Module: tf

TensorFlow

pip install tensorflow

Modules

audio module: Public API for tf.audio namespace.

autodiff module: Public API for tf.autodiff namespace.

autograph module: Conversion of plain Python into TensorFlow graph code.

bitwise module: Operations for manipulating the binary representations of integers.

compat module: Compatibility functions.

config module: Public API for tf.config namespace.

data module: tf.data.Dataset API for input pipelines.

debugging module: Public API for tf.debugging namespace.

distribute module: Library for running a computation across multiple devices.

dtypes module: Public API for tf.dtypes namespace.

errors module: Exception types for TensorFlow errors.

estimator module: Estimator: High level tools for working with models.

experimental module: Public API for tf.experimental namespace.

feature_column module: Public API for tf.feature_column namespace.

graph_util module: Helpers to manipulate a tensor graph in python.

image module: Image ops.

initializers module: Keras initializer serialization / deserialization.

io module: Public API for tf.io namespace.

keras module: Implementation of the Keras API meant to be a high-level API for TensorFlow.

linalg module: Operations for linear algebra.

lite module: Public API for tf.lite namespace.

lookup module: Public API for tf.lookup namespace.

losses module: Built-in loss functions.

math module: Math Operations.

metrics module: Built-in metrics.

mixed_precision module: Public API for tf.mixed_precision namespace.

mlir module: Public API for tf.mlir namespace.

nest module: Public API for tf.nest namespace.

nn module: Wrappers for primitive Neural Net (NN) Operations.

optimizers module: Built-in optimizer classes.

profiler module: Public API for tf.profiler namespace.

quantization module: Public API for tf.quantization namespace.

queue module: Public API for tf.queue namespace.

ragged module: Ragged Tensors.

random module: Public API for tf.random namespace.

raw_ops module: Public API for tf.raw_ops namespace.

saved_model module: Public API for tf.saved_model namespace.

sets module: Tensorflow set operations.

signal module: Signal processing operations.

sparse module: Sparse Tensor Representation.

strings module: Operations for working with string Tensors.

summary module: Operations for writing summary data, for use in analysis and visualization.

sysconfig module: System configuration library.

test module: Testing.

tpu module: Ops related to Tensor Processing Units.

train module: Support for training models.

version module: Public API for tf.version namespace.

xla module: Public API for tf.xla namespace.

Classes

class AggregationMethod: A class listing aggregation methods used to combine gradients.

class CriticalSection: Critical section.

class DType: Represents the type of the elements in a Tensor.

class DeviceSpec: Represents a (possibly partial) specification for a TensorFlow device.

class GradientTape: Record operations for automatic differentiation.

class Graph: A TensorFlow computation, represented as a dataflow graph.

class IndexedSlices: A sparse representation of a set of tensor slices at given indices.