repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
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chainer | chainer-master/chainer/distributions/multivariate_normal.py | import math
import numpy
import chainer
from chainer import backend
from chainer.backends import cuda
from chainer import distribution
from chainer.functions.array import broadcast
from chainer.functions.array import diagonal
from chainer.functions.array import expand_dims
from chainer.functions.array import squeeze
... | 7,498 | 29.860082 | 79 | py |
chainer | chainer-master/chainer/distributions/poisson.py | import chainer
from chainer.backends import cuda
from chainer import distribution
from chainer.functions.math import exponential
from chainer.functions.math import lgamma
from chainer import utils
from chainer.utils import cache
class Poisson(distribution.Distribution):
"""Poisson Distribution.
The probabil... | 2,317 | 24.472527 | 76 | py |
chainer | chainer-master/chainer/distributions/laplace.py | import math
import numpy
import chainer
from chainer import backend
from chainer.backends import cuda
from chainer import distribution
from chainer.functions.math import exponential
from chainer import utils
from chainer.utils import cache
class LaplaceCDF(chainer.function_node.FunctionNode):
def forward(self,... | 4,060 | 24.38125 | 74 | py |
chainer | chainer-master/chainer/distributions/categorical.py | import numpy
import chainer
from chainer import backend
from chainer import distribution
from chainer.functions.activation import log_softmax
from chainer.functions.math import exponential
from chainer.functions.math import sum as sum_mod
from chainer.utils import argument
from chainer.utils import cache
class Categ... | 2,792 | 28.4 | 77 | py |
chainer | chainer-master/chainer/distributions/independent.py | import numpy
from chainer.backend import cuda
from chainer import distribution
from chainer.functions.array import repeat
from chainer.functions.array import reshape
from chainer.functions.array import transpose
from chainer.functions.math import prod
from chainer.functions.math import sum as sum_mod
from chainer.util... | 8,777 | 34.112 | 82 | py |
chainer | chainer-master/chainer/distributions/__init__.py | """Collection of distribution implementations."""
from chainer.distributions.bernoulli import Bernoulli # NOQA
from chainer.distributions.beta import Beta # NOQA
from chainer.distributions.categorical import Categorical # NOQA
from chainer.distributions.cauchy import Cauchy # NOQA
from chainer.distributions.chisqu... | 1,225 | 54.727273 | 80 | py |
chainer | chainer-master/chainer/distributions/gamma.py | import chainer
from chainer.backends import cuda
from chainer import distribution
from chainer.functions.array import broadcast
from chainer.functions.array import where
from chainer.functions.math import digamma
from chainer.functions.math import exponential
from chainer.functions.math import lgamma
from chainer.utils... | 2,914 | 27.028846 | 79 | py |
chainer | chainer-master/chainer/distributions/exponential.py | import chainer
from chainer.backends import cuda
from chainer import distribution
from chainer.functions.array import where
from chainer.functions.math import exponential
from chainer.functions.math import exponential_m1
from chainer.functions.math import logarithm_1p
from chainer.utils import cache
class Exponential... | 2,615 | 24.398058 | 72 | py |
chainer | chainer-master/chainer/distributions/bernoulli.py | import numpy
import chainer
from chainer import backend
from chainer.backends import cuda
from chainer import distribution
import chainer.distributions.utils
from chainer.functions.activation import sigmoid
from chainer.functions.array import where
from chainer.functions.math import exponential
from chainer.functions.... | 5,412 | 29.410112 | 76 | py |
chainer | chainer-master/chainer/dataset/dataset_mixin.py | import numpy
import six
class DatasetMixin(object):
"""Default implementation of dataset indexing.
DatasetMixin provides the :meth:`__getitem__` operator. The default
implementation uses :meth:`get_example` to extract each example, and
combines the results into a list. This mixin makes it easy to im... | 2,919 | 32.563218 | 79 | py |
chainer | chainer-master/chainer/dataset/download.py | import hashlib
import os
import shutil
import sys
import filelock
from six.moves.urllib import request
from chainer import utils
_dataset_root = os.environ.get(
'CHAINER_DATASET_ROOT',
os.path.join(os.path.expanduser('~'), '.chainer', 'dataset'))
def get_dataset_root():
"""Gets the path to the root di... | 5,087 | 30.8 | 79 | py |
chainer | chainer-master/chainer/dataset/iterator.py | class Iterator(object):
"""Base class of all dataset iterators.
Iterator iterates over the dataset, yielding a minibatch at each
iteration. Minibatch is a list of examples. Each implementation should
implement an iterator protocol (e.g., the :meth:`__next__` method).
Note that, even if the iterat... | 2,809 | 31.298851 | 79 | py |
chainer | chainer-master/chainer/dataset/convert.py | import collections
import numpy
import six
import chainer
from chainer import backend
from chainer.backends import cuda
class Converter(object):
"""Base class of converters.
Converters receive batched data retrieved from iterators and perform
arbitrary transforms as well as device transfer.
Imple... | 21,146 | 37.102703 | 83 | py |
chainer | chainer-master/chainer/dataset/__init__.py | # import classes and functions
from chainer.dataset.convert import concat_examples # NOQA
from chainer.dataset.convert import ConcatWithAsyncTransfer # NOQA
from chainer.dataset.convert import converter # NOQA
from chainer.dataset.convert import Converter # NOQA
from chainer.dataset.convert import to_device # NOQA... | 829 | 54.333333 | 74 | py |
chainer | chainer-master/chainer/dataset/tabular/_asmode.py | from chainer.dataset.tabular import tabular_dataset
class _Astuple(tabular_dataset.TabularDataset):
def __init__(self, dataset):
self._dataset = dataset
def __len__(self):
return len(self._dataset)
@property
def keys(self):
return self._dataset.keys
@property
def mo... | 1,024 | 20.354167 | 63 | py |
chainer | chainer-master/chainer/dataset/tabular/_transform.py | import six
from chainer.dataset.tabular import tabular_dataset
class _Transform(tabular_dataset.TabularDataset):
def __init__(self, dataset, keys, transform):
if not isinstance(keys, tuple):
keys = keys,
self._dataset = dataset
self._keys = keys
self._transform = tra... | 5,703 | 36.038961 | 74 | py |
chainer | chainer-master/chainer/dataset/tabular/_with_converter.py | from chainer.dataset.tabular import tabular_dataset
class _WithConverter(tabular_dataset.TabularDataset):
def __init__(self, dataset, converter):
self._dataset = dataset
self._converter = converter
def __len__(self):
return len(self._dataset)
@property
def keys(self):
... | 775 | 24.032258 | 63 | py |
chainer | chainer-master/chainer/dataset/tabular/from_data.py | import chainer
from chainer.dataset.tabular import tabular_dataset
def from_data(data, *, size=None):
"""Create a TabularDataset from lists/arrays/callables.
>>> from chainer.dataset import tabular
>>>
>>> dataset = tabular.from_data([0, 1, 2])
>>> dataset[0]
0
>>> dataset = tabular.from_... | 5,074 | 25.570681 | 79 | py |
chainer | chainer-master/chainer/dataset/tabular/_join.py | import six
from chainer.dataset.tabular import tabular_dataset
class _Join(tabular_dataset.TabularDataset):
def __init__(self, *datasets):
keys = set(datasets[0].keys)
for dataset in datasets[1:]:
if not len(dataset) == len(datasets[0]):
raise ValueError('All datasets... | 2,138 | 32.421875 | 79 | py |
chainer | chainer-master/chainer/dataset/tabular/delegate_dataset.py | from chainer.dataset.tabular import tabular_dataset
class DelegateDataset(tabular_dataset.TabularDataset):
"""A helper class to implement a TabularDataset.
This class wraps an instance of :class:`~chainer.dataset.TabularDataset`
and provides methods of :class:`~chainer.dataset.TabularDataset`.
This ... | 1,637 | 26.3 | 76 | py |
chainer | chainer-master/chainer/dataset/tabular/_slice.py | import numbers
import numpy as np
import six
from chainer.dataset.tabular import tabular_dataset
class _Slice(tabular_dataset.TabularDataset):
def __init__(self, dataset, indices, keys):
if keys is None:
self._unary = None
elif isinstance(keys, tuple):
self._unary = Fals... | 4,631 | 27.95 | 77 | py |
chainer | chainer-master/chainer/dataset/tabular/_concat.py | import six
from chainer.dataset.tabular import tabular_dataset
class _Concat(tabular_dataset.TabularDataset):
def __init__(self, *datasets):
for dataset in datasets[1:]:
if not dataset.keys == datasets[0].keys:
raise ValueError('All datasets must have the same keys')
... | 3,939 | 33.561404 | 76 | py |
chainer | chainer-master/chainer/dataset/tabular/__init__.py | from chainer.dataset.tabular import _asmode # NOQA
from chainer.dataset.tabular import _concat # NOQA
from chainer.dataset.tabular import _join # NOQA
from chainer.dataset.tabular import _slice # NOQA
from chainer.dataset.tabular import _transform # NOQA
from chainer.dataset.tabular import _with_converter # NOQA
... | 462 | 45.3 | 76 | py |
chainer | chainer-master/chainer/dataset/tabular/tabular_dataset.py | import six
import chainer
from chainer.dataset import dataset_mixin
class TabularDataset(dataset_mixin.DatasetMixin):
"""An abstract class that represents tabular dataset.
This class represents a tabular dataset.
In a tabular dataset, all examples have the same number of elements.
For example, all e... | 8,797 | 29.978873 | 79 | py |
chainer | chainer-master/chainer/links/__init__.py | """Collection of :class:`~chainer.Link` implementations."""
from chainer.links.activation.maxout import Maxout # NOQA
from chainer.links.activation.prelu import PReLU # NOQA
from chainer.links.activation.simplified_dropconnect import SimplifiedDropconnect # NOQA
from chainer.links.activation.swish import Swish # N... | 4,325 | 65.553846 | 111 | py |
chainer | chainer-master/chainer/links/theano/theano_function.py | import collections
from chainer.functions.theano import theano_function
from chainer import link
from chainer.utils import collections_abc
def _to_var_tuple(vs):
import theano
msg = ('inputs and outputs must be a TensorVariable, a list '
'of TensorVariable or a tuple of TensorVariable')
if is... | 3,740 | 32.702703 | 79 | py |
chainer | chainer-master/chainer/links/theano/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/chainer/links/normalization/group_normalization.py | import numpy
import chainer
from chainer.functions.normalization import group_normalization
from chainer import initializers
from chainer import link
from chainer import variable
class GroupNormalization(link.Link):
"""Group normalization layer on outputs of convolution functions.
This link implements a "gr... | 3,944 | 37.676471 | 79 | py |
chainer | chainer-master/chainer/links/normalization/layer_normalization.py | from chainer.functions.normalization import layer_normalization
from chainer import link
from chainer import utils
from chainer import variable
class LayerNormalization(link.Link):
"""Layer normalization layer on outputs of linear functions.
.. warning::
This feature is experimental. The interface ... | 2,961 | 34.686747 | 78 | py |
chainer | chainer-master/chainer/links/normalization/batch_renormalization.py | import chainer
from chainer import configuration
from chainer.functions.normalization import batch_normalization
from chainer.functions.normalization import batch_renormalization
from chainer.links.normalization.batch_normalization import BatchNormalization
class BatchRenormalization(BatchNormalization):
"""Batc... | 3,511 | 38.022222 | 81 | py |
chainer | chainer-master/chainer/links/normalization/decorrelated_batch_normalization.py | import functools
import warnings
import numpy
import chainer
from chainer import configuration
from chainer import functions
from chainer import link
import chainer.serializer as serializer_mod
from chainer.utils import argument
class DecorrelatedBatchNormalization(link.Link):
"""Decorrelated batch normalizati... | 7,674 | 35.20283 | 79 | py |
chainer | chainer-master/chainer/links/normalization/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/chainer/links/normalization/batch_normalization.py | import numpy
import six
import chainer
from chainer import configuration
from chainer import functions
from chainer import initializers
from chainer import link
from chainer.graph_optimizations.static_graph_utilities import static_code
from chainer.utils import argument
from chainer import variable
class BatchNormal... | 14,478 | 38.887052 | 79 | py |
chainer | chainer-master/chainer/links/rnn/lstm.py | import six
import chainer
from chainer.functions.array import concat
from chainer.functions.array import split_axis
from chainer.functions.rnn import lstm
from chainer import initializers
from chainer import link
from chainer.links.connection import linear
from chainer import utils
from chainer import variable
class... | 11,379 | 34.673981 | 79 | py |
chainer | chainer-master/chainer/links/rnn/n_step_gru.py | from chainer.functions.rnn import n_step_gru as rnn
from chainer.links.rnn import n_step_rnn
class NStepGRUBase(n_step_rnn.NStepRNNBase):
"""__init__(self, n_layers, in_size, out_size, dropout, use_bi_direction)
Base link class for Stacked GRU/BiGRU links.
This link is base link class for :func:`chaine... | 3,012 | 28.831683 | 78 | py |
chainer | chainer-master/chainer/links/rnn/zoneoutlstm.py | import chainer
from chainer.functions.activation import sigmoid
from chainer.functions.activation import tanh
from chainer.functions.array import reshape
from chainer.functions.array import split_axis
from chainer.functions.noise import zoneout
from chainer import link
from chainer.links.connection import linear
from c... | 3,551 | 33.485437 | 79 | py |
chainer | chainer-master/chainer/links/rnn/gru.py | from chainer.functions.activation import sigmoid
from chainer.functions.activation import tanh
from chainer.functions.math import linear_interpolate
from chainer import link
from chainer.links.connection import linear
from chainer import variable
class GRUBase(link.Chain):
def __init__(self, in_size, out_size, i... | 9,127 | 34.379845 | 79 | py |
chainer | chainer-master/chainer/links/rnn/mgu.py | import numpy
import chainer
from chainer.functions.activation import sigmoid
from chainer.functions.activation import tanh
from chainer.functions.array import concat
from chainer.functions.math import linear_interpolate
from chainer import link
from chainer.links.connection import linear
class MGUBase(link.Chain):
... | 1,872 | 26.544118 | 66 | py |
chainer | chainer-master/chainer/links/rnn/tree_lstm.py | import numpy
from chainer.functions.activation import sigmoid
from chainer.functions.activation import tanh
from chainer.functions.array import concat
from chainer.functions.array import split_axis
from chainer.functions.rnn import tree_lstm
from chainer import link
from chainer.links.connection import linear
class ... | 9,745 | 37.674603 | 79 | py |
chainer | chainer-master/chainer/links/rnn/n_step_lstm.py | from chainer.functions.rnn import n_step_lstm as rnn
from chainer.links.rnn import n_step_rnn
class NStepLSTMBase(n_step_rnn.NStepRNNBase):
"""Base link class for Stacked LSTM/BiLSTM links.
This link is base link class for :func:`chainer.links.NStepLSTM` and
:func:`chainer.links.NStepBiLSTM`.
This l... | 6,131 | 34.651163 | 79 | py |
chainer | chainer-master/chainer/links/rnn/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/chainer/links/rnn/n_step_rnn.py | import numpy
import six
import chainer
from chainer.functions.array import permutate
from chainer.functions.array import transpose_sequence
from chainer.functions.rnn import n_step_rnn as rnn
from chainer import initializers
from chainer import link
from chainer.utils import argument
from chainer import variable
def... | 12,967 | 33.954178 | 79 | py |
chainer | chainer-master/chainer/links/rnn/peephole.py | import chainer
from chainer.functions.activation import sigmoid
from chainer.functions.activation import tanh
from chainer.functions.array import reshape
from chainer.functions.array import split_axis
from chainer import link
from chainer.links.connection import linear
from chainer import variable
class StatefulPeeph... | 4,445 | 37.327586 | 78 | py |
chainer | chainer-master/chainer/links/activation/simplified_dropconnect.py | import numpy
from chainer.functions.noise import simplified_dropconnect
from chainer import initializers
from chainer import link
from chainer import variable
class SimplifiedDropconnect(link.Link):
"""Fully-connected layer with simplified dropconnect regularization.
Notice:
This implementation cannot ... | 4,271 | 40.076923 | 78 | py |
chainer | chainer-master/chainer/links/activation/maxout.py | import numpy
import chainer
from chainer.functions.activation import maxout
from chainer import initializer
from chainer import link
from chainer.links.connection import linear
class Maxout(link.Chain):
"""Fully-connected maxout layer.
Let ``M``, ``P`` and ``N`` be an input dimension, a pool size,
and a... | 4,114 | 34.782609 | 74 | py |
chainer | chainer-master/chainer/links/activation/swish.py | from chainer.functions.activation import swish
from chainer import initializers
from chainer import link
from chainer import variable
class Swish(link.Link):
"""Swish activation function as a link.
Args:
beta_shape (tuple of ints or None): Shape of the parameter variable
:math:`\\beta`. ... | 3,025 | 30.852632 | 84 | py |
chainer | chainer-master/chainer/links/activation/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/chainer/links/activation/prelu.py | from chainer.functions.activation import prelu
from chainer import link
from chainer import variable
class PReLU(link.Link):
"""Parametric ReLU function as a link.
Args:
shape (tuple of ints): Shape of the parameter array.
init (float): Initial parameter value.
See the paper for details... | 2,445 | 29.197531 | 84 | py |
chainer | chainer-master/chainer/links/connection/inceptionbn.py | import chainer
from chainer.functions.activation import relu
from chainer.functions.array import concat
from chainer.functions.pooling import average_pooling_2d
from chainer.functions.pooling import max_pooling_nd
from chainer import link
from chainer.links.connection import convolution_2d
from chainer.links.normalizat... | 5,325 | 41.608 | 79 | py |
chainer | chainer-master/chainer/links/connection/highway.py | from chainer.functions.activation import relu
from chainer.functions.activation import sigmoid
from chainer import link
from chainer.links.connection import linear
class Highway(link.Chain):
"""Highway module.
In highway network, two gates are added to the ordinal non-linear
transformation (:math:`H(x) ... | 3,146 | 40.407895 | 79 | py |
chainer | chainer-master/chainer/links/connection/bilinear.py | import numpy
from chainer.backends import cuda
from chainer.functions.connection import bilinear
from chainer import initializers
from chainer import link
from chainer import variable
class Bilinear(link.Link):
"""Bilinear layer that performs tensor multiplication.
Bilinear is a primitive link that wraps t... | 4,659 | 40.981982 | 79 | py |
chainer | chainer-master/chainer/links/connection/inception.py | from chainer.functions.activation import relu
from chainer.functions.array import concat
from chainer.functions.pooling import max_pooling_nd
from chainer import link
from chainer.links.connection import convolution_2d
class Inception(link.Chain):
"""Inception module of GoogLeNet.
It applies four different ... | 3,601 | 42.39759 | 78 | py |
chainer | chainer-master/chainer/links/connection/scale.py | import chainer
from chainer.functions.math import scale
from chainer import link
from chainer.links.connection import bias
from chainer import variable
class Scale(link.Chain):
"""Broadcasted elementwise product with learnable parameters.
Computes a elementwise product as :func:`~chainer.functions.scale`
... | 3,229 | 36.126437 | 79 | py |
chainer | chainer-master/chainer/links/connection/deconvolution_2d.py | import numpy
from chainer.backends import cuda
from chainer.functions.connection import deconvolution_2d
from chainer import initializers
from chainer import link
from chainer.utils import argument
from chainer import variable
class Deconvolution2D(link.Link):
"""__init__(self, in_channels, out_channels, ksize=... | 7,614 | 39.078947 | 79 | py |
chainer | chainer-master/chainer/links/connection/convolution_nd.py | from chainer.functions.connection import convolution_nd
from chainer import initializers
from chainer import link
from chainer.utils import argument
from chainer.utils import conv_nd
from chainer import variable
class ConvolutionND(link.Link):
"""N-dimensional convolution layer.
This link wraps the :func:`~c... | 10,487 | 40.291339 | 79 | py |
chainer | chainer-master/chainer/links/connection/linear.py | import typing as tp # NOQA
from chainer.functions.connection import linear
from chainer import initializers
from chainer import link
from chainer import types # NOQA
from chainer import utils
from chainer import variable
class Linear(link.Link):
"""Linear layer (a.k.a.\\ fully-connected layer).
This is ... | 6,784 | 35.875 | 89 | py |
chainer | chainer-master/chainer/links/connection/deconvolution_nd.py | from chainer.functions.connection import deconvolution_nd
from chainer import initializers
from chainer import link
from chainer.utils import conv_nd
from chainer import variable
class DeconvolutionND(link.Link):
"""N-dimensional deconvolution function.
This link wraps :func:`~chainer.functions.deconvolution... | 7,585 | 38.926316 | 79 | py |
chainer | chainer-master/chainer/links/connection/parameter.py | from chainer.backends import cuda
from chainer.functions.math import identity
from chainer import link
class Parameter(link.Link):
"""Link that just holds a parameter and returns it.
.. deprecated:: v1.5
The parameters are stored as variables since v1.5. Use them directly
instead.
Args:
... | 1,231 | 26.377778 | 78 | py |
chainer | chainer-master/chainer/links/connection/depthwise_convolution_2d.py | import numpy
from chainer.functions.connection import depthwise_convolution_2d
from chainer import initializers
from chainer import link
from chainer import variable
class DepthwiseConvolution2D(link.Link):
"""Two-dimensional depthwise convolutional layer.
This link wraps the :func:`~chainer.functions.dept... | 3,761 | 36.62 | 79 | py |
chainer | chainer-master/chainer/links/connection/local_convolution_2d.py | from chainer.functions.connection import local_convolution_2d
from chainer import initializers
from chainer import link
from chainer import variable
def _pair(x):
if hasattr(x, '__getitem__'):
return x
return x, x
def _conv_output_length(input_length, filter_size, stride):
output_length = input_... | 4,038 | 37.836538 | 79 | py |
chainer | chainer-master/chainer/links/connection/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/chainer/links/connection/deformable_convolution_2d.py | from chainer.functions import deformable_convolution_2d_sampler
from chainer import initializers
from chainer.initializers import constant
from chainer import link
from chainer.links.connection.convolution_2d import Convolution2D
from chainer import variable
class DeformableConvolution2D(link.Chain):
"""Two-dimen... | 5,452 | 39.69403 | 78 | py |
chainer | chainer-master/chainer/links/connection/bias.py | import chainer
from chainer.functions.math import bias
from chainer import link
from chainer import variable
class Bias(link.Link):
"""Broadcasted elementwise summation with learnable parameters.
Computes a elementwise summation as :func:`~chainer.functions.bias`
function does except that its second inpu... | 2,045 | 30.96875 | 79 | py |
chainer | chainer-master/chainer/links/connection/convolution_2d.py | import chainer
from chainer.functions.connection import convolution_2d
from chainer import initializers
from chainer import link
from chainer import memory_layouts
from chainer.utils import argument
from chainer import variable
class Convolution2D(link.Link):
"""__init__(self, in_channels, out_channels, ksize=No... | 10,408 | 39.344961 | 79 | py |
chainer | chainer-master/chainer/links/connection/mlp_convolution_2d.py | from chainer.functions.activation import relu
from chainer import link
from chainer.links.connection import convolution_2d
from chainer.utils import argument
class MLPConvolution2D(link.ChainList):
"""__init__(self, in_channels, out_channels, ksize=None, stride=1, \
pad=0, activation=relu.relu, conv_init=None, b... | 4,629 | 41.477064 | 78 | py |
chainer | chainer-master/chainer/links/connection/embed_id.py | from chainer.functions.connection import embed_id
from chainer.initializers import normal
from chainer import link
from chainer import variable
class EmbedID(link.Link):
"""Efficient linear layer for one-hot input.
This is a link that wraps the :func:`~chainer.functions.embed_id` function.
This link hol... | 2,838 | 30.898876 | 79 | py |
chainer | chainer-master/chainer/links/connection/dilated_convolution_2d.py | from chainer.functions.connection import dilated_convolution_2d
from chainer import initializers
from chainer import link
from chainer import variable
class DilatedConvolution2D(link.Link):
"""Two-dimensional dilated convolutional layer.
This link wraps the :func:`~chainer.functions.dilated_convolution_2d`
... | 5,146 | 34.253425 | 78 | py |
chainer | chainer-master/chainer/links/loss/negative_sampling.py | import numpy
import chainer
from chainer.functions.loss import negative_sampling
from chainer import link
from chainer.utils import argument
from chainer.utils import walker_alias
from chainer import variable
class NegativeSampling(link.Link):
"""Negative sampling loss layer.
This link wraps the :func:`~ch... | 3,154 | 35.264368 | 79 | py |
chainer | chainer-master/chainer/links/loss/black_out.py | import numpy
from chainer.functions.loss import black_out
from chainer import link
from chainer.utils import walker_alias
from chainer import variable
class BlackOut(link.Link):
"""BlackOut loss layer.
.. seealso:: :func:`~chainer.functions.black_out` for more detail.
Args:
in_size (int): Dime... | 1,822 | 28.403226 | 77 | py |
chainer | chainer-master/chainer/links/loss/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/chainer/links/loss/hierarchical_softmax.py | import copy
import numpy
import six
import chainer
from chainer.backends import cuda
from chainer import device_resident
from chainer import function
from chainer.initializers import uniform
from chainer import link
from chainer import utils
from chainer.utils import type_check
from chainer import variable
class Tr... | 12,026 | 31.860656 | 79 | py |
chainer | chainer-master/chainer/links/loss/crf1d.py | from chainer.functions.array import transpose_sequence
from chainer.functions.loss import crf1d
from chainer import initializers
from chainer import link
from chainer.links.rnn.n_step_rnn import argsort_list_descent
from chainer.links.rnn.n_step_rnn import permutate_list
from chainer import variable
class CRF1d(link.... | 3,495 | 34.313131 | 75 | py |
chainer | chainer-master/chainer/links/caffe/caffe_function.py | import warnings
import numpy
import six
from chainer import configuration
from chainer import functions
from chainer import initializer
from chainer import link
from chainer.links.caffe.protobuf3 import caffe_pb2 as caffe_pb
from chainer.links.connection import convolution_2d
from chainer.links.connection import deco... | 22,528 | 31.841108 | 79 | py |
chainer | chainer-master/chainer/links/caffe/__init__.py | from chainer.links.caffe.caffe_function import CaffeFunction # NOQA
| 69 | 34 | 68 | py |
chainer | chainer-master/chainer/links/caffe/protobuf3/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/chainer/links/caffe/protobuf3/caffe_pb2.py | # Generated by the protocol buffer compiler. DO NOT EDIT!
# source: caffe.proto
import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
from google.protobuf.internal import enum_type_wrapper
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _mes... | 242,354 | 41.963127 | 27,796 | py |
chainer | chainer-master/chainer/links/model/classifier.py | from chainer.functions.evaluation import accuracy
from chainer.functions.loss import softmax_cross_entropy
from chainer import link
from chainer import reporter
class Classifier(link.Chain):
"""A simple classifier model.
This is an example of chain that wraps another chain. It computes the
loss and accu... | 6,083 | 39.56 | 79 | py |
chainer | chainer-master/chainer/links/model/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/chainer/links/model/vision/resnet.py | import collections
import os
import sys
import warnings
import numpy
try:
from PIL import Image
available = True
except ImportError as e:
available = False
_import_error = e
import chainer
from chainer.dataset.convert import concat_examples
from chainer.dataset import download
from chainer import func... | 33,339 | 41.74359 | 94 | py |
chainer | chainer-master/chainer/links/model/vision/vgg.py | import collections
import os
import sys
import numpy
try:
from PIL import Image
available = True
except ImportError as e:
available = False
_import_error = e
import chainer
from chainer.dataset.convert import concat_examples
from chainer.dataset import download
from chainer import function
from chaine... | 20,475 | 39.546535 | 79 | py |
chainer | chainer-master/chainer/links/model/vision/googlenet.py | import collections
import os
import sys
import numpy
try:
from PIL import Image
available = True
except ImportError as e:
available = False
_import_error = e
import chainer
from chainer.dataset.convert import concat_examples
from chainer.dataset import download
from chainer import function
from chaine... | 18,874 | 40.032609 | 80 | py |
chainer | chainer-master/chainer/links/model/vision/__init__.py | 0 | 0 | 0 | py | |
chainer | chainer-master/chainer/training/extension.py | from chainer.utils import argument
PRIORITY_WRITER = 300
PRIORITY_EDITOR = 200
PRIORITY_READER = 100
class Extension(object):
"""Base class of trainer extensions.
Extension of :class:`Trainer` is a callable object that takes the trainer
object as the argument. It also provides some default configurati... | 6,662 | 36.644068 | 79 | py |
chainer | chainer-master/chainer/training/trigger.py | # For backward compatibility
from chainer.training.triggers.interval_trigger import IntervalTrigger # NOQA
from chainer.training.util import _never_fire_trigger # NOQA
from chainer.training.util import get_trigger # NOQA
| 224 | 44 | 78 | py |
chainer | chainer-master/chainer/training/updater.py | from chainer.training._updater import Updater # NOQA
# For backward compatibility
from chainer.training.updaters.parallel_updater import ParallelUpdater # NOQA
from chainer.training.updaters.standard_updater import StandardUpdater # NOQA
| 242 | 39.5 | 78 | py |
chainer | chainer-master/chainer/training/util.py | from chainer.training.triggers import interval_trigger
def get_trigger(trigger):
"""Gets a trigger object.
Trigger object is a callable that accepts a
:class:`~chainer.training.Trainer` object as an argument and returns a
boolean value. When it returns True, various kinds of events can occur
depe... | 1,741 | 38.590909 | 79 | py |
chainer | chainer-master/chainer/training/_updater.py | class Updater(object):
"""Interface of updater objects for trainers.
:class:`~chainer.training.Updater` implements a training iteration
as :meth:`update`. Typically, the updating iteration proceeds as follows.
- Fetch a minibatch from :mod:`~chainer.dataset`
via :class:`~chainer.dataset.Iterato... | 2,697 | 30.741176 | 79 | py |
chainer | chainer-master/chainer/training/__init__.py | from chainer.training import extensions # NOQA
from chainer.training import triggers # NOQA
from chainer.training import updaters # NOQA
from chainer.training import util # NOQA
# import classes and functions
from chainer.training.extension import Extension # NOQA
from chainer.training.extension import make_exten... | 868 | 47.277778 | 62 | py |
chainer | chainer-master/chainer/training/trainer.py | import collections
import os
import sys
import time
import traceback
import six
from chainer import reporter as reporter_module
from chainer import serializer as serializer_module
from chainer.training import extension as extension_module
from chainer.training import trigger as trigger_module
from chainer.utils impor... | 16,918 | 40.775309 | 79 | py |
chainer | chainer-master/chainer/training/updaters/standard_updater.py | import warnings
import six
import chainer
from chainer.backends import cuda
from chainer.dataset import convert
from chainer.dataset import iterator as iterator_module
from chainer import device_resident
from chainer.training import _updater
from chainer.utils import argument
class StandardUpdater(_updater.Updater)... | 10,516 | 37.665441 | 79 | py |
chainer | chainer-master/chainer/training/updaters/multiprocess_parallel_updater.py | import multiprocessing
import warnings
import numpy
import six
import chainer
from chainer.backends import cuda
from chainer.dataset import convert
from chainer import reporter
from chainer.training.updaters import standard_updater
try:
from cupy.cuda import nccl
_available = True
except Exception:
_ava... | 16,699 | 32.737374 | 79 | py |
chainer | chainer-master/chainer/training/updaters/__init__.py | from chainer.training.updaters.multiprocess_parallel_updater import MultiprocessParallelUpdater # NOQA
from chainer.training.updaters.parallel_updater import ParallelUpdater # NOQA
from chainer.training.updaters.standard_updater import StandardUpdater # NOQA
| 262 | 64.75 | 103 | py |
chainer | chainer-master/chainer/training/updaters/parallel_updater.py | import copy
import six
import chainer
from chainer.dataset import convert
from chainer import function
from chainer.training.updaters import standard_updater
class ParallelUpdater(standard_updater.StandardUpdater):
"""Implementation of a parallel GPU Updater.
This is an implementation of :class:`Updater` ... | 6,102 | 38.121795 | 79 | py |
chainer | chainer-master/chainer/training/extensions/snapshot_writers.py | import multiprocessing
import os
import shutil
import threading
from six.moves import queue
from chainer.serializers import npz
from chainer import utils
class Writer(object):
"""Base class of snapshot writers.
:class:`~chainer.training.extensions.Snapshot` invokes ``__call__`` of this
class every tim... | 10,153 | 29.492492 | 79 | py |
chainer | chainer-master/chainer/training/extensions/inverse_shift.py | from __future__ import division
import numpy
from chainer.training import extension
class InverseShift(extension.Extension):
"""Trainer extension to shift an optimizer attribute.
The new value is computed according to the fomula below:
new_attr = init_attr * (1 + gamma * iter) ^ (- power), which is co... | 3,302 | 36.11236 | 79 | py |
chainer | chainer-master/chainer/training/extensions/multistep_shift.py | from __future__ import division
from chainer.training import extension
class MultistepShift(extension.Extension):
"""Trainer extension to shift an optimizer attribute in several steps.
This extension changes an optimizer attribute in several steps, every step
the attribute will multiply a factor ``gamm... | 2,599 | 39 | 78 | py |
chainer | chainer-master/chainer/training/extensions/progress_bar.py | from __future__ import division
import datetime
import sys
from chainer.training import extension
from chainer.training.extensions import util
class ProgressBar(extension.Extension):
"""Trainer extension to print a progress bar and recent training status.
This extension prints a progress bar at every call.... | 3,454 | 32.221154 | 79 | py |
chainer | chainer-master/chainer/training/extensions/exponential_shift.py | from __future__ import division
import numpy
from chainer.training import extension
class ExponentialShift(extension.Extension):
"""Trainer extension to exponentially shift an optimizer attribute.
This extension exponentially increases or decreases the specified attribute
of the optimizer. The typical... | 3,023 | 35 | 79 | py |
chainer | chainer-master/chainer/training/extensions/linear_shift.py | from __future__ import division
import numpy
from chainer.training import extension
class LinearShift(extension.Extension):
"""Trainer extension to change an optimizer attribute linearly.
This extension changes an optimizer attribute from the first value to the
last value linearly within a specified d... | 2,786 | 33.8375 | 79 | py |
chainer | chainer-master/chainer/training/extensions/_snapshot.py | import os
import warnings
import chainer
from chainer.serializers import npz
from chainer.training import extension
from chainer.training.extensions import snapshot_writers
from chainer.utils import argument
def _find_snapshot_files(fmt, path):
'''Only prefix and suffix match
TODO(kuenishi): currently clean... | 16,835 | 38.801418 | 79 | py |
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