doc_content stringlengths 1 386k | doc_id stringlengths 5 188 |
|---|---|
Module: tf.compat.v1.keras.applications.inception_resnet_v2 Inception-ResNet V2 model for Keras. Reference:
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning (AAAI 2017) Functions InceptionResNetV2(...): Instantiates the Inception-ResNet v2 architecture. decode_predictions(...): Decod... | tensorflow.compat.v1.keras.applications.inception_resnet_v2 |
Module: tf.compat.v1.keras.applications.inception_v3 Inception V3 model for Keras. Reference:
Rethinking the Inception Architecture for Computer Vision (CVPR 2016) Functions InceptionV3(...): Instantiates the Inception v3 architecture. decode_predictions(...): Decodes the prediction of an ImageNet model. preprocess_... | tensorflow.compat.v1.keras.applications.inception_v3 |
Module: tf.compat.v1.keras.applications.mobilenet MobileNet v1 models for Keras. MobileNet is a general architecture and can be used for multiple use cases. Depending on the use case, it can use different input layer size and different width factors. This allows different width models to reduce the number of multiply-a... | tensorflow.compat.v1.keras.applications.mobilenet |
Module: tf.compat.v1.keras.applications.mobilenet_v2 MobileNet v2 models for Keras. MobileNetV2 is a general architecture and can be used for multiple use cases. Depending on the use case, it can use different input layer size and different width factors. This allows different width models to reduce the number of multi... | tensorflow.compat.v1.keras.applications.mobilenet_v2 |
Module: tf.compat.v1.keras.applications.mobilenet_v3 MobileNet v3 models for Keras. Functions decode_predictions(...): Decodes the prediction of an ImageNet model. preprocess_input(...): Preprocesses a tensor or Numpy array encoding a batch of images. | tensorflow.compat.v1.keras.applications.mobilenet_v3 |
Module: tf.compat.v1.keras.applications.nasnet NASNet-A models for Keras. NASNet refers to Neural Architecture Search Network, a family of models that were designed automatically by learning the model architectures directly on the dataset of interest. Here we consider NASNet-A, the highest performance model that was fo... | tensorflow.compat.v1.keras.applications.nasnet |
Module: tf.compat.v1.keras.applications.resnet ResNet models for Keras. Reference:
Deep Residual Learning for Image Recognition (CVPR 2015) Functions ResNet101(...): Instantiates the ResNet101 architecture. ResNet152(...): Instantiates the ResNet152 architecture. ResNet50(...): Instantiates the ResNet50 architecture... | tensorflow.compat.v1.keras.applications.resnet |
Module: tf.compat.v1.keras.applications.resnet50 Public API for tf.keras.applications.resnet50 namespace. Functions ResNet50(...): Instantiates the ResNet50 architecture. decode_predictions(...): Decodes the prediction of an ImageNet model. preprocess_input(...): Preprocesses a tensor or Numpy array encoding a batch of... | tensorflow.compat.v1.keras.applications.resnet50 |
Module: tf.compat.v1.keras.applications.resnet_v2 ResNet v2 models for Keras. Reference:
Identity Mappings in Deep Residual Networks (CVPR 2016) Functions ResNet101V2(...): Instantiates the ResNet101V2 architecture. ResNet152V2(...): Instantiates the ResNet152V2 architecture. ResNet50V2(...): Instantiates the ResNet... | tensorflow.compat.v1.keras.applications.resnet_v2 |
Module: tf.compat.v1.keras.applications.vgg16 VGG16 model for Keras. Reference:
Very Deep Convolutional Networks for Large-Scale Image Recognition (ICLR 2015) Functions VGG16(...): Instantiates the VGG16 model. decode_predictions(...): Decodes the prediction of an ImageNet model. preprocess_input(...): Preprocesses ... | tensorflow.compat.v1.keras.applications.vgg16 |
Module: tf.compat.v1.keras.applications.vgg19 VGG19 model for Keras. Reference:
Very Deep Convolutional Networks for Large-Scale Image Recognition (ICLR 2015) Functions VGG19(...): Instantiates the VGG19 architecture. decode_predictions(...): Decodes the prediction of an ImageNet model. preprocess_input(...): Prepro... | tensorflow.compat.v1.keras.applications.vgg19 |
Module: tf.compat.v1.keras.applications.xception Xception V1 model for Keras. On ImageNet, this model gets to a top-1 validation accuracy of 0.790 and a top-5 validation accuracy of 0.945. Reference:
Xception: Deep Learning with Depthwise Separable Convolutions (CVPR 2017) Functions Xception(...): Instantiates the X... | tensorflow.compat.v1.keras.applications.xception |
Module: tf.compat.v1.keras.backend Keras backend API. Classes class name_scope: A context manager for use when defining a Python op. Functions clear_session(...): Resets all state generated by Keras. epsilon(...): Returns the value of the fuzz factor used in numeric expressions. floatx(...): Returns the default float t... | tensorflow.compat.v1.keras.backend |
tf.compat.v1.keras.backend.get_session Returns the TF session to be used by the backend.
tf.compat.v1.keras.backend.get_session(
op_input_list=()
)
If a default TensorFlow session is available, we will return it. Else, we will return the global Keras session assuming it matches the current graph. If no global Ker... | tensorflow.compat.v1.keras.backend.get_session |
tf.compat.v1.keras.backend.name_scope A context manager for use when defining a Python op. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.name_scope
tf.compat.v1.keras.backend.name_scope(
name, default_name=None, values=None
)
This context manager validates that t... | tensorflow.compat.v1.keras.backend.name_scope |
tf.compat.v1.keras.backend.set_session Sets the global TensorFlow session.
tf.compat.v1.keras.backend.set_session(
session
)
Arguments
session A TF Session. | tensorflow.compat.v1.keras.backend.set_session |
Module: tf.compat.v1.keras.callbacks Callbacks: utilities called at certain points during model training. Classes class BaseLogger: Callback that accumulates epoch averages of metrics. class CSVLogger: Callback that streams epoch results to a CSV file. class Callback: Abstract base class used to build new callbacks. cl... | tensorflow.compat.v1.keras.callbacks |
tf.compat.v1.keras.callbacks.TensorBoard Enable visualizations for TensorBoard. Inherits From: TensorBoard, Callback
tf.compat.v1.keras.callbacks.TensorBoard(
log_dir='./logs', histogram_freq=0, batch_size=32, write_graph=True,
write_grads=False, write_images=False, embeddings_freq=0,
embeddings_layer_name... | tensorflow.compat.v1.keras.callbacks.tensorboard |
Module: tf.compat.v1.keras.constraints Constraints: functions that impose constraints on weight values. Classes class Constraint class MaxNorm: MaxNorm weight constraint. class MinMaxNorm: MinMaxNorm weight constraint. class NonNeg: Constrains the weights to be non-negative. class RadialConstraint: Constrains Conv2D ke... | tensorflow.compat.v1.keras.constraints |
Module: tf.compat.v1.keras.datasets Public API for tf.keras.datasets namespace. Modules boston_housing module: Boston housing price regression dataset. cifar10 module: CIFAR10 small images classification dataset. cifar100 module: CIFAR100 small images classification dataset. fashion_mnist module: Fashion-MNIST dataset.... | tensorflow.compat.v1.keras.datasets |
Module: tf.compat.v1.keras.datasets.boston_housing Boston housing price regression dataset. Functions load_data(...): Loads the Boston Housing dataset. | tensorflow.compat.v1.keras.datasets.boston_housing |
Module: tf.compat.v1.keras.datasets.cifar10 CIFAR10 small images classification dataset. Functions load_data(...): Loads CIFAR10 dataset. | tensorflow.compat.v1.keras.datasets.cifar10 |
Module: tf.compat.v1.keras.datasets.cifar100 CIFAR100 small images classification dataset. Functions load_data(...): Loads CIFAR100 dataset. | tensorflow.compat.v1.keras.datasets.cifar100 |
Module: tf.compat.v1.keras.datasets.fashion_mnist Fashion-MNIST dataset. Functions load_data(...): Loads the Fashion-MNIST dataset. | tensorflow.compat.v1.keras.datasets.fashion_mnist |
Module: tf.compat.v1.keras.datasets.imdb IMDB sentiment classification dataset. Functions get_word_index(...): Retrieves a dict mapping words to their index in the IMDB dataset. load_data(...): Loads the IMDB dataset. | tensorflow.compat.v1.keras.datasets.imdb |
Module: tf.compat.v1.keras.datasets.mnist MNIST handwritten digits dataset. Functions load_data(...): Loads the MNIST dataset. | tensorflow.compat.v1.keras.datasets.mnist |
Module: tf.compat.v1.keras.datasets.reuters Reuters topic classification dataset. Functions get_word_index(...): Retrieves a dict mapping words to their index in the Reuters dataset. load_data(...): Loads the Reuters newswire classification dataset. | tensorflow.compat.v1.keras.datasets.reuters |
Module: tf.compat.v1.keras.estimator Keras estimator API. Functions model_to_estimator(...): Constructs an Estimator instance from given keras model. | tensorflow.compat.v1.keras.estimator |
tf.compat.v1.keras.estimator.model_to_estimator Constructs an Estimator instance from given keras model.
tf.compat.v1.keras.estimator.model_to_estimator(
keras_model=None, keras_model_path=None, custom_objects=None, model_dir=None,
config=None, checkpoint_format='saver', metric_names_map=None,
export_outpu... | tensorflow.compat.v1.keras.estimator.model_to_estimator |
Module: tf.compat.v1.keras.experimental Public API for tf.keras.experimental namespace. Classes class CosineDecay: A LearningRateSchedule that uses a cosine decay schedule. class CosineDecayRestarts: A LearningRateSchedule that uses a cosine decay schedule with restarts. class LinearCosineDecay: A LearningRateSchedule ... | tensorflow.compat.v1.keras.experimental |
tf.compat.v1.keras.experimental.export_saved_model Exports a tf.keras.Model as a Tensorflow SavedModel.
tf.compat.v1.keras.experimental.export_saved_model(
model, saved_model_path, custom_objects=None, as_text=False,
input_signature=None, serving_only=False
)
Note that at this time, subclassed models can only... | tensorflow.compat.v1.keras.experimental.export_saved_model |
tf.compat.v1.keras.experimental.load_from_saved_model Loads a keras Model from a SavedModel created by export_saved_model().
tf.compat.v1.keras.experimental.load_from_saved_model(
saved_model_path, custom_objects=None
)
This function reinstantiates model state by: 1) loading model topology from json (this will ev... | tensorflow.compat.v1.keras.experimental.load_from_saved_model |
Module: tf.compat.v1.keras.initializers Keras initializer serialization / deserialization. Classes class Constant: Initializer that generates tensors with constant values. class Identity: Initializer that generates the identity matrix. class Initializer: Initializer base class: all Keras initializers inherit from this ... | tensorflow.compat.v1.keras.initializers |
tf.compat.v1.keras.initializers.Constant Initializer that generates tensors with constant values. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.constant_initializer, tf.compat.v1.initializers.constant, tf.compat.v1.keras.initializers.constant
tf.compat.v1.keras.initia... | tensorflow.compat.v1.keras.initializers.constant |
tf.compat.v1.keras.initializers.glorot_normal The Glorot normal initializer, also called Xavier normal initializer. Inherits From: VarianceScaling View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.glorot_normal_initializer, tf.compat.v1.initializers.glorot_normal
tf.compa... | tensorflow.compat.v1.keras.initializers.glorot_normal |
tf.compat.v1.keras.initializers.glorot_uniform The Glorot uniform initializer, also called Xavier uniform initializer. Inherits From: VarianceScaling View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.glorot_uniform_initializer, tf.compat.v1.initializers.glorot_uniform
tf.... | tensorflow.compat.v1.keras.initializers.glorot_uniform |
tf.compat.v1.keras.initializers.he_normal Initializer capable of adapting its scale to the shape of weights tensors. Inherits From: VarianceScaling
tf.compat.v1.keras.initializers.he_normal(
seed=None
)
With distribution="truncated_normal" or "untruncated_normal", samples are drawn from a truncated/untruncated no... | tensorflow.compat.v1.keras.initializers.he_normal |
tf.compat.v1.keras.initializers.he_uniform Initializer capable of adapting its scale to the shape of weights tensors. Inherits From: VarianceScaling
tf.compat.v1.keras.initializers.he_uniform(
seed=None
)
With distribution="truncated_normal" or "untruncated_normal", samples are drawn from a truncated/untruncated ... | tensorflow.compat.v1.keras.initializers.he_uniform |
tf.compat.v1.keras.initializers.Identity Initializer that generates the identity matrix. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.initializers.identity, tf.compat.v1.keras.initializers.identity
tf.compat.v1.keras.initializers.Identity(
gain=1.0, dtype=tf.dtyp... | tensorflow.compat.v1.keras.initializers.identity |
tf.compat.v1.keras.initializers.lecun_normal Initializer capable of adapting its scale to the shape of weights tensors. Inherits From: VarianceScaling
tf.compat.v1.keras.initializers.lecun_normal(
seed=None
)
With distribution="truncated_normal" or "untruncated_normal", samples are drawn from a truncated/untrunca... | tensorflow.compat.v1.keras.initializers.lecun_normal |
tf.compat.v1.keras.initializers.lecun_uniform Initializer capable of adapting its scale to the shape of weights tensors. Inherits From: VarianceScaling
tf.compat.v1.keras.initializers.lecun_uniform(
seed=None
)
With distribution="truncated_normal" or "untruncated_normal", samples are drawn from a truncated/untrun... | tensorflow.compat.v1.keras.initializers.lecun_uniform |
tf.compat.v1.keras.initializers.Ones Initializer that generates tensors initialized to 1. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.initializers.ones, tf.compat.v1.keras.initializers.ones, tf.compat.v1.ones_initializer
tf.compat.v1.keras.initializers.Ones(
dty... | tensorflow.compat.v1.keras.initializers.ones |
tf.compat.v1.keras.initializers.Orthogonal Initializer that generates an orthogonal matrix. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.initializers.orthogonal, tf.compat.v1.keras.initializers.orthogonal, tf.compat.v1.orthogonal_initializer
tf.compat.v1.keras.initia... | tensorflow.compat.v1.keras.initializers.orthogonal |
tf.compat.v1.keras.initializers.RandomNormal Initializer that generates tensors with a normal distribution. Inherits From: random_normal_initializer View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.keras.initializers.normal, tf.compat.v1.keras.initializers.random_normal
... | tensorflow.compat.v1.keras.initializers.randomnormal |
tf.compat.v1.keras.initializers.RandomUniform Initializer that generates tensors with a uniform distribution. Inherits From: random_uniform_initializer View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.keras.initializers.random_uniform, tf.compat.v1.keras.initializers.unifo... | tensorflow.compat.v1.keras.initializers.randomuniform |
tf.compat.v1.keras.initializers.TruncatedNormal Initializer that generates a truncated normal distribution. Inherits From: truncated_normal_initializer View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.keras.initializers.truncated_normal
tf.compat.v1.keras.initializers.Tr... | tensorflow.compat.v1.keras.initializers.truncatednormal |
tf.compat.v1.keras.initializers.VarianceScaling Initializer capable of adapting its scale to the shape of weights tensors. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.initializers.variance_scaling, tf.compat.v1.variance_scaling_initializer
tf.compat.v1.keras.initial... | tensorflow.compat.v1.keras.initializers.variancescaling |
tf.compat.v1.keras.initializers.Zeros Initializer that generates tensors initialized to 0. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.initializers.zeros, tf.compat.v1.keras.initializers.zeros, tf.compat.v1.zeros_initializer
tf.compat.v1.keras.initializers.Zeros(
... | tensorflow.compat.v1.keras.initializers.zeros |
Module: tf.compat.v1.keras.layers Keras layers API. Modules experimental module: Public API for tf.keras.layers.experimental namespace. Classes class AbstractRNNCell: Abstract object representing an RNN cell. class Activation: Applies an activation function to an output. class ActivityRegularization: Layer that applies... | tensorflow.compat.v1.keras.layers |
tf.compat.v1.keras.layers.BatchNormalization Layer that normalizes its inputs. Inherits From: Layer, Module
tf.compat.v1.keras.layers.BatchNormalization(
axis=-1, momentum=0.99, epsilon=0.001, center=True, scale=True,
beta_initializer='zeros', gamma_initializer='ones',
moving_mean_initializer='zeros',
... | tensorflow.compat.v1.keras.layers.batchnormalization |
tf.compat.v1.keras.layers.CuDNNGRU Fast GRU implementation backed by cuDNN. Inherits From: RNN, Layer, Module
tf.compat.v1.keras.layers.CuDNNGRU(
units, kernel_initializer='glorot_uniform',
recurrent_initializer='orthogonal',
bias_initializer='zeros', kernel_regularizer=None,
recurrent_regularizer=None... | tensorflow.compat.v1.keras.layers.cudnngru |
tf.compat.v1.keras.layers.CuDNNLSTM Fast LSTM implementation backed by cuDNN. Inherits From: RNN, Layer, Module
tf.compat.v1.keras.layers.CuDNNLSTM(
units, kernel_initializer='glorot_uniform',
recurrent_initializer='orthogonal',
bias_initializer='zeros', unit_forget_bias=True,
kernel_regularizer=None, ... | tensorflow.compat.v1.keras.layers.cudnnlstm |
tf.compat.v1.keras.layers.DenseFeatures A layer that produces a dense Tensor based on given feature_columns. Inherits From: Layer, Module
tf.compat.v1.keras.layers.DenseFeatures(
feature_columns, trainable=True, name=None, partitioner=None, **kwargs
)
Generally a single example in training data is described with ... | tensorflow.compat.v1.keras.layers.densefeatures |
tf.compat.v1.keras.layers.disable_v2_dtype_behavior Disables the V2 dtype behavior for Keras layers.
tf.compat.v1.keras.layers.disable_v2_dtype_behavior()
See tf.compat.v1.keras.layers.enable_v2_dtype_behavior. | tensorflow.compat.v1.keras.layers.disable_v2_dtype_behavior |
tf.compat.v1.keras.layers.enable_v2_dtype_behavior Enable the V2 dtype behavior for Keras layers.
tf.compat.v1.keras.layers.enable_v2_dtype_behavior()
By default, the V2 dtype behavior is enabled in TensorFlow 2, so this function is only useful if tf.compat.v1.disable_v2_behavior has been called. Since mixed precisio... | tensorflow.compat.v1.keras.layers.enable_v2_dtype_behavior |
Module: tf.compat.v1.keras.layers.experimental Public API for tf.keras.layers.experimental namespace. Modules preprocessing module: Public API for tf.keras.layers.experimental.preprocessing namespace. Classes class EinsumDense: A layer that uses tf.einsum as the backing computation. class RandomFourierFeatures: Layer t... | tensorflow.compat.v1.keras.layers.experimental |
Module: tf.compat.v1.keras.layers.experimental.preprocessing Public API for tf.keras.layers.experimental.preprocessing namespace. Classes class CategoryCrossing: Category crossing layer. class CategoryEncoding: CategoryEncoding layer. class CenterCrop: Crop the central portion of the images to target height and width. ... | tensorflow.compat.v1.keras.layers.experimental.preprocessing |
tf.compat.v1.keras.layers.experimental.preprocessing.CategoryEncoding CategoryEncoding layer. Inherits From: CategoryEncoding, PreprocessingLayer, Layer, Module
tf.compat.v1.keras.layers.experimental.preprocessing.CategoryEncoding(
max_tokens=None, output_mode=BINARY, sparse=False, **kwargs
)
This layer provides ... | tensorflow.compat.v1.keras.layers.experimental.preprocessing.categoryencoding |
tf.compat.v1.keras.layers.experimental.preprocessing.IntegerLookup Maps integers from a vocabulary to integer indices. Inherits From: IntegerLookup, PreprocessingLayer, Layer, Module
tf.compat.v1.keras.layers.experimental.preprocessing.IntegerLookup(
max_values=None, num_oov_indices=1, mask_value=0, oov_value=-1, ... | tensorflow.compat.v1.keras.layers.experimental.preprocessing.integerlookup |
tf.compat.v1.keras.layers.experimental.preprocessing.Normalization Feature-wise normalization of the data. Inherits From: Normalization, PreprocessingLayer, Layer, Module
tf.compat.v1.keras.layers.experimental.preprocessing.Normalization(
axis=-1, dtype=None, **kwargs
)
This layer will coerce its inputs into a di... | tensorflow.compat.v1.keras.layers.experimental.preprocessing.normalization |
tf.compat.v1.keras.layers.experimental.preprocessing.StringLookup Maps strings from a vocabulary to integer indices. Inherits From: StringLookup, PreprocessingLayer, Layer, Module
tf.compat.v1.keras.layers.experimental.preprocessing.StringLookup(
max_tokens=None, num_oov_indices=1, mask_token='',
oov_token='[U... | tensorflow.compat.v1.keras.layers.experimental.preprocessing.stringlookup |
tf.compat.v1.keras.layers.experimental.preprocessing.TextVectorization Text vectorization layer. Inherits From: TextVectorization, PreprocessingLayer, Layer, Module
tf.compat.v1.keras.layers.experimental.preprocessing.TextVectorization(
max_tokens=None, standardize=text_vectorization.LOWER_AND_STRIP_PUNCTUATION,
... | tensorflow.compat.v1.keras.layers.experimental.preprocessing.textvectorization |
tf.compat.v1.keras.layers.GRU Gated Recurrent Unit - Cho et al. 2014. Inherits From: RNN, Layer, Module
tf.compat.v1.keras.layers.GRU(
units, activation='tanh',
recurrent_activation='hard_sigmoid', use_bias=True,
kernel_initializer='glorot_uniform',
recurrent_initializer='orthogonal',
bias_initiali... | tensorflow.compat.v1.keras.layers.gru |
tf.compat.v1.keras.layers.GRUCell Cell class for the GRU layer. Inherits From: Layer, Module
tf.compat.v1.keras.layers.GRUCell(
units, activation='tanh',
recurrent_activation='hard_sigmoid', use_bias=True,
kernel_initializer='glorot_uniform',
recurrent_initializer='orthogonal',
bias_initializer='ze... | tensorflow.compat.v1.keras.layers.grucell |
tf.compat.v1.keras.layers.LSTM Long Short-Term Memory layer - Hochreiter 1997. Inherits From: RNN, Layer, Module
tf.compat.v1.keras.layers.LSTM(
units, activation='tanh',
recurrent_activation='hard_sigmoid', use_bias=True,
kernel_initializer='glorot_uniform',
recurrent_initializer='orthogonal',
bia... | tensorflow.compat.v1.keras.layers.lstm |
tf.compat.v1.keras.layers.LSTMCell Cell class for the LSTM layer. Inherits From: Layer, Module
tf.compat.v1.keras.layers.LSTMCell(
units, activation='tanh',
recurrent_activation='hard_sigmoid', use_bias=True,
kernel_initializer='glorot_uniform',
recurrent_initializer='orthogonal',
bias_initializer=... | tensorflow.compat.v1.keras.layers.lstmcell |
Module: tf.compat.v1.keras.losses Built-in loss functions. Classes class BinaryCrossentropy: Computes the cross-entropy loss between true labels and predicted labels. class CategoricalCrossentropy: Computes the crossentropy loss between the labels and predictions. class CategoricalHinge: Computes the categorical hinge ... | tensorflow.compat.v1.keras.losses |
Module: tf.compat.v1.keras.metrics Built-in metrics. Classes class AUC: Computes the approximate AUC (Area under the curve) via a Riemann sum. class Accuracy: Calculates how often predictions equal labels. class BinaryAccuracy: Calculates how often predictions match binary labels. class BinaryCrossentropy: Computes the... | tensorflow.compat.v1.keras.metrics |
Module: tf.compat.v1.keras.mixed_precision Keras mixed precision API. See the mixed precision guide to learn how to use the API. Modules experimental module: Public API for tf.keras.mixed_precision.experimental namespace. Classes class LossScaleOptimizer: An optimizer that applies loss scaling to prevent numeric underf... | tensorflow.compat.v1.keras.mixed_precision |
Module: tf.compat.v1.keras.mixed_precision.experimental Public API for tf.keras.mixed_precision.experimental namespace. Classes class LossScaleOptimizer: An deprecated optimizer that applies loss scaling. | tensorflow.compat.v1.keras.mixed_precision.experimental |
Module: tf.compat.v1.keras.models Code for model cloning, plus model-related API entries. Classes class Model: Model groups layers into an object with training and inference features. class Sequential: Sequential groups a linear stack of layers into a tf.keras.Model. Functions clone_model(...): Clone any Model instance... | tensorflow.compat.v1.keras.models |
Module: tf.compat.v1.keras.optimizers Built-in optimizer classes. For more examples see the base class tf.keras.optimizers.Optimizer. Modules schedules module: Public API for tf.keras.optimizers.schedules namespace. Classes class Adadelta: Optimizer that implements the Adadelta algorithm. class Adagrad: Optimizer that ... | tensorflow.compat.v1.keras.optimizers |
Module: tf.compat.v1.keras.optimizers.schedules Public API for tf.keras.optimizers.schedules namespace. Classes class ExponentialDecay: A LearningRateSchedule that uses an exponential decay schedule. class InverseTimeDecay: A LearningRateSchedule that uses an inverse time decay schedule. class LearningRateSchedule: A s... | tensorflow.compat.v1.keras.optimizers.schedules |
Module: tf.compat.v1.keras.preprocessing Keras data preprocessing utils. Modules image module: Set of tools for real-time data augmentation on image data. sequence module: Utilities for preprocessing sequence data. text module: Utilities for text input preprocessing. | tensorflow.compat.v1.keras.preprocessing |
Module: tf.compat.v1.keras.preprocessing.image Set of tools for real-time data augmentation on image data. Classes class DirectoryIterator: Iterator capable of reading images from a directory on disk. class ImageDataGenerator: Generate batches of tensor image data with real-time data augmentation. class Iterator: Base ... | tensorflow.compat.v1.keras.preprocessing.image |
Module: tf.compat.v1.keras.preprocessing.sequence Utilities for preprocessing sequence data. Classes class TimeseriesGenerator: Utility class for generating batches of temporal data. Functions make_sampling_table(...): Generates a word rank-based probabilistic sampling table. pad_sequences(...): Pads sequences to the s... | tensorflow.compat.v1.keras.preprocessing.sequence |
Module: tf.compat.v1.keras.preprocessing.text Utilities for text input preprocessing. Classes class Tokenizer: Text tokenization utility class. Functions hashing_trick(...): Converts a text to a sequence of indexes in a fixed-size hashing space. one_hot(...): One-hot encodes a text into a list of word indexes of size n... | tensorflow.compat.v1.keras.preprocessing.text |
Module: tf.compat.v1.keras.regularizers Built-in regularizers. Classes class L1: A regularizer that applies a L1 regularization penalty. class L1L2: A regularizer that applies both L1 and L2 regularization penalties. class L2: A regularizer that applies a L2 regularization penalty. class Regularizer: Regularizer base c... | tensorflow.compat.v1.keras.regularizers |
Module: tf.compat.v1.keras.utils Public API for tf.keras.utils namespace. Classes class CustomObjectScope: Exposes custom classes/functions to Keras deserialization internals. class GeneratorEnqueuer: Builds a queue out of a data generator. class OrderedEnqueuer: Builds a Enqueuer from a Sequence. class Progbar: Displa... | tensorflow.compat.v1.keras.utils |
Module: tf.compat.v1.keras.wrappers Public API for tf.keras.wrappers namespace. Modules scikit_learn module: Wrapper for using the Scikit-Learn API with Keras models. | tensorflow.compat.v1.keras.wrappers |
Module: tf.compat.v1.keras.wrappers.scikit_learn Wrapper for using the Scikit-Learn API with Keras models. Classes class KerasClassifier: Implementation of the scikit-learn classifier API for Keras. class KerasRegressor: Implementation of the scikit-learn regressor API for Keras. | tensorflow.compat.v1.keras.wrappers.scikit_learn |
Module: tf.compat.v1.layers Public API for tf.layers namespace. Modules experimental module: Public API for tf.layers.experimental namespace. Classes class AveragePooling1D: Average Pooling layer for 1D inputs. class AveragePooling2D: Average pooling layer for 2D inputs (e.g. images). class AveragePooling3D: Average po... | tensorflow.compat.v1.layers |
tf.compat.v1.layers.AveragePooling1D Average Pooling layer for 1D inputs. Inherits From: AveragePooling1D, Layer, Layer, Module
tf.compat.v1.layers.AveragePooling1D(
pool_size, strides, padding='valid',
data_format='channels_last', name=None, **kwargs
)
Arguments
pool_size An integer or tuple/list of... | tensorflow.compat.v1.layers.averagepooling1d |
tf.compat.v1.layers.AveragePooling2D Average pooling layer for 2D inputs (e.g. images). Inherits From: AveragePooling2D, Layer, Layer, Module
tf.compat.v1.layers.AveragePooling2D(
pool_size, strides, padding='valid',
data_format='channels_last', name=None, **kwargs
)
Arguments
pool_size An integer or... | tensorflow.compat.v1.layers.averagepooling2d |
tf.compat.v1.layers.AveragePooling3D Average pooling layer for 3D inputs (e.g. volumes). Inherits From: AveragePooling3D, Layer, Layer, Module
tf.compat.v1.layers.AveragePooling3D(
pool_size, strides, padding='valid',
data_format='channels_last', name=None, **kwargs
)
Arguments
pool_size An integer o... | tensorflow.compat.v1.layers.averagepooling3d |
tf.compat.v1.layers.average_pooling1d Average Pooling layer for 1D inputs.
tf.compat.v1.layers.average_pooling1d(
inputs, pool_size, strides, padding='valid',
data_format='channels_last', name=None
)
Arguments
inputs The tensor over which to pool. Must have rank 3.
pool_size An integer or tuple... | tensorflow.compat.v1.layers.average_pooling1d |
tf.compat.v1.layers.average_pooling2d Average pooling layer for 2D inputs (e.g. images).
tf.compat.v1.layers.average_pooling2d(
inputs, pool_size, strides, padding='valid',
data_format='channels_last', name=None
)
Arguments
inputs The tensor over which to pool. Must have rank 4.
pool_size An in... | tensorflow.compat.v1.layers.average_pooling2d |
tf.compat.v1.layers.average_pooling3d Average pooling layer for 3D inputs (e.g. volumes).
tf.compat.v1.layers.average_pooling3d(
inputs, pool_size, strides, padding='valid',
data_format='channels_last', name=None
)
Arguments
inputs The tensor over which to pool. Must have rank 5.
pool_size An i... | tensorflow.compat.v1.layers.average_pooling3d |
tf.compat.v1.layers.BatchNormalization Batch Normalization layer from (Ioffe et al., 2015). Inherits From: BatchNormalization, Layer, Layer, Module
tf.compat.v1.layers.BatchNormalization(
axis=-1, momentum=0.99, epsilon=0.001, center=True, scale=True,
beta_initializer=tf.zeros_initializer(),
gamma_initiali... | tensorflow.compat.v1.layers.batchnormalization |
tf.compat.v1.layers.batch_normalization Functional interface for the batch normalization layer from_config(Ioffe et al., 2015).
tf.compat.v1.layers.batch_normalization(
inputs, axis=-1, momentum=0.99, epsilon=0.001, center=True, scale=True,
beta_initializer=tf.zeros_initializer(),
gamma_initializer=tf.ones... | tensorflow.compat.v1.layers.batch_normalization |
tf.compat.v1.layers.Conv1D 1D convolution layer (e.g. temporal convolution). Inherits From: Conv1D, Layer, Layer, Module
tf.compat.v1.layers.Conv1D(
filters, kernel_size, strides=1, padding='valid',
data_format='channels_last', dilation_rate=1, activation=None,
use_bias=True, kernel_initializer=None, bias_... | tensorflow.compat.v1.layers.conv1d |
tf.compat.v1.layers.Conv2D 2D convolution layer (e.g. spatial convolution over images). Inherits From: Conv2D, Layer, Layer, Module
tf.compat.v1.layers.Conv2D(
filters, kernel_size, strides=(1, 1), padding='valid',
data_format='channels_last', dilation_rate=(1, 1), activation=None,
use_bias=True, kernel_in... | tensorflow.compat.v1.layers.conv2d |
tf.compat.v1.layers.Conv2DTranspose Transposed 2D convolution layer (sometimes called 2D Deconvolution). Inherits From: Conv2DTranspose, Conv2D, Layer, Layer, Module
tf.compat.v1.layers.Conv2DTranspose(
filters, kernel_size, strides=(1, 1), padding='valid',
data_format='channels_last', activation=None, use_bia... | tensorflow.compat.v1.layers.conv2dtranspose |
tf.compat.v1.layers.conv2d_transpose Functional interface for transposed 2D convolution layer.
tf.compat.v1.layers.conv2d_transpose(
inputs, filters, kernel_size, strides=(1, 1), padding='valid',
data_format='channels_last', activation=None, use_bias=True,
kernel_initializer=None, bias_initializer=tf.zeros... | tensorflow.compat.v1.layers.conv2d_transpose |
tf.compat.v1.layers.Conv3D 3D convolution layer (e.g. spatial convolution over volumes). Inherits From: Conv3D, Layer, Layer, Module
tf.compat.v1.layers.Conv3D(
filters, kernel_size, strides=(1, 1, 1), padding='valid',
data_format='channels_last', dilation_rate=(1, 1, 1), activation=None,
use_bias=True, ke... | tensorflow.compat.v1.layers.conv3d |
tf.compat.v1.layers.Conv3DTranspose Transposed 3D convolution layer (sometimes called 3D Deconvolution). Inherits From: Conv3DTranspose, Conv3D, Layer, Layer, Module
tf.compat.v1.layers.Conv3DTranspose(
filters, kernel_size, strides=(1, 1, 1), padding='valid',
data_format='channels_last', activation=None, use_... | tensorflow.compat.v1.layers.conv3dtranspose |
tf.compat.v1.layers.conv3d_transpose Functional interface for transposed 3D convolution layer.
tf.compat.v1.layers.conv3d_transpose(
inputs, filters, kernel_size, strides=(1, 1, 1), padding='valid',
data_format='channels_last', activation=None, use_bias=True,
kernel_initializer=None, bias_initializer=tf.ze... | tensorflow.compat.v1.layers.conv3d_transpose |
tf.compat.v1.layers.Dense Densely-connected layer class. Inherits From: Dense, Layer, Layer, Module
tf.compat.v1.layers.Dense(
units, activation=None, use_bias=True, kernel_initializer=None,
bias_initializer=tf.zeros_initializer(), kernel_regularizer=None,
bias_regularizer=None, activity_regularizer=None, ... | tensorflow.compat.v1.layers.dense |
tf.compat.v1.layers.Dropout Applies Dropout to the input. Inherits From: Dropout, Layer, Layer, Module
tf.compat.v1.layers.Dropout(
rate=0.5, noise_shape=None, seed=None, name=None, **kwargs
)
Dropout consists in randomly setting a fraction rate of input units to 0 at each update during training time, which helps... | tensorflow.compat.v1.layers.dropout |
Module: tf.compat.v1.layers.experimental Public API for tf.layers.experimental namespace. Functions keras_style_scope(...): Use Keras-style variable management. set_keras_style(...): Use Keras-style variable management. | tensorflow.compat.v1.layers.experimental |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.