U f{j/@sddlZddlmZmZmZmZmZmZm Z m Z da dddZ ed dd Z ed!d d Zed"d d Zd#ddZddZddZd$ddZd%ddZe d&ddZd'ddZdS)(N) sizeof_fmtlogger get_configwarn_explain_exceptionverbosefill_doc _check_optionF availablecCs>tstdd}n$ddl}|jjtddd|}t|S)aGet the amount of free memory for CUDA operations. Parameters ---------- kind : str Can be "available" or "total". Returns ------- memory : str The amount of available or total memory as a human-readable string. z+CUDA not enabled, returning zero for memoryrNr)r total) _cuda_capablercupycudaruntimeZ memGetInfodictr)kindZmemrrG/var/www/html/bwave/python/venv/lib/python3.8/site-packages/mne/cuda.pyget_cuda_memorys rcCstrdS|s,tdddkr,tddSdaz ddl}Wntk rZtdYdSXttd d }zt ||Wn$t k rtd t YdSXd atd t dS)aPInitialize CUDA functionality. This function attempts to load the necessary interfaces (hardware connectivity) to run CUDA-based filtering. This function should only need to be run once per session. If the config var (set via mne.set_config or in ENV) MNE_USE_CUDA == 'true', this function will be executed when the first CUDA setup is performed. If this variable is not set, this function can be manually executed. Parameters ---------- ignore_config : bool If True, ignore the config value MNE_USE_CUDA and force init. %(verbose)s N MNE_USE_CUDAfalsetruez3CUDA not enabled in config, skipping initializationFrz'module cupy not found, CUDA not enabledZMNE_CUDA_DEVICE0zPso CUDA device could be initialized, likely a hardware error, CUDA not enabled%sTz&Enabling CUDA with %s available memory) r rlowerrinfor ImportErrorrint_set_cuda_device Exceptionrr)Z ignore_configrr device_idrrr init_cuda$s.  r!cCs@trt||n,tdddkr4tt||ntddS)zSet the CUDA device temporarily for the current session. Parameters ---------- device_id : int Numeric ID of the CUDA-capable device you want MNE-Python to use. %(verbose)s rrrzCould not set CUDA device because CUDA is not enabled; either run mne.cuda.init_cuda() first, or set the MNE_USE_CUDA config variable to "true".N)r rrrr!r)r rrrrset_cuda_deviceSs   r"cCs,ddl}|j|td|dS)zSet the CUDA device.rNzNow using CUDA device {})rrZDeviceZuserrformat)r rrrrrrhsrFFT FIR filteringc Csddlm}m}t||||||dd}t|trtd|dd}ttrddl }z | |d }t d |Wn4t k r} zt d t| W5d} ~ XYnX|j|ttd n t d ||fS)aaSet up repeated CUDA FFT multiplication with a given filter. Parameters ---------- n_jobs : int | str If n_jobs == 'cuda', the function will attempt to set up for CUDA FFT multiplication. h : array The filtering function that will be used repeatedly. n_fft : int The number of points in the FFT. kind : str The kind to report to the user. Returns ------- n_jobs : int Sets n_jobs = 1 if n_jobs == 'cuda' was passed in, otherwise original n_jobs is passed. cuda_dict : dict Dictionary with the following CUDA-related variables: use_cuda : bool Whether CUDA should be used. fft_plan : instance of FFTPlan FFT plan to use in calculating the FFT. ifft_plan : instance of FFTPlan FFT plan to use in calculating the IFFT. x_fft : instance of gpuarray Empty allocated GPU space for storing the result of the frequency-domain multiplication. x : instance of gpuarray Empty allocated GPU space for the data to filter. h_fft : array | instance of gpuarray This will either be a gpuarray (if CUDA enabled) or ndarray. Notes ----- This function is designed to be used with fft_multiply_repeated(). rrfftirfft)n)n_fftr&r'h_fftn_jobsrrNr*zUsing CUDA for %szhCUDA not used, could not instantiate memory (arrays may be too large: "%s"), falling back to n_jobs=None)r*r&r'ICUDA not used, CUDA could not be initialized, falling back to n_jobs=None) scipy.fftr&r'r isinstancestrr r!r rarrayrrrupdate_cuda_upload_rfft_cuda_irfft_get) r+hr)rr&r' cuda_dictrr*exprrr!_setup_cuda_fft_multiply_repeatedss.)    r8cCs4|d||d}||d9}|d||d}|S)aDo FFT multiplication by a filter function (possibly using CUDA). Parameters ---------- h_fft : 1-d array or gpuarray The filtering array to apply. x : 1-d array The array to filter. n_fft : int The number of points in the FFT. cuda_dict : dict Dictionary constructed using setup_cuda_multiply_repeated(). Returns ------- x : 1-d array Filtered version of x. r&r)r*r'r)xr6x_fftrrr_fft_multiply_repeateds r;cCsddlm}m}td||d}t|dd}|}|d||dddd|dd |d|<|d|}t|trtd |d d}t t rz ddl }| |}t d Wntk rt d YqX|jdttdn t d||d<||fS)aOSet up CUDA FFT resampling. Parameters ---------- n_jobs : int | str If n_jobs == 'cuda', the function will attempt to set up for CUDA FFT resampling. W : array The filtering function to be used during resampling. If n_jobs='cuda', this function will be shortened (since CUDA assumes FFTs of real signals are half the length of the signal) and turned into a gpuarray. new_len : int The size of the array following resampling. Returns ------- n_jobs : int Sets n_jobs = 1 if n_jobs == 'cuda' was passed in, otherwise original n_jobs is passed. cuda_dict : dict Dictionary with the following CUDA-related variables: use_cuda : bool Whether CUDA should be used. fft_plan : instance of FFTPlan FFT plan to use in calculating the FFT. ifft_plan : instance of FFTPlan FFT plan to use in calculating the IFFT. x_fft : instance of gpuarray Empty allocated GPU space for storing the result of the frequency-domain multiplication. x : instance of gpuarray Empty allocated GPU space for the data to resample. Notes ----- This function is designed to be used with fft_resample(). rr%F)use_cudar&r'rNg@r+r,zUsing CUDA for FFT resamplingzbCUDA not used, could not instantiate memory (arrays may be too large), falling back to n_jobs=NoneTr-W)r.r&r'rlencopyr/r0r r!r rr1rrrr2r3r4)r+r?new_lenr&r'r6Z rfft_len_xrrrr_setup_cuda_fft_resamples0'2     rCr>cCs ddl}|jj||||dS)zUpload and compute rfft.rNr(axis)rfftr&r1r9r(rErrrrr3sr3cCsddl}|jj|||dS)zCompute irfft and get.rNrD)rrFr'getrGrrrr4 sr4reflect_limitedc Cs|dkrtddn|}|jtjkr.|tj}t|||}t|}||k}|rR|n|}|d|d} |ddkr|d} | | | d|rdnd9<| |d 9} |d | |} |dkr| |d| jd|d} | S) aDo FFT resampling with a filter function (possibly using CUDA). Parameters ---------- x : 1-d array The array to resample. Will be converted to float64 if necessary. new_len : int The size of the output array (before removing padding). npads : tuple of int Amount of padding to apply to the start and end of the signal before resampling. to_removes : tuple of int Number of samples to remove after resampling. cuda_dict : dict Dictionary constructed using setup_cuda_multiply_repeated(). %(pad)s The default is ``'reflect_limited'``. .. versionadded:: 0.15 Returns ------- x : 1-d array Filtered version of x. NF)r<r&r=rrg?r?r') rdtypenpZfloat64Zastype _smart_padr@anyshape) r9rBZnpadsZ to_removesr6padZold_lenZshorterZuse_lenr:Znyqyrrr _fft_resample&s         rQc Cst|}|jdkst|dkr(|S|dkrN)rKZasarrayrNAssertionErrorallrM RuntimeErrorZzerosmaxr@rJZ concatenaterOtuple)r9Zn_padrOZl_z_padZr_z_padrrrrL\s   &&$"rL)r )FN)N)N)r$)r>)r>)NrI)rI)numpyrKutilsrrrrrrr r r rr!r"rr8r;rCr3r4rQrLrrrrs((  .  CG   5