Did I find the right examples for you? yes no      Crawl my project      Python Jobs

All Samples(9)  |  Call(2)  |  Derive(0)  |  Import(7)

src/p/y/pylearn2-HEAD/pylearn2/training_algorithms/sgd.py   pylearn2(Download)
from theano.gof.op import get_debug_values
 
from pylearn2.monitor import Monitor
from pylearn2.space import CompositeSpace, NullSpace
from pylearn2.train_extensions import TrainExtension

src/p/y/pylearn2-HEAD/pylearn2/training_algorithms/default.py   pylearn2(Download)
import functools
 
from pylearn2.monitor import Monitor
from pylearn2.training_algorithms.training_algorithm import TrainingAlgorithm
from pylearn2.utils import safe_zip

src/p/y/pylearn2-HEAD/pylearn2/training_algorithms/bgd.py   pylearn2(Download)
from theano.compat.python2x import OrderedDict
 
from pylearn2.monitor import Monitor
from pylearn2.optimization.batch_gradient_descent import BatchGradientDescent
from pylearn2.utils.iteration import is_stochastic

src/p/y/pylearn2-HEAD/pylearn2/train.py   pylearn2(Download)
from pylearn2.utils import serial
from pylearn2.utils.string_utils import preprocess
from pylearn2.monitor import Monitor
from pylearn2.space import NullSpace
from pylearn2.utils.timing import log_timing, total_seconds

src/p/y/pylearn2-HEAD/pylearn2/tests/test_monitor.py   pylearn2(Download)
from pylearn2.monitor import _err_ambig_data
from pylearn2.monitor import _err_no_data
from pylearn2.monitor import Monitor
from pylearn2.monitor import push_monitor
from pylearn2.space import VectorSpace
    def channel_scaling_checker(num_examples, mode, num_batches, batch_size):
        num_features = 2
        monitor = Monitor(DummyModel(num_features))
        dataset = DummyDataset(num_examples, num_features)
        monitor.add_dataset(dataset=dataset, mode=mode,
        monitor.add_channel(name='mean', ipt=vis_batch, val=mean, dataset=dataset,
                            data_specs=data_specs)
        monitor()
        assert 'mean' in monitor.channels
        mean = monitor.channels['mean']

src/p/y/pylearn2-HEAD/pylearn2/training_algorithms/tests/test_sgd.py   pylearn2(Download)
from pylearn2.datasets.dense_design_matrix import DenseDesignMatrix
from pylearn2.models.model import Model
from pylearn2.monitor import Monitor
from pylearn2.space import CompositeSpace, Conv2DSpace, VectorSpace
from pylearn2.termination_criteria import EpochCounter

src/p/y/pylearn2-HEAD/pylearn2/tests/test_train.py   pylearn2(Download)
__email__ = "goodfeli@iro"
import numpy as np
from pylearn2.monitor import Monitor
from pylearn2.train import Train
from pylearn2.datasets.dense_design_matrix import DenseDesignMatrix