def run(self): # Instantiate driver classes mir = Mirror(self.distribution, self.log) nv = Nvidia(self.distribution, self.log) ati = ATI(self.distribution, self.log) bc = Broadcom(self.distribution, self.log) pae = PAE(self.distribution, self.log) # First check for mirror for code in self.hwCodesWithStatusList: if code[0] == hwCodes[4]: if code[1] != packageStatus[2]: mir.installMirror() # Now install the hardware drivers for code in self.hwCodesWithStatusList: # First check for mirror if code[0] != hwCodes[4]: if code[0] == hwCodes[0]: if code[1] != packageStatus[2]: nv.installNvidia() elif code[0] == hwCodes[1]: if code[1] != packageStatus[2]: ati.installATI() elif code[0] == hwCodes[2]: if code[1] != packageStatus[2]: bc.installBroadcom() elif code[0] == hwCodes[3]: if code[1] != packageStatus[2]: pae.installPAE()
def run(self): hwList = [] nv = Nvidia(self.distribution, self.log) ati = ATI(self.distribution, self.log) bc = Broadcom(self.distribution, self.log) pae = PAE(self.distribution, self.log) # Collect supported hardware hwNvidia = nv.getNvidia() hwATI = ati.getATI() hwBroadcom = bc.getBroadcom() hwPae = pae.getPae() # Combine all found hardware in a single list for line in hwNvidia: hwList.append(line) for line in hwATI: hwList.append(line) for line in hwBroadcom: hwList.append(line) for line in hwPae: hwList.append(line) return hwList
def run(self): hwList = [] #mir = Mirror(self.distribution, self.log) nv = Nvidia(self.distribution, self.log) ati = ATI(self.distribution, self.log) bc = Broadcom(self.distribution, self.log) pae = PAE(self.distribution, self.log) # Collect supported hardware #mirror = mir.getFastestMirror() hwNvidia = nv.getNvidia() hwATI = ati.getATI() hwBroadcom = bc.getBroadcom() hwPae = pae.getPae() # Combine all found hardware in a single list #for line in mirror: # hwList.append(line) for line in hwPae: hwList.append(line) for line in hwNvidia: hwList.append(line) for line in hwATI: hwList.append(line) for line in hwBroadcom: hwList.append(line) return hwList
def train(configPath, name): useGpu = os.environ.get('GNUMPY_USE_GPU', 'auto') if useGpu == "no": mode = "cpu" else: mode = "gpu" print '========================================================' print 'train %s' % name print "the program is on %s" % mode print '=======================================================' config = configparser.ConfigParser( interpolation=configparser.ExtendedInterpolation()) config.read(configPath) model_name = config.get(name, 'model') if model_name == "ae": from ae import AE model = AE(config, name) elif model_name == "lae": from lae import LAE model = LAE(config, name) elif model_name == "pae": from pae import PAE model = PAE(config, name) elif model_name == "sae": from sae import SAE model = SAE(config, name) elif model_name == "msae": from msae import MSAE model = MSAE(config, name) model.train()
def run(self): # Instantiate driver classes nv = Nvidia(self.distribution, self.log) ati = ATI(self.distribution, self.log) bc = Broadcom(self.distribution, self.log) pae = PAE(self.distribution, self.log) for code in self.hwCodesWithStatusList: if code[0] == hwCodes[0]: if code[1] == packageStatus[0]: nv.removeNvidia() elif code[0] == hwCodes[1]: if code[1] == packageStatus[0]: ati.removeATI() elif code[0] == hwCodes[2]: if code[1] == packageStatus[0]: bc.removeBroadcom() elif code[0] == hwCodes[3]: if code[1] == packageStatus[0]: pae.removePAE()
def loadModel(self, config, name): """ name: path to model file or section name for the model """ if os.path.exists(name): from ae import AE model = AE.load(name) else: modelname = self.readField(config, name, "model") if modelname == "lae": from lae import LAE model = LAE(config, name) elif modelname == "pae": from pae import PAE model = PAE(config, name) elif modelname == 'ae': from ae import AE model = AE(config, name) return model
flags = SETUP(DATASET) noise_dist = UniformNoise(flags.NOISE_DIM) NOISE_PERTURB = 0.01 if DATASET == 'grid': data_dist = Grid() elif DATASET == 'low_dim_embed': data_dist = LowDimEmbed() elif DATASET == 'color_mnist': data_dist = CMNIST(os.path.join('data', 'mnist')) elif DATASET == 'cifar_100': data_dist = CIFAR100(os.path.join('data', 'cifar-100')) NOISE_PERTURB = 0.005 if METHOD == 'pae': from pae import PAE model = PAE(data_dist, noise_dist, flags, args) elif METHOD == 'wae': from wae import WAE model = WAE(data_dist, noise_dist, flags, args) elif METHOD == 'cougan': noise_dist = NormalNoise(flags.NOISE_DIM) from cougan import CoulombGAN model = CoulombGAN(data_dist, noise_dist, flags, args) elif METHOD == 'bigan': from bigan import BiGAN model = BiGAN(data_dist, noise_dist, flags, args) elif METHOD == 'veegan': if DATASET == 'grid': flags.NOISE_DIM = 254 # refer to author's implementation flags.GEN_ARCH[0] = flags.NOISE_DIM flags.ENC_ARCH[-1] = flags.NOISE_DIM