numpy.show_config

Here are the examples of the python api numpy.show_config taken from open source projects. By voting up you can indicate which examples are most useful and appropriate.

3 Examples 7

Example 1

Project: attention-lvcsr Source File: check_blas.py
def execute(execute=True, verbose=True, M=2000, N=2000, K=2000,
            iters=10, order='C'):
    """
    :param execute: If True, execute a Theano function that should call gemm.
    :param verbose: If True, will print some Theano flags and env variables.
    :param M,N,K: The M,N,K size used by gemm.
    :param iters: The number of calls to gemm to do.

    :return: a tuple (execution time,
                      str that represents the implementation used)
    """

    if verbose:
        print('Some Theano flags:')
        print('    blas.ldflags=', theano.config.blas.ldflags)
        print('    compiledir=', theano.config.compiledir)
        print('    floatX=', theano.config.floatX)
        print('    device=', theano.config.device)
        print('Some OS information:')
        print('    sys.platform=', sys.platform)
        print('    sys.version=', sys.version)
        print('    sys.prefix=', sys.prefix)
        print('Some environment variables:')
        print('    MKL_NUM_THREADS=', os.getenv('MKL_NUM_THREADS'))
        print('    OMP_NUM_THREADS=', os.getenv('OMP_NUM_THREADS'))
        print('    GOTO_NUM_THREADS=', os.getenv('GOTO_NUM_THREADS'))
        print()
        print('Numpy config: (used when the Theano flag'
              ' "blas.ldflags" is empty)')
        numpy.show_config()
        print('Numpy dot module:', numpy.dot.__module__)
        print('Numpy location:', numpy.__file__)
        print('Numpy version:', numpy.__version__)
        if (theano.config.device.startswith("gpu") or
                theano.config.init_gpu_device.startswith("gpu")):
            print('nvcc version:')
            subprocess.call((theano.sandbox.cuda.nvcc_compiler.nvcc_path,
                             "--version"))
            print()

    a = theano.shared(numpy.ones((M, N), dtype=theano.config.floatX,
                                 order=order))
    b = theano.shared(numpy.ones((N, K), dtype=theano.config.floatX,
                                 order=order))
    c = theano.shared(numpy.ones((M, K), dtype=theano.config.floatX,
                                 order=order))
    f = theano.function([], updates=[(c, 0.4 * c + .8 * T.dot(a, b))])

    if any([x.op.__class__.__name__ == 'Gemm' for x in
            f.maker.fgraph.toposort()]):
        c_impl = [hasattr(thunk, 'cthunk')
                  for node, thunk in zip(f.fn.nodes, f.fn.thunks)
                  if node.op.__class__.__name__ == "Gemm"]
        assert len(c_impl) == 1
        if c_impl[0]:
            impl = 'CPU (with direct Theano binding to blas)'
        else:
            impl = 'CPU (without direct Theano binding to blas but with numpy/scipy binding to blas)'
    elif any([x.op.__class__.__name__ == 'GpuGemm' for x in
              f.maker.fgraph.toposort()]):
        impl = 'GPU'
    else:
        impl = 'ERROR, unable to tell if Theano used the cpu or the gpu:\n'
        impl += str(f.maker.fgraph.toposort())

    t0 = 0
    t1 = -1

    if execute:
        sync = (hasattr(theano, "sandbox") and
                hasattr(theano.sandbox, "cuda") and
                theano.sandbox.cuda.cuda_available)
        t0 = time.time()
        for i in range(iters):
            f()
        if sync:
            theano.sandbox.cuda.synchronize()
        t1 = time.time()
    return t1 - t0, impl

Example 2

Project: robothon Source File: utils.py
Function: get_include
def get_include():
    """
    Return the directory that contains the numpy \\*.h header files.

    Extension modules that need to compile against numpy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d

Example 3

Project: AWS-Lambda-ML-Microservice-Skeleton Source File: utils.py
Function: get_include
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d