Loading docs/_static/theme_overrides.css 0 → 100644 +13 −0 Original line number Diff line number Diff line /* override table width restrictions */ @media screen and (min-width: 767px) { .wy-table-responsive table td { /* !important prevents the common CSS stylesheets from overriding this as on RTD they are loaded after this stylesheet */ white-space: normal !important; } .wy-table-responsive { overflow: visible !important; } } docs/conf.py +6 −0 Original line number Diff line number Diff line Loading @@ -62,6 +62,12 @@ html_theme_path = [sphinx_rtd_theme.get_html_theme_path()] # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] html_context = { 'css_files': [ '_static/theme_overrides.css', # override wide tables in RTD theme ], } # The name of an image file (relative to this directory) to place at the top # of the sidebar. html_logo = '_static/logo.png' Loading docs/models.rst +102 −0 Original line number Diff line number Diff line Model Classes ============= DeepChem maintains an extensive collection of models for scientific applications. Model Cheatsheet ---------------- If you're just getting started with DeepChem, you're probably interested in the basics. The place to get started is this "model cheatsheet" that lists various types of custom DeepChem models. Note that some wrappers like `SklearnModel` and `XGBoostModel` which wrap external machine learning libraries are excluded, but this table is otherwise complete. As a note about how to read this table, each row describes what's needed to invoke a given model. Some models must be applied with given `Transformer` or `Featurizer` objects. Some models also have custom training methods. You can read off what's needed to train the model from the table below. +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | Model | Type | Input Type | Transformations | Acceptable Featurizers | Fit Method | +==================================+============+================+=================+================================================================+===============+ | `AtomicConvModel` | Classifier/| Tuple | | `ComplexNeighborListFragmentAtomicCoordinates` | `fit` | | | Regressor | | | | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `ChemCeption` | Classifier/| Tensor of shape| | `SmilesToImage` | `fit` | | | Regressor | `(N, M, c)` | | | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `CNN` | Classifier/| Tensor of shape| | | `fit` | | | Regressor | `(N, c)` or | | | | | | | `(N, M, c)` or | | | | | | | `(N, M, L, c)` | | | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `DTNNModel` | Classifier/| Matrix of | | `CoulombMatrix` | `fit` | | | Regressor | shape `(N, N)` | | | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `DAGModel` | Classifier/| `ConvMol` | `DAGTransformer`| `ConvMolFeaturizer` | `fit` | | | Regressor | | | | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `GraphConvModel` | Classifier/| `ConvMol` | | `ConvMolFeaturizer` | `fit` | | | Regressor | | | | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `MPNNModel` | Classifier/| `WeaveMol` | | `WeaveFeaturizer` | `fit` | | | Regressor | | | | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `MultitaskClassifier` | Classifier | Vector of | | `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `MultitaskRegressor` | Classifier | Vector of | | `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `MultitaskRegressor` | Classifier | Vector of | | `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `MultitaskFitTransformRegressor` | Classifier | Vector of | | `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `MultitaskRVClassifier` | Classifier | Vector of | `IRVTransformer`| `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `ProgressiveMultitaskClassifier` | Classifier | Vector of | | `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `ProgressiveMultitaskRegressor` | Classifier | Vector of | | `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `RobustMultitaskClassifier` | Classifier | Vector of | | `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `RobustMultitaskRegressor` | Classifier | Vector of | | `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `ScScoreModel` | Classifier | Vector of | | `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `SeqToSeq` | Sequence | Sequence | | |`fit_sequences`| +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `Smiles2Vec` | Classifier/| Sequence | | `SmilesToSeq` | `fit` | | | Regressor | | | | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `TextCNNModel` | Classifier/| String | | | `fit` | | | Regressor | | | | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `WGAN` | Adversarial| Pair | | |`fit_gan` | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ Model ----- Loading Loading
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docs/models.rst +102 −0 Original line number Diff line number Diff line Model Classes ============= DeepChem maintains an extensive collection of models for scientific applications. Model Cheatsheet ---------------- If you're just getting started with DeepChem, you're probably interested in the basics. The place to get started is this "model cheatsheet" that lists various types of custom DeepChem models. Note that some wrappers like `SklearnModel` and `XGBoostModel` which wrap external machine learning libraries are excluded, but this table is otherwise complete. As a note about how to read this table, each row describes what's needed to invoke a given model. Some models must be applied with given `Transformer` or `Featurizer` objects. Some models also have custom training methods. You can read off what's needed to train the model from the table below. +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | Model | Type | Input Type | Transformations | Acceptable Featurizers | Fit Method | +==================================+============+================+=================+================================================================+===============+ | `AtomicConvModel` | Classifier/| Tuple | | `ComplexNeighborListFragmentAtomicCoordinates` | `fit` | | | Regressor | | | | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `ChemCeption` | Classifier/| Tensor of shape| | `SmilesToImage` | `fit` | | | Regressor | `(N, M, c)` | | | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `CNN` | Classifier/| Tensor of shape| | | `fit` | | | Regressor | `(N, c)` or | | | | | | | `(N, M, c)` or | | | | | | | `(N, M, L, c)` | | | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `DTNNModel` | Classifier/| Matrix of | | `CoulombMatrix` | `fit` | | | Regressor | shape `(N, N)` | | | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `DAGModel` | Classifier/| `ConvMol` | `DAGTransformer`| `ConvMolFeaturizer` | `fit` | | | Regressor | | | | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `GraphConvModel` | Classifier/| `ConvMol` | | `ConvMolFeaturizer` | `fit` | | | Regressor | | | | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `MPNNModel` | Classifier/| `WeaveMol` | | `WeaveFeaturizer` | `fit` | | | Regressor | | | | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `MultitaskClassifier` | Classifier | Vector of | | `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `MultitaskRegressor` | Classifier | Vector of | | `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `MultitaskRegressor` | Classifier | Vector of | | `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `MultitaskFitTransformRegressor` | Classifier | Vector of | | `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `MultitaskRVClassifier` | Classifier | Vector of | `IRVTransformer`| `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `ProgressiveMultitaskClassifier` | Classifier | Vector of | | `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `ProgressiveMultitaskRegressor` | Classifier | Vector of | | `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `RobustMultitaskClassifier` | Classifier | Vector of | | `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `RobustMultitaskRegressor` | Classifier | Vector of | | `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `ScScoreModel` | Classifier | Vector of | | `CircularFingerprint`, | `fit` | | | | shape `(N,)` | | `RDKitDescriptors`, `CoulombMatrixEig`, `RdkitGridFeaturizer`, | | | | | | | `BindingPocketFeaturizer`, | | | | | | | `AdjacencyFingerprint`, `ElementPropertyFingerprint`, | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `SeqToSeq` | Sequence | Sequence | | |`fit_sequences`| +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `Smiles2Vec` | Classifier/| Sequence | | `SmilesToSeq` | `fit` | | | Regressor | | | | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `TextCNNModel` | Classifier/| String | | | `fit` | | | Regressor | | | | | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ | `WGAN` | Adversarial| Pair | | |`fit_gan` | +----------------------------------+------------+----------------+-----------------+----------------------------------------------------------------+---------------+ Model ----- Loading
