SYMBOL INDEX (1067 symbols across 93 files)

FILE: docs/conf.py
  class Mock (line 25) | class Mock(MagicMock):
    method __getattr__ (line 27) | def __getattr__(cls, name):

FILE: examples/plot_cheap_unet.py
  function label_transform (line 33) | def label_transform(x):
  function train_model (line 79) | def train_model(model, loaders, **kwargs):
  function predict (line 113) | def predict(trainer, test_loader,  save_dir=None):
  class CheapConv (line 164) | class CheapConv(nn.Module):
    method __init__ (line 165) | def __init__(self, in_channels, out_channels, activated):
    method forward (line 179) | def forward(self, x):
  class CheapConvBlock (line 186) | class CheapConvBlock(nn.Module):
    method __init__ (line 187) | def __init__(self, in_channels, out_channels, activated):
    method forward (line 199) | def forward(self, x):
  class MySimple2DCpUnet (line 213) | class MySimple2DCpUnet(UNetBase):
    method __init__ (line 214) | def __init__(self, in_channels, out_channels, depth=3, residual=False,...
    method conv_op_factory (line 218) | def conv_op_factory(self, in_channels, out_channels, part, index):

FILE: examples/plot_train_side_loss_unet.py
  class MySideLossUNet (line 39) | class MySideLossUNet(nn.Module):
    method __init__ (line 40) | def __init__(self, in_channels, out_channels, depth=3):
    method forward (line 80) | def forward(self, input):
  class MySideLoss (line 105) | class MySideLoss(nn.Module):
    method __init__ (line 109) | def __init__(self):
    method forward (line 116) | def forward(self, predictions, target):

FILE: examples/plot_unet_tutorial.py
  function label_transform (line 32) | def label_transform(x):
  function train_model (line 112) | def train_model(model, loaders, **kwargs):
  function predict (line 148) | def predict(trainer, test_loader,  save_dir=None):
  class MySimple2DUnet (line 206) | class MySimple2DUnet(UNetBase):
    method __init__ (line 207) | def __init__(self, in_channels, out_channels, depth=3, **kwargs):
    method conv_op_factory (line 211) | def conv_op_factory(self, in_channels, out_channels, part, index):
    method downsample_op_factory (line 242) | def downsample_op_factory(self, index):
    method upsample_op_factory (line 246) | def upsample_op_factory(self, index):

FILE: examples/regularized_mnist.py
  class RegularizedLinear (line 25) | class RegularizedLinear(nn.Linear):
    method __init__ (line 26) | def __init__(self, *args, ar_weight=1e-3, l1_weight=1e-3, **kwargs):
    method forward (line 32) | def forward(self, input):
  function model_fn (line 39) | def model_fn():
  function mnist_data_loaders (line 50) | def mnist_data_loaders(args):
  function train_model (line 68) | def train_model(args):
  function main (line 105) | def main(argv):

FILE: inferno/extensions/containers/graph.py
  class NNGraph (line 20) | class NNGraph(nx.DiGraph):
    method copy (line 27) | def copy(self, **init_kwargs):
  class Graph (line 51) | class Graph(nn.Module):
    method __init__ (line 81) | def __init__(self, graph=None):
    method graph (line 102) | def graph(self):
    method graph (line 116) | def graph(self, value):
    method is_node_in_graph (line 120) | def is_node_in_graph(self, name):
    method is_source_node (line 135) | def is_source_node(self, name):
    method is_sink_node (line 157) | def is_sink_node(self, name):
    method output_nodes (line 180) | def output_nodes(self):
    method input_nodes (line 194) | def input_nodes(self):
    method graph_is_valid (line 208) | def graph_is_valid(self):
    method assert_graph_is_valid (line 221) | def assert_graph_is_valid(self):
    method add_node (line 233) | def add_node(self, name, module, previous=None):
    method add_input_node (line 261) | def add_input_node(self, name):
    method add_output_node (line 280) | def add_output_node(self, name, previous=None):
    method add_edge (line 301) | def add_edge(self, from_node, to_node):
    method apply_on_graph (line 329) | def apply_on_graph(self, function, *args, **kwargs):
    method get_module_for_nodes (line 333) | def get_module_for_nodes(self, names):
    method to_device (line 358) | def to_device(self, names, target_device, device_ordinal=None, asynchr...
    method get_parameters_for_nodes (line 373) | def get_parameters_for_nodes(self, names, named=False):
    method clear_payloads (line 385) | def clear_payloads(self, graph=None):
    method forward_through_node (line 392) | def forward_through_node(self, name, input=None):
    method forward (line 445) | def forward(self, *inputs):

FILE: inferno/extensions/containers/sequential.py
  class Sequential1 (line 8) | class Sequential1(nn.Sequential):
    method __len__ (line 10) | def __len__(self):
  class Sequential2 (line 14) | class Sequential2(Sequential1):
    method forward (line 19) | def forward(self, *input):

FILE: inferno/extensions/criteria/core.py
  class Criteria (line 9) | class Criteria(nn.Module):
    method __init__ (line 11) | def __init__(self, *criteria):
    method forward (line 22) | def forward(self, prediction, target):
  class As2DCriterion (line 41) | class As2DCriterion(nn.Module):
    method __init__ (line 46) | def __init__(self, criterion):
    method forward (line 54) | def forward(self, prediction, target):

FILE: inferno/extensions/criteria/elementwise_measures.py
  class WeightedMSELoss (line 5) | class WeightedMSELoss(nn.Module):
    method __init__ (line 8) | def __init__(self, positive_class_weight=1., positive_class_value=1., ...
    method forward (line 18) | def forward(self, input, target):

FILE: inferno/extensions/criteria/regularized.py
  function collect_losses (line 18) | def collect_losses(module):
  function build_criterion (line 38) | def build_criterion(criterion, *args, **kwargs):
  class RegularizedLoss (line 61) | class RegularizedLoss(nn.Module):
    method __init__ (line 65) | def __init__(self, criterion, *args, **kwargs):
    method forward (line 69) | def forward(self, *args, trainer=None, model=None, **kwargs):
  class RegularizedCrossEntropyLoss (line 112) | class RegularizedCrossEntropyLoss(RegularizedLoss):
    method __init__ (line 113) | def __init__(self, *args, **kwargs):
  class RegularizedBCEWithLogitsLoss (line 117) | class RegularizedBCEWithLogitsLoss(RegularizedLoss):
    method __init__ (line 118) | def __init__(self, *args, **kwargs):
  class RegularizedBCELoss (line 122) | class RegularizedBCELoss(RegularizedLoss):
    method __init__ (line 123) | def __init__(self, *args, **kwargs):
  class RegularizedMSELoss (line 127) | class RegularizedMSELoss(RegularizedLoss):
    method __init__ (line 128) | def __init__(self, *args, **kwargs):
  class RegularizedNLLLoss (line 132) | class RegularizedNLLLoss(RegularizedLoss):
    method __init__ (line 133) | def __init__(self, *args, **kwargs):

FILE: inferno/extensions/criteria/set_similarity_measures.py
  class SorensenDiceLoss (line 7) | class SorensenDiceLoss(nn.Module):
    method __init__ (line 13) | def __init__(self, weight=None, channelwise=True, eps=1e-6):
    method forward (line 28) | def forward(self, input, target):
  class GeneralizedDiceLoss (line 63) | class GeneralizedDiceLoss(nn.Module):
    method __init__ (line 70) | def __init__(self, weight=None, channelwise=False, eps=1e-6):
    method forward (line 76) | def forward(self, input, target):

FILE: inferno/extensions/initializers/base.py
  class Initializer (line 11) | class Initializer(object):
    method __call__ (line 22) | def __call__(self, module):
    method call_on_bias (line 41) | def call_on_bias(self, tensor):
    method call_on_weight (line 44) | def call_on_weight(self, tensor):
    method call_on_tensor (line 47) | def call_on_tensor(self, tensor):
    method initializes_weight (line 51) | def initializes_weight(cls):
    method initializes_bias (line 55) | def initializes_bias(cls):
  class Initialization (line 59) | class Initialization(Initializer):
    method __init__ (line 60) | def __init__(self, weight_initializer=None, bias_initializer=None):
    method call_on_weight (line 90) | def call_on_weight(self, tensor):
    method call_on_bias (line 93) | def call_on_bias(self, tensor):
  class WeightInitFunction (line 97) | class WeightInitFunction(Initializer):
    method __init__ (line 98) | def __init__(self, init_function, *init_function_args, **init_function...
    method call_on_weight (line 105) | def call_on_weight(self, tensor):
  class BiasInitFunction (line 109) | class BiasInitFunction(Initializer):
    method __init__ (line 110) | def __init__(self, init_function, *init_function_args, **init_function...
    method call_on_bias (line 117) | def call_on_bias(self, tensor):
  class TensorInitFunction (line 121) | class TensorInitFunction(Initializer):
    method __init__ (line 122) | def __init__(self, init_function, *init_function_args, **init_function...
    method call_on_tensor (line 129) | def call_on_tensor(self, tensor):

FILE: inferno/extensions/initializers/presets.py
  class Constant (line 15) | class Constant(Initializer):
    method __init__ (line 17) | def __init__(self, constant):
    method call_on_tensor (line 20) | def call_on_tensor(self, tensor):
  class NormalWeights (line 25) | class NormalWeights(Initializer):
    method __init__ (line 30) | def __init__(self, mean=0., stddev=1., sqrt_gain_over_fan_in=None):
    method compute_fan_in (line 35) | def compute_fan_in(self, tensor):
    method call_on_weight (line 41) | def call_on_weight(self, tensor):
  class OrthogonalWeightsZeroBias (line 52) | class OrthogonalWeightsZeroBias(Initialization):
    method __init__ (line 53) | def __init__(self, orthogonal_gain=1.):
  class KaimingNormalWeightsZeroBias (line 61) | class KaimingNormalWeightsZeroBias(Initialization):
    method __init__ (line 62) | def __init__(self, relu_leakage=0):
  class SELUWeightsZeroBias (line 70) | class SELUWeightsZeroBias(Initialization):
    method __init__ (line 71) | def __init__(self):
  class ELUWeightsZeroBias (line 77) | class ELUWeightsZeroBias(Initialization):
    method __init__ (line 78) | def __init__(self):

FILE: inferno/extensions/layers/activations.py
  class SELU (line 8) | class SELU(nn.Module):
    method forward (line 9) | def forward(self, input):
    method selu (line 13) | def selu(x):

FILE: inferno/extensions/layers/convolutional.py
  class ConvActivation (line 24) | class ConvActivation(nn.Module):
    method __init__ (line 27) | def __init__(
    method forward (line 123) | def forward(self, input):
    method _pair_or_triplet (line 132) | def _pair_or_triplet(self, object_):
    method _get_padding (line 140) | def _get_padding(self, _kernel_size, _dilation):
    method get_padding (line 146) | def get_padding(self, kernel_size, dilation):
  class _BNReLUSomeConv (line 160) | class _BNReLUSomeConv(object):
    method forward (line 161) | def forward(self, input):
  class BNReLUConvBaseND (line 167) | class BNReLUConvBaseND(_BNReLUSomeConv, ConvActivation):
    method __init__ (line 168) | def __init__(self, in_channels, out_channels, kernel_size, dim, stride...
  function _register_conv_cls (line 184) | def _register_conv_cls(conv_name,  fix=None, default=None):
  function _register_bnr_conv_cls (line 225) | def _register_bnr_conv_cls(conv_name,  fix=None, default=None):
  class GlobalConv2D (line 264) | class GlobalConv2D(nn.Module):
    method __init__ (line 269) | def __init__(
    method forward (line 317) | def forward(self, input_):

FILE: inferno/extensions/layers/convolutional_blocks.py
  class ResidualBlock (line 10) | class ResidualBlock(nn.Module):
    method __init__ (line 11) | def __init__(self, layers, resample=None):
    method forward (line 17) | def forward(self, input):
  class PreActSimpleResidualBlock (line 27) | class PreActSimpleResidualBlock(ResidualBlock):
    method __init__ (line 28) | def __init__(self, in_channels, num_hidden_channels, upsample=False, d...

FILE: inferno/extensions/layers/device.py
  class DeviceTransfer (line 9) | class DeviceTransfer(nn.Module):
    method __init__ (line 11) | def __init__(self, target_device, device_ordinal=None, asynchronous=Fa...
    method forward (line 34) | def forward(self, *inputs):
  class OnDevice (line 46) | class OnDevice(nn.Module):
    method __init__ (line 52) | def __init__(self, module, target_device, device_ordinal=None, asynchr...
    method transfer_module (line 84) | def transfer_module(self, module):
    method forward (line 92) | def forward(self, *inputs):

FILE: inferno/extensions/layers/identity.py
  class Identity (line 5) | class Identity(nn.Module):
    method __init__ (line 6) | def __init__(self):
    method forward (line 9) | def forward(self, x):

FILE: inferno/extensions/layers/normalization.py
  class BatchNormND (line 4) | class BatchNormND(nn.Module):
    method __init__ (line 5) | def __init__(self, dim, num_features,
    method forward (line 13) | def forward(self, x):

FILE: inferno/extensions/layers/reshape.py
  class View (line 16) | class View(nn.Module):
    method __init__ (line 17) | def __init__(self, as_shape):
    method validate_as_shape (line 21) | def validate_as_shape(self, as_shape):
    method forward (line 30) | def forward(self, input):
  class AsMatrix (line 38) | class AsMatrix(View):
    method __init__ (line 39) | def __init__(self):
  class Flatten (line 43) | class Flatten(View):
    method __init__ (line 44) | def __init__(self):
  class As3D (line 48) | class As3D(nn.Module):
    method __init__ (line 49) | def __init__(self, channel_as_z=False, num_channels_or_num_z_slices=1):
    method forward (line 54) | def forward(self, input):
  class As2D (line 82) | class As2D(nn.Module):
    method __init__ (line 83) | def __init__(self, z_as_channel=True):
    method forward (line 87) | def forward(self, input):
  class Concatenate (line 103) | class Concatenate(nn.Module):
    method __init__ (line 105) | def __init__(self, dim=1):
    method forward (line 109) | def forward(self, *inputs):
  class ResizeAndConcatenate (line 113) | class ResizeAndConcatenate(nn.Module):
    method __init__ (line 125) | def __init__(self, target_size, pool_mode='average', dim=1):
    method forward (line 135) | def forward(self, *inputs):
  class Cat (line 164) | class Cat(Concatenate):
  class PoolCat (line 169) | class PoolCat(ResizeAndConcatenate):
  class GlobalMeanPooling (line 174) | class GlobalMeanPooling(ResizeAndConcatenate):
    method __init__ (line 176) | def __init__(self):
  class GlobalMaxPooling (line 180) | class GlobalMaxPooling(ResizeAndConcatenate):
    method __init__ (line 182) | def __init__(self):
  class Sum (line 186) | class Sum(nn.Module):
    method forward (line 188) | def forward(self, *inputs):
  class SplitChannels (line 192) | class SplitChannels(nn.Module):
    method __init__ (line 194) | def __init__(self, channel_index):
    method forward (line 198) | def forward(self, input):
  class Squeeze (line 212) | class Squeeze(nn.Module):
    method __init__ (line 213) | def __init__(self):
    method forward (line 215) | def  forward(self, x):
  class RemoveSingletonDimension (line 218) | class RemoveSingletonDimension(nn.Module):
    method __init__ (line 219) | def __init__(self, dim=1):
    method forward (line 222) | def  forward(self, x):

FILE: inferno/extensions/layers/sampling.py
  class Upsample (line 8) | class Upsample(nn.Module):
    method __init__ (line 9) | def __init__(self, size=None, scale_factor=None, mode='nearest', align...
    method forward (line 24) | def forward(self, input):
  class AnisotropicUpsample (line 32) | class AnisotropicUpsample(nn.Module):
    method __init__ (line 33) | def __init__(self, scale_factor):
    method forward (line 37) | def forward(self, input):
  class AnisotropicPool (line 52) | class AnisotropicPool(nn.MaxPool3d):
    method __init__ (line 53) | def __init__(self, downscale_factor):
  class AnisotropicUpsample2D (line 59) | class AnisotropicUpsample2D(nn.Module):
    method __init__ (line 60) | def __init__(self, scale_factor):
    method forward (line 64) | def forward(self, input):
  class AnisotropicPool2D (line 78) | class AnisotropicPool2D(nn.MaxPool2d):
    method __init__ (line 79) | def __init__(self, downscale_factor):

FILE: inferno/extensions/metrics/arand.py
  class ArandScore (line 7) | class ArandScore(Metric):
    method __init__ (line 14) | def __init__(self, average_slices=True):
    method _arand_for_tensor (line 18) | def _arand_for_tensor(self, prediction, target):
    method forward (line 49) | def forward(self, prediction, target):
  class ArandError (line 64) | class ArandError(ArandScore):
    method __init__ (line 66) | def __init__(self, **super_kwargs):
    method forward (line 69) | def forward(self, prediction, target):
  function adapted_rand (line 75) | def adapted_rand(seg, gt):

FILE: inferno/extensions/metrics/base.py
  class Metric (line 3) | class Metric(object):
    method forward (line 5) | def forward(self, *args, **kwargs):
    method __call__ (line 8) | def __call__(self, prediction, target, **kwargs):

FILE: inferno/extensions/metrics/categorical.py
  class CategoricalError (line 7) | class CategoricalError(Metric):
    method __init__ (line 9) | def __init__(self, aggregation_mode='mean'):
    method forward (line 13) | def forward(self, prediction, target):
  class IOU (line 42) | class IOU(Metric):
    method __init__ (line 44) | def __init__(self, ignore_class=None, sharpen_prediction=False, eps=1e...
    method forward (line 50) | def forward(self, prediction, target):
  class NegativeIOU (line 133) | class NegativeIOU(IOU):
    method forward (line 134) | def forward(self, prediction, target):

FILE: inferno/extensions/metrics/cremi_score.py
  function cremi_metrics (line 9) | def cremi_metrics(seg, gt, no_seg_ignore=True):

FILE: inferno/extensions/metrics/voi.py
  class VoiScore (line 7) | class VoiScore(Metric):
    method forward (line 15) | def forward(self, prediction, target):
  function voi (line 29) | def voi(seg, gt, ignore_reconstruction=[], ignore_groundtruth=[0]):
  function split_vi (line 65) | def split_vi(x, y=None, ignore_x=[0], ignore_y=[0]):
  function vi_tables (line 102) | def vi_tables(x, y=None, ignore_x=[0], ignore_y=[0]):
  function contingency_table (line 156) | def contingency_table(seg, gt, ignore_seg=[0], ignore_gt=[0], norm=True):
  function divide_columns (line 196) | def divide_columns(matrix, row, in_place=False):
  function divide_rows (line 235) | def divide_rows(matrix, column, in_place=False):
  function xlogx (line 274) | def xlogx(x, out=None, in_place=False):

FILE: inferno/extensions/models/res_unet.py
  class _ResBlockBase (line 15) | class _ResBlockBase(nn.Module):
    method __init__ (line 16) | def __init__(self, in_channels, out_channels, dim,
    method activated_skip_op_factory (line 50) | def activated_skip_op_factory(self, in_channels, out_channels):
    method nonactivated_conv_op_factory (line 53) | def nonactivated_conv_op_factory(self, in_channels, out_channels, index):
    method activation_op_factory (line 56) | def activation_op_factory(self, index):
    method forward (line 59) | def forward(self, input):
  class _ResBlock (line 90) | class _ResBlock(_ResBlockBase):
    method __init__ (line 91) | def __init__(self, in_channels, out_channels, dim, size=2, activated=T...
    method activated_skip_op_factory (line 130) | def activated_skip_op_factory(self, in_channels, out_channels):
    method nonactivated_conv_op_factory (line 139) | def nonactivated_conv_op_factory(self, in_channels, out_channels, index):
    method activation_op_factory (line 148) | def activation_op_factory(self, index):
    method batchnorm_op_factory (line 151) | def batchnorm_op_factory(self, in_channels):
  class ResBlockUNet (line 159) | class ResBlockUNet(UNetBase):
    method __init__ (line 171) | def __init__(self, in_channels, dim, out_channels, unet_kwargs=None,
    method conv_op_factory (line 192) | def conv_op_factory(self, in_channels, out_channels, part, index):

FILE: inferno/extensions/models/unet.py
  class UNetBase (line 13) | class UNetBase(nn.Module):
    method __init__ (line 38) | def __init__(self, in_channels, dim, out_channels=None, depth=3,
    method _get_num_channels (line 122) | def _get_num_channels(self, depth):
    method _init__downstream (line 126) | def _init__downstream(self):
    method _init__bottom (line 152) | def _init__bottom(self):
    method _init__upstream (line 166) | def _init__upstream(self):
    method _make_upsample_kwargs (line 201) | def _make_upsample_kwargs(self, upsample_mode):
    method _forward_sanity_check (line 220) | def _forward_sanity_check(self, input):
    method _check_scaling (line 235) | def _check_scaling(self, input):
    method forward (line 242) | def forward(self, input):
    method downsample_op_factory (line 308) | def downsample_op_factory(self, index):
    method upsample_op_factory (line 312) | def upsample_op_factory(self, index):\
    method conv_op_factory (line 316) | def conv_op_factory(self, in_channels, out_channels, part, index):
    method _dropout (line 319) | def _dropout(self, x):
  class UNet (line 327) | class UNet(UNetBase):
    method __init__ (line 332) | def __init__(self, in_channels, out_channels, dim,
    method forward (line 364) | def forward(self, input):
    method conv_op_factory (line 370) | def conv_op_factory(self, in_channels, out_channels, part, index):

FILE: inferno/extensions/optimizers/adam.py
  class Adam (line 5) | class Adam(Optimizer):
    method __init__ (line 24) | def __init__(self, params, lr=1e-3, betas=(0.9, 0.999), eps=1e-8,
    method step (line 31) | def step(self, closure=None):

FILE: inferno/extensions/optimizers/annealed_adam.py
  class AnnealedAdam (line 4) | class AnnealedAdam(Adam):
    method __init__ (line 26) | def __init__(self, params, lr=1e-3, betas=(0.9, 0.999), eps=1e-8,
    method step (line 33) | def step(self, closure=None):

FILE: inferno/io/box/binary_blobs.py
  class BinaryBlobs (line 7) | class BinaryBlobs(data.Dataset):
    method __init__ (line 10) | def __init__(self, size=20, length=512, blob_size_fraction=0.1,
    method __getitem__ (line 44) | def __getitem__(self, index):
    method __len__ (line 108) | def __len__(self):
  function get_binary_blob_loaders (line 112) | def get_binary_blob_loaders(train_batch_size=1, test_batch_size=1,

FILE: inferno/io/box/camvid.py
  function is_image_file (line 22) | def is_image_file(filename):
  function make_dataset (line 74) | def make_dataset(dir):
  function label_to_long_tensor (line 85) | def label_to_long_tensor(pic):
  function label_to_pil_image (line 92) | def label_to_pil_image(label):
  class CamVid (line 109) | class CamVid(data.Dataset):
    method __init__ (line 123) | def __init__(self, root, split='train',
    method __getitem__ (line 145) | def __getitem__(self, index):
    method __len__ (line 158) | def __len__(self):
    method download (line 161) | def download(self):
  function get_camvid_loaders (line 168) | def get_camvid_loaders(root_directory, image_shape=(360, 480), labels_as...

FILE: inferno/io/box/cifar.py
  function get_cifar10_loaders (line 8) | def get_cifar10_loaders(root_directory, train_batch_size=128, test_batch...
  function get_cifar100_loaders (line 64) | def get_cifar100_loaders(root_directory, train_batch_size=128, test_batc...

FILE: inferno/io/box/cityscapes.py
  function get_matching_labelimage_file (line 173) | def get_matching_labelimage_file(f, groundtruth):
  function get_filelist (line 180) | def get_filelist(path):
  function make_dataset (line 190) | def make_dataset(path, split):
  function extract_image (line 211) | def extract_image(path, image_path):
  class Cityscapes (line 219) | class Cityscapes(data.Dataset):
    method __init__ (line 237) | def __init__(self, root_folder, split='train', read_from_zip_archive=T...
    method __getitem__ (line 263) | def __getitem__(self, index):
    method __len__ (line 284) | def __len__(self):
    method download (line 287) | def download(self):
    method get_image_and_label_roots (line 292) | def get_image_and_label_roots(self):
  function make_transforms (line 312) | def make_transforms(image_shape, labels_as_onehot):
  function get_cityscapes_loaders (line 351) | def get_cityscapes_loaders(root_directory, image_shape=(1024, 2048), lab...

FILE: inferno/io/core/base.py
  class SyncableDataset (line 4) | class SyncableDataset(Dataset):
    method __init__ (line 5) | def __init__(self, base_sequence=None):
    method sync_with (line 8) | def sync_with(self, dataset):
    method __len__ (line 13) | def __len__(self):
  class IndexSpec (line 22) | class IndexSpec(object):
    method __init__ (line 28) | def __init__(self, index=None, base_sequence_at_index=None):
    method __int__ (line 32) | def __int__(self):

FILE: inferno/io/core/concatenate.py
  class Concatenate (line 6) | class Concatenate(Dataset):
    method __init__ (line 11) | def __init__(self, *datasets, transforms=None):
    method map_index (line 18) | def map_index(self, index):
    method __getitem__ (line 40) | def __getitem__(self, index):
    method __len__ (line 51) | def __len__(self):
    method __repr__ (line 54) | def __repr__(self):

FILE: inferno/io/core/data_utils.py
  function implements_sync_primitives (line 2) | def implements_sync_primitives(dataset):
  function defines_base_sequence (line 6) | def defines_base_sequence(dataset):

FILE: inferno/io/core/zip.py
  class Zip (line 11) | class Zip(SyncableDataset):
    method __init__ (line 17) | def __init__(self, *datasets, sync=False, transforms=None):
    method sync_datasets (line 40) | def sync_datasets(self):
    method sync_with (line 46) | def sync_with(self, dataset):
    method __getitem__ (line 53) | def __getitem__(self, index):
    method __len__ (line 63) | def __len__(self):
    method __repr__ (line 69) | def __repr__(self):
  class ZipReject (line 79) | class ZipReject(Zip):
    method __init__ (line 85) | def __init__(self, *datasets, sync=False, transforms=None,
    method remove_rejected (line 131) | def remove_rejected(self):
    method __len__ (line 140) | def __len__(self):
    method next_index_to_try (line 147) | def next_index_to_try(self, index):
    method fetch_from_rejection_datasets (line 153) | def fetch_from_rejection_datasets(self, index):
    method __getitem__ (line 158) | def __getitem__(self, index):

FILE: inferno/io/transform/base.py
  class Transform (line 5) | class Transform(object):
    method __init__ (line 20) | def __init__(self, apply_to=None):
    method build_random_variables (line 31) | def build_random_variables(self, **kwargs):
    method clear_random_variables (line 34) | def clear_random_variables(self):
    method get_random_variable (line 37) | def get_random_variable(self, key, default=None, build=True,
    method set_random_variable (line 48) | def set_random_variable(self, key, value):
    method __call__ (line 51) | def __call__(self, *tensors, **transform_function_kwargs):
    method _apply_tensor_function (line 81) | def _apply_tensor_function(self, tensor, **transform_function_kwargs):
    method _apply_image_function (line 87) | def _apply_image_function(self, tensor, **transform_function_kwargs):
    method _apply_volume_function (line 115) | def _apply_volume_function(self, tensor, **transform_function_kwargs):
  class Compose (line 142) | class Compose(object):
    method __init__ (line 144) | def __init__(self, *transforms):
    method add (line 154) | def add(self, transform):
    method remove (line 159) | def remove(self, name):
    method __call__ (line 169) | def __call__(self, *tensors):
  class DTypeMapping (line 176) | class DTypeMapping(object):

FILE: inferno/io/transform/generic.py
  class Normalize (line 7) | class Normalize(Transform):
    method __init__ (line 9) | def __init__(self, eps=1e-4, mean=None, std=None, ignore_value=None, *...
    method tensor_function (line 28) | def tensor_function(self, tensor):
  class NormalizeRange (line 50) | class NormalizeRange(Transform):
    method __init__ (line 52) | def __init__(self, normalize_by=255., **super_kwargs):
    method tensor_function (line 64) | def tensor_function(self, tensor):
  class Project (line 68) | class Project(Transform):
    method __init__ (line 74) | def __init__(self, projection, **super_kwargs):
    method tensor_function (line 86) | def tensor_function(self, tensor):
  class Label2OneHot (line 93) | class Label2OneHot(Transform, DTypeMapping):
    method __init__ (line 95) | def __init__(self, num_classes, dtype='float', **super_kwargs):
    method tensor_function (line 110) | def tensor_function(self, tensor):
  class Cast (line 121) | class Cast(Transform, DTypeMapping):
    method __init__ (line 123) | def __init__(self, dtype='float', **super_kwargs):
    method tensor_function (line 136) | def tensor_function(self, tensor):
  class AsTorchBatch (line 140) | class AsTorchBatch(Transform):
    method __init__ (line 148) | def __init__(self, dimensionality, add_channel_axis_if_necessary=True,...
    method _to_batch (line 167) | def _to_batch(self, tensor):
    method tensor_function (line 196) | def tensor_function(self, tensor):

FILE: inferno/io/transform/image.py
  class PILImage2NumPyArray (line 13) | class PILImage2NumPyArray(Transform):
    method tensor_function (line 19) | def tensor_function(self, tensor):
  class Scale (line 33) | class Scale(Transform):
    method __init__ (line 44) | def __init__(self, output_image_shape, interpolation_order=3, zoom_kwa...
    method image_function (line 69) | def image_function(self, image):
  class RandomCrop (line 87) | class RandomCrop(Transform):
    method __init__ (line 99) | def __init__(self, output_image_shape, **super_kwargs):
    method clear_random_variables (line 122) | def clear_random_variables(self):
    method build_random_variables (line 126) | def build_random_variables(self, height_leeway, width_leeway):
    method image_function (line 134) | def image_function(self, image):
  class RandomSizedCrop (line 168) | class RandomSizedCrop(Transform):
    method __init__ (line 175) | def __init__(self, ratio_between=None, height_ratio_between=None, widt...
    method build_random_variables (line 222) | def build_random_variables(self, image_shape):
    method image_function (line 252) | def image_function(self, image):
  class RandomGammaCorrection (line 282) | class RandomGammaCorrection(Transform):
    method __init__ (line 291) | def __init__(self, gamma_between=(0.5, 2.), gain=1, **super_kwargs):
    method build_random_variables (line 306) | def build_random_variables(self):
    method image_function (line 312) | def image_function(self, image):
  class ElasticTransform (line 319) | class ElasticTransform(Transform):
    method __init__ (line 324) | def __init__(self, alpha, sigma, order=1, invert=False, **super_kwargs):
    method build_random_variables (line 332) | def build_random_variables(self, **kwargs):
    method cast (line 352) | def cast(self, image):
    method uncast (line 358) | def uncast(self, image):
    method image_function (line 364) | def image_function(self, image):
  class AdditiveGaussianNoise (line 380) | class AdditiveGaussianNoise(Transform):
    method __init__ (line 382) | def __init__(self, sigma, **super_kwargs):
    method build_random_variables (line 386) | def build_random_variables(self, **kwargs):
    method image_function (line 391) | def image_function(self, image):
  class RandomRotate (line 396) | class RandomRotate(Transform):
    method __init__ (line 398) | def __init__(self, **super_kwargs):
    method build_random_variables (line 401) | def build_random_variables(self, **kwargs):
    method image_function (line 405) | def image_function(self, image):
  class RandomTranspose (line 409) | class RandomTranspose(Transform):
    method __init__ (line 411) | def __init__(self, **super_kwargs):
    method build_random_variables (line 414) | def build_random_variables(self, **kwargs):
    method image_function (line 418) | def image_function(self, image):
  class RandomFlip (line 424) | class RandomFlip(Transform):
    method __init__ (line 426) | def __init__(self, allow_lr_flips=True, allow_ud_flips=True, **super_k...
    method build_random_variables (line 431) | def build_random_variables(self, **kwargs):
    method image_function (line 436) | def image_function(self, image):
  class CenterCrop (line 444) | class CenterCrop(Transform):
    method __init__ (line 446) | def __init__(self, size, **super_kwargs):
    method image_function (line 451) | def image_function(self, image):
  class BinaryMorphology (line 463) | class BinaryMorphology(Transform):
    method __init__ (line 468) | def __init__(self, mode, num_iterations=1, morphology_kwargs=None, **s...
    method image_function (line 492) | def image_function(self, image):
  class BinaryDilation (line 505) | class BinaryDilation(BinaryMorphology):
    method __init__ (line 507) | def __init__(self, num_iterations=1, morphology_kwargs=None, **super_k...
  class BinaryErosion (line 513) | class BinaryErosion(BinaryMorphology):
    method __init__ (line 515) | def __init__(self, num_iterations=1, morphology_kwargs=None, **super_k...
  class FineRandomRotations (line 521) | class FineRandomRotations(Transform):
    method __init__ (line 533) | def __init__(self, angle_range, axes=(1,2), mask_label=0, **super_kwar...
    method build_random_variables (line 539) | def build_random_variables(self):
    method batch_function (line 545) | def batch_function(self, image):
  class RandomScaleSegmentation (line 551) | class RandomScaleSegmentation(Transform):
    method __init__ (line 561) | def __init__(self, scale_range, resize=True, pad_const=0, **super_kwar...
    method build_random_variables (line 567) | def build_random_variables(self):
    method batch_function (line 573) | def batch_function(self, image):

FILE: inferno/io/transform/volume.py
  class RandomFlip3D (line 9) | class RandomFlip3D(Transform):
    method __init__ (line 10) | def __init__(self, **super_kwargs):
    method build_random_variables (line 13) | def build_random_variables(self, **kwargs):
    method volume_function (line 19) | def volume_function(self, volume):
  class RandomRot3D (line 29) | class RandomRot3D(Transform):
    method __init__ (line 30) | def __init__(self, rot_range, p=0.125, reshape=False, order=0, mode='n...
    method build_random_variables (line 38) | def build_random_variables(self, **kwargs):
    method volume_function (line 49) | def volume_function(self, volume):
  class AdditiveRandomNoise3D (line 73) | class AdditiveRandomNoise3D(Transform):
    method __init__ (line 83) | def __init__(self, shape, std, **super_kwargs):
    method build_random_variables (line 88) | def build_random_variables(self, **kwargs):
    method volume_function (line 93) | def volume_function(self, volume):
  class AdditiveNoise (line 99) | class AdditiveNoise(Transform):
    method __init__ (line 109) | def __init__(self, sigma, mode='gaussian', **super_kwargs):
    method tensor_function (line 115) | def tensor_function(self, volume):
  class CentralSlice (line 120) | class CentralSlice(Transform):
    method volume_function (line 121) | def volume_function(self, volume):
  class VolumeCenterCrop (line 126) | class VolumeCenterCrop(Transform):
    method __init__ (line 128) | def __init__(self, size, **super_kwargs):
    method volume_function (line 134) | def volume_function(self, volume):
  class VolumeAsymmetricCrop (line 143) | class VolumeAsymmetricCrop(Transform):
    method __init__ (line 145) | def __init__(self, crop_left, crop_right, **super_kwargs):
    method volume_function (line 154) | def volume_function(self, volume):
  class Slices2Channels (line 160) | class Slices2Channels(Transform):
    method __init__ (line 164) | def __init__(self, num_channels, downsampling=1, **super_kwargs):
    method batch_function (line 169) | def batch_function(self, batch):
  class RandomScale3D (line 187) | class RandomScale3D(Transform):
    method __init__ (line 189) | def __init__(self, zoom_factor_range, interpolation_order=0, p=0.5,
    method build_random_variables (line 218) | def build_random_variables(self, **kwargs):
    method volume_function (line 227) | def volume_function(self, volume):
  class RandomBinaryMorphology3D (line 243) | class RandomBinaryMorphology3D(Transform):
    method __init__ (line 248) | def __init__(self, p=0.5, num_iter_range=(1, 5), morphology_kwargs=Non...
    method build_random_variables (line 272) | def build_random_variables(self, **kwargs):
    method volume_function (line 278) | def volume_function(self, volume):
  class CropPad2Divisible (line 295) | class CropPad2Divisible(Transform):
    method __init__ (line 302) | def __init__(self, divisor=16, crop_pad_threshold=0.2,
    method volume_function (line 330) | def volume_function(self, volume):
  class CropPad2Size (line 349) | class CropPad2Size(Transform):
    method __init__ (line 354) | def __init__(self, output_size, mode='constant',
    method volume_function (line 375) | def volume_function(self, volume):

FILE: inferno/io/volumetric/lazy_volume_loader.py
  function filter_base_sequence (line 26) | def filter_base_sequence(input_path, input_key,
  class LazyVolumeLoaderBase (line 54) | class LazyVolumeLoaderBase(SyncableDataset):
    method __init__ (line 55) | def __init__(self, dataset, window_size, stride, downsampling_ratio=No...
    method load_base_sequence (line 98) | def load_base_sequence(base_sequence):
    method normalize_slice (line 109) | def normalize_slice(self, data_slice):
    method get_shape (line 120) | def get_shape(self):
    method make_sliding_windows (line 131) | def make_sliding_windows(self):
    method __getitem__ (line 139) | def __getitem__(self, index):
    method clone (line 200) | def clone(self, dataset=None, transforms=None, name=None):
    method __repr__ (line 216) | def __repr__(self):
  class LazyVolumeLoader (line 221) | class LazyVolumeLoader(LazyVolumeLoaderBase):
    method __init__ (line 222) | def __init__(self, file_impl, path,
    method validate_data_slice (line 269) | def validate_data_slice(self, data_slice):
  class LazyHDF5VolumeLoader (line 274) | class LazyHDF5VolumeLoader(LazyVolumeLoader):
    method __init__ (line 275) | def __init__(self, path, path_in_h5_dataset=None, data_slice=None, tra...
    method __del__ (line 284) | def __del__(self):
  class LazyN5VolumeLoader (line 288) | class LazyN5VolumeLoader(LazyVolumeLoader):
    method __init__ (line 289) | def __init__(self, path, path_in_file=None, data_slice=None, transform...
  class LazyZarrVolumeLoader (line 301) | class LazyZarrVolumeLoader(LazyVolumeLoader):
    method __init__ (line 302) | def __init__(self, path, path_in_file=None, data_slice=None, transform...

FILE: inferno/io/volumetric/volume.py
  class VolumeLoader (line 13) | class VolumeLoader(SyncableDataset):
    method __init__ (line 40) | def __init__(self, volume, window_size, stride, downsampling_ratio=Non...
    method pad_volume (line 94) | def pad_volume(self, padding=None):
    method make_sliding_windows (line 108) | def make_sliding_windows(self):
    method __getitem__ (line 117) | def __getitem__(self, index):
    method clone (line 133) | def clone(self, volume=None, transforms=None, name=None):
    method __repr__ (line 149) | def __repr__(self):
  class HDF5VolumeLoader (line 153) | class HDF5VolumeLoader(VolumeLoader):
    method is_h5 (line 182) | def is_h5(file_path):
    method __init__ (line 191) | def __init__(self, path, path_in_h5_dataset=None, data_slice=None, tra...
  class TIFVolumeLoader (line 246) | class TIFVolumeLoader(VolumeLoader):
    method __init__ (line 248) | def __init__(self, path, data_slice=None, transforms=None, name=None, ...

FILE: inferno/io/volumetric/volumetric_utils.py
  function slidingwindowslices (line 5) | def slidingwindowslices(shape, window_size, strides,
  function slidingwindowslices_depr (line 63) | def slidingwindowslices_depr(shape, nhoodsize, stride=1, ds=1, window=No...
  function parse_data_slice (line 137) | def parse_data_slice(data_slice):

FILE: inferno/trainers/basic.py
  class Trainer (line 39) | class Trainer(object):
    method __init__ (line 56) | def __init__(self, model=None):
    method mixed_precision (line 148) | def mixed_precision(self):
    method mixed_precision (line 153) | def mixed_precision(self, mp):
    method apex_opt_level (line 167) | def apex_opt_level(self):
    method apex_opt_level (line 171) | def apex_opt_level(self, opt_level):
    method console (line 177) | def console(self):
    method set_console (line 181) | def set_console(self, console):
    method quiet (line 186) | def quiet(self):
    method callbacks (line 191) | def callbacks(self):
    method register_callback (line 195) | def register_callback(self, callback, trigger='auto', **callback_kwargs):
    method model (line 221) | def model(self):
    method model (line 227) | def model(self, value):
    method bind_model (line 230) | def bind_model(self, model):
    method model_is_defined (line 254) | def model_is_defined(self):
    method retain_graph (line 258) | def retain_graph(self):
    method retain_graph (line 262) | def retain_graph(self, value):
    method backprop_every (line 267) | def backprop_every(self):
    method backprop_every (line 271) | def backprop_every(self, value):
    method set_backprop_every (line 274) | def set_backprop_every(self, num_steps):
    method optimizer (line 293) | def optimizer(self):
    method optimizer (line 299) | def optimizer(self, value):
    method optimizer_is_defined (line 308) | def optimizer_is_defined(self):
    method build_optimizer (line 311) | def build_optimizer(self, method, param_groups=None, **kwargs):
    method criterion (line 357) | def criterion(self):
    method criterion (line 363) | def criterion(self, value):
    method build_criterion (line 372) | def build_criterion(self, method, **kwargs):
    method criterion_is_defined (line 426) | def criterion_is_defined(self):
    method validation_criterion (line 430) | def validation_criterion(self):
    method validation_criterion (line 437) | def validation_criterion(self, value):
    method build_validation_criterion (line 446) | def build_validation_criterion(self, method, **kwargs):
    method validation_criterion_is_train_criterion (line 499) | def validation_criterion_is_train_criterion(self, yes=True):
    method validation_criterion_is_defined (line 506) | def validation_criterion_is_defined(self):
    method metric (line 510) | def metric(self):
    method metric (line 516) | def metric(self, value):
    method evaluating_metric_every (line 523) | def evaluating_metric_every(self):
    method evaluate_metric_every (line 526) | def evaluate_metric_every(self, frequency):
    method evaluate_metric_now (line 547) | def evaluate_metric_now(self):
    method evaluate_metric_now (line 568) | def evaluate_metric_now(self, value):
    method build_metric (line 571) | def build_metric(self, method, **kwargs):
    method metric_is_defined (line 608) | def metric_is_defined(self):
    method eval_mode (line 612) | def eval_mode(self):
    method train_mode (line 622) | def train_mode(self):
    method train_loader (line 633) | def train_loader(self):
    method train_loader (line 638) | def train_loader(self, value):
    method validate_loader (line 643) | def validate_loader(self):
    method validate_loader (line 648) | def validate_loader(self, value):
    method logger (line 653) | def logger(self):
    method logger (line 658) | def logger(self, value):
    method log_directory (line 665) | def log_directory(self):
    method log_directory (line 670) | def log_directory(self, value):
    method pickle_module (line 676) | def pickle_module(self):
    method pickle_module (line 684) | def pickle_module(self, value):
    method saving_every (line 692) | def saving_every(self):
    method save_at_best_validation_score (line 696) | def save_at_best_validation_score(self, yes=True):
    method save_now (line 702) | def save_now(self):
    method save_now (line 725) | def save_now(self, value):
    method save_every (line 729) | def save_every(self, frequency, to_directory=None,
    method save_directory (line 755) | def save_directory(self):
    method save_to_directory (line 758) | def save_to_directory(self, to_directory=None, checkpoint_filename=None,
    method validating_every (line 776) | def validating_every(self):
    method validate_now (line 780) | def validate_now(self):
    method validate_now (line 805) | def validate_now(self, value):
    method validate_every (line 808) | def validate_every(self, frequency, for_num_iterations=None):
    method iteration_count (line 833) | def iteration_count(self):
    method epoch_count (line 837) | def epoch_count(self):
    method target_batch_dim (line 841) | def target_batch_dim(self):
    method target_batch_dim (line 845) | def target_batch_dim(self, value):
    method set_target_batch_dim (line 851) | def set_target_batch_dim(self, value):
    method build_logger (line 855) | def build_logger(self, logger=None, log_directory=None, **kwargs):
    method set_log_directory (line 893) | def set_log_directory(self, log_directory):
    method update_state (line 917) | def update_state(self, key, value):
    method update_state_from_dictionary (line 923) | def update_state_from_dictionary(self, dictionary):
    method update_state_from_model_state_hooks (line 929) | def update_state_from_model_state_hooks(self):
    method get_state (line 935) | def get_state(self, key, default=None):
    method current_learning_rate (line 942) | def current_learning_rate(self):
    method get_current_learning_rate (line 945) | def get_current_learning_rate(self):
    method to (line 960) | def to(self, device):
    method cuda (line 976) | def cuda(self, devices=None, base_device=None):
    method cpu (line 1019) | def cpu(self):
    method is_cuda (line 1036) | def is_cuda(self):
    method to_device (line 1040) | def to_device(self, objects):
    method apply_model (line 1046) | def apply_model(self, *inputs):
    method cast (line 1058) | def cast(self, objects):
    method set_precision (line 1073) | def set_precision(self, dtype):
    method dtype (line 1093) | def dtype(self):
    method dtype (line 1097) | def dtype(self, value):
    method bind_loader (line 1100) | def bind_loader(self, name, loader, num_inputs=None, num_targets=1):
    method get_loader_specs (line 1151) | def get_loader_specs(self, name):
    method fetch_next_batch (line 1157) | def fetch_next_batch(self, from_loader='train', restart_exhausted_gene...
    method verify_batch (line 1183) | def verify_batch(self, batch, from_loader):
    method split_batch (line 1201) | def split_batch(self, batch, from_loader):
    method restart_generators (line 1219) | def restart_generators(self, of_loader=None):
    method wrap_batch (line 1231) | def wrap_batch(self, batch, from_loader=None, requires_grad=False):
    method next_iteration (line 1277) | def next_iteration(self):
    method next_epoch (line 1280) | def next_epoch(self):
    method stop_fitting (line 1294) | def stop_fitting(self, max_num_iterations=None, max_num_epochs=None):
    method set_max_num_iterations (line 1313) | def set_max_num_iterations(self, max_num_iterations):
    method set_max_num_epochs (line 1338) | def set_max_num_epochs(self, max_num_epochs):
    method fit (line 1361) | def fit(self, max_num_iterations=None, max_num_epochs=None):
    method apply_model_and_loss (line 1426) | def apply_model_and_loss(self, inputs, target, backward=True, mode=None):
    method train_for (line 1457) | def train_for(self, num_iterations=None, break_callback=None):
    method validate_for (line 1535) | def validate_for(self, num_iterations=None, loader_name='validate'):
    method record_validation_results (line 1657) | def record_validation_results(self, validation_loss, validation_error):
    method get_config (line 1671) | def get_config(self, exclude_loader=True):
    method set_config (line 1683) | def set_config(self, config_dict):
    method save (line 1692) | def save(self, exclude_loader=True, stash_best_checkpoint=True):
    method save_model (line 1731) | def save_model(self, to_directory=None):
    method load (line 1739) | def load(self, from_directory=None, best=False, filename=None, map_loc...
    method load_model (line 1776) | def load_model(self, from_directory=None, filename=None):
    method load_ (line 1786) | def load_(self, *args, **kwargs):
    method print (line 1791) | def print(self, message):
    method build (line 1795) | def build(cls, model=None, **trainer_config):

FILE: inferno/trainers/callbacks/base.py
  class CallbackEngine (line 4) | class CallbackEngine(object):
    method __init__ (line 46) | def __init__(self):
    method register_new_trigger (line 52) | def register_new_trigger(self, trigger_name):
    method bind_trainer (line 56) | def bind_trainer(self, trainer):
    method unbind_trainer (line 60) | def unbind_trainer(self):
    method trainer_is_bound (line 65) | def trainer_is_bound(self):
    method register_callback (line 68) | def register_callback(self, callback, trigger='auto', bind_trainer=True):
    method rebind_trainer_to_all_callbacks (line 92) | def rebind_trainer_to_all_callbacks(self):
    method call (line 103) | def call(self, trigger, **kwargs):
    method get_config (line 109) | def get_config(self):
    method set_config (line 115) | def set_config(self, config_dict):
    method __getstate__ (line 119) | def __getstate__(self):
    method __setstate__ (line 122) | def __setstate__(self, state):
  class Callback (line 126) | class Callback(object):
    method __init__ (line 128) | def __init__(self):
    method register_instance (line 134) | def register_instance(cls, instance):
    method get_instances (line 141) | def get_instances(cls):
    method trainer (line 148) | def trainer(self):
    method bind_trainer (line 151) | def bind_trainer(self, trainer):
    method unbind_trainer (line 155) | def unbind_trainer(self):
    method __call__ (line 159) | def __call__(self, **kwargs):
    method get_config (line 165) | def get_config(self):
    method set_config (line 170) | def set_config(self, config_dict):
    method __getstate__ (line 174) | def __getstate__(self):
    method __setstate__ (line 177) | def __setstate__(self, state):
    method toggle_debug (line 180) | def toggle_debug(self):
    method debug_print (line 184) | def debug_print(self, message):

FILE: inferno/trainers/callbacks/console.py
  class StdoutPrinter (line 4) | class StdoutPrinter(object):
    method print (line 5) | def print(self, message):
  class Console (line 9) | class Console(object):
    method __init__ (line 15) | def __init__(self, printer=StdoutPrinter()):
    method set_console (line 19) | def set_console(self, console):
    method _print (line 22) | def _print(self, message, level):
    method info (line 28) | def info(self, message):
    method print (line 31) | def print(self, message):
    method progress (line 34) | def progress(self, message):
    method warning (line 37) | def warning(self, message):
    method debug (line 40) | def debug(self, message):
    method _toggle (line 43) | def _toggle(self, level, state):
    method toggle_info (line 50) | def toggle_info(self, state):
    method toggle_progress (line 53) | def toggle_progress(self, state):
    method toggle_warning (line 56) | def toggle_warning(self, state):
  class ShowMinimalConsoleInfo (line 61) | class ShowMinimalConsoleInfo(Callback):
    method __init__ (line 67) | def __init__(self, *args, **kwargs):
    method begin_of_fit (line 70) | def begin_of_fit(self,**_):
    method end_of_epoch (line 73) | def end_of_epoch(self, **_):

FILE: inferno/trainers/callbacks/essentials.py
  class NaNDetector (line 12) | class NaNDetector(Callback):
    method end_of_training_iteration (line 13) | def end_of_training_iteration(self, **_):
  class PersistentSave (line 22) | class PersistentSave(Callback):
    method __init__ (line 23) | def __init__(self, template='checkpoint.pytorch.epoch{epoch_count}.ite...
    method begin_of_save (line 27) | def begin_of_save(self, **kwargs):
    method end_of_save (line 31) | def end_of_save(self, save_to_directory, **_):
  class DumpHDF5Every (line 41) | class DumpHDF5Every(Callback):
    method __init__ (line 43) | def __init__(self, frequency, to_directory,
    method dump_every (line 64) | def dump_every(self):
    method dump_every (line 68) | def dump_every(self, value):
    method dump_now (line 75) | def dump_now(self):
    method add_to_dump_cache (line 80) | def add_to_dump_cache(self, key, value):
    method clear_dump_cache (line 87) | def clear_dump_cache(self):
    method dump_state (line 90) | def dump_state(self, key, dump_while='training'):
    method dump_states (line 113) | def dump_states(self, keys, dump_while='training'):
    method get_file_path (line 118) | def get_file_path(self, mode):
    method dump (line 131) | def dump(self, mode):
    method end_of_training_iteration (line 147) | def end_of_training_iteration(self, **_):
    method end_of_validation_run (line 160) | def end_of_validation_run(self, **_):
  class SaveAtBestValidationScore (line 173) | class SaveAtBestValidationScore(Callback):
    method __init__ (line 179) | def __init__(self, smoothness=0, verbose=False):
    method end_of_validation_run (line 188) | def end_of_validation_run(self, **_):
  class ParameterEMA (line 223) | class ParameterEMA(Callback):
    method __init__ (line 225) | def __init__(self, momentum):
    method maintain (line 239) | def maintain(self):
    method apply (line 245) | def apply(self):
    method end_of_training_iteration (line 252) | def end_of_training_iteration(self, **_):
  class GradientClip (line 256) | class GradientClip(Callback):
    method __init__ (line 257) | def __init__(self, clip_value=None, clip_norm=None):
    method mode (line 270) | def mode(self):
    method norm_or_value (line 274) | def norm_or_value(self):
    method after_model_and_loss_is_applied (line 277) | def after_model_and_loss_is_applied(self, **_):
  class GarbageCollection (line 281) | class GarbageCollection(Callback):
    method end_of_training_iteration (line 287) | def end_of_training_iteration(self, **_):

FILE: inferno/trainers/callbacks/gradients.py
  class LogOutputGradients (line 6) | class LogOutputGradients(Callback):
    method __init__ (line 9) | def __init__(self, frequency):
    method log_every (line 16) | def log_every(self):
    method log_every (line 20) | def log_every(self, value):
    method hook (line 26) | def hook(self, module, grad_input, grad_output):
    method add_hook (line 38) | def add_hook(self):
    method begin_of_fit (line 41) | def begin_of_fit(self, **kwargs):
    method begin_of_save (line 46) | def begin_of_save(self, **_):
    method end_of_save (line 52) | def end_of_save(self, **_):

FILE: inferno/trainers/callbacks/logging/__init__.py
  function get_logger (line 10) | def get_logger(name):

FILE: inferno/trainers/callbacks/logging/base.py
  class Logger (line 5) | class Logger(Callback):
    method __init__ (line 13) | def __init__(self, log_directory=None):
    method log_directory (line 20) | def log_directory(self):
    method log_directory (line 29) | def log_directory(self, value):
    method set_log_directory (line 32) | def set_log_directory(self, log_directory):

FILE: inferno/trainers/callbacks/logging/tensorboard.py
  class TaggedImage (line 12) | class TaggedImage(object):
    method __init__ (line 13) | def __init__(self, array, tag):
  class TensorboardLogger (line 18) | class TensorboardLogger(Logger):
    method __init__ (line 27) | def __init__(self, log_directory=None,
    method writer (line 85) | def writer(self):
    method log_scalars_every (line 91) | def log_scalars_every(self):
    method log_scalars_every (line 97) | def log_scalars_every(self, value):
    method log_scalars_now (line 101) | def log_scalars_now(self):
    method log_images_every (line 109) | def log_images_every(self):
    method log_images_every (line 115) | def log_images_every(self, value):
    method log_images_now (line 119) | def log_images_now(self):
    method log_histograms_every (line 127) | def log_histograms_every(self):
    method log_histograms_every (line 133) | def log_histograms_every(self, value):
    method log_histograms_now (line 137) | def log_histograms_now(self):
    method observe_state (line 144) | def observe_state(self, key, observe_while='training'):
    method unobserve_state (line 167) | def unobserve_state(self, key, observe_while='training'):
    method unobserve_states (line 176) | def unobserve_states(self, keys, observe_while='training'):
    method observe_training_and_validation_state (line 181) | def observe_training_and_validation_state(self, key):
    method observe_states (line 185) | def observe_states(self, keys, observe_while='training'):
    method observe_training_and_validation_states (line 190) | def observe_training_and_validation_states(self, keys):
    method log_object (line 195) | def log_object(self, tag, object_,
    method end_of_training_iteration (line 235) | def end_of_training_iteration(self, **_):
    method end_of_validation_run (line 253) | def end_of_validation_run(self, **_):
    method _tag_image (line 266) | def _tag_image(self, image, base_tag, prefix=None, instance_num=None, ...
    method extract_images_from_batch (line 279) | def extract_images_from_batch(self, batch, base_tag=None, prefix=None):
    method log_image_or_volume_batch (line 359) | def log_image_or_volume_batch(self, tag, batch, step=None):
    method log_scalar (line 365) | def log_scalar(self, tag, value, step):
    method log_images (line 377) | def log_images(self, tag, images, step, image_format='CHW'):
    method _order_image_axes (line 401) | def _order_image_axes(image, image_format='CHW', target_format='CHW'):
    method _normalize_image (line 436) | def _normalize_image(image):
    method log_histogram (line 443) | def log_histogram(self, tag, values, step, bins=1000):
    method get_config (line 448) | def get_config(self):

FILE: inferno/trainers/callbacks/scheduling.py
  class _Scheduler (line 8) | class _Scheduler(Callback):
    method __init__ (line 9) | def __init__(self, monitor='auto', monitor_momentum=0., monitor_while=...
    method monitor (line 20) | def monitor(self):
    method monitor (line 25) | def monitor(self, value):
    method monitor_value (line 29) | def monitor_value(self):
    method monitor_while (line 33) | def monitor_while(self):
    method monitor_while (line 46) | def monitor_while(self, value):
    method get_monitor_value (line 58) | def get_monitor_value(self):
    method maintain_monitor_moving_average (line 88) | def maintain_monitor_moving_average(self):
  class AutoLR (line 94) | class AutoLR(_Scheduler):
    method __init__ (line 101) | def __init__(self, factor, patience, required_minimum_relative_improve...
    method patience (line 163) | def patience(self):
    method patience (line 168) | def patience(self, value):
    method cooldown_duration (line 172) | def cooldown_duration(self):
    method cooldown_duration (line 176) | def cooldown_duration(self, value):
    method duration_since_last_decay (line 181) | def duration_since_last_decay(self):
    method duration_since_last_improvment (line 201) | def duration_since_last_improvment(self):
    method out_of_patience (line 221) | def out_of_patience(self):
    method in_cooldown (line 225) | def in_cooldown(self):
    method decay (line 231) | def decay(self):
    method maintain_monitor_moving_average (line 244) | def maintain_monitor_moving_average(self):
    method monitor_value_has_significantly_improved (line 250) | def monitor_value_has_significantly_improved(self):
    method end_of_training_iteration (line 278) | def end_of_training_iteration(self, **_):
    method end_of_validation_run (line 289) | def end_of_validation_run(self, **_):
    method is_significantly_less_than (line 303) | def is_significantly_less_than(x, y, min_relative_delta):
  class AutoLRDecay (line 311) | class AutoLRDecay(AutoLR):
  class DecaySpec (line 321) | class DecaySpec(object):
    method __init__ (line 323) | def __init__(self, duration, factor):
    method match (line 330) | def match(self, iteration_count=None, epoch_count=None, when_equal_ret...
    method new (line 342) | def new(self):
    method build_from (line 346) | def build_from(cls, args):
  class ManualLR (line 357) | class ManualLR(Callback):
    method __init__ (line 358) | def __init__(self, decay_specs, exclude_param_groups=None):
    method match (line 365) | def match(self):
    method decay (line 379) | def decay(self, factor):
    method end_of_training_iteration (line 390) | def end_of_training_iteration(self, **_):
  class SaveModelRegularly (line 397) | class SaveModelRegularly(Callback):
    method __init__ (line 400) | def __init__(self, frequency):
    method save_now (line 405) | def save_now(self):
    method end_of_training_iteration (line 410) | def end_of_training_iteration(self, **_):

FILE: inferno/trainers/callbacks/tqdm.py
  class TQDMPrinter (line 7) | class TQDMPrinter(object):
    method __init__ (line 8) | def __init__(self, progress):
    method print (line 11) | def print(self, message):
  class TQDMConsole (line 19) | class TQDMConsole(Console):
    method __init__ (line 20) | def __init__(self):
  class TQDMProgressBar (line 24) | class TQDMProgressBar(Callback):
    method __init__ (line 25) | def __init__(self, *args, **kwargs):
    method bind_trainer (line 32) | def bind_trainer(self, *args, **kwargs):
    method _init_epoch_bar_train (line 37) | def _init_epoch_bar_train(self):
    method print (line 43) | def print(self, message, **_):
    method begin_of_fit (line 50) | def begin_of_fit(self, max_num_epochs, **_):
    method end_of_fit (line 57) | def end_of_fit(self, **_):
    method begin_of_epoch (line 62) | def begin_of_epoch(self, **_):
    method end_of_epoch (line 66) | def end_of_epoch(self, **_):
    method begin_of_training_iteration (line 70) | def begin_of_training_iteration(self, **_):
    method begin_of_validation_iteration (line 78) | def begin_of_validation_iteration(self, **_):
    method begin_of_training_run (line 82) | def begin_of_training_run(self, **_):
    method end_of_training_run (line 85) | def end_of_training_run(self, **_):
    method begin_of_validation_run (line 91) | def begin_of_validation_run(self, num_iterations, num_iterations_in_ge...
    method end_of_validation_run (line 100) | def end_of_validation_run(self, **_):

FILE: inferno/trainers/callbacks/tqdmstub.py
  class TQDMProgressBar (line 3) | class TQDMProgressBar(Callback):
    method __init__ (line 4) | def __init__(self, *args, **kwargs):
    method bind_trainer (line 7) | def bind_trainer(self, *args, **kwargs):
    method begin_of_fit (line 11) | def begin_of_fit(self, **_):

FILE: inferno/utils/exceptions.py
  function assert_ (line 4) | def assert_(condition, message='', exception_type=AssertionError):
  class ShapeError (line 13) | class ShapeError(ValueError):
  class FrequencyValueError (line 17) | class FrequencyValueError(ValueError):
  class DeviceError (line 21) | class DeviceError(ValueError):
  class NotSetError (line 25) | class NotSetError(ValueError):
  class NotTorchModuleError (line 32) | class NotTorchModuleError(TypeError):
  class FrequencyTypeError (line 36) | class FrequencyTypeError(TypeError):
  class DTypeError (line 40) | class DTypeError(TypeError):
  class ClassNotFoundError (line 47) | class ClassNotFoundError(LookupError):
  class NotUnwrappableError (line 54) | class NotUnwrappableError(NotImplementedError):

FILE: inferno/utils/io_utils.py
  function fromh5 (line 9) | def fromh5(path, datapath=None, dataslice=None, asnumpy=True, preptrain=...
  function toh5 (line 29) | def toh5(data, path, datapath='data', compression=None, chunks=None):
  function fromz5 (line 35) | def fromz5(path, datapath, dataslice=None, n_threads=8):
  function yaml2dict (line 47) | def yaml2dict(path):
  function print_tensor (line 56) | def print_tensor(tensor, prefix, directory):

FILE: inferno/utils/math_utils.py
  function max_allowed_ds_steps (line 3) | def max_allowed_ds_steps(shape, factor):

FILE: inferno/utils/model_utils.py
  function is_model_cuda (line 5) | def is_model_cuda(model):
  class ModelTester (line 13) | class ModelTester(object):
    method __init__ (line 14) | def __init__(self, input_shape, expected_output_shape):
    method cuda (line 19) | def cuda(self):
    method get_input (line 23) | def get_input(self):
    method __call__ (line 30) | def __call__(self, model):
  class MultiscaleModelTester (line 49) | class MultiscaleModelTester(ModelTester):
    method __call__ (line 50) | def __call__(self, model):

FILE: inferno/utils/partial_cls.py
  function partial_cls (line 13) | def partial_cls(base_cls, name, module, fix=None, default=None):
  function register_partial_cls (line 120) | def register_partial_cls(base_cls, name, module, fix=None, default=None):
  class Conv (line 130) | class Conv(object):
    method __init__ (line 131) | def __init__(self, dim, activation, stride=1):

FILE: inferno/utils/python_utils.py
  function ensure_dir (line 11) | def ensure_dir(directory):
  function require_dict_kwargs (line 27) | def require_dict_kwargs(kwargs, msg=None):
  function is_listlike (line 53) | def is_listlike(x):
  function to_iterable (line 57) | def to_iterable(x):
  function from_iterable (line 61) | def from_iterable(x):
  function robust_len (line 65) | def robust_len(x):
  function as_tuple_of_len (line 69) | def as_tuple_of_len(x, len_):
  function has_callable_attr (line 79) | def has_callable_attr(object_, name):
  function is_maybe_list_of (line 83) | def is_maybe_list_of(check_function):
  class delayed_keyboard_interrupt (line 92) | class delayed_keyboard_interrupt(object):
    method __enter__ (line 100) | def __enter__(self):
    method handler (line 106) | def handler(self, sig, frame):
    method __exit__ (line 109) | def __exit__(self, type, value, traceback):
  function get_config_for_name (line 116) | def get_config_for_name(config, name):
  function deprecated (line 129) | def deprecated(reason):

FILE: inferno/utils/test_utils.py
  function generate_random_data (line 7) | def generate_random_data(num_samples, shape, num_classes, hardness=0.3, ...
  function generate_random_dataset (line 18) | def generate_random_dataset(num_samples, shape, num_classes, hardness=0....
  function generate_random_dataloader (line 29) | def generate_random_dataloader(num_samples, shape, num_classes, hardness...

FILE: inferno/utils/torch_utils.py
  function unwrap (line 8) | def unwrap(input_, to_cpu=True, as_numpy=False, extract_item=False):
  function is_tensor (line 37) | def is_tensor(object_):
  function is_label_tensor (line 42) | def is_label_tensor(object_):
  function is_image_tensor (line 46) | def is_image_tensor(object_):
  function is_volume_tensor (line 50) | def is_volume_tensor(object_):
  function is_image_or_volume_tensor (line 54) | def is_image_or_volume_tensor(object_):
  function is_label_image_tensor (line 58) | def is_label_image_tensor(object_):
  function is_label_volume_tensor (line 62) | def is_label_volume_tensor(object_):
  function is_label_image_or_volume_tensor (line 66) | def is_label_image_or_volume_tensor(object_):
  function is_matrix_tensor (line 70) | def is_matrix_tensor(object_):
  function is_scalar_tensor (line 74) | def is_scalar_tensor(object_):
  function is_vector_tensor (line 78) | def is_vector_tensor(object_):
  function assert_same_size (line 82) | def assert_same_size(tensor_1, tensor_2):
  function where (line 88) | def where(condition, if_true, if_false):
  function flatten_samples (line 118) | def flatten_samples(input_):
  function clip_gradients_ (line 143) | def clip_gradients_(parameters, mode, norm_or_value):

FILE: inferno/utils/train_utils.py
  class AverageMeter (line 6) | class AverageMeter(object):
    method __init__ (line 11) | def __init__(self):
    method reset (line 17) | def reset(self):
    method update (line 23) | def update(self, val, n=1):
  class MovingAverage (line 30) | class MovingAverage(object):
    method __init__ (line 32) | def __init__(self, momentum=0):
    method reset (line 37) | def reset(self):
    method update (line 40) | def update(self, val):
    method relative_change (line 49) | def relative_change(self):
  class CLUI (line 57) | class CLUI(object):
    method __call__ (line 60) | def __call__(self, f):
  class Frequency (line 94) | class Frequency(object):
    method __init__ (line 96) | def __init__(self, value=None, units=None):
    method value (line 106) | def value(self):
    method value (line 110) | def value(self, value):
    method units (line 124) | def units(self):
    method units (line 128) | def units(self, value):
    method assert_value_consistent (line 134) | def assert_value_consistent(self, value=None):
    method assert_units_consistent (line 146) | def assert_units_consistent(self, units=None):
    method is_consistent (line 154) | def is_consistent(self):
    method epoch (line 162) | def epoch(self):
    method iteration (line 166) | def iteration(self):
    method by_epoch (line 171) | def by_epoch(self):
    method by_iteration (line 175) | def by_iteration(self):
    method every (line 178) | def every(self, value):
    method match (line 182) | def match(self, iteration_count=None, epoch_count=None, persistent=Fal...
    method __str__ (line 199) | def __str__(self):
    method __repr__ (line 202) | def __repr__(self):
    method from_string (line 206) | def from_string(cls, string):
    method build_from (line 221) | def build_from(cls, args, priority='iterations'):
  class Duration (line 234) | class Duration(Frequency):
    method match (line 236) | def match(self, iteration_count=None, epoch_count=None, when_equal_ret...
    method compare (line 245) | def compare(self, iteration_count=None, epoch_count=None):
    method __sub__ (line 254) | def __sub__(self, other):
  class NoLogger (line 265) | class NoLogger(object):
    method __init__ (line 266) | def __init__(self, logdir=None):
    method log_value (line 269) | def log_value(self, *kwargs):
  function set_state (line 273) | def set_state(module, key, value):
  function get_state (line 285) | def get_state(module, key, default=None):

FILE: tests/test_extensions/test_containers/test_graph.py
  class TestGraph (line 6) | class TestGraph(unittest.TestCase):
    method setUp (line 7) | def setUp(self):
    method test_graph_dummy_basic (line 31) | def test_graph_dummy_basic(self):
    method test_graph_dummy_inception (line 64) | def test_graph_dummy_inception(self):
    method test_graph_basic (line 89) | def test_graph_basic(self):
    method test_graph_device_transfers (line 102) | def test_graph_device_transfers(self):
    method test_multi_gpu (line 119) | def test_multi_gpu(self):

FILE: tests/test_extensions/test_criteria/test_core.py
  class TestCore (line 6) | class TestCore(unittest.TestCase):
    method test_as_2d_criterion (line 7) | def test_as_2d_criterion(self):

FILE: tests/test_extensions/test_criteria/test_elementwise_measures.py
  class TestElementwiseMeasures (line 6) | class TestElementwiseMeasures(unittest.TestCase):
    method test_weighted_mse_loss (line 7) | def test_weighted_mse_loss(self):

FILE: tests/test_extensions/test_criteria/test_set_similarity_measures.py
  class SetSimilarityTest (line 5) | class SetSimilarityTest(unittest.TestCase):
    method get_dummy_variables (line 6) | def get_dummy_variables(self):
    method get_dummy_variables_with_channels_and_classes (line 11) | def get_dummy_variables_with_channels_and_classes(self):
  class TestSorensenDice (line 18) | class TestSorensenDice(SetSimilarityTest):
    method test_channelwise (line 20) | def test_channelwise(self):
  class TestGeneralizedSorensenDice (line 35) | class TestGeneralizedSorensenDice(SetSimilarityTest):
    method test_channelwise (line 36) | def test_channelwise(self):

FILE: tests/test_extensions/test_layers/deprecated/building_blocks.py
  class ResBlockTest (line 6) | class ResBlockTest(unittest.TestCase):
    method test_2D_simple_ (line 8) | def test_2D_simple_(self):
    method test_3D_simple_ (line 16) | def test_3D_simple_(self):
    method test_2D_simple_2 (line 24) | def test_2D_simple_2(self):
    method test_2D_simple_3 (line 32) | def test_2D_simple_3(self):
    method test_2D_simple_4 (line 40) | def test_2D_simple_4(self):
    method test_2D_simple_5 (line 49) | def test_2D_simple_5(self):
    method test_2D_simple_6 (line 58) | def test_2D_simple_6(self):
    method test_3D_simple_6 (line 67) | def test_3D_simple_6(self):

FILE: tests/test_extensions/test_layers/test_activations.py
  class ActivationTest (line 6) | class ActivationTest(unittest.TestCase):
    method test_selu (line 7) | def test_selu(self):

FILE: tests/test_extensions/test_layers/test_convolutional.py
  class TestConvolutional (line 6) | class TestConvolutional(unittest.TestCase):
    method test_bn_relu_depthwise_conv2d_pyinn (line 8) | def test_bn_relu_depthwise_conv2d_pyinn(self):

FILE: tests/test_extensions/test_layers/test_device.py
  class TransferTest (line 6) | class TransferTest(unittest.TestCase):
    method test_device_transfer (line 8) | def test_device_transfer(self):
    method test_on_device (line 22) | def test_on_device(self):

FILE: tests/test_extensions/test_layers/test_reshape.py
  class TestReshape (line 5) | class TestReshape(unittest.TestCase):
    method _get_input_variable (line 6) | def _get_input_variable(self, *shape):
    method test_as_matrix (line 9) | def test_as_matrix(self):
    method test_flatten (line 17) | def test_flatten(self):
    method test_as_2d (line 25) | def test_as_2d(self):
    method test_as_3d (line 39) | def test_as_3d(self):

FILE: tests/test_extensions/test_metrics/categorical.py
  class TestCategorical (line 6) | class TestCategorical(unittest.TestCase):
    method test_iou_basic (line 7) | def test_iou_basic(self):
    method test_iou_with_ignore_class (line 17) | def test_iou_with_ignore_class(self):
    method test_multiclass_iou (line 26) | def test_multiclass_iou(self):
    method test_multiclass_iou_with_ignore_class (line 37) | def test_multiclass_iou_with_ignore_class(self):

FILE: tests/test_extensions/test_models/test_res_unet.py
  class ResUNetTest (line 7) | class ResUNetTest(unittest.TestCase):
    method test_res_unet_2d (line 8) | def test_res_unet_2d(self):
    method test_res_unet_3d (line 15) | def test_res_unet_3d(self):
    method test_2d_side_out_bot_up (line 23) | def test_2d_side_out_bot_up(self):
    method test_2d_side_out_up (line 42) | def test_2d_side_out_up(self):
    method test_2d_side_out_down (line 60) | def test_2d_side_out_down(self):

FILE: tests/test_extensions/test_models/test_unet.py
  class _MultiscaleUNet (line 6) | class _MultiscaleUNet(UNet):
    method conv_op_factory (line 7) | def conv_op_factory(self, in_channels, out_channels, part, index):
    method forward (line 10) | def forward(self, input):
  class UNetTest (line 17) | class UNetTest(unittest.TestCase):
    method test_unet_2d (line 18) | def test_unet_2d(self):
    method test_unet_3d (line 24) | def test_unet_3d(self):
    method test_monochannel_unet_3d (line 31) | def test_monochannel_unet_3d(self):
    method test_inverse_pyramid_unet_2d (line 44) | def test_inverse_pyramid_unet_2d(self):

FILE: tests/test_inferno.py
  class TestInferno (line 24) | class TestInferno(unittest.TestCase):
    method read_environment_variables (line 32) | def read_environment_variables(self):
    method setUp (line 40) | def setUp(self):
    method setUpDatasets (line 44) | def setUpDatasets(self):
    method setUpCallbacks (line 65) | def setUpCallbacks(self):
    method generate_random_data (line 82) | def generate_random_data(self, num_samples, shape, num_classes,
    method tearDown (line 92) | def tearDown(self):
    method build_graph_model (line 97) | def build_graph_model(self):
    method test_training_cpu (line 113) | def test_training_cpu(self):

FILE: tests/test_io/test_box/test_camvid.py
  function _camvid_available (line 10) | def _camvid_available():
  class TestCamvid (line 14) | class TestCamvid(unittest.TestCase):
    method get_camvid_root (line 18) | def get_camvid_root(self):
    method test_camvid_dataset_without_transforms (line 26) | def test_camvid_dataset_without_transforms(self):
    method _test_camvid_dataset_with_transforms (line 37) | def _test_camvid_dataset_with_transforms(self):
    method test_camvid_dataset_with_transforms (line 74) | def test_camvid_dataset_with_transforms(self):
    method test_camvid_dataset_with_transforms_onehot (line 96) | def test_camvid_dataset_with_transforms_onehot(self):

FILE: tests/test_io/test_box/test_cityscapes.py
  function _cityscapes_available (line 10) | def _cityscapes_available():
  class TestCityscapes (line 14) | class TestCityscapes(unittest.TestCase):
    method get_cityscapes_root (line 19) | def get_cityscapes_root(self):
    method test_cityscapes_dataset_without_transforms (line 27) | def test_cityscapes_dataset_without_transforms(self):
    method test_cityscapes_dataset_without_transforms_unzipped (line 38) | def test_cityscapes_dataset_without_transforms_unzipped(self):
    method test_cityscapes_dataset_with_transforms (line 50) | def test_cityscapes_dataset_with_transforms(self):
    method test_cityscapes_dataset_with_transforms_unzipped (line 82) | def test_cityscapes_dataset_with_transforms_unzipped(self):

FILE: tests/test_io/test_core/test_concatenate.py
  class ConcatenateTest (line 4) | class ConcatenateTest(unittest.TestCase):
    method test_concatenate (line 5) | def test_concatenate(self):

FILE: tests/test_io/test_core/test_zip.py
  class ZipTest (line 4) | class ZipTest(unittest.TestCase):
    method test_zip_minimal (line 5) | def test_zip_minimal(self):
    method test_zip_sync (line 28) | def test_zip_sync(self):
    method test_zip_reject (line 32) | def test_zip_reject(self):

FILE: tests/test_io/test_volumetric/test_lazy_volume_loader.py
  class TestLazyVolumeLoader (line 19) | class TestLazyVolumeLoader(unittest.TestCase):
    method tearDown (line 21) | def tearDown(self):
    method test_h5_loader (line 28) | def test_h5_loader(self):
    method test_h5_loader_data_slice (line 47) | def test_h5_loader_data_slice(self):
    method test_h5_loader_pad (line 69) | def test_h5_loader_pad(self):
    method test_h5_loader_data_slice_pad (line 91) | def test_h5_loader_data_slice_pad(self):

FILE: tests/test_io/test_volumetric/test_volume_loader.py
  class TestVolumeLoader (line 9) | class TestVolumeLoader(unittest.TestCase):
    method setUp (line 11) | def setUp(self):
    method test_loader (line 14) | def test_loader(self):
  class TestHDF5VolumeLoader (line 26) | class TestHDF5VolumeLoader(unittest.TestCase):
    method setUp (line 28) | def setUp(self):
    method tearDown (line 37) | def tearDown(self):
    method test_hdf5_loader (line 43) | def test_hdf5_loader(self):

FILE: tests/test_training/test_basic.py
  class TestTrainer (line 8) | class TestTrainer(TestCase):
    method _make_test_model (line 16) | def _make_test_model():
    method test_cifar (line 33) | def test_cifar(self):
    method test_multi_io (line 64) | def test_multi_io(self):
    method test_serialization (line 109) | def test_serialization(self):
    method test_multi_gpu (line 132) | def test_multi_gpu(self):
    method test_save (line 160) | def test_save(self):
    method test_multi_gpu_setup (line 169) | def test_multi_gpu_setup(self):

FILE: tests/test_training/test_callbacks/test_base.py
  class DummyCallback (line 10) | class DummyCallback(Callback):
    method end_of_training_iteration (line 11) | def end_of_training_iteration(self, **_):
  class WrongDummyCallback (line 15) | class WrongDummyCallback(Callback):
    method end_of_iteration (line 16) | def end_of_iteration(self):
  class CallbackMechTest (line 20) | class CallbackMechTest(unittest.TestCase):
    method setUp (line 23) | def setUp(self):
    method tearDown (line 26) | def tearDown(self):
    method test_serialization (line 30) | def test_serialization(self):
    method test_auto_registry (line 45) | def test_auto_registry(self):
    method test_instance_registry (line 55) | def test_instance_registry(self):

FILE: tests/test_training/test_callbacks/test_essentials.py
  class TestEssentials (line 13) | class TestEssentials(unittest.TestCase):
    method setUp (line 16) | def setUp(self):
    method test_dump_hdf5_every (line 41) | def test_dump_hdf5_every(self):
    method tearDown (line 81) | def tearDown(self):

FILE: tests/test_training/test_callbacks/test_logging/test_base.py
  class DummyLogger (line 7) | class DummyLogger(Logger):
    method end_of_training_iteration (line 8) | def end_of_training_iteration(self, **_):
  class TestLogger (line 12) | class TestLogger(unittest.TestCase):
    method test_serialization (line 15) | def test_serialization(self):

FILE: tests/test_training/test_callbacks/test_logging/test_tensorboard.py
  class TestTensorboard (line 15) | class TestTensorboard(unittest.TestCase):
    method _make_test_model (line 22) | def _make_test_model(input_channels):
    method tearDown (line 36) | def tearDown(self):
    method get_random_dataloaders (line 43) | def get_random_dataloaders(self, input_channels=3):
    method get_trainer (line 59) | def get_trainer(self, input_channels):
    method test_tensorboard (line 81) | def test_tensorboard(self):
    method test_tensorboard_grayscale (line 85) | def test_tensorboard_grayscale(self):
    method test_serialization (line 89) | def test_serialization(self):

FILE: tests/test_training/test_callbacks/test_scheduling.py
  class TestSchedulers (line 7) | class TestSchedulers(unittest.TestCase):
    method test_manual_lr (line 9) | def test_manual_lr(self):

FILE: tests/test_utils/test_model_utils.py
  class ModelUtilTester (line 8) | class ModelUtilTester(unittest.TestCase):
    method test_model_tester (line 9) | def test_model_tester(self):
    method test_model_tester_cuda (line 15) | def test_model_tester_cuda(self):

FILE: tests/test_utils/test_partial_cls.py
  class TestCls (line 8) | class TestCls(object):
    method __init__ (line 9) | def __init__(self, a, b, c=1, d=2):
  class PartialClsTester (line 15) | class PartialClsTester(unittest.TestCase):
    method test_partial_cls (line 17) | def test_partial_cls(self):
    method test_update_existing_default_cls (line 40) | def test_update_existing_default_cls(self):
    method test_fix_nothing (line 57) | def test_fix_nothing(self):
    method test_fix_all (line 72) | def test_fix_all(self):
    method test_default_all (line 98) | def test_default_all(self):

FILE: tests/test_utils/test_train_utils.py
  class FrequencyTest (line 6) | class FrequencyTest(unittest.TestCase):
    method test_from_string (line 7) | def test_from_string(self):
    method test_from_tuple (line 19) | def test_from_tuple(self):
    method test_is_consistent (line 24) | def test_is_consistent(self):
    method test_init (line 29) | def test_init(self):
    method test_duration (line 34) | def test_duration(self):