Module Expr Str Import alias identifier Import alias Import alias ImportFrom alias ImportFrom alias alias alias ImportFrom alias FunctionDef arguments args defaults body Expr Str Expr Call NameLoad Import alias Assign TupleStore NameStore NameStore Call AttributeLoad NameLoad attr Assign NameStore Call NameLoad Call AttributeLoad AttributeLoad NameLoad attr attr Num keyword Num keyword Num keyword Num With Call AttributeLoad NameLoad attr NameLoad Str NameStore body Expr Call AttributeLoad NameLoad attr Str keyword Call AttributeLoad NameLoad attr Expr Call AttributeLoad NameLoad attr Str keyword Call AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr BinOpMod NameLoad Dict Str NameLoad Expr Call AttributeLoad NameLoad attr Expr Call AttributeLoad NameLoad attr NameLoad decorator_list FunctionDef arguments args defaults body Expr Str Expr Call NameLoad Import alias Assign TupleStore NameStore NameStore Call AttributeLoad NameLoad attr Assign NameStore Call NameLoad Call AttributeLoad AttributeLoad NameLoad attr attr Num keyword Num keyword TupleLoad Num Num keyword Num keyword TupleLoad Str Num Num Str keyword Num With Call AttributeLoad NameLoad attr NameLoad Str NameStore body Expr Call AttributeLoad NameLoad attr Str keyword Call AttributeLoad NameLoad attr Expr Call AttributeLoad NameLoad attr Str keyword Call AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr BinOpMod NameLoad Dict Str NameLoad Expr Call AttributeLoad NameLoad attr Expr Call AttributeLoad NameLoad attr NameLoad decorator_list FunctionDef arguments args defaults body Expr Str Expr Call NameLoad Import alias Assign TupleStore NameStore NameStore Call AttributeLoad NameLoad attr Assign NameStore Call NameLoad Call AttributeLoad AttributeLoad NameLoad attr attr Num keyword Num keyword Num keyword Num With Call AttributeLoad NameLoad attr NameLoad Str NameStore body Expr Call AttributeLoad NameLoad attr Str keyword Call AttributeLoad NameLoad attr Expr Call AttributeLoad NameLoad attr Str keyword Call AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr BinOpMod NameLoad Dict Str NameLoad Expr Call AttributeLoad NameLoad attr Expr Call AttributeLoad NameLoad attr NameLoad decorator_list FunctionDef arguments args defaults body Expr Str Expr Call NameLoad Import alias Assign TupleStore NameStore NameStore Call AttributeLoad NameLoad attr Assign NameStore Call NameLoad Call AttributeLoad AttributeLoad NameLoad attr attr Num keyword Num keyword Num keyword Num With Call AttributeLoad NameLoad attr NameLoad Str NameStore body Expr Call AttributeLoad NameLoad attr Str keyword Call AttributeLoad NameLoad attr Expr Call AttributeLoad NameLoad attr Str keyword Call AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr BinOpMod NameLoad Dict Str NameLoad Expr Call AttributeLoad NameLoad attr Expr Call AttributeLoad NameLoad attr NameLoad decorator_list Assign NameStore Str Assign NameStore Str Assign NameStore Str Assign NameStore Str
N/A N/A 
HDF5 dataset tests.
 N/A numpy np N/A os N/A tempfile pylearn2.config yaml_parse pylearn2.testing.datasets random_dense_design_matrix random_one_hot_dense_design_matrix random_one_hot_topological_dense_design_matrix pylearn2.testing.skip skip_if_no_h5py test_hdf5_design_matrix N/A N/A N/A N/A N/A Train using an HDF5 dataset. N/A N/A skip_if_no_h5py N/A h5py N/A N/A handle filename N/A N/A tempfile mkstemp N/A dataset N/A random_one_hot_dense_design_matrix N/A N/A N/A np random RandomState 1 num_examples 10 dim 5 num_classes 3 N/A N/A N/A h5py File filename w f N/A N/A N/A N/A f create_dataset X data N/A N/A dataset get_design_matrix N/A N/A N/A f create_dataset y data N/A N/A dataset get_targets N/A trainer N/A N/A yaml_parse load N/A design_matrix_yaml N/A filename filename N/A N/A N/A trainer main_loop N/A N/A N/A os remove filename N/A test_hdf5_topo_view N/A N/A N/A N/A N/A Train using an HDF5 dataset with topo_view instead of X. N/A N/A skip_if_no_h5py N/A h5py N/A N/A handle filename N/A N/A tempfile mkstemp N/A dataset N/A random_one_hot_topological_dense_design_matrix N/A N/A N/A np random RandomState 1 num_examples 10 shape N/A 2 2 channels 3 axes N/A b 0 1 c num_classes 3 N/A N/A N/A h5py File filename w f N/A N/A N/A N/A f create_dataset topo_view data N/A N/A dataset get_topological_view N/A N/A N/A f create_dataset y data N/A N/A dataset get_targets N/A trainer N/A N/A yaml_parse load N/A topo_view_yaml N/A filename filename N/A N/A N/A trainer main_loop N/A N/A N/A os remove filename N/A test_hdf5_convert_to_one_hot N/A N/A N/A N/A N/A Train using an HDF5 dataset with one-hot target conversion. N/A N/A skip_if_no_h5py N/A h5py N/A N/A handle filename N/A N/A tempfile mkstemp N/A dataset N/A random_dense_design_matrix N/A N/A N/A np random RandomState 1 num_examples 10 dim 5 num_classes 3 N/A N/A N/A h5py File filename w f N/A N/A N/A N/A f create_dataset X data N/A N/A dataset get_design_matrix N/A N/A N/A f create_dataset y data N/A N/A dataset get_targets N/A trainer N/A N/A yaml_parse load N/A convert_to_one_hot_yaml N/A filename filename N/A N/A N/A trainer main_loop N/A N/A N/A os remove filename N/A test_hdf5_load_all N/A N/A N/A N/A N/A Train using an HDF5 dataset with all data loaded into memory. N/A N/A skip_if_no_h5py N/A h5py N/A N/A handle filename N/A N/A tempfile mkstemp N/A dataset N/A random_one_hot_dense_design_matrix N/A N/A N/A np random RandomState 1 num_examples 10 dim 5 num_classes 3 N/A N/A N/A h5py File filename w f N/A N/A N/A N/A f create_dataset X data N/A N/A dataset get_design_matrix N/A N/A N/A f create_dataset y data N/A N/A dataset get_targets N/A trainer N/A N/A yaml_parse load N/A load_all_yaml N/A filename filename N/A N/A N/A trainer main_loop N/A N/A N/A os remove filename N/A N/A design_matrix_yaml 
!obj:pylearn2.train.Train {
    dataset: &train !obj:pylearn2.datasets.hdf5.HDF5Dataset {
        filename: %(filename)s,
        X: X,
        y: y,
    },
    model: !obj:pylearn2.models.mlp.MLP {
        layers: [
                 !obj:pylearn2.models.mlp.Sigmoid {
                     layer_name: h0,
                     dim: 10,
                     irange: .005,
                 },
                 !obj:pylearn2.models.mlp.Softmax {
                     layer_name: y,
                     n_classes: 3,
                     irange: 0.
                 }
                ],
        nvis: 5,
    },
    algorithm: !obj:pylearn2.training_algorithms.sgd.SGD {
        batch_size: 5,
        learning_rate: .1,
        monitoring_dataset:
            {
                'train' : *train,
            },
        termination_criterion:
            !obj:pylearn2.termination_criteria.EpochCounter {
                max_epochs: 1,
            },
    },
}
 N/A topo_view_yaml 
!obj:pylearn2.train.Train {
    dataset: &train !obj:pylearn2.datasets.hdf5.HDF5Dataset {
        filename: %(filename)s,
        topo_view: topo_view,
        y: y,
    },
    model: !obj:pylearn2.models.mlp.MLP {
        layers: [
                 !obj:pylearn2.models.mlp.Sigmoid {
                     layer_name: h0,
                     dim: 10,
                     irange: .005,
                 },
                 !obj:pylearn2.models.mlp.Softmax {
                     layer_name: y,
                     n_classes: 3,
                     irange: 0.
                 }
                ],
        nvis: 12,
    },
    algorithm: !obj:pylearn2.training_algorithms.sgd.SGD {
        batch_size: 5,
        learning_rate: .1,
        monitoring_dataset:
            {
                'train' : *train,
            },
        termination_criterion:
            !obj:pylearn2.termination_criteria.EpochCounter {
                max_epochs: 1,
            },
    },
}
 N/A convert_to_one_hot_yaml 
!obj:pylearn2.train.Train {
    dataset: &train !obj:pylearn2.datasets.hdf5.HDF5Dataset {
        filename: %(filename)s,
        X: X,
        y: y,
        y_labels: 3
    },
    model: !obj:pylearn2.models.mlp.MLP {
        layers: [
                 !obj:pylearn2.models.mlp.Sigmoid {
                     layer_name: h0,
                     dim: 10,
                     irange: .005,
                 },
                 !obj:pylearn2.models.mlp.Softmax {
                     layer_name: y,
                     n_classes: 3,
                     irange: 0.
                 }
                ],
        nvis: 5,
    },
    algorithm: !obj:pylearn2.training_algorithms.sgd.SGD {
        batch_size: 5,
        learning_rate: .1,
        monitoring_dataset:
            {
                'train' : *train,
            },
        termination_criterion:
            !obj:pylearn2.termination_criteria.EpochCounter {
                max_epochs: 1,
            },
    },
}
 N/A load_all_yaml 
!obj:pylearn2.train.Train {
    dataset: &train !obj:pylearn2.datasets.hdf5.HDF5Dataset {
        filename: %(filename)s,
        X: X,
        y: y,
        load_all: 1,
    },
    model: !obj:pylearn2.models.mlp.MLP {
        layers: [
                 !obj:pylearn2.models.mlp.Sigmoid {
                     layer_name: h0,
                     dim: 10,
                     irange: .005,
                 },
                 !obj:pylearn2.models.mlp.Softmax {
                     layer_name: y,
                     n_classes: 3,
                     irange: 0.
                 }
                ],
        nvis: 5,
    },
    algorithm: !obj:pylearn2.training_algorithms.sgd.SGD {
        batch_size: 5,
        learning_rate: .1,
        monitoring_dataset:
            {
                'train' : *train,
            },
        termination_criterion:
            !obj:pylearn2.termination_criteria.EpochCounter {
                max_epochs: 1,
            },
    },
}
