koreyou

# Written by Yuta Koreeda
# CC-BY
import numpy as np


class ExtremeLearningMachine(object):
    def __init__(self, n_unit, activation=None):
        self._activation = self._sig if activation is None else activation
        self._n_unit = n_unit

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###### Editor debris ########

*.org
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¥#*

# spyder
.spyderproject/

# pycharm

koreyou

koreyou

import chainer
import chainer.functions as F
import chainer.links as L
from chainer import training
from chainer.training import extensions

# Network definition
class MLP(chainer.Chain):
    def __init__(self, n_out):
        super(MLP, self).__init__()

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def lock(f):
    """ decorator which locks class method
    You need property _lock defined as in the following.
    self._lock = threading.Lock()
    """
    def body(self, *args, **kwargs):
        with self._lock:  
            return f(self, *args, **kwargs)
    return body

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@contextlib.contextmanager
def safe_mkdir(path, dir=None):
    """ Create a directory in safe(r) way. Specified directory is created only when
    whole operations in `with` scoped is completed successfully. All the files
    that are created within the temporaly generated dir will be kept within.

    This may not work in some OS.
    """
    if dir is None:
        dir = os.path.dirname(path)

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def sequence_mask(x, length, value=0.):
    xp = cuda.get_array_module(length.data)
    # create permutation on (length.ndim + 1) dimension and expand dims until it has shame rank as x
    perms = xp.arange(x.shape[length.ndim]).reshape(
        [1] * length.ndim + [-1] + [1] * (x.ndim - length.ndim -1))
    length = length.reshape([1] * (length.ndim - 1) + [-1] + [1] * (x.ndim - length.ndim))
    pad = xp.ones_like(x) * value
    mask = xp.broadcast_to(perms, x.shape) < length
    return F.where(mask, x, pad)

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koreyou

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