def train(self, solverFilename, logFile, weights=None): # hackaround: this backend doesn't log to one file but to a db in a subdirectory import caffe caffe.setup_teeing(logFile) from pymill.CNN import MillSolver as ms self.solver = ms.MillSolver(solver_def=solverFilename, weights=weights, gpus=[int(x) for x in self._gpus.split(',')]) self.solver.run_solver()
def resume(self, solverFilename, solverstateFilename, logFile): # hackaround: this backend doesn't log to one file but to a db in a subdirectory import caffe caffe.setup_teeing(logFile) log_dir = os.path.abspath(logFile) from pymill.CNN import MillSolver as ms self.solver = ms.MillSolver(solver_def=solverFilename, solver_state=solverstateFilename, gpus=[int(x) for x in self._gpus.split(',')]) self.solver.run_solver()
def train(self, solverFilename, logFile, weights=None): # hackaround: this backend doesn't log to one file but to a db in a subdirectory import caffe caffe.setup_teeing(logFile) from pymill.CNN import MillSolver as ms self.solver = ms.MillSolver( solver_def=solverFilename, weights=weights, gpus=[int(x) for x in self._gpus.split(',')]) self.solver.run_solver()
def resume(self, solverFilename, solverstateFilename, logFile): # hackaround: this backend doesn't log to one file but to a db in a subdirectory import caffe caffe.setup_teeing(logFile) log_dir = os.path.abspath(logFile) from pymill.CNN import MillSolver as ms self.solver = ms.MillSolver( solver_def=solverFilename, solver_state=solverstateFilename, gpus=[int(x) for x in self._gpus.split(',')]) self.solver.run_solver()