Module: tf

TensorFlow 2.0 RC

卖空期货Caution: This is a developer preview. You will likely find some bugs, performance issues, and more, and we encourage you to tell us about them. We value your feedback!

卖空期货These docs were generated from the beta build of TensorFlow 2.0.

You can install the exact version that was used to generate these docs with:

pip install tensorflow==2.0.0-rc0

Modules

audio module: Public API for tf.audio namespace.

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

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

compat卖空期货 module: Functions for Python 2 vs. 3 compatibility.

config module: Public API for tf.config namespace.

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

debugging卖空期货 module: Public API for tf.debugging namespace.

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

dtypes卖空期货 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卖空期货 module: Public API for tf.feature_column namespace.

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

image module: Image processing and decoding 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卖空期货 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卖空期货 module: Math Operations.

metrics module: Built-in metrics.

nest module: Public API for tf.nest namespace.

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

optimizers module: Built-in optimizer classes.

quantization module: Public API for tf.quantization namespace.

queue module: Public API for tf.queue namespace.

ragged module: Ragged Tensors.

random卖空期货 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卖空期货 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卖空期货 module: Testing.

tpu卖空期货 module: Ops related to Tensor Processing Units.

train module: Support for training models.

version卖空期货 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.

class IndexedSlicesSpec: Type specification for a tf.IndexedSlices.

class Module: Base neural network module class.

class Operation卖空期货: Represents a graph node that performs computation on tensors.

class OptionalSpec卖空期货: Represents an optional potentially containing a structured value.

class RaggedTensor卖空期货: Represents a ragged tensor.

class RaggedTensorSpec: Type specification for a tf.RaggedTensor.

class RegisterGradient: A decorator for registering the gradient function for an op type.

class SparseTensor卖空期货: Represents a sparse tensor.

class SparseTensorSpec: Type specification for a tf.SparseTensor.

class Tensor: Represents one of the outputs of an Operation.

class TensorArray: Class wrapping dynamic-sized, per-time-step, write-once Tensor arrays.

class TensorArraySpec: Type specification for a tf.TensorArray.

class TensorShape: Represents the shape of a Tensor.

class TensorSpec卖空期货: Describes a tf.Tensor.

class TypeSpec: Specifies a TensorFlow value type.

class UnconnectedGradients卖空期货: Controls how gradient computation behaves when y does not depend on x.

class Variable卖空期货: See the .

class VariableAggregation: Indicates how a distributed variable will be aggregated.

class VariableSynchronization卖空期货: Indicates when a distributed variable will be synced.

class constant_initializer卖空期货: Initializer that generates tensors with constant values.

class name_scope卖空期货: A context manager for use when defining a Python op.

class ones_initializer: Initializer that generates tensors initialized to 1.

class random_normal_initializer: Initializer that generates tensors with a normal distribution.

class random_uniform_initializer: Initializer that generates tensors with a uniform distribution.

class zeros_initializer卖空期货: Initializer that generates tensors initialized to 0.

Functions

Assert(...): Asserts that the given condition is true.

abs(...): Computes the absolute value of a tensor.

acos(...): Computes acos of x element-wise.

acosh(...)卖空期货: Computes inverse hyperbolic cosine of x element-wise.

add(...): Returns x + y element-wise.

add_n(...): Adds all input tensors element-wise.

argmax(...)卖空期货: Returns the index with the largest value across axes of a tensor.

argmin(...): Returns the index with the smallest value across axes of a tensor.

argsort(...): Returns the indices of a tensor that give its sorted order along an axis.

as_dtype(...): Converts the given type_value to a DType.

as_string(...): Converts each entry in the given tensor to strings.

asin(...): Computes the trignometric inverse sine of x element-wise.

asinh(...): Computes inverse hyperbolic sine of x element-wise.

assert_equal(...): Assert the condition x == y卖空期货 holds element-wise.

assert_greater(...): Assert the condition x > y卖空期货 holds element-wise.

assert_less(...): Assert the condition x < y holds element-wise.

assert_rank(...): Assert that x has rank equal to rank.

atan(...)卖空期货: Computes the trignometric inverse tangent of x element-wise.

atan2(...): Computes arctangent of y/x卖空期货 element-wise, respecting signs of the arguments.

atanh(...): Computes inverse hyperbolic tangent of x element-wise.

batch_to_space(...)卖空期货: BatchToSpace for N-D tensors of type T.

bitcast(...)卖空期货: Bitcasts a tensor from one type to another without copying data.

boolean_mask(...): Apply boolean mask to tensor.

broadcast_dynamic_shape(...)卖空期货: Computes the shape of a broadcast given symbolic shapes.

broadcast_static_shape(...): Computes the shape of a broadcast given known shapes.

broadcast_to(...): Broadcast an array for a compatible shape.

case(...)卖空期货: Create a case operation.

cast(...)卖空期货: Casts a tensor to a new type.

clip_by_global_norm(...): Clips values of multiple tensors by the ratio of the sum of their norms.

clip_by_norm(...)卖空期货: Clips tensor values to a maximum L2-norm.

clip_by_value(...): Clips tensor values to a specified min and max.

complex(...): Converts two real numbers to a complex number.

concat(...): Concatenates tensors along one dimension.

cond(...): Return true_fn() if the predicate pred is true else false_fn().

constant(...): Creates a constant tensor.

control_dependencies(...): Wrapper for Graph.control_dependencies()卖空期货 using the default graph.

convert_to_tensor(...): Converts the given value to a Tensor.

cos(...): Computes cos of x element-wise.

cosh(...): Computes hyperbolic cosine of x element-wise.

cumsum(...): Compute the cumulative sum of the tensor x along axis.

custom_gradient(...): Decorator to define a function with a custom gradient.

device(...): Specifies the device for ops created/executed in this context.

divide(...): Computes Python style division of x by y.

dynamic_partition(...): Partitions data into num_partitions tensors using indices from partitions.

dynamic_stitch(...): Interleave the values from the data tensors into a single tensor.

edit_distance(...)卖空期货: Computes the Levenshtein distance between sequences.

einsum(...): A generalized contraction between tensors of arbitrary dimension.

ensure_shape(...): Updates the shape of a tensor and checks at runtime that the shape holds.

equal(...): Returns the truth value of (x == y) element-wise.

executing_eagerly(...): Returns True if the current thread has eager execution enabled.

exp(...): Computes exponential of x element-wise. \(y = e^x\).

expand_dims(...): Inserts a dimension of 1 into a tensor's shape.

extract_volume_patches(...): Extract patches from input and put them in the "depth" output dimension. 3D extension of extract_image_patches.

eye(...)卖空期货: Construct an identity matrix, or a batch of matrices.

fill(...): Creates a tensor filled with a scalar value.

fingerprint(...): Generates fingerprint values.

floor(...): Returns element-wise largest integer not greater than x.

foldl(...): foldl on the list of tensors unpacked from elems on dimension 0.

foldr(...): foldr on the list of tensors unpacked from elems卖空期货 on dimension 0.

function(...): Creates a callable TensorFlow graph from a Python function.

gather(...): Gather slices from params axis axis according to indices.

gather_nd(...): Gather slices from params into a Tensor with shape specified by indices.

get_logger(...)卖空期货: Return TF logger instance.

get_static_value(...): Returns the constant value of the given tensor, if efficiently calculable.

grad_pass_through(...): Creates a grad-pass-through op with the forward behavior provided in f.

gradients(...): Constructs symbolic derivatives of sum of ys w.r.t. x in xs.

greater(...): Returns the truth value of (x > y) element-wise.

greater_equal(...)卖空期货: Returns the truth value of (x >= y) element-wise.

group(...)卖空期货: Create an op that groups multiple operations.

guarantee_const(...): Gives a guarantee to the TF runtime that the input tensor is a constant.

hessians(...): Constructs the Hessian of sum of ys with respect to x in xs.

histogram_fixed_width(...): Return histogram of values.

histogram_fixed_width_bins(...): Bins the given values for use in a histogram.

identity(...): Return a tensor with the same shape and contents as input.

identity_n(...)卖空期货: Returns a list of tensors with the same shapes and contents as the input

import_graph_def(...): Imports the graph from graph_def into the current default Graph. (deprecated arguments)

init_scope(...)卖空期货: A context manager that lifts ops out of control-flow scopes and function-building graphs.

is_tensor(...): Checks whether x is a tensor or "tensor-like".

less(...): Returns the truth value of (x < y) element-wise.

less_equal(...)卖空期货: Returns the truth value of (x <= y) element-wise.

linspace(...)卖空期货: Generates values in an interval.

load_library(...): Loads a TensorFlow plugin.

load_op_library(...)卖空期货: Loads a TensorFlow plugin, containing custom ops and kernels.

logical_and(...): Returns the truth value of x AND y element-wise.

logical_not(...): Returns the truth value of NOT x element-wise.

logical_or(...): Returns the truth value of x OR y element-wise.

make_ndarray(...): Create a numpy ndarray from a tensor.

make_tensor_proto(...): Create a TensorProto.

map_fn(...): map on the list of tensors unpacked from elems卖空期货 on dimension 0.

matmul(...): Multiplies matrix a by matrix b, producing a * b.

matrix_square_root(...): Computes the matrix square root of one or more square matrices:

maximum(...): Returns the max of x and y (i.e. x > y ? x : y) element-wise.

meshgrid(...)卖空期货: Broadcasts parameters for evaluation on an N-D grid.

minimum(...)卖空期货: Returns the min of x and y (i.e. x < y ? x : y) element-wise.

multiply(...): Returns x * y element-wise.

negative(...): Computes numerical negative value element-wise.

no_gradient(...): Specifies that ops of type op_type卖空期货 is not differentiable.

no_op(...)卖空期货: Does nothing. Only useful as a placeholder for control edges.

nondifferentiable_batch_function(...)卖空期货: Batches the computation done by the decorated function.

norm(...): Computes the norm of vectors, matrices, and tensors.

not_equal(...): Returns the truth value of (x != y) element-wise.

numpy_function(...): Wraps a python function and uses it as a TensorFlow op.

one_hot(...): Returns a one-hot tensor.

ones(...): Creates a tensor with all elements set to 1.

ones_like(...): Creates a tensor with all elements set to zero.

pad(...): Pads a tensor.

parallel_stack(...): Stacks a list of rank-R tensors into one rank-(R+1) tensor in parallel.

pow(...)卖空期货: Computes the power of one value to another.

print(...): Print the specified inputs.

py_function(...): Wraps a python function into a TensorFlow op that executes it eagerly.

range(...): Creates a sequence of numbers.

rank(...): Returns the rank of a tensor.

realdiv(...): Returns x / y element-wise for real types.

recompute_grad(...)卖空期货: An eager-compatible version of recompute_grad.

reduce_all(...)卖空期货: Computes the "logical and" of elements across dimensions of a tensor.

reduce_any(...): Computes the "logical or" of elements across dimensions of a tensor.

reduce_logsumexp(...)卖空期货: Computes log(sum(exp(elements across dimensions of a tensor))).

reduce_max(...)卖空期货: Computes the maximum of elements across dimensions of a tensor.

reduce_mean(...): Computes the mean of elements across dimensions of a tensor.

reduce_min(...): Computes the minimum of elements across dimensions of a tensor.

reduce_prod(...): Computes the product of elements across dimensions of a tensor.

reduce_sum(...): Computes the sum of elements across dimensions of a tensor.

register_tensor_conversion_function(...): Registers a function for converting objects of base_type to Tensor.

required_space_to_batch_paddings(...): Calculate padding required to make block_shape divide input_shape.

reshape(...)卖空期货: Reshapes a tensor.

reverse(...): Reverses specific dimensions of a tensor.

reverse_sequence(...)卖空期货: Reverses variable length slices.

roll(...): Rolls the elements of a tensor along an axis.

round(...): Rounds the values of a tensor to the nearest integer, element-wise.

saturate_cast(...): Performs a safe saturating cast of value to dtype.

scalar_mul(...): Multiplies a scalar times a Tensor or IndexedSlices object.

scan(...): scan on the list of tensors unpacked from elems卖空期货 on dimension 0.

scatter_nd(...): Scatter updates into a new tensor according to indices.

searchsorted(...): Searches input tensor for values on the innermost dimension.

sequence_mask(...): Returns a mask tensor representing the first N positions of each cell.

shape(...): Returns the shape of a tensor.

shape_n(...): Returns shape of tensors.

sigmoid(...): Computes sigmoid of x element-wise.

sign(...): Returns an element-wise indication of the sign of a number.

sin(...): Computes sine of x element-wise.

sinh(...): Computes hyperbolic sine of x element-wise.

size(...)

slice(...)卖空期货: Extracts a slice from a tensor.

sort(...)卖空期货: Sorts a tensor.

space_to_batch(...)卖空期货: SpaceToBatch for N-D tensors of type T.

space_to_batch_nd(...)卖空期货: SpaceToBatch for N-D tensors of type T.

split(...): Splits a tensor into sub tensors.

sqrt(...)卖空期货: Computes square root of x element-wise.

square(...)卖空期货: Computes square of x element-wise.

squeeze(...): Removes dimensions of size 1 from the shape of a tensor.

stack(...): Stacks a list of rank-R tensors into one rank-(R+1) tensor.

stop_gradient(...): Stops gradient computation.

strided_slice(...)卖空期货: Extracts a strided slice of a tensor (generalized python array indexing).

subtract(...)卖空期货: Returns x - y element-wise.

switch_case(...): Create a switch/case operation, i.e. an integer-indexed conditional.

tan(...): Computes tan of x element-wise.

tanh(...): Computes hyperbolic tangent of x element-wise.

tensor_scatter_nd_add(...): Adds sparse updates to an existing tensor according to indices.

tensor_scatter_nd_sub(...): Subtracts sparse updates from an existing tensor according to indices.

tensor_scatter_nd_update(...): Scatter updates into an existing tensor according to indices.

tensordot(...)卖空期货: Tensor contraction of a and b along specified axes.

tile(...): Constructs a tensor by tiling a given tensor.

timestamp(...)卖空期货: Provides the time since epoch in seconds.

transpose(...): Transposes a.

truediv(...)卖空期货: Divides x / y elementwise (using Python 3 division operator semantics).

truncatediv(...): Returns x / y element-wise for integer types.

truncatemod(...): Returns element-wise remainder of division. This emulates C semantics in that

tuple(...)卖空期货: Group tensors together.

unique(...): Finds unique elements in a 1-D tensor.

unique_with_counts(...): Finds unique elements in a 1-D tensor.

unravel_index(...)卖空期货: Converts a flat index or array of flat indices into a tuple of

unstack(...): Unpacks the given dimension of a rank-R tensor into rank-(R-1) tensors.

variable_creator_scope(...): Scope which defines a variable creation function to be used by variable().

vectorized_map(...): Parallel map on the list of tensors unpacked from elems on dimension 0.

where(...): Return the elements, either from x or y, depending on the condition.

while_loop(...): Repeat body while the condition cond is true.

zeros(...): Creates a tensor with all elements set to zero.

zeros_like(...): Creates a tensor with all elements set to zero.

Other Members

  • bfloat16
  • bool
  • complex128
  • complex64
  • double
  • float16
  • float32
  • float64
  • half
  • int16
  • int32
  • int64
  • int8
  • newaxis = None
  • qint16
  • qint32
  • qint8
  • quint16
  • quint8
  • resource
  • string
  • uint16
  • uint32
  • uint64
  • uint8
  • variant

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