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  • jactorch.cli
  • jactorch.cuda
    • jactorch.cuda.copy
  • jactorch.data
    • jactorch.data.collate
      • jactorch.data.collate.collate_v1
      • jactorch.data.collate.collate_v2
      • jactorch.data.collate.collate_v3
      • jactorch.data.collate.utils
    • jactorch.data.dataloader
      • jactorch.data.dataloader.dataloader
      • jactorch.data.dataloader.dataloader_torch030
    • jactorch.data.dataset
    • jactorch.data.layout
  • jactorch.functional
    • jactorch.functional.arith
    • jactorch.functional.clustering
    • jactorch.functional.grad
    • jactorch.functional.indexing
    • jactorch.functional.kernel
    • jactorch.functional.linalg
    • jactorch.functional.loglinear
    • jactorch.functional.masking
    • jactorch.functional.probability
    • jactorch.functional.quantization
    • jactorch.functional.range
    • jactorch.functional.sampling
    • jactorch.functional.shape
  • jactorch.graph
    • jactorch.graph.context
    • jactorch.graph.nn_env
    • jactorch.graph.parameter
    • jactorch.graph.variable
  • jactorch.io
    • jactorch.io.StateDictKeyError
  • jactorch.models
    • jactorch.models.vision
      • jactorch.models.vision.resnet
      • jactorch.models.vision.vgg
  • jactorch.nn
    • jactorch.nn.cnn
      • jactorch.nn.cnn.conv
      • jactorch.nn.cnn.coord_conv
      • jactorch.nn.cnn.functional
      • jactorch.nn.cnn.layers
    • jactorch.nn.container
    • jactorch.nn.embedding
    • jactorch.nn.functional
    • jactorch.nn.gumbel_softmax
      • jactorch.nn.gumbel_softmax.functional
      • jactorch.nn.gumbel_softmax.softmax
    • jactorch.nn.linear
    • jactorch.nn.losses
    • jactorch.nn.neural_logic
      • jactorch.nn.neural_logic.layer
      • jactorch.nn.neural_logic.modules
        • jactorch.nn.neural_logic.modules.dimension
        • jactorch.nn.neural_logic.modules.neural_logic
      • jactorch.nn.neural_logic.recurrent_layer
    • jactorch.nn.normalization
    • jactorch.nn.probability
    • jactorch.nn.prroi_pool
      • jactorch.nn.prroi_pool.functional
    • jactorch.nn.quickaccess
    • jactorch.nn.residual
    • jactorch.nn.rnn_layers
    • jactorch.nn.rnn_utils
    • jactorch.nn.simple
    • jactorch.nn.sync_batchnorm
    • jactorch.nn.word_embedding
  • jactorch.optim
    • jactorch.optim.accum_grad
    • jactorch.optim.custom_optimizer_base
    • jactorch.optim.optimizer_group
    • jactorch.optim.quickaccess
    • jactorch.optim.weight_decay
  • jactorch.parallel
    • jactorch.parallel.comm
    • jactorch.parallel.data_parallel
    • jactorch.parallel.dict_gather
    • jactorch.parallel.replicate
    • jactorch.parallel.replication_callback
    • jactorch.parallel.user_scattered
  • jactorch.quickstart
    • jactorch.quickstart.inference
    • jactorch.quickstart.models
    • jactorch.quickstart.train
  • jactorch.train
    • jactorch.train.env
    • jactorch.train.monitor
    • jactorch.train.tb
    • jactorch.train.utils
  • jactorch.transforms
    • jactorch.transforms.bbox
      • jactorch.transforms.bbox.functional
      • jactorch.transforms.bbox.transforms
    • jactorch.transforms.coor
      • jactorch.transforms.coor.functional
      • jactorch.transforms.coor.transforms
    • jactorch.transforms.image
      • jactorch.transforms.image.functional
      • jactorch.transforms.image.transforms
    • jactorch.transforms.vision
      • jactorch.transforms.vision.functional
        • jactorch.transforms.vision.functional.bbox
        • jactorch.transforms.vision.functional.coor
        • jactorch.transforms.vision.functional.image
      • jactorch.transforms.vision.transforms
  • jactorch.utils
    • jactorch.utils.grad
    • jactorch.utils.init
    • jactorch.utils.meta
    • jactorch.utils.unittest
  • jactorch.vision
    • jactorch.vision.conv
    • jactorch.vision.geometry
    • jactorch.vision.gradient
    • jactorch.vision.morphology
    • jactorch.vision.peak
    • jactorch.vision.smooth
  • jactorch
  • jactorch.graph

jactorch.graph#

Submodules

context

Context manager used in a forward pass.

nn_env

parameter

Utilities to access, filter, and mark parameters in a torch.nn.Module.

variable

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