Man pages for keras
R Interface to 'Keras'

activation_reluActivation functions
adaptFits the state of the preprocessing layer to the data being...
application_densenetInstantiates the DenseNet architecture.
application_efficientnetInstantiates the EfficientNetB0 architecture
application_inception_resnet_v2Inception-ResNet v2 model, with weights trained on ImageNet
application_inception_v3Inception V3 model, with weights pre-trained on ImageNet.
application_mobilenetMobileNet model architecture.
application_mobilenet_v2MobileNetV2 model architecture
application_mobilenet_v3Instantiates the MobileNetV3Large architecture
application_nasnetInstantiates a NASNet model.
application_resnetInstantiates the ResNet architecture
application_vggVGG16 and VGG19 models for Keras.
application_xceptionInstantiates the Xception architecture
backendKeras backend tensor engine
bidirectionalBidirectional wrapper for RNNs
callback_backup_and_restoreCallback to back up and restore the training state
callback_csv_loggerCallback that streams epoch results to a csv file
callback_early_stoppingStop training when a monitored quantity has stopped...
callback_lambdaCreate a custom callback
callback_learning_rate_schedulerLearning rate scheduler.
callback_model_checkpointSave the model after every epoch.
callback_progbar_loggerCallback that prints metrics to stdout.
callback_reduce_lr_on_plateauReduce learning rate when a metric has stopped improving.
callback_remote_monitorCallback used to stream events to a server.
callback_tensorboardTensorBoard basic visualizations
callback_terminate_on_naanCallback that terminates training when a NaN loss is...
clone_modelClone a model instance. a Keras model for training
constraintsWeight constraints
count_paramsCount the total number of scalars composing the weights.
create_layerCreate a Keras Layer
create_layer_wrapperCreate a Keras Layer wrapper
create_wrapper(Deprecated) Create a Keras Wrapper
custom_metricCustom metric function
dataset_boston_housingBoston housing price regression dataset
dataset_cifar10CIFAR10 small image classification
dataset_cifar100CIFAR100 small image classification
dataset_fashion_mnistFashion-MNIST database of fashion articles
dataset_imdbIMDB Movie reviews sentiment classification
dataset_mnistMNIST database of handwritten digits
dataset_reutersReuters newswire topics classification
evaluate_generator(Deprecated) Evaluates the model on a data generator. a Keras model a Saved Model
fit_generator(Deprecated) Fits the model on data yielded batch-by-batch by...
fit_image_data_generatorFit image data generator internal statistics to some sample... a Keras model
fit_text_tokenizerUpdate tokenizer internal vocabulary based on a list of texts...
flow_images_from_dataGenerates batches of augmented/normalized data from image...
flow_images_from_dataframeTakes the dataframe and the path to a directory and generates...
flow_images_from_directoryGenerates batches of data from images in a directory (with...
freeze_weightsFreeze and unfreeze weights
generator_nextRetrieve the next item from a generator
get_configLayer/Model configuration
get_fileDownloads a file from a URL if it not already in the cache.
get_input_atRetrieve tensors for layers with multiple nodes
get_layerRetrieves a layer based on either its name (unique) or index.
get_weightsLayer/Model weights as R arrays
grapes-py_class-grapesMake a python class constructor
grapes-set-active-grapesMake an Active Binding
hdf5_matrixRepresentation of HDF5 dataset to be used instead of an R...
image_data_generatorDeprecated Generate batches of image data with real-time data...
image_dataset_from_directoryCreate a dataset from a directory
image_loadLoads an image into PIL format.
imagenet_decode_predictionsDecodes the prediction of an ImageNet model.
imagenet_preprocess_inputPreprocesses a tensor or array encoding a batch of images.
image_to_array3D array representation of images
implementationKeras implementation
initializer_constantInitializer that generates tensors initialized to a constant...
initializer_glorot_normalGlorot normal initializer, also called Xavier normal...
initializer_glorot_uniformGlorot uniform initializer, also called Xavier uniform...
initializer_he_normalHe normal initializer.
initializer_he_uniformHe uniform variance scaling initializer.
initializer_identityInitializer that generates the identity matrix.
initializer_lecun_normalLeCun normal initializer.
initializer_lecun_uniformLeCun uniform initializer.
initializer_onesInitializer that generates tensors initialized to 1.
initializer_orthogonalInitializer that generates a random orthogonal matrix.
initializer_random_normalInitializer that generates tensors with a normal...
initializer_random_uniformInitializer that generates tensors with a uniform...
initializer_truncated_normalInitializer that generates a truncated normal distribution.
initializer_variance_scalingInitializer capable of adapting its scale to the shape of...
initializer_zerosInitializer that generates tensors initialized to 0.
install_kerasInstall TensorFlow and Keras, including all Python...
is_keras_availableCheck if Keras is Available
k_absElement-wise absolute value.
k_allBitwise reduction (logical AND).
k_anyBitwise reduction (logical OR).
k_arangeCreates a 1D tensor containing a sequence of integers.
k_argmaxReturns the index of the maximum value along an axis.
k_argminReturns the index of the minimum value along an axis.
k_backendActive Keras backend
k_batch_dotBatchwise dot product.
k_batch_flattenTurn a nD tensor into a 2D tensor with same 1st dimension.
k_batch_get_valueReturns the value of more than one tensor variable.
k_batch_normalizationApplies batch normalization on x given mean, var, beta and...
k_batch_set_valueSets the values of many tensor variables at once.
k_bias_addAdds a bias vector to a tensor.
k_binary_crossentropyBinary crossentropy between an output tensor and a target...
k_castCasts a tensor to a different dtype and returns it.
k_cast_to_floatxCast an array to the default Keras float type.
k_categorical_crossentropyCategorical crossentropy between an output tensor and a...
k_clear_sessionDestroys the current TF graph and creates a new one.
k_clipElement-wise value clipping.
k_concatenateConcatenates a list of tensors alongside the specified axis.
k_constantCreates a constant tensor.
k_conv1d1D convolution.
k_conv2d2D convolution.
k_conv2d_transpose2D deconvolution (i.e. transposed convolution).
k_conv3d3D convolution.
k_conv3d_transpose3D deconvolution (i.e. transposed convolution).
k_cosComputes cos of x element-wise.
k_count_paramsReturns the static number of elements in a Keras variable or...
k_ctc_batch_costRuns CTC loss algorithm on each batch element.
k_ctc_decodeDecodes the output of a softmax.
k_ctc_label_dense_to_sparseConverts CTC labels from dense to sparse.
k_cumprodCumulative product of the values in a tensor, alongside the...
k_cumsumCumulative sum of the values in a tensor, alongside the...
k_depthwise_conv2dDepthwise 2D convolution with separable filters.
k_dotMultiplies 2 tensors (and/or variables) and returns a...
k_dropoutSets entries in 'x' to zero at random, while scaling the...
k_dtypeReturns the dtype of a Keras tensor or variable, as a string.
k_eluExponential linear unit.
k_epsilonFuzz factor used in numeric expressions.
k_equalElement-wise equality between two tensors.
kerasMain Keras module
keras_arrayKeras array object
KerasCallback(Deprecated) Base R6 class for Keras callbacks
KerasConstraint(Deprecated) Base R6 class for Keras constraints
KerasLayer(Deprecated) Base R6 class for Keras layers
keras_modelKeras Model
keras_model_custom(Deprecated) Create a Keras custom model
keras_model_sequentialKeras Model composed of a linear stack of layers
keras-packageR interface to Keras
KerasWrapper(Deprecated) Base R6 class for Keras wrappers
k_evalEvaluates the value of a variable.
k_expElement-wise exponential.
k_expand_dimsAdds a 1-sized dimension at index 'axis'.
k_eyeInstantiate an identity matrix and returns it.
k_flattenFlatten a tensor.
k_floatxDefault float type
k_foldlReduce elems using fn to combine them from left to right.
k_foldrReduce elems using fn to combine them from right to left.
k_functionInstantiates a Keras function
k_gatherRetrieves the elements of indices 'indices' in the tensor...
k_get_sessionTF session to be used by the backend.
k_get_uidGet the uid for the default graph.
k_get_valueReturns the value of a variable.
k_get_variable_shapeReturns the shape of a variable.
k_gradientsReturns the gradients of 'variables' w.r.t. 'loss'.
k_greaterElement-wise truth value of (x > y).
k_greater_equalElement-wise truth value of (x >= y).
k_hard_sigmoidSegment-wise linear approximation of sigmoid.
k_identityReturns a tensor with the same content as the input tensor.
k_image_data_formatDefault image data format convention ('channels_first' or...
k_in_test_phaseSelects 'x' in test phase, and 'alt' otherwise.
k_in_top_kReturns whether the 'targets' are in the top 'k'...
k_in_train_phaseSelects 'x' in train phase, and 'alt' otherwise.
k_int_shapeReturns the shape of tensor or variable as a list of int or...
k_is_keras_tensorReturns whether 'x' is a Keras tensor.
k_is_placeholderReturns whether 'x' is a placeholder.
k_is_sparseReturns whether a tensor is a sparse tensor.
k_is_tensorReturns whether 'x' is a symbolic tensor.
k_l2_normalizeNormalizes a tensor wrt the L2 norm alongside the specified...
k_learning_phaseReturns the learning phase flag.
k_lessElement-wise truth value of (x < y).
k_less_equalElement-wise truth value of (x <= y).
k_local_conv1dApply 1D conv with un-shared weights.
k_local_conv2dApply 2D conv with un-shared weights.
k_logElement-wise log.
k_logsumexp(Deprecated) Computes log(sum(exp(elements across dimensions...
k_manual_variable_initializationSets the manual variable initialization flag.
k_map_fnMap the function fn over the elements elems and return the...
k_maxMaximum value in a tensor.
k_maximumElement-wise maximum of two tensors.
k_meanMean of a tensor, alongside the specified axis.
k_minMinimum value in a tensor.
k_minimumElement-wise minimum of two tensors.
k_moving_average_updateCompute the moving average of a variable.
k_ndimReturns the number of axes in a tensor, as an integer.
k_normalize_batch_in_trainingComputes mean and std for batch then apply...
k_not_equalElement-wise inequality between two tensors.
k_one_hotComputes the one-hot representation of an integer tensor.
k_onesInstantiates an all-ones tensor variable and returns it.
k_ones_likeInstantiates an all-ones variable of the same shape as...
k_permute_dimensionsPermutes axes in a tensor.
k_placeholderInstantiates a placeholder tensor and returns it.
k_pool2d2D Pooling.
k_pool3d3D Pooling.
k_powElement-wise exponentiation.
k_print_tensorPrints 'message' and the tensor value when evaluated.
k_prodMultiplies the values in a tensor, alongside the specified...
k_random_bernoulliReturns a tensor with random binomial distribution of values.
k_random_normalReturns a tensor with normal distribution of values.
k_random_normal_variableInstantiates a variable with values drawn from a normal...
k_random_uniformReturns a tensor with uniform distribution of values.
k_random_uniform_variableInstantiates a variable with values drawn from a uniform...
k_reluRectified linear unit.
k_repeatRepeats a 2D tensor.
k_repeat_elementsRepeats the elements of a tensor along an axis.
k_reset_uidsReset graph identifiers.
k_reshapeReshapes a tensor to the specified shape.
k_resize_imagesResizes the images contained in a 4D tensor.
k_resize_volumesResizes the volume contained in a 5D tensor.
k_reverseReverse a tensor along the specified axes.
k_rnnIterates over the time dimension of a tensor
k_roundElement-wise rounding to the closest integer.
k_separable_conv2d2D convolution with separable filters.
k_set_learning_phaseSets the learning phase to a fixed value.
k_set_valueSets the value of a variable, from an R array.
k_shapeReturns the symbolic shape of a tensor or variable.
k_sigmoidElement-wise sigmoid.
k_signElement-wise sign.
k_sinComputes sin of x element-wise.
k_softmaxSoftmax of a tensor.
k_softplusSoftplus of a tensor.
k_softsignSoftsign of a tensor.
k_sparse_categorical_crossentropyCategorical crossentropy with integer targets.
k_spatial_2d_paddingPads the 2nd and 3rd dimensions of a 4D tensor.
k_spatial_3d_paddingPads 5D tensor with zeros along the depth, height, width...
k_sqrtElement-wise square root.
k_squareElement-wise square.
k_squeezeRemoves a 1-dimension from the tensor at index 'axis'.
k_stackStacks a list of rank 'R' tensors into a rank 'R+1' tensor.
k_stdStandard deviation of a tensor, alongside the specified axis.
k_stop_gradientReturns 'variables' but with zero gradient w.r.t. every other...
k_sumSum of the values in a tensor, alongside the specified axis.
k_switchSwitches between two operations depending on a scalar value.
k_tanhElement-wise tanh.
k_temporal_paddingPads the middle dimension of a 3D tensor.
k_tileCreates a tensor by tiling 'x' by 'n'.
k_to_denseConverts a sparse tensor into a dense tensor and returns it.
k_transposeTransposes a tensor and returns it.
k_truncated_normalReturns a tensor with truncated random normal distribution of...
k_unstackUnstack rank 'R' tensor into a list of rank 'R-1' tensors.
k_updateUpdate the value of 'x' to 'new_x'.
k_update_addUpdate the value of 'x' by adding 'increment'.
k_update_subUpdate the value of 'x' by subtracting 'decrement'.
k_varVariance of a tensor, alongside the specified axis.
k_variableInstantiates a variable and returns it.
k_zerosInstantiates an all-zeros variable and returns it.
k_zeros_likeInstantiates an all-zeros variable of the same shape as...
Layer(Deprecated) Create a custom Layer
layer_activationApply an activation function to an output.
layer_activation_eluExponential Linear Unit.
layer_activation_leaky_reluLeaky version of a Rectified Linear Unit.
layer_activation_parametric_reluParametric Rectified Linear Unit.
layer_activation_reluRectified Linear Unit activation function
layer_activation_seluScaled Exponential Linear Unit.
layer_activation_softmaxSoftmax activation function.
layer_activation_thresholded_reluThresholded Rectified Linear Unit.
layer_activity_regularizationLayer that applies an update to the cost function based input...
layer_addLayer that adds a list of inputs.
layer_additive_attentionAdditive attention layer, a.k.a. Bahdanau-style attention
layer_alpha_dropoutApplies Alpha Dropout to the input.
layer_attentionDot-product attention layer, a.k.a. Luong-style attention
layer_averageLayer that averages a list of inputs.
layer_average_pooling_1dAverage pooling for temporal data.
layer_average_pooling_2dAverage pooling operation for spatial data.
layer_average_pooling_3dAverage pooling operation for 3D data (spatial or...
layer_batch_normalizationLayer that normalizes its inputs
layer_category_encodingA preprocessing layer which encodes integer features.
layer_center_cropCrop the central portion of the images to target height and...
layer_concatenateLayer that concatenates a list of inputs.
layer_conv_1d1D convolution layer (e.g. temporal convolution).
layer_conv_1d_transposeTransposed 1D convolution layer (sometimes called...
layer_conv_2d2D convolution layer (e.g. spatial convolution over images).
layer_conv_2d_transposeTransposed 2D convolution layer (sometimes called...
layer_conv_3d3D convolution layer (e.g. spatial convolution over volumes).
layer_conv_3d_transposeTransposed 3D convolution layer (sometimes called...
layer_conv_lstm_1d1D Convolutional LSTM
layer_conv_lstm_2dConvolutional LSTM.
layer_conv_lstm_3d3D Convolutional LSTM
layer_cropping_1dCropping layer for 1D input (e.g. temporal sequence).
layer_cropping_2dCropping layer for 2D input (e.g. picture).
layer_cropping_3dCropping layer for 3D data (e.g. spatial or spatio-temporal).
layer_cudnn_gru(Deprecated) Fast GRU implementation backed by CuDNN.
layer_cudnn_lstm(Deprecated) Fast LSTM implementation backed by CuDNN.
layer_denseAdd a densely-connected NN layer to an output
layer_dense_featuresConstructs a DenseFeatures.
layer_depthwise_conv_1dDepthwise 1D convolution
layer_depthwise_conv_2dDepthwise separable 2D convolution.
layer_discretizationA preprocessing layer which buckets continuous features by...
layer_dotLayer that computes a dot product between samples in two...
layer_dropoutApplies Dropout to the input.
layer_embeddingTurns positive integers (indexes) into dense vectors of fixed...
layer_flattenFlattens an input
layer_gaussian_dropoutApply multiplicative 1-centered Gaussian noise.
layer_gaussian_noiseApply additive zero-centered Gaussian noise.
layer_global_average_pooling_1dGlobal average pooling operation for temporal data.
layer_global_average_pooling_2dGlobal average pooling operation for spatial data.
layer_global_average_pooling_3dGlobal Average pooling operation for 3D data.
layer_global_max_pooling_1dGlobal max pooling operation for temporal data.
layer_global_max_pooling_2dGlobal max pooling operation for spatial data.
layer_global_max_pooling_3dGlobal Max pooling operation for 3D data.
layer_gruGated Recurrent Unit - Cho et al.
layer_gru_cellCell class for the GRU layer
layer_hashingA preprocessing layer which hashes and bins categorical...
layer_inputInput layer
layer_integer_lookupA preprocessing layer which maps integer features to...
layer_lambdaWraps arbitrary expression as a layer
layer_layer_normalizationLayer normalization layer (Ba et al., 2016).
layer_locally_connected_1dLocally-connected layer for 1D inputs.
layer_locally_connected_2dLocally-connected layer for 2D inputs.
layer_lstmLong Short-Term Memory unit - Hochreiter 1997.
layer_lstm_cellCell class for the LSTM layer
layer_maskingMasks a sequence by using a mask value to skip timesteps.
layer_maximumLayer that computes the maximum (element-wise) a list of...
layer_max_pooling_1dMax pooling operation for temporal data.
layer_max_pooling_2dMax pooling operation for spatial data.
layer_max_pooling_3dMax pooling operation for 3D data (spatial or...
layer_minimumLayer that computes the minimum (element-wise) a list of...
layer_multi_head_attentionMultiHeadAttention layer
layer_multiplyLayer that multiplies (element-wise) a list of inputs.
layer_normalizationA preprocessing layer which normalizes continuous features.
layer_permutePermute the dimensions of an input according to a given...
layer_random_brightnessA preprocessing layer which randomly adjusts brightness...
layer_random_contrastAdjust the contrast of an image or images by a random factor
layer_random_cropRandomly crop the images to target height and width
layer_random_flipRandomly flip each image horizontally and vertically
layer_random_heightRandomly vary the height of a batch of images during training
layer_random_rotationRandomly rotate each image
layer_random_translationRandomly translate each image during training
layer_random_widthRandomly vary the width of a batch of images during training
layer_random_zoomA preprocessing layer which randomly zooms images during...
layer_repeat_vectorRepeats the input n times.
layer_rescalingMultiply inputs by 'scale' and adds 'offset'
layer_reshapeReshapes an output to a certain shape.
layer_resizingImage resizing layer
layer_rnnBase class for recurrent layers
layer_separable_conv_1dDepthwise separable 1D convolution.
layer_separable_conv_2dSeparable 2D convolution.
layer_simple_rnnFully-connected RNN where the output is to be fed back to...
layer_simple_rnn_cellCell class for SimpleRNN
layer_spatial_dropout_1dSpatial 1D version of Dropout.
layer_spatial_dropout_2dSpatial 2D version of Dropout.
layer_spatial_dropout_3dSpatial 3D version of Dropout.
layer_stacked_rnn_cellsWrapper allowing a stack of RNN cells to behave as a single...
layer_string_lookupA preprocessing layer which maps string features to integer...
layer_subtractLayer that subtracts two inputs.
layer_text_vectorizationA preprocessing layer which maps text features to integer...
layer_unit_normalizationUnit normalization layer
layer_upsampling_1dUpsampling layer for 1D inputs.
layer_upsampling_2dUpsampling layer for 2D inputs.
layer_upsampling_3dUpsampling layer for 3D inputs.
layer_zero_padding_1dZero-padding layer for 1D input (e.g. temporal sequence).
layer_zero_padding_2dZero-padding layer for 2D input (e.g. picture).
layer_zero_padding_3dZero-padding layer for 3D data (spatial or spatio-temporal).
learning_rate_schedule_cosine_decayA LearningRateSchedule that uses a cosine decay schedule
learning_rate_schedule_cosine_decay_restartsA LearningRateSchedule that uses a cosine decay schedule with...
learning_rate_schedule_exponential_decayA LearningRateSchedule that uses an exponential decay...
learning_rate_schedule_inverse_time_decayA LearningRateSchedule that uses an inverse time decay...
learning_rate_schedule_piecewise_constant_decayA LearningRateSchedule that uses a piecewise constant decay...
learning_rate_schedule_polynomial_decayA LearningRateSchedule that uses a polynomial decay schedule
loss_cosine_proximity(Deprecated) loss_cosine_proximity
loss-functionsLoss functions
make_sampling_tableGenerates a word rank-based probabilistic sampling table.
metric_accuracyCalculates how often predictions equal labels
metric_aucApproximates the AUC (Area under the curve) of the ROC or PR...
metric_binary_accuracyCalculates how often predictions match binary labels
metric_binary_crossentropyComputes the crossentropy metric between the labels and...
metric_categorical_accuracyCalculates how often predictions match one-hot labels
metric_categorical_crossentropyComputes the crossentropy metric between the labels and...
metric_categorical_hingeComputes the categorical hinge metric between 'y_true' and...
metric_cosine_proximity(Deprecated) metric_cosine_proximity
metric_cosine_similarityComputes the cosine similarity between the labels and...
metric_false_negativesCalculates the number of false negatives
metric_false_positivesCalculates the number of false positives
metric_hingeComputes the hinge metric between 'y_true' and 'y_pred'
metric_kullback_leibler_divergenceComputes Kullback-Leibler divergence
metric_logcosh_errorComputes the logarithm of the hyperbolic cosine of the...
metric_meanComputes the (weighted) mean of the given values
metric_mean_absolute_errorComputes the mean absolute error between the labels and...
metric_mean_absolute_percentage_errorComputes the mean absolute percentage error between 'y_true'...
metric_mean_iouComputes the mean Intersection-Over-Union metric
metric_mean_relative_errorComputes the mean relative error by normalizing with the...
metric_mean_squared_errorComputes the mean squared error between labels and...
metric_mean_squared_logarithmic_errorComputes the mean squared logarithmic error
metric_mean_tensorComputes the element-wise (weighted) mean of the given...
metric_mean_wrapperWraps a stateless metric function with the Mean metric
metric_poissonComputes the Poisson metric between 'y_true' and 'y_pred'
metric_precisionComputes the precision of the predictions with respect to the...
metric_precision_at_recallComputes best precision where recall is >= specified value
metric_recallComputes the recall of the predictions with respect to the...
metric_recall_at_precisionComputes best recall where precision is >= specified value
metric_root_mean_squared_errorComputes root mean squared error metric between 'y_true' and...
metric_sensitivity_at_specificityComputes best sensitivity where specificity is >= specified...
metric_sparse_categorical_accuracyCalculates how often predictions match integer labels
metric_sparse_categorical_crossentropyComputes the crossentropy metric between the labels and...
metric_sparse_top_k_categorical_accuracyComputes how often integer targets are in the top 'K'...
metric_specificity_at_sensitivityComputes best specificity where sensitivity is >= specified...
metric_squared_hingeComputes the squared hinge metric
metric_sumComputes the (weighted) sum of the given values
metric_top_k_categorical_accuracyComputes how often targets are in the top 'K' predictions
metric_true_negativesCalculates the number of true negatives
metric_true_positivesCalculates the number of true positives
model_from_saved_modelLoad a Keras model from the Saved Model format
model_to_jsonModel configuration as JSON
model_to_saved_model(Deprecated) Export to Saved Model format
model_to_yamlModel configuration as YAML
multi-assignAssign values to names
multi_gpu_model(Deprecated) Replicates a model on different GPUs.
new-classesDefine new keras types
new_learning_rate_schedule_classCreate a new learning rate schedule type
normalizeNormalize a matrix or nd-array
optimizer_adadeltaOptimizer that implements the Adadelta algorithm
optimizer_adagradOptimizer that implements the Adagrad algorithm
optimizer_adamOptimizer that implements the Adam algorithm
optimizer_adamaxOptimizer that implements the Adamax algorithm
optimizer_ftrlOptimizer that implements the FTRL algorithm
optimizer_nadamOptimizer that implements the Nadam algorithm
optimizer_rmspropOptimizer that implements the RMSprop algorithm
optimizer_sgdGradient descent (with momentum) optimizer
pad_sequencesPads sequences to the same length
pipePipe operator a Keras model
plot.keras_training_historyPlot training history
pop_layerRemove the last layer in a model
predict_generator(Deprecated) Generates predictions for the input samples from... predictions from a Keras model
predict_on_batchReturns predictions for a single batch of samples.
predict_proba(Deprecated) Generates probability or class probability...
reexportsObjects exported from other packages
regularizer_l1L1 and L2 regularization
regularizer_orthogonalA regularizer that encourages input vectors to be orthogonal...
reset_statesReset the states for a layer
save_model_hdf5Save/Load models using HDF5 files
save_model_tfSave/Load models using SavedModel format
save_model_weights_hdf5Save/Load model weights using HDF5 files
save_model_weights_tfSave model weights in the SavedModel format
save_text_tokenizerSave a text tokenizer to an external file
sequences_to_matrixConvert a list of sequences into a matrix.
serialize_modelSerialize a model to an R object
skipgramsGenerates skipgram word pairs. a summary of a Keras model
text_dataset_from_directoryGenerate a '' from text files in a directory
text_hashing_trickConverts a text to a sequence of indexes in a fixed-size...
text_one_hotOne-hot encode a text into a list of word indexes in a...
texts_to_matrixConvert a list of texts to a matrix.
texts_to_sequencesTransform each text in texts in a sequence of integers.
texts_to_sequences_generatorTransforms each text in texts in a sequence of integers.
text_tokenizerText tokenization utility
text_to_word_sequenceConvert text to a sequence of words (or tokens).
time_distributedThis layer wrapper allows to apply a layer to every temporal...
timeseries_dataset_from_arrayCreates a dataset of sliding windows over a timeseries...
timeseries_generatorUtility function for generating batches of temporal data.
to_categoricalConverts a class vector (integers) to binary class matrix.
train_on_batchSingle gradient update or model evaluation over one batch of...
use_implementationSelect a Keras implementation and backend
with_custom_object_scopeProvide a scope with mappings of names to custom objects
zip_listszip lists
keras documentation built on Aug. 16, 2023, 1:07 a.m.