{ "_id": "6ae50974327abcdf86868e0b", "Package": "mlr3torch", "Title": "Deep Learning with 'mlr3'", "Version": "0.4.0", "Authors@R": "c(person(given = \"Sebastian\",\nfamily = \"Fischer\",\nrole = c(\"cre\", \"aut\"),\nemail = \"sebf.fischer@gmail.com\",\ncomment = c(ORCID = \"0000-0002-9609-3197\")),\nperson(given = \"Bernd\",\nfamily = \"Bischl\",\nrole = \"ctb\",\nemail = \"bernd_bischl@gmx.net\",\ncomment = c(ORCID = \"0000-0001-6002-6980\")),\nperson(given = \"Lukas\",\nfamily = \"Burk\",\nrole = \"ctb\",\nemail = \"github@quantenbrot.de\",\ncomment = c(ORCID = \"0000-0001-7528-3795\")),\nperson(given = \"Martin\",\nfamily = \"Binder\",\nrole = \"aut\",\nemail = \"mlr.developer@mb706.com\"),\nperson(given = \"Florian\",\nfamily = \"Pfisterer\",\nrole = \"ctb\",\nemail = \"pfistererf@googlemail.com\",\ncomment = c(ORCID = \"0000-0001-8867-762X\")),\nperson(given = \"Carson\",\nfamily = \"Zhang\",\nrole = \"ctb\",\nemail = \"carsonzhang4@gmail.com\")\n)", "Description": "Deep Learning library that extends the mlr3 framework by\nbuilding upon the 'torch' package. It makes it convenient to\nbuild, train, and evaluate deep learning models without having\nto worry about low level details. Custom architectures can be\ncreated using the graph language defined in 'mlr3pipelines'.", "License": "LGPL (>= 3)", "BugReports": "https://github.com/mlr-org/mlr3torch/issues", "URL": "https://mlr3torch.mlr-org.com/,\nhttps://github.com/mlr-org/mlr3torch/", "Config/testthat/edition": "3", "NeedsCompilation": "no", "ByteCompile": "yes", "Encoding": "UTF-8", "Collate": "'CallbackSet.R' 'aaa.R' 'TorchCallback.R'\n'CallbackSetCheckpoint.R' 'CallbackSetEarlyStopping.R'\n'CallbackSetHistory.R' 'CallbackSetLRScheduler.R'\n'CallbackSetProgress.R' 'CallbackSetTB.R'\n'CallbackSetUnfreeze.R' 'ContextTorch.R' 'DataBackendLazy.R'\n'utils.R' 'DataDescriptor.R' 'LearnerTorch.R'\n'GraphLearnerTorch.R' 'LearnerFTTransformer.R'\n'LearnerTorchFeatureless.R' 'LearnerTorchImage.R'\n'LearnerTorchMLP.R' 'TorchDescriptor.R' 'TorchLoss.R'\n'task_dataset.R' 'shape.R' 'PipeOpTorchIngress.R'\n'LearnerTorchModel.R' 'LearnerTorchModule.R'\n'LearnerTorchRealMLP.R' 'LearnerTorchTabM.R'\n'LearnerTorchTabResNet.R' 'LearnerTorchVision.R'\n'MeasureTorch.R' 'ModelDescriptor.R' 'PipeOpModule.R'\n'PipeOpTorch.R' 'PipeOpTaskPreprocTorch.R'\n'PipeOpTorchActivation.R' 'PipeOpTorchAdaptiveAvgPool.R'\n'PipeOpTorchAdaptiveMaxPool.R' 'PipeOpTorchAvgPool.R'\n'PipeOpTorchBatchNorm.R' 'PipeOpTorchBlock.R'\n'PipeOpTorchCallbacks.R' 'PipeOpTorchConv.R'\n'PipeOpTorchConvTranspose.R' 'PipeOpTorchDropout.R'\n'PipeOpTorchFTCLS.R' 'PipeOpTorchFTTransformerBlock.R'\n'PipeOpTorchFn.R' 'PipeOpTorchGroupNorm.R' 'PipeOpTorchHead.R'\n'PipeOpTorchIdentity.R' 'PipeOpTorchLayerNorm.R'\n'PipeOpTorchLinear.R' 'PipeOpTorchLoss.R'\n'PipeOpTorchMaxPool.R' 'PipeOpTorchMerge.R'\n'PipeOpTorchModel.R' 'PipeOpTorchMultiheadAttention.R'\n'PipeOpTorchOptimizer.R' 'PipeOpTorchRecurrent.R'\n'PipeOpTorchReshape.R' 'PipeOpTorchSoftmax.R'\n'PipeOpTorchTokenizer.R' 'PipeOpTorchTransformerEncoderLayer.R'\n'PredictionTorch.R' 'Select.R' 'TaskClassif_cifar.R'\n'TaskClassif_lazy_iris.R' 'TaskClassif_melanoma.R'\n'TaskClassif_mnist.R' 'TaskClassif_tiny_imagenet.R'\n'TaskTorch.R' 'TorchOptimizer.R' 'bibentries.R' 'cache.R'\n'lazy_tensor.R' 'learner_torch_methods.R' 'materialize.R'\n'merge_graphs.R' 'multi_tensor_dataset.R' 'nn.R' 'nn_graph.R'\n'paramset_torchlearner.R' 'pipeop_torch.R' 'preprocess.R'\n'rd_info.R' 'with_torch_settings.R' 'zzz.R'", "Config/roxygen2/version": "8.1.0", "Packaged": { "Date": "2026-10-30 21:12:13 UTC", "User": "root" }, "Author": "Sebastian Fischer [cre, aut] (ORCID:\n), Bernd Bischl [ctb]\n(ORCID: ), Lukas Burk\n[ctb] (ORCID: ), Martin\nBinder [aut], Florian Pfisterer [ctb] (ORCID:\n), Carson Zhang [ctb]", "Maintainer": "Sebastian Fischer ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-10-30 19:34:27 UTC", "RemoteUrl": "https://github.com/cran/mlr3torch", "RemoteRef": "HEAD", "RemoteSha": "ab1494873b713dedb1cb64290f2fdf2e6ca77190", "_user": "cran", "_type": "src", "_file": "mlr3torch_0.4.0.tar.gz", "_fileid": "https://r2.ropensci.org/18769f25fd9412377299081b5bbd4d67c90948cc5898c2239e90548c61876900", "_filesize": 2343965, "_sha256": "18769f25fd9412377299081b5bbd4d67c90948cc5898c2239e90548c61876900", "_expires": "2027-02-07T21:17:38.000Z", "_created": "2026-10-30T21:12:13.000Z", "_published": "2026-10-30T21:17:40.112Z", "_upstream": "https://github.com/cran/mlr3torch", "_status": "success", "_maintainer": { "name": "Sebastian Fischer", "email": "sebf.fischer@gmail.com", "login": "sebffischer", "description": "PhD Student in Statistics", "uuid": 20975557, "orcid": "0000-0002-9609-3197" }, "_jobs": [ { "job": 124316122433, "time": 236, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "13012961207" }, { "job": 124316122450, "time": 182, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "13011444356" }, { "job": 124314204209, "time": 253, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "13012541551" }, { "job": 124316122467, "time": 121, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "13013120562" }, { "job": 124316122405, "time": 203, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "13012791152" }, { "job": 124316122453, "time": 182, "config": "windows-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "13013055621" } ], "_buildurl": "https://github.com/r-universe/cran/actions/runs/41128780613", "_commit": { "id": "ab1494873b713dedb1cb64290f2fdf2e6ca77190", "author": "Sebastian Fischer ", "committer": "cran-robot ", "message": "version 0.4.0\n", "time": 1793388867 }, "_distro": "resolute", "_host": "GitHub-Actions", "_registered": true, "_dependencies": [ { "package": "mlr3", "version": ">= 1.8.0", "role": "Depends" }, { "package": "mlr3pipelines", "version": ">= 0.11.0", "role": "Depends" }, { "package": "torch", "version": ">= 0.16.2", "role": "Depends" }, { "package": "R", "version": ">= 4.2.0", "role": "Depends" }, { "package": "backports", "role": "Imports" }, { "package": "cli", "role": "Imports" }, { "package": "checkmate", "version": ">= 2.2.0", "role": "Imports" }, { "package": "coro", "role": "Imports" }, { "package": "data.table", "role": "Imports" }, { "package": "lgr", "role": "Imports" }, { "package": "methods", "role": "Imports" }, { "package": "mlr3misc", "version": ">= 0.23", "role": "Imports" }, { "package": "paradox", "version": ">= 1.0.0", "role": "Imports" }, { "package": "R6", "role": "Imports" }, { "package": "withr", "role": "Imports" }, { "package": "callr", "role": "Suggests" }, { "package": "curl", "role": "Suggests" }, { "package": "future", "role": "Suggests" }, { "package": "ggplot2", "role": "Suggests" }, { "package": "igraph", "role": "Suggests" }, { "package": "jsonlite", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "mirai", "role": "Suggests" }, { "package": "mlr3tuning", "version": ">= 1.0.0", "role": "Suggests" }, { "package": "progress", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "rpart", "role": "Suggests" }, { "package": "viridis", "role": "Suggests" }, { "package": "visNetwork", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" }, { "package": "tibble", "role": "Suggests" }, { "package": "tfevents", "role": "Suggests" }, { "package": "torchvision", "version": ">= 0.10.0", "role": "Suggests" }, { "package": "waldo", "role": "Suggests" } ], "_owner": "cran", "_selfowned": false, "_usedby": 2, "_updates": [ { "week": "2025-44", "n": 1 }, { "week": "2026-05", "n": 1 }, { "week": "2026-44", "n": 1 } ], "_tags": [ { "name": "0.3.2", "date": "2025-10-31" }, { "name": "0.3.3", "date": "2026-01-31" }, { "name": "0.4.0", "date": "2026-10-30" } ], "_stars": 0, "_contributors": [ { "user": "sebffischer", "count": 10, "uuid": 20975557 } ], "_userbio": { "uuid": 6899542, "type": "organization", "name": "cran", "followers": 634, "description": "Unofficial read-only mirror of all CRAN R packages" }, "_downloads": { "count": 2843, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/mlr3torch" }, "_devurl": "https://github.com/mlr-org/mlr3torch", "_pkgdown": "https://mlr3torch.mlr-org.com/", "_searchresults": 109, "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/manual.pdf", "extra/mlr3torch.html", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md" ], "_homeurl": "https://github.com/mlr-org/mlr3torch", "_realowner": "mlr-org", "_cranurl": false, "_releases": [ { "version": "0.1.0", "date": "2024-07-08" }, { "version": "0.1.1", "date": "2024-09-12" }, { "version": "0.1.2", "date": "2024-10-15" }, { "version": "0.2.0", "date": "2025-02-07" }, { "version": "0.2.1", "date": "2025-02-13" }, { "version": "0.3.0", "date": "2025-07-07" }, { "version": "0.3.1", "date": "2025-08-26" }, { "version": "0.3.2", "date": "2025-10-31" }, { "version": "0.3.3", "date": "2026-01-31" }, { "version": "0.4.0", "date": "2026-10-30" } ], "_exports": [ "as_data_descriptor", "as_lazy_tensor", "as_learner_torch", "as_lr_scheduler", "as_task_torch", "as_torch_callback", "as_torch_callbacks", "as_torch_loss", "as_torch_optimizer", "assert_dim_in_range", "assert_known_dims", "assert_lazy_tensor", "assert_ndim", "assert_not_batch_dim", "assert_positive_extent", "assert_same_batch_size", "assert_same_ndim", "assert_shape", "assert_shapes", "auto_device", "batchgetter_categ", "batchgetter_num", "broadcast_shapes", "callback_set", "CallbackSet", "CallbackSetCheckpoint", "CallbackSetHistory", "CallbackSetLRScheduler", "CallbackSetLRSchedulerOneCycle", "CallbackSetLRSchedulerReduceOnPlateau", "CallbackSetProgress", "CallbackSetTB", "CallbackSetUnfreeze", "ContextTorch", "DataBackendLazy", "DataDescriptor", "encode_prediction", "get_batch_constructor", "get_batch_size", "get_target_batchgetter", "GraphLearnerTorch", "infer_shapes", "ingress_categ", "ingress_ltnsr", "ingress_num", "is_lazy_tensor", "lazy_shape", "lazy_tensor", "LearnerTorch", "LearnerTorchFeatureless", "LearnerTorchFTTransformer", "LearnerTorchImage", "LearnerTorchMLP", "LearnerTorchModel", "LearnerTorchModule", "LearnerTorchRealMLP", "LearnerTorchTabM", "LearnerTorchTabResNet", "LearnerTorchVision", "materialize", "MeasureTorch", "MeasureTorchDefault", "mlr3torch_callbacks", "mlr3torch_losses", "mlr3torch_optimizers", "model_descriptor_to_learner", "model_descriptor_to_module", "model_descriptor_union", "ModelDescriptor", "msr_torch", "nn", "nn_ft_cls", "nn_ft_transformer_block", "nn_geglu", "nn_graph", "nn_merge_cat", "nn_merge_prod", "nn_merge_sum", "nn_reglu", "nn_reshape", "nn_squeeze", "nn_tokenizer_categ", "nn_tokenizer_num", "nn_unsqueeze", "output_dim_for", "pipeop_preproc_torch", "pipeop_torch", "PipeOpModule", "PipeOpPreprocTorchAugmentCenterCrop", "PipeOpPreprocTorchAugmentColorJitter", "PipeOpPreprocTorchAugmentCrop", "PipeOpPreprocTorchAugmentHflip", "PipeOpPreprocTorchAugmentRandomAffine", "PipeOpPreprocTorchAugmentRandomChoice", "PipeOpPreprocTorchAugmentRandomCrop", "PipeOpPreprocTorchAugmentRandomHorizontalFlip", "PipeOpPreprocTorchAugmentRandomOrder", "PipeOpPreprocTorchAugmentRandomResizedCrop", "PipeOpPreprocTorchAugmentRandomVerticalFlip", "PipeOpPreprocTorchAugmentResizedCrop", "PipeOpPreprocTorchAugmentRotate", "PipeOpPreprocTorchAugmentVflip", "PipeOpPreprocTorchTrafoAdjustBrightness", "PipeOpPreprocTorchTrafoAdjustGamma", "PipeOpPreprocTorchTrafoAdjustHue", "PipeOpPreprocTorchTrafoAdjustSaturation", "PipeOpPreprocTorchTrafoGrayscale", "PipeOpPreprocTorchTrafoNop", "PipeOpPreprocTorchTrafoNormalize", "PipeOpPreprocTorchTrafoPad", "PipeOpPreprocTorchTrafoReshape", "PipeOpPreprocTorchTrafoResize", "PipeOpPreprocTorchTrafoRgbToGrayscale", "PipeOpTaskPreprocTorch", "PipeOpTorch", "PipeOpTorchAdaptiveAvgPool1D", "PipeOpTorchAdaptiveAvgPool2D", "PipeOpTorchAdaptiveAvgPool3D", "PipeOpTorchAdaptiveMaxPool1D", "PipeOpTorchAdaptiveMaxPool2D", "PipeOpTorchAdaptiveMaxPool3D", "PipeOpTorchAvgPool1D", "PipeOpTorchAvgPool2D", "PipeOpTorchAvgPool3D", "PipeOpTorchBatchNorm1D", "PipeOpTorchBatchNorm2D", "PipeOpTorchBatchNorm3D", "PipeOpTorchBlock", "PipeOpTorchCallbacks", "PipeOpTorchCELU", "PipeOpTorchConv1D", "PipeOpTorchConv2D", "PipeOpTorchConv3D", "PipeOpTorchConvTranspose1D", "PipeOpTorchConvTranspose2D", "PipeOpTorchConvTranspose3D", "PipeOpTorchDropout", "PipeOpTorchDropout2D", "PipeOpTorchDropout3D", "PipeOpTorchELU", "PipeOpTorchFlatten", "PipeOpTorchFn", "PipeOpTorchFTCLS", "PipeOpTorchFTTransformerBlock", "PipeOpTorchGeGLU", "PipeOpTorchGELU", "PipeOpTorchGLU", "PipeOpTorchGroupNorm", "PipeOpTorchGRU", "PipeOpTorchHardShrink", "PipeOpTorchHardSigmoid", "PipeOpTorchHardTanh", "PipeOpTorchHead", "PipeOpTorchIdentity", "PipeOpTorchIngress", "PipeOpTorchIngressCategorical", "PipeOpTorchIngressLazyTensor", "PipeOpTorchIngressNumeric", "PipeOpTorchLayerNorm", "PipeOpTorchLeakyReLU", "PipeOpTorchLinear", "PipeOpTorchLogSigmoid", "PipeOpTorchLogSoftmax", "PipeOpTorchLoss", "PipeOpTorchLSTM", "PipeOpTorchMaxPool1D", "PipeOpTorchMaxPool2D", "PipeOpTorchMaxPool3D", "PipeOpTorchMerge", "PipeOpTorchMergeCat", "PipeOpTorchMergeProd", "PipeOpTorchMergeSum", "PipeOpTorchModel", "PipeOpTorchModelClassif", "PipeOpTorchModelRegr", "PipeOpTorchMultiheadAttention", "PipeOpTorchOptimizer", "PipeOpTorchPReLU", "PipeOpTorchRecurrent", "PipeOpTorchReGLU", "PipeOpTorchReLU", "PipeOpTorchReLU6", "PipeOpTorchReshape", "PipeOpTorchRNN", "PipeOpTorchRReLU", "PipeOpTorchSELU", "PipeOpTorchSigmoid", "PipeOpTorchSiLU", "PipeOpTorchSoftmax", "PipeOpTorchSoftmax2D", "PipeOpTorchSoftmin", "PipeOpTorchSoftPlus", "PipeOpTorchSoftShrink", "PipeOpTorchSoftSign", "PipeOpTorchSqueeze", "PipeOpTorchTanh", "PipeOpTorchTanhShrink", "PipeOpTorchThreshold", "PipeOpTorchTokenizerCateg", "PipeOpTorchTokenizerNum", "PipeOpTorchTransformerEncoderLayer", "PipeOpTorchUnflatten", "PipeOpTorchUnsqueeze", "PredictionTorch", "replace_head", "reshape_output_shape", "resolve_dim", "select_all", "select_grep", "select_invert", "select_name", "select_none", "shape_to_str", "t_clbk", "t_clbks", "t_loss", "t_losses", "t_opt", "t_opts", "task_dataset", "TaskTorch", "torch_callback", "TorchCallback", "TorchDescriptor", "TorchIngressToken", "TorchLoss", "TorchOptimizer" ], "_help": [ { "page": "mlr3torch-package", "title": "mlr3torch: Deep Learning with 'mlr3'", "topics": [ "mlr3torch-package", "mlr3torch" ] }, { "page": "as_data_descriptor", "title": "Convert to Data Descriptor", "topics": [ "as_data_descriptor" ] }, { "page": "as_lazy_tensor", "title": "Convert to Lazy Tensor", "topics": [ "as_lazy_tensor", "as_lazy_tensor.dataset" ] }, { "page": "as_learner_torch", "title": "Convert a Graph to a Torch Learner", "concept": [ "Graph Network", "Learner" ], "topics": [ "as_learner_torch", "as_learner_torch.Graph", "as_learner_torch.GraphLearner", "as_learner_torch.PipeOp" ] }, { "page": "as_lr_scheduler", "title": "Convert to CallbackSetLRScheduler", "topics": [ "as_lr_scheduler" ] }, { "page": "as_task_torch", "title": "Create a Generic Torch Task", "topics": [ "as_task_torch" ] }, { "page": "as_torch_callback", "title": "Convert to a TorchCallback", "concept": [ "Callback" ], "topics": [ "as_torch_callback" ] }, { "page": "as_torch_callbacks", "title": "Convert to a list of Torch Callbacks", "concept": [ "Callback", "Torch Descriptor" ], "topics": [ "as_torch_callbacks" ] }, { "page": "as_torch_loss", "title": "Convert to TorchLoss", "concept": [ "Torch Descriptor" ], "topics": [ "as_torch_loss" ] }, { "page": "as_torch_optimizer", "title": "Convert to TorchOptimizer", "concept": [ "Torch Descriptor" ], "topics": [ "as_torch_optimizer" ] }, { "page": "assert_dim_in_range", "title": "Assert that a Dimension Exists", "concept": [ "Shape Assertions" ], "topics": [ "assert_dim_in_range" ] }, { "page": "assert_known_dims", "title": "Assert that Dimensions are Known", "concept": [ "Shape Assertions" ], "topics": [ "assert_known_dims" ] }, { "page": "assert_lazy_tensor", "title": "Assert Lazy Tensor", "topics": [ "assert_lazy_tensor" ] }, { "page": "assert_ndim", "title": "Assert the Number of Dimensions of a Shape", "concept": [ "Shape Assertions" ], "topics": [ "assert_ndim" ] }, { "page": "assert_not_batch_dim", "title": "Assert that a Dimension is not the Batch Dimension", "concept": [ "Shape Assertions" ], "topics": [ "assert_not_batch_dim" ] }, { "page": "assert_positive_extent", "title": "Assert that a Computed Output Size is Positive", "concept": [ "Shape Assertions" ], "topics": [ "assert_positive_extent" ] }, { "page": "assert_same_batch_size", "title": "Assert that Shapes have the Same Batch Size", "concept": [ "Shape Assertions" ], "topics": [ "assert_same_batch_size" ] }, { "page": "assert_same_ndim", "title": "Assert that Shapes have the Same Number of Dimensions", "concept": [ "Shape Assertions" ], "topics": [ "assert_same_ndim" ] }, { "page": "assert_shape", "title": "Assert a Shape", "concept": [ "Shape Assertions" ], "topics": [ "assert_shape" ] }, { "page": "assert_shapes", "title": "Assert a List of Shapes", "concept": [ "Shape Assertions" ], "topics": [ "assert_shapes" ] }, { "page": "auto_device", "title": "Auto Device", "topics": [ "auto_device" ] }, { "page": "batchgetter_categ", "title": "Batchgetter for Categorical data", "topics": [ "batchgetter_categ" ] }, { "page": "batchgetter_num", "title": "Batchgetter for Numeric Data", "topics": [ "batchgetter_num" ] }, { "page": "callback_set", "title": "Create a Set of Callbacks for Torch", "concept": [ "Callback" ], "topics": [ "callback_set" ] }, { "page": "cross_entropy", "title": "Cross Entropy Loss", "topics": [ "cross_entropy" ] }, { "page": "DataDescriptor", "title": "Data Descriptor", "topics": [ "DataDescriptor" ] }, { "page": "encode_prediction", "title": "Encode the Network Output as a Prediction", "topics": [ "encode_prediction" ] }, { "page": "get_batch_constructor", "title": "Batch Constructor for a Task", "topics": [ "get_batch_constructor" ] }, { "page": "get_batch_size", "title": "Extract the Batch Size for a Given Phase", "topics": [ "get_batch_size" ] }, { "page": "get_target_batchgetter", "title": "Target Batchgetter for a Task", "topics": [ "get_target_batchgetter" ] }, { "page": "GraphLearnerTorch", "title": "Graph Learner for Torch Networks", "concept": [ "Learner" ], "topics": [ "GraphLearnerTorch" ] }, { "page": "infer_shapes", "title": "Infer Shapes", "concept": [ "Shape Inference" ], "topics": [ "infer_shapes" ] }, { "page": "ingress_categ", "title": "Ingress Token for Categorical Features", "topics": [ "ingress_categ" ] }, { "page": "ingress_ltnsr", "title": "Ingress Token for Lazy Tensor Feature", "topics": [ "ingress_ltnsr" ] }, { "page": "ingress_num", "title": "Ingress Token for Numeric Features", "topics": [ "ingress_num" ] }, { "page": "is_lazy_tensor", "title": "Check for lazy tensor", "topics": [ "is_lazy_tensor" ] }, { "page": "lazy_shape", "title": "Shape of Lazy Tensor", "topics": [ "lazy_shape" ] }, { "page": "lazy_tensor", "title": "Create a lazy tensor", "topics": [ "lazy_tensor" ] }, { "page": "materialize", "title": "Materialize Lazy Tensor Columns", "topics": [ "materialize", "materialize.list" ] }, { "page": "mlr_backends_lazy", "title": "Lazy Data Backend", "topics": [ "DataBackendLazy", "mlr_backends_lazy" ] }, { "page": "mlr_callback_set", "title": "Base Class for Callbacks", "concept": [ "Callback" ], "topics": [ "CallbackSet", "mlr_callback_set" ] }, { "page": "mlr_callback_set.checkpoint", "title": "Checkpoint Callback", "concept": [ "Callback" ], "topics": [ "CallbackSetCheckpoint", "mlr_callback_set.checkpoint" ] }, { "page": "mlr_callback_set.history", "title": "History Callback", "topics": [ "CallbackSetHistory", "mlr_callback_set.history" ] }, { "page": "mlr_callback_set.lr_scheduler", "title": "Learning Rate Scheduling Callback", "topics": [ "CallbackSetLRScheduler", "mlr_callback_set.lr_scheduler" ] }, { "page": "mlr_callback_set.lr_scheduler_one_cycle", "title": "OneCycle Learning Rate Scheduling Callback", "topics": [ "CallbackSetLRSchedulerOneCycle", "mlr_callback_set.lr_scheduler_one_cycle" ] }, { "page": "mlr_callback_set.lr_scheduler_reduce_on_plateau", "title": "Reduce On Plateau Learning Rate Scheduler", "topics": [ "CallbackSetLRSchedulerReduceOnPlateau", "mlr_callback_set.lr_scheduler_reduce_on_plateau" ] }, { "page": "mlr_callback_set.progress", "title": "Progress Callback", "concept": [ "Callback" ], "topics": [ "CallbackSetProgress", "mlr_callback_set.progress" ] }, { "page": "mlr_callback_set.tb", "title": "TensorBoard Logging Callback", "concept": [ "Callback" ], "topics": [ "CallbackSetTB", "mlr_callback_set.tb" ] }, { "page": "mlr_callback_set.unfreeze", "title": "Unfreezing Weights Callback", "concept": [ "Callback" ], "topics": [ "CallbackSetUnfreeze", "mlr_callback_set.unfreeze" ] }, { "page": "mlr_context_torch", "title": "Context for Torch Learner", "concept": [ "Callback" ], "topics": [ "ContextTorch", "mlr_context_torch" ] }, { "page": "mlr_learners_torch", "title": "Base Class for Torch Learners", "concept": [ "Learner" ], "topics": [ "LearnerTorch", "mlr_learners_torch" ] }, { "page": "mlr_learners_torch_image", "title": "Image Learner", "concept": [ "Learner" ], "topics": [ "LearnerTorchImage", "mlr_learners_torch_image" ] }, { "page": "mlr_learners_torch_model", "title": "Learner Torch Model", "concept": [ "Graph Network", "Learner" ], "topics": [ "LearnerTorchModel", "mlr_learners_torch_model" ] }, { "page": "mlr_learners.ft_transformer", "title": "FT-Transformer", "concept": [ "Learner" ], "topics": [ "LearnerTorchFTTransformer", "mlr_learners.ft_transformer" ] }, { "page": "mlr_learners.mlp", "title": "Multi Layer Perceptron", "concept": [ "Learner" ], "topics": [ "LearnerTorchMLP", "mlr_learners.mlp" ] }, { "page": "mlr_learners.module", "title": "Learner Torch Module", "concept": [ "Learner" ], "topics": [ "LearnerTorchModule", "mlr_learners.module" ] }, { "page": "mlr_learners.realmlp", "title": "RealMLP", "concept": [ "Learner" ], "topics": [ "LearnerTorchRealMLP", "mlr_learners.realmlp" ] }, { "page": "mlr_learners.tab_resnet", "title": "Tabular ResNet", "concept": [ "Learner" ], "topics": [ "LearnerTorchTabResNet", "mlr_learners.tab_resnet" ] }, { "page": "mlr_learners.tabm", "title": "TabM", "concept": [ "Learner" ], "topics": [ "LearnerTorchTabM", "mlr_learners.tabm" ] }, { "page": "mlr_learners.torch_featureless", "title": "Featureless Torch Learner", "concept": [ "Learner" ], "topics": [ "LearnerTorchFeatureless", "mlr_learners.torch_featureless" ] }, { "page": "mlr_learners.torchvision", "title": "Image Classification Networks from torchvision", "topics": [ "LearnerTorchVision", "mlr_learners.torchvision" ] }, { "page": "mlr_measures_torch", "title": "Measure for a Generic Torch Task", "concept": [ "Measure" ], "topics": [ "MeasureTorch", "mlr_measures_torch" ] }, { "page": "mlr_measures_torch.default", "title": "Default Measure of a Generic Torch Task", "concept": [ "Measure" ], "topics": [ "MeasureTorchDefault", "mlr_measures_torch.default" ] }, { "page": "mlr_pipeops_augment_center_crop", "title": "Center Crop Augmentation", "topics": [ "mlr_pipeops_augment_center_crop", "PipeOpPreprocTorchAugmentCenterCrop" ] }, { "page": "mlr_pipeops_augment_color_jitter", "title": "Color Jitter Augmentation", "topics": [ "mlr_pipeops_augment_color_jitter", "PipeOpPreprocTorchAugmentColorJitter" ] }, { "page": "mlr_pipeops_augment_crop", "title": "Crop Augmentation", "topics": [ "mlr_pipeops_augment_crop", "PipeOpPreprocTorchAugmentCrop" ] }, { "page": "mlr_pipeops_augment_hflip", "title": "Horizontal Flip Augmentation", "topics": [ "mlr_pipeops_augment_hflip", "PipeOpPreprocTorchAugmentHflip" ] }, { "page": "mlr_pipeops_augment_random_affine", "title": "Random Affine Augmentation", "topics": [ "mlr_pipeops_augment_random_affine", "PipeOpPreprocTorchAugmentRandomAffine" ] }, { "page": "mlr_pipeops_augment_random_choice", "title": "Random Choice Augmentation", "topics": [ "mlr_pipeops_augment_random_choice", "PipeOpPreprocTorchAugmentRandomChoice" ] }, { "page": "mlr_pipeops_augment_random_crop", "title": "Random Crop Augmentation", "topics": [ "mlr_pipeops_augment_random_crop", "PipeOpPreprocTorchAugmentRandomCrop" ] }, { "page": "mlr_pipeops_augment_random_horizontal_flip", "title": "Random Horizontal Flip Augmentation", "topics": [ "mlr_pipeops_augment_random_horizontal_flip", "PipeOpPreprocTorchAugmentRandomHorizontalFlip" ] }, { "page": "mlr_pipeops_augment_random_order", "title": "Random Order Augmentation", "topics": [ "mlr_pipeops_augment_random_order", "PipeOpPreprocTorchAugmentRandomOrder" ] }, { "page": "mlr_pipeops_augment_random_resized_crop", "title": "Random Resized Crop Augmentation", "topics": [ "mlr_pipeops_augment_random_resized_crop", "PipeOpPreprocTorchAugmentRandomResizedCrop" ] }, { "page": "mlr_pipeops_augment_random_vertical_flip", "title": "Random Vertical Flip Augmentation", "topics": [ "mlr_pipeops_augment_random_vertical_flip", "PipeOpPreprocTorchAugmentRandomVerticalFlip" ] }, { "page": "mlr_pipeops_augment_resized_crop", "title": "Resized Crop Augmentation", "topics": [ "mlr_pipeops_augment_resized_crop", "PipeOpPreprocTorchAugmentResizedCrop" ] }, { "page": "mlr_pipeops_augment_rotate", "title": "Rotate Augmentation", "topics": [ "mlr_pipeops_augment_rotate", "PipeOpPreprocTorchAugmentRotate" ] }, { "page": "mlr_pipeops_augment_vflip", "title": "Vertical Flip Augmentation", "topics": [ "mlr_pipeops_augment_vflip", "PipeOpPreprocTorchAugmentVflip" ] }, { "page": "mlr_pipeops_module", "title": "Class for Torch Module Wrappers", "concept": [ "Graph Network" ], "topics": [ "mlr_pipeops_module", "PipeOpModule" ] }, { "page": "mlr_pipeops_nn_adaptive_avg_pool1d", "title": "1D Adaptive Average Pooling", "topics": [ "mlr_pipeops_nn_adaptive_avg_pool1d", "PipeOpTorchAdaptiveAvgPool1D" ] }, { "page": "mlr_pipeops_nn_adaptive_avg_pool2d", "title": "2D Adaptive Average Pooling", "topics": [ "mlr_pipeops_nn_adaptive_avg_pool2d", "PipeOpTorchAdaptiveAvgPool2D" ] }, { "page": "mlr_pipeops_nn_adaptive_avg_pool3d", "title": "3D Adaptive Average Pooling", "topics": [ "mlr_pipeops_nn_adaptive_avg_pool3d", "PipeOpTorchAdaptiveAvgPool3D" ] }, { "page": "mlr_pipeops_nn_adaptive_max_pool1d", "title": "1D Adaptive Max Pooling", "topics": [ "mlr_pipeops_nn_adaptive_max_pool1d", "PipeOpTorchAdaptiveMaxPool1D" ] }, { "page": "mlr_pipeops_nn_adaptive_max_pool2d", "title": "2D Adaptive Max Pooling", "topics": [ "mlr_pipeops_nn_adaptive_max_pool2d", "PipeOpTorchAdaptiveMaxPool2D" ] }, { "page": "mlr_pipeops_nn_adaptive_max_pool3d", "title": "3D Adaptive Max Pooling", "topics": [ "mlr_pipeops_nn_adaptive_max_pool3d", "PipeOpTorchAdaptiveMaxPool3D" ] }, { "page": "mlr_pipeops_nn_avg_pool1d", "title": "1D Average Pooling", "topics": [ "mlr_pipeops_nn_avg_pool1d", "PipeOpTorchAvgPool1D" ] }, { "page": "mlr_pipeops_nn_avg_pool2d", "title": "2D Average Pooling", "topics": [ "mlr_pipeops_nn_avg_pool2d", "PipeOpTorchAvgPool2D" ] }, { "page": "mlr_pipeops_nn_avg_pool3d", "title": "3D Average Pooling", "topics": [ "mlr_pipeops_nn_avg_pool3d", "PipeOpTorchAvgPool3D" ] }, { "page": "mlr_pipeops_nn_batch_norm1d", "title": "1D Batch Normalization", "topics": [ "mlr_pipeops_nn_batch_norm1d", "PipeOpTorchBatchNorm1D" ] }, { "page": "mlr_pipeops_nn_batch_norm2d", "title": "2D Batch Normalization", "topics": [ "mlr_pipeops_nn_batch_norm2d", "PipeOpTorchBatchNorm2D" ] }, { "page": "mlr_pipeops_nn_batch_norm3d", "title": "3D Batch Normalization", "topics": [ "mlr_pipeops_nn_batch_norm3d", "PipeOpTorchBatchNorm3D" ] }, { "page": "mlr_pipeops_nn_block", "title": "Block Repetition", "topics": [ "mlr_pipeops_nn_block", "PipeOpTorchBlock" ] }, { "page": "mlr_pipeops_nn_celu", "title": "CELU Activation Function", "topics": [ "mlr_pipeops_nn_celu", "PipeOpTorchCELU" ] }, { "page": "mlr_pipeops_nn_conv_transpose1d", "title": "Transpose 1D Convolution", "topics": [ "mlr_pipeops_nn_conv_transpose1d", "PipeOpTorchConvTranspose1D" ] }, { "page": "mlr_pipeops_nn_conv_transpose2d", "title": "Transpose 2D Convolution", "topics": [ "mlr_pipeops_nn_conv_transpose2d", "PipeOpTorchConvTranspose2D" ] }, { "page": "mlr_pipeops_nn_conv_transpose3d", "title": "Transpose 3D Convolution", "topics": [ "mlr_pipeops_nn_conv_transpose3d", "PipeOpTorchConvTranspose3D" ] }, { "page": "mlr_pipeops_nn_conv1d", "title": "1D Convolution", "topics": [ "mlr_pipeops_nn_conv1d", "PipeOpTorchConv1D" ] }, { "page": "mlr_pipeops_nn_conv2d", "title": "2D Convolution", "topics": [ "mlr_pipeops_nn_conv2d", "PipeOpTorchConv2D" ] }, { "page": "mlr_pipeops_nn_conv3d", "title": "3D Convolution", "topics": [ "mlr_pipeops_nn_conv3d", "PipeOpTorchConv3D" ] }, { "page": "mlr_pipeops_nn_dropout", "title": "Dropout", "topics": [ "mlr_pipeops_nn_dropout", "PipeOpTorchDropout" ] }, { "page": "mlr_pipeops_nn_dropout2d", "title": "2D Dropout", "topics": [ "mlr_pipeops_nn_dropout2d", "PipeOpTorchDropout2D" ] }, { "page": "mlr_pipeops_nn_dropout3d", "title": "3D Dropout", "topics": [ "mlr_pipeops_nn_dropout3d", "PipeOpTorchDropout3D" ] }, { "page": "mlr_pipeops_nn_elu", "title": "ELU Activation Function", "topics": [ "mlr_pipeops_nn_elu", "PipeOpTorchELU" ] }, { "page": "mlr_pipeops_nn_flatten", "title": "Flattens a Tensor", "topics": [ "mlr_pipeops_nn_flatten", "PipeOpTorchFlatten" ] }, { "page": "mlr_pipeops_nn_fn", "title": "Custom Function", "topics": [ "mlr_pipeops_nn_fn", "PipeOpTorchFn" ] }, { "page": "mlr_pipeops_nn_ft_cls", "title": "CLS Token for FT-Transformer", "topics": [ "mlr_pipeops_nn_ft_cls", "PipeOpTorchFTCLS" ] }, { "page": "mlr_pipeops_nn_ft_transformer_block", "title": "Single Transformer Block for the FT-Transformer", "topics": [ "mlr_pipeops_nn_ft_transformer_block", "PipeOpTorchFTTransformerBlock" ] }, { "page": "mlr_pipeops_nn_geglu", "title": "GeGLU Activation Function", "topics": [ "mlr_pipeops_nn_geglu", "PipeOpTorchGeGLU" ] }, { "page": "mlr_pipeops_nn_gelu", "title": "GELU Activation Function", "topics": [ "mlr_pipeops_nn_gelu", "PipeOpTorchGELU" ] }, { "page": "mlr_pipeops_nn_glu", "title": "GLU Activation Function", "topics": [ "mlr_pipeops_nn_glu", "PipeOpTorchGLU" ] }, { "page": "mlr_pipeops_nn_group_norm", "title": "Group Normalization", "topics": [ "mlr_pipeops_nn_group_norm", "PipeOpTorchGroupNorm" ] }, { "page": "mlr_pipeops_nn_gru", "title": "Gated Recurrent Unit", "topics": [ "mlr_pipeops_nn_gru", "PipeOpTorchGRU" ] }, { "page": "mlr_pipeops_nn_hardshrink", "title": "Hard Shrink Activation Function", "topics": [ "mlr_pipeops_nn_hardshrink", "PipeOpTorchHardShrink" ] }, { "page": "mlr_pipeops_nn_hardsigmoid", "title": "Hard Sigmoid Activation Function", "topics": [ "mlr_pipeops_nn_hardsigmoid", "PipeOpTorchHardSigmoid" ] }, { "page": "mlr_pipeops_nn_hardtanh", "title": "Hard Tanh Activation Function", "topics": [ "mlr_pipeops_nn_hardtanh", "PipeOpTorchHardTanh" ] }, { "page": "mlr_pipeops_nn_head", "title": "Output Head", "topics": [ "mlr_pipeops_nn_head", "PipeOpTorchHead" ] }, { "page": "mlr_pipeops_nn_identity", "title": "Identity Layer", "topics": [ "mlr_pipeops_nn_identity", "PipeOpTorchIdentity" ] }, { "page": "mlr_pipeops_nn_layer_norm", "title": "Layer Normalization", "topics": [ "mlr_pipeops_nn_layer_norm", "PipeOpTorchLayerNorm" ] }, { "page": "mlr_pipeops_nn_leaky_relu", "title": "Leaky ReLU Activation Function", "topics": [ "mlr_pipeops_nn_leaky_relu", "PipeOpTorchLeakyReLU" ] }, { "page": "mlr_pipeops_nn_linear", "title": "Linear Layer", "topics": [ "mlr_pipeops_nn_linear", "PipeOpTorchLinear" ] }, { "page": "mlr_pipeops_nn_log_sigmoid", "title": "Log Sigmoid Activation Function", "topics": [ "mlr_pipeops_nn_log_sigmoid", "PipeOpTorchLogSigmoid" ] }, { "page": "mlr_pipeops_nn_log_softmax", "title": "Log Softmax", "topics": [ "mlr_pipeops_nn_log_softmax", "PipeOpTorchLogSoftmax" ] }, { "page": "mlr_pipeops_nn_lstm", "title": "Long Short-Term Memory", "topics": [ "mlr_pipeops_nn_lstm", "PipeOpTorchLSTM" ] }, { "page": "mlr_pipeops_nn_max_pool1d", "title": "1D Max Pooling", "topics": [ "mlr_pipeops_nn_max_pool1d", "PipeOpTorchMaxPool1D" ] }, { "page": "mlr_pipeops_nn_max_pool2d", "title": "2D Max Pooling", "topics": [ "mlr_pipeops_nn_max_pool2d", "PipeOpTorchMaxPool2D" ] }, { "page": "mlr_pipeops_nn_max_pool3d", "title": "3D Max Pooling", "topics": [ "mlr_pipeops_nn_max_pool3d", "PipeOpTorchMaxPool3D" ] }, { "page": "mlr_pipeops_nn_merge", "title": "Merge Operation", "topics": [ "mlr_pipeops_nn_merge", "PipeOpTorchMerge" ] }, { "page": "mlr_pipeops_nn_merge_cat", "title": "Merge by Concatenation", "topics": [ "mlr_pipeops_nn_merge_cat", "PipeOpTorchMergeCat" ] }, { "page": "mlr_pipeops_nn_merge_prod", "title": "Merge by Product", "topics": [ "mlr_pipeops_nn_merge_prod", "PipeOpTorchMergeProd" ] }, { "page": "mlr_pipeops_nn_merge_sum", "title": "Merge by Summation", "topics": [ "mlr_pipeops_nn_merge_sum", "PipeOpTorchMergeSum" ] }, { "page": "mlr_pipeops_nn_multihead_attention", "title": "Multi-Head Attention", "topics": [ "mlr_pipeops_nn_multihead_attention", "PipeOpTorchMultiheadAttention" ] }, { "page": "mlr_pipeops_nn_prelu", "title": "PReLU Activation Function", "topics": [ "mlr_pipeops_nn_prelu", "PipeOpTorchPReLU" ] }, { "page": "mlr_pipeops_nn_recurrent", "title": "Recurrent Layer", "concept": [ "PipeOps" ], "topics": [ "mlr_pipeops_nn_recurrent", "PipeOpTorchRecurrent" ] }, { "page": "mlr_pipeops_nn_reglu", "title": "ReGLU Activation Function", "topics": [ "mlr_pipeops_nn_reglu", "PipeOpTorchReGLU" ] }, { "page": "mlr_pipeops_nn_relu", "title": "ReLU Activation Function", "topics": [ "mlr_pipeops_nn_relu", "PipeOpTorchReLU" ] }, { "page": "mlr_pipeops_nn_relu6", "title": "ReLU6 Activation Function", "topics": [ "mlr_pipeops_nn_relu6", "PipeOpTorchReLU6" ] }, { "page": "mlr_pipeops_nn_reshape", "title": "Reshape a Tensor", "topics": [ "mlr_pipeops_nn_reshape", "PipeOpTorchReshape" ] }, { "page": "mlr_pipeops_nn_rnn", "title": "Simple Recurrent Layer", "topics": [ "mlr_pipeops_nn_rnn", "PipeOpTorchRNN" ] }, { "page": "mlr_pipeops_nn_rrelu", "title": "RReLU Activation Function", "topics": [ "mlr_pipeops_nn_rrelu", "PipeOpTorchRReLU" ] }, { "page": "mlr_pipeops_nn_selu", "title": "SELU Activation Function", "topics": [ "mlr_pipeops_nn_selu", "PipeOpTorchSELU" ] }, { "page": "mlr_pipeops_nn_sigmoid", "title": "Sigmoid Activation Function", "topics": [ "mlr_pipeops_nn_sigmoid", "PipeOpTorchSigmoid" ] }, { "page": "mlr_pipeops_nn_silu", "title": "SiLU Activation Function", "topics": [ "mlr_pipeops_nn_silu", "PipeOpTorchSiLU" ] }, { "page": "mlr_pipeops_nn_softmax", "title": "Softmax", "topics": [ "mlr_pipeops_nn_softmax", "PipeOpTorchSoftmax" ] }, { "page": "mlr_pipeops_nn_softmax2d", "title": "2D Softmax", "topics": [ "mlr_pipeops_nn_softmax2d", "PipeOpTorchSoftmax2D" ] }, { "page": "mlr_pipeops_nn_softmin", "title": "Softmin", "topics": [ "mlr_pipeops_nn_softmin", "PipeOpTorchSoftmin" ] }, { "page": "mlr_pipeops_nn_softplus", "title": "SoftPlus Activation Function", "topics": [ "mlr_pipeops_nn_softplus", "PipeOpTorchSoftPlus" ] }, { "page": "mlr_pipeops_nn_softshrink", "title": "Soft Shrink Activation Function", "topics": [ "mlr_pipeops_nn_softshrink", "PipeOpTorchSoftShrink" ] }, { "page": "mlr_pipeops_nn_softsign", "title": "SoftSign Activation Function", "topics": [ "mlr_pipeops_nn_softsign", "PipeOpTorchSoftSign" ] }, { "page": "mlr_pipeops_nn_squeeze", "title": "Squeeze a Tensor", "topics": [ "mlr_pipeops_nn_squeeze", "PipeOpTorchSqueeze" ] }, { "page": "mlr_pipeops_nn_tanh", "title": "Tanh Activation Function", "topics": [ "mlr_pipeops_nn_tanh", "PipeOpTorchTanh" ] }, { "page": "mlr_pipeops_nn_tanhshrink", "title": "Tanh Shrink Activation Function", "topics": [ "mlr_pipeops_nn_tanhshrink", "PipeOpTorchTanhShrink" ] }, { "page": "mlr_pipeops_nn_threshold", "title": "Threshold Activation Function", "topics": [ "mlr_pipeops_nn_threshold", "PipeOpTorchThreshold" ] }, { "page": "mlr_pipeops_nn_tokenizer_categ", "title": "Categorical Tokenizer", "topics": [ "mlr_pipeops_nn_tokenizer_categ", "PipeOpTorchTokenizerCateg" ] }, { "page": "mlr_pipeops_nn_tokenizer_num", "title": "Numeric Tokenizer", "topics": [ "mlr_pipeops_nn_tokenizer_num", "PipeOpTorchTokenizerNum" ] }, { "page": "mlr_pipeops_nn_transformer_encoder_layer", "title": "Transformer Encoder Layer", "topics": [ "mlr_pipeops_nn_transformer_encoder_layer", "PipeOpTorchTransformerEncoderLayer" ] }, { "page": "mlr_pipeops_nn_unflatten", "title": "Unflattens a Tensor", "topics": [ "mlr_pipeops_nn_unflatten", "PipeOpTorchUnflatten" ] }, { "page": "mlr_pipeops_nn_unsqueeze", "title": "Unsqueeze a Tensor", "topics": [ "mlr_pipeops_nn_unsqueeze", "PipeOpTorchUnsqueeze" ] }, { "page": "mlr_pipeops_preproc_torch", "title": "Base Class for Lazy Tensor Preprocessing", "topics": [ "mlr_pipeops_preproc_torch", "PipeOpTaskPreprocTorch" ] }, { "page": "mlr_pipeops_torch", "title": "Base Class for Torch Module Constructor Wrappers", "concept": [ "Graph Network" ], "topics": [ "mlr_pipeops_torch", "PipeOpTorch" ] }, { "page": "mlr_pipeops_torch_callbacks", "title": "Callback Configuration", "concept": [ "Model Configuration" ], "topics": [ "mlr_pipeops_torch_callbacks", "PipeOpTorchCallbacks" ] }, { "page": "mlr_pipeops_torch_ingress", "title": "Entrypoint to Torch Network", "concept": [ "Graph Network" ], "topics": [ "mlr_pipeops_torch_ingress", "PipeOpTorchIngress" ] }, { "page": "mlr_pipeops_torch_ingress_categ", "title": "Torch Entry Point for Categorical Features", "concept": [ "Graph Network" ], "topics": [ "mlr_pipeops_torch_ingress_categ", "PipeOpTorchIngressCategorical" ] }, { "page": "mlr_pipeops_torch_ingress_ltnsr", "title": "Ingress for Lazy Tensor", "concept": [ "Graph Network" ], "topics": [ "mlr_pipeops_torch_ingress_ltnsr", "PipeOpTorchIngressLazyTensor" ] }, { "page": "mlr_pipeops_torch_ingress_num", "title": "Torch Entry Point for Numeric Features", "concept": [ "Graph Network" ], "topics": [ "mlr_pipeops_torch_ingress_num", "PipeOpTorchIngressNumeric" ] }, { "page": "mlr_pipeops_torch_loss", "title": "Loss Configuration", "concept": [ "Model Configuration" ], "topics": [ "mlr_pipeops_torch_loss", "PipeOpTorchLoss" ] }, { "page": "mlr_pipeops_torch_model", "title": "PipeOp Torch Model", "concept": [ "PipeOps" ], "topics": [ "mlr_pipeops_torch_model", "PipeOpTorchModel" ] }, { "page": "mlr_pipeops_torch_model_classif", "title": "PipeOp Torch Classifier", "topics": [ "mlr_pipeops_torch_model_classif", "PipeOpTorchModelClassif" ] }, { "page": "mlr_pipeops_torch_model_regr", "title": "Torch Regression Model", "topics": [ "mlr_pipeops_torch_model_regr", "PipeOpTorchModelRegr" ] }, { "page": "mlr_pipeops_torch_optimizer", "title": "Optimizer Configuration", "concept": [ "Model Configuration" ], "topics": [ "mlr_pipeops_torch_optimizer", "PipeOpTorchOptimizer" ] }, { "page": "mlr_pipeops_trafo_adjust_brightness", "title": "Adjust Brightness Transformation", "topics": [ "mlr_pipeops_trafo_adjust_brightness", "PipeOpPreprocTorchTrafoAdjustBrightness" ] }, { "page": "mlr_pipeops_trafo_adjust_gamma", "title": "Adjust Gamma Transformation", "topics": [ "mlr_pipeops_trafo_adjust_gamma", "PipeOpPreprocTorchTrafoAdjustGamma" ] }, { "page": "mlr_pipeops_trafo_adjust_hue", "title": "Adjust Hue Transformation", "topics": [ "mlr_pipeops_trafo_adjust_hue", "PipeOpPreprocTorchTrafoAdjustHue" ] }, { "page": "mlr_pipeops_trafo_adjust_saturation", "title": "Adjust Saturation Transformation", "topics": [ "mlr_pipeops_trafo_adjust_saturation", "PipeOpPreprocTorchTrafoAdjustSaturation" ] }, { "page": "mlr_pipeops_trafo_grayscale", "title": "Grayscale Transformation", "topics": [ "mlr_pipeops_trafo_grayscale", "PipeOpPreprocTorchTrafoGrayscale" ] }, { "page": "PipeOpPreprocTorchTrafoNop", "title": "No Transformation", "topics": [ "mlr_pipeops_trafo_nop", "PipeOpPreprocTorchTrafoNop" ] }, { "page": "mlr_pipeops_trafo_normalize", "title": "Normalization Transformation", "topics": [ "mlr_pipeops_trafo_normalize", "PipeOpPreprocTorchTrafoNormalize" ] }, { "page": "mlr_pipeops_trafo_pad", "title": "Padding Transformation", "topics": [ "mlr_pipeops_trafo_pad", "PipeOpPreprocTorchTrafoPad" ] }, { "page": "PipeOpPreprocTorchTrafoReshape", "title": "Reshaping Transformation", "topics": [ "mlr_pipeops_trafo_reshape", "PipeOpPreprocTorchTrafoReshape" ] }, { "page": "mlr_pipeops_trafo_resize", "title": "Resizing Transformation", "topics": [ "mlr_pipeops_trafo_resize", "PipeOpPreprocTorchTrafoResize" ] }, { "page": "mlr_pipeops_trafo_rgb_to_grayscale", "title": "RGB to Grayscale Transformation", "topics": [ "mlr_pipeops_trafo_rgb_to_grayscale", "PipeOpPreprocTorchTrafoRgbToGrayscale" ] }, { "page": "mlr_tasks_cifar", "title": "CIFAR Classification Tasks", "topics": [ "mlr_tasks_cifar", "mlr_tasks_cifar10", "mlr_tasks_cifar100" ] }, { "page": "mlr_tasks_lazy_iris", "title": "Iris Classification Task", "topics": [ "mlr_tasks_lazy_iris" ] }, { "page": "mlr_tasks_melanoma", "title": "Melanoma Image classification", "topics": [ "mlr_tasks_melanoma" ] }, { "page": "mlr_tasks_mnist", "title": "MNIST Image classification", "topics": [ "mlr_tasks_mnist" ] }, { "page": "mlr_tasks_tiny_imagenet", "title": "Tiny ImageNet Classification Task", "topics": [ "mlr_tasks_tiny_imagenet" ] }, { "page": "mlr_tasks_torch", "title": "Generic Torch Task", "concept": [ "Task" ], "topics": [ "mlr_tasks_torch", "TaskTorch" ] }, { "page": "mlr3torch_callbacks", "title": "Dictionary of Torch Callbacks", "concept": [ "Callback", "Dictionary" ], "topics": [ "mlr3torch_callbacks" ] }, { "page": "mlr3torch_losses", "title": "Loss Functions", "concept": [ "Dictionary", "Torch Descriptor" ], "topics": [ "mlr3torch_losses" ] }, { "page": "mlr3torch_optimizers", "title": "Optimizers", "concept": [ "Dictionary", "Torch Descriptor" ], "topics": [ "mlr3torch_optimizers" ] }, { "page": "model_descriptor_to_learner", "title": "Create a Torch Learner from a ModelDescriptor", "concept": [ "Graph Network" ], "topics": [ "model_descriptor_to_learner" ] }, { "page": "model_descriptor_to_module", "title": "Create a nn_graph from ModelDescriptor", "concept": [ "Graph Network" ], "topics": [ "model_descriptor_to_module" ] }, { "page": "model_descriptor_union", "title": "Union of ModelDescriptors", "concept": [ "Graph Network", "Model Configuration" ], "topics": [ "model_descriptor_union" ] }, { "page": "ModelDescriptor", "title": "Represent a Model with Meta-Info", "concept": [ "Graph Network", "Model Configuration" ], "topics": [ "ModelDescriptor" ] }, { "page": "msr_torch", "title": "Create a Measure for a Generic Torch Task", "topics": [ "msr_torch" ] }, { "page": "nn", "title": "Create a Neural Network Layer", "topics": [ "nn" ] }, { "page": "nn_ft_cls", "title": "CLS Token for FT-Transformer", "topics": [ "nn_ft_cls" ] }, { "page": "nn_ft_transformer_block", "title": "Single Transformer Block for FT-Transformer", "topics": [ "nn_ft_transformer_block" ] }, { "page": "nn_geglu", "title": "GeGLU Module", "topics": [ "nn_geglu" ] }, { "page": "nn_graph", "title": "Graph Network", "concept": [ "Graph Network" ], "topics": [ "nn_graph" ] }, { "page": "nn_merge_cat", "title": "Concatenates multiple tensors", "topics": [ "nn_merge_cat" ] }, { "page": "nn_merge_prod", "title": "Product of multiple tensors", "topics": [ "nn_merge_prod" ] }, { "page": "nn_merge_sum", "title": "Sum of multiple tensors", "topics": [ "nn_merge_sum" ] }, { "page": "nn_reglu", "title": "ReGLU Module", "topics": [ "nn_reglu" ] }, { "page": "nn_reshape", "title": "Reshape", "topics": [ "nn_reshape" ] }, { "page": "nn_squeeze", "title": "Squeeze", "topics": [ "nn_squeeze" ] }, { "page": "nn_tokenizer_categ", "title": "Categorical Tokenizer", "topics": [ "nn_tokenizer_categ" ] }, { "page": "nn_tokenizer_num", "title": "Numeric Tokenizer", "topics": [ "nn_tokenizer_num" ] }, { "page": "nn_unsqueeze", "title": "Unsqueeze", "topics": [ "nn_unsqueeze" ] }, { "page": "output_dim_for", "title": "Network Output Dimension", "topics": [ "output_dim_for" ] }, { "page": "pipeop_preproc_torch", "title": "Create Torch Preprocessing PipeOps", "topics": [ "pipeop_preproc_torch" ] }, { "page": "pipeop_torch", "title": "Create a PipeOpTorch", "concept": [ "Graph Network" ], "topics": [ "pipeop_torch" ] }, { "page": "PredictionTorch", "title": "Prediction Object for a Generic Torch Task", "concept": [ "Prediction" ], "topics": [ "PredictionTorch" ] }, { "page": "reshape_output_shape", "title": "Output Shape of a Reshape", "concept": [ "Shape Inference" ], "topics": [ "reshape_output_shape" ] }, { "page": "Select", "title": "Selector Functions for Character Vectors", "topics": [ "Select", "select_all", "select_grep", "select_invert", "select_name", "select_none" ] }, { "page": "shape_helpers", "title": "Helpers for Shape Inference", "concept": [ "Shape Inference" ], "topics": [ "broadcast_shapes", "resolve_dim", "shape_helpers", "shape_to_str" ] }, { "page": "t_clbk", "title": "Sugar Function for Torch Callback", "concept": [ "Callback", "Torch Descriptor" ], "topics": [ "t_clbk", "t_clbks" ] }, { "page": "t_loss", "title": "Loss Function Quick Access", "concept": [ "Torch Descriptor" ], "topics": [ "t_loss", "t_losses" ] }, { "page": "t_opt", "title": "Optimizers Quick Access", "concept": [ "Dictionary", "Torch Descriptor" ], "topics": [ "t_opt", "t_opts" ] }, { "page": "task_dataset", "title": "Create a Dataset from a Task", "topics": [ "task_dataset" ] }, { "page": "torch_callback", "title": "Create a Callback Descriptor", "concept": [ "Callback" ], "topics": [ "torch_callback" ] }, { "page": "TorchCallback", "title": "Torch Callback", "concept": [ "Callback", "Torch Descriptor" ], "topics": [ "TorchCallback" ] }, { "page": "TorchDescriptor", "title": "Base Class for Torch Descriptors", "concept": [ "Torch Descriptor" ], "topics": [ "TorchDescriptor" ] }, { "page": "TorchIngressToken", "title": "Torch Ingress Token", "concept": [ "Graph Network" ], "topics": [ "TorchIngressToken" ] }, { "page": "TorchLoss", "title": "Torch Loss", "concept": [ "Torch Descriptor" ], "topics": [ "TorchLoss" ] }, { "page": "TorchOptimizer", "title": "Torch Optimizer", "concept": [ "Torch Descriptor" ], "topics": [ "TorchOptimizer" ] } ], "_pkglogo": "https://github.com/cran/mlr3torch/raw/HEAD/man/figures/logo.svg", "_readme": "https://github.com/cran/mlr3torch/raw/HEAD/README.md", "_rundeps": [ "backports", "bit", "bit64", "callr", "checkmate", "cli", "codetools", "coro", "data.table", "desc", "digest", "evaluate", "farver", "future", "future.apply", "globals", "glue", "jsonlite", "labeling", "lgr", "lifecycle", "listenv", "magrittr", "mirai", "mlbench", "mlr3", "mlr3measures", "mlr3misc", "mlr3pipelines", "nanonext", "otel", "palmerpenguins", "paradox", "parallelly", "processx", "PRROC", "ps", "R6", "RColorBrewer", "Rcpp", "rlang", "safetensors", "scales", "torch", "uuid", "viridisLite", "withr" ], "_score": 4.445445867070391, "_indexed": false, "_nocasepkg": "mlr3torch", "_universes": [ "cran" ], "_indexurl": "https://mlr-org.r-universe.dev/mlr3torch", "_previous": "0.3.3", "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.4.0", "date": "2026-10-30T21:15:21.000Z", "distro": "resolute", "commit": "ab1494873b713dedb1cb64290f2fdf2e6ca77190", "fileid": "https://r2.ropensci.org/09e4ebd861882c59f9f86799f24d42273b077e7a45eec6273b3ab0f02aea5d40", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/41128780613" }, { "r": "4.6.1", "os": "linux", "version": "0.4.0", "date": "2026-10-30T21:15:10.000Z", "distro": "resolute", "commit": "ab1494873b713dedb1cb64290f2fdf2e6ca77190", "fileid": "https://r2.ropensci.org/6b4195723c61a810768c5420048110ace1e2a40e49de65e1e3e6056a85e524f9", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/41128780613" }, { "r": "4.6.0", "os": "wasm", "version": "0.4.0", "date": "2026-10-30T21:15:17.000Z", "commit": "ab1494873b713dedb1cb64290f2fdf2e6ca77190", "fileid": "https://r2.ropensci.org/f9d0510ad83954909be3ffeae60e999bd7f25b105ad1c5f1777df878e8b64abb", "status": "success", "buildurl": "https://github.com/r-universe/cran/actions/runs/41128780613" }, { "r": "4.7.0", "os": "win", "version": "0.4.0", "date": "2026-10-30T21:14:19.000Z", "commit": "ab1494873b713dedb1cb64290f2fdf2e6ca77190", "fileid": "https://r2.ropensci.org/7586eb1a79be60e610eb55df68b8ae0d906d5eb8489c39ce615117b4cf94d0ab", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/41128780613" }, { "r": "4.6.1", "os": "win", "version": "0.4.0", "date": "2026-10-30T21:14:23.000Z", "commit": "ab1494873b713dedb1cb64290f2fdf2e6ca77190", "fileid": "https://r2.ropensci.org/1201874c4c59aecdec3e6b451aa0a4232746ab4ac5f699d802e1e11367eb5e65", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/41128780613" } ] }