
        obj.update()
        # obj.figures()
        lastscore = score
        score = obj.bound()
        improvement = (score - lastscore) / np.abs(lastscore)
        print('iteration {}: bound = {:.2f} ({:.5f} improvement)'.format(
            i, score, improvement))


def benchmark(N=100):
    X = spectrogram()
    elapsed = []
    for n in range(N):
        s = time.clock()
        test_gap(X)
        e = time.clock() - s
        elapsed.append(e)
        print(e)

    print("Mean elapsed time:", np.mean(elapsed))


benchmark(10)
np.show_config()
scipy.show_config()
librosa.show_versions()

今の自分ならjuliaのコードをめっちゃ速くできる自信があるけど、（続く

Ubuntu 16.04

Julia

Mean elapsed time: 14.6447493191

Julia Version 0.7.0-DEV.565
Commit d3db312* (2017-06-13 07:52 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: Intel(R) Core(TM) i7-7700K CPU @ 4.20GHz
  WORD_SIZE: 64
  BLAS: libopenblas (NO_LAPACKE DYNAMIC_ARCH NO_AFFINITY Prescott)
  LAPACK: liblapack
  LIBM: libopenlibm
  LLVM: libLLVM-4.0.0 (ORCJIT, skylake)

Python

Mean elapsed time: 33.2673037
blas_mkl_info:
    libraries = ['mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'iomp5', 'pthread']
    library_dirs = ['/home/ryuichi/anaconda3/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/home/ryuichi/anaconda3/include']
blas_opt_info:
    libraries = ['mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'iomp5', 'pthread']
    library_dirs = ['/home/ryuichi/anaconda3/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/home/ryuichi/anaconda3/include']
lapack_mkl_info:
    libraries = ['mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'iomp5', 'pthread']
    library_dirs = ['/home/ryuichi/anaconda3/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/home/ryuichi/anaconda3/include']
lapack_opt_info:
    libraries = ['mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'iomp5', 'pthread']
    library_dirs = ['/home/ryuichi/anaconda3/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/home/ryuichi/anaconda3/include']
lapack_mkl_info:
    libraries = ['mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'iomp5', 'pthread']
    library_dirs = ['/home/ryuichi/anaconda3/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/home/ryuichi/anaconda3/include']
lapack_opt_info:
    libraries = ['mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'iomp5', 'pthread']
    library_dirs = ['/home/ryuichi/anaconda3/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/home/ryuichi/anaconda3/include']
blas_mkl_info:
    libraries = ['mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'iomp5', 'pthread']
    library_dirs = ['/home/ryuichi/anaconda3/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/home/ryuichi/anaconda3/include']
blas_opt_info:
    libraries = ['mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'iomp5', 'pthread']
    library_dirs = ['/home/ryuichi/anaconda3/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/home/ryuichi/anaconda3/include']
INSTALLED VERSIONS
------------------
python: 3.6.0 |Anaconda custom (64-bit)| (default, Dec 23 2016, 12:22:00) 
[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)]

librosa: 0.5.1

audioread: installed, no version number available
numpy: 1.12.1
scipy: 0.19.0
sklearn: 0.18.1
joblib: 0.11
decorator: 4.0.11
six: 1.10.0
resampy: 0.1.5

numpydoc: installed, no version number available
sphinx: 1.5.1
sphinx_rtd_theme: 0.2.4
sphinxcontrib.versioning: 2.2.1
matplotlib: 2.0.0
numba: 0.32.0