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How to use add_loader_options method in avocado

Best Python code snippet using avocado_python

TrainingDriver.py

Source:TrainingDriver.py

...45    parser.add_argument('--elastic-momentum',help='worker SGD momentum for EASGD',46            type=float, default=0, dest='elastic_momentum')47def add_downpour_options(parser):48    parser.add_argument('--optimizer',help='optimizer for master to use in downpour',default='adam')49def add_loader_options(parser):50    parser.add_argument('--preload-data', help='Preload files as we read them', default=0, type=int, dest='data_preload')51    parser.add_argument('--cache-data', help='Cache the input files to a provided directory', default='', dest='caching_dir')52    parser.add_argument('--copy-command', help='Specific command line to copy the data into the cache. Expect a string with two {} first is the source (from input file list), second is the bare file name at destination. Like "cp {} {}"', default=None, dest='copy_command')53def add_target_options(parser):54    parser.add_argument('--early-stopping', default=None,55                        dest='early_stopping', help='patience for early stopping')56    parser.add_argument('--target-metric', default=None,57                        dest='target_metric', help='Passing configuration for a target metric')58    59def make_train_parser():60    parser = argparse.ArgumentParser()    61    parser.add_argument('--timeline',help='Record timeline of activity', action='store_true')62    add_train_options(parser)63    return parser64def add_checkpoint_options(parser):65    parser.add_argument('--restore', help='pass a file to retore the variables from', default=None)66    parser.add_argument('--checkpoint', help='Base name of the checkpointing file. If omitted no checkpointing will be done', default=None)67    parser.add_argument('--checkpoint-interval', help='Number of epochs between checkpoints', default=5, type=int, dest='checkpoint_interval')68    69def add_train_options(parser):70    parser.add_argument('--verbose',help='display metrics for each training batch',action='store_true')71    parser.add_argument('--monitor',help='Monitor cpu and gpu utilization', action='store_true')72    parser.add_argument('--backend', help='specify the backend to be used', choices= ['keras','torch'],default='keras')73    parser.add_argument('--thread_validation', help='run a single process', action='store_true')74    75    # model arguments76    parser.add_argument('--model', help='File containing model architecture (serialized in JSON/pickle, or provided in a .py file')77    parser.add_argument('--trial-name', help='descriptive name for trial', 78            default='train', dest='trial_name')79    # training data arguments80    parser.add_argument('--train_data', help='text file listing data inputs for training', default=None)81    parser.add_argument('--val_data', help='text file lis`ting data inputs for validation', default=None)82    parser.add_argument('--features-name', help='name of HDF5 dataset with input features',83            default='features', dest='features_name')84    parser.add_argument('--labels-name', help='name of HDF5 dataset with output labels',85            default='labels', dest='labels_name')86    87    parser.add_argument('--batch', help='batch size', default=100, type=int)88    89    # configuration of network topology90    parser.add_argument('--n-masters', dest='n_masters', help='number of master processes', default=1, type=int)91    parser.add_argument('--n-processes', dest='n_processes', help='number of processes per worker', default=1, type=int)92    parser.add_argument('--max-gpus', dest='max_gpus', help='max GPUs to use', type=int, default=1)93    # configuration of training process94    parser.add_argument('--epochs', help='number of training epochs', default=1, type=int)95    parser.add_argument('--loss',help='loss function',default='binary_crossentropy')96    add_target_options(parser)97    add_worker_options(parser)98    parser.add_argument('--sync-every', help='how often to sync weights with master', 99            default=1, type=int, dest='sync_every')100    parser.add_argument('--mode',help='Mode of operation.'101                        'One of "downpour" (Downpour), "easgd" (Elastic Averaging SGD) or "gem" (Gradient Energy Matching)',default='gem',choices=['downpour','easgd','gem'])102    add_master_option(parser)103    add_gem_options(parser)104    add_easgd_options(parser)105    add_downpour_options(parser)106    107    add_loader_options(parser)108    109    add_log_option(parser)110    add_checkpoint_options(parser)111def make_loader( args, features_name, labels_name, train_list):112    data = H5Data( batch_size=args.batch,113                   cache = args.caching_dir,114                   copy_command = args.copy_command,                   115                   preloading = args.data_preload,116                   features_name=features_name,117                   labels_name=labels_name,118    )119    # We initialize the Data object with the training data list120    # so that we can use it to count the number of training examples121    data.set_full_file_names( train_list )...

MPIGDriver.py

Source:MPIGDriver.py

...33            default='features', dest='features_name')34    parser.add_argument('--labels-name', help='name of HDF5 dataset with output labels',35            default='labels', dest='labels_name')36    parser.add_argument('--batch', help='batch size', default=100, type=int)37    add_loader_options(parser)38    # configuration of network topology39    parser.add_argument('--masters', help='number of master processes', default=1, type=int)40    parser.add_argument('--n-processes', dest='processes', help='number of processes per worker', default=1, type=int)41    parser.add_argument('--max-gpus', dest='max_gpus', help='max GPUs to use', 42            type=int, default=-1)43    parser.add_argument('--master-gpu',help='master process should get a gpu',44            action='store_true', dest='master_gpu')45    parser.add_argument('--synchronous',help='run in synchronous mode',action='store_true')46    # configuration of training process47    parser.add_argument('--epochs', help='number of training epochs', default=1, type=int)48    parser.add_argument('--optimizer',help='optimizer for master to use',default='adam')49    parser.add_argument('--loss',help='loss function',default='binary_crossentropy')50    parser.add_argument('--early-stopping', default=None,51                        dest='early_stopping', help='Configuration for early stopping')...

options.py

Source:options.py

1def add_loader_options(parser):2    parser.add_argument('--data_dir', default='../data', type=str, help="Data directory")3    parser.add_argument('--count_dir', default='../counts', type=str, help="Counts directory")4    parser.add_argument('--id', default="test", type=str, help="Data/counts subdirectory")5    parser.add_argument('--max_factor_dimensions', default=5, type=int, help="Max number of vars for clause")6    parser.add_argument('--batch_size', default=10, type=int, help="Number of formulae in each batch")7def add_model_options(parser):8    parser.add_argument('--msg_passing_iters', type=int, default=5, help="Number of BPNN iters")9    parser.add_argument('--learning_rate', type=float, default=0.0001, help="Initial learning rate")10    parser.add_argument('--step_size', type=int, default=200, help="Step size for the scheduler")11    parser.add_argument('--lr_decay', type=float, default=0.5, help="Learning rate decay for the scheduler")12    parser.add_argument('--damp_param_factor_var', type=float, default=0.5, help="Damping factor-to-variable messages")13    parser.add_argument('--damp_param_var_factor', type=float, default=0.5, help="Damping variable-to-factor messages")14    parser.add_argument('--neural_bp', type=eval, default=True,15                        help="Whether to perform Neural Loopy Belief Propagation or standard Loopy Belief Propagation")...

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