Module: tf

TensorFlow 2.0 RC

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!

金坛期货配资These docs were generated from the beta build of TensorFlow 2.0.

金坛期货配资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 module: Conversion of plain Python into TensorFlow graph code.

bitwise金坛期货配资 module: Operations for manipulating the binary representations of integers.

compat 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金坛期货配资 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金坛期货配资 module: Exception types for TensorFlow errors.

estimator金坛期货配资 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金坛期货配资 module: Image processing and decoding ops.

initializers module: Keras initializer serialization / deserialization.

io金坛期货配资 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金坛期货配资 module: Built-in loss functions.

math module: Math Operations.

metrics module: Built-in metrics.

nest module: Public API for tf.nest namespace.

nn金坛期货配资 module: Wrappers for primitive Neural Net (NN) Operations.

optimizers module: Built-in optimizer classes.

quantization module: Public API for tf.quantization namespace.

queue金坛期货配资 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金坛期货配资 module: Public API for tf.saved_model namespace.

sets金坛期货配资 module: Tensorflow set operations.

signal module: Signal processing operations.

sparse金坛期货配资 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金坛期货配资 module: System configuration library.

test金坛期货配资 module: Testing.

tpu module: Ops related to Tensor Processing Units.

train金坛期货配资 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金坛期货配资: 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金坛期货配资: Record operations for automatic differentiation.

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

class IndexedSlices金坛期货配资: A sparse representation of a set of tensor slices at given indices.

class IndexedSlicesSpec: Type specification for a tf.IndexedSlices.

class Module金坛期货配资: Base neural network module class.

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

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

class RaggedTensor金坛期货配资: 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: 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: Describes a tf.Tensor.

class TypeSpec: Specifies a TensorFlow value type.

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

class Variable金坛期货配资: See the .

class VariableAggregation金坛期货配资: Indicates how a distributed variable will be aggregated.

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

class constant_initializer金坛期货配资: Initializer that generates tensors with constant values.

class name_scope金坛期货配资: A context manager for use when defining a Python op.

class ones_initializer: Initializer that generates tensors initialized to 1.

class random_normal_initializer金坛期货配资: Initializer that generates tensors with a normal distribution.

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

class zeros_initializer: Initializer that generates tensors initialized to 0.

Functions

Assert(...)金坛期货配资: Asserts that the given condition is true.

abs(...)金坛期货配资: Computes the absolute value of a tensor.

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

acosh(...)金坛期货配资: Computes inverse hyperbolic cosine of x element-wise.

add(...)金坛期货配资: Returns x + y element-wise.

add_n(...)金坛期货配资: Adds all input tensors element-wise.

argmax(...)金坛期货配资: 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(...)金坛期货配资: 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 holds element-wise.

assert_greater(...): Assert the condition x > y金坛期货配资 holds element-wise.

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

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

atan(...)金坛期货配资: Computes the trignometric inverse tangent of x element-wise.

atan2(...): Computes arctangent of y/x金坛期货配资 element-wise, respecting signs of the arguments.

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

batch_to_space(...)金坛期货配资: BatchToSpace for N-D tensors of type T.

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

boolean_mask(...)金坛期货配资: Apply boolean mask to tensor.

broadcast_dynamic_shape(...)金坛期货配资: Computes the shape of a broadcast given symbolic shapes.

broadcast_static_shape(...)金坛期货配资: Computes the shape of a broadcast given known shapes.

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

case(...): Create a case operation.

cast(...)金坛期货配资: 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(...): Clips tensor values to a maximum L2-norm.

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

complex(...)金坛期货配资: 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() using the default graph.

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

cos(...)金坛期货配资: 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(...)金坛期货配资: 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(...): Computes the Levenshtein distance between sequences.

einsum(...)金坛期货配资: A generalized contraction between tensors of arbitrary dimension.

ensure_shape(...)金坛期货配资: Updates the shape of a tensor and checks at runtime that the shape holds.

equal(...)金坛期货配资: 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(...): Construct an identity matrix, or a batch of matrices.

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

fingerprint(...)金坛期货配资: Generates fingerprint values.

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

foldl(...): foldl on the list of tensors unpacked from elems金坛期货配资 on dimension 0.

foldr(...): foldr on the list of tensors unpacked from elems金坛期货配资 on dimension 0.

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

gather(...)金坛期货配资: 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(...)金坛期货配资: 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(...)金坛期货配资: Returns the truth value of (x > y) element-wise.

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

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

guarantee_const(...)金坛期货配资: 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(...): 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金坛期货配资. (deprecated arguments)

init_scope(...)金坛期货配资: 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(...)金坛期货配资: Returns the truth value of (x < y) element-wise.

less_equal(...)金坛期货配资: Returns the truth value of (x <= y) element-wise.

linspace(...): Generates values in an interval.

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

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

logical_and(...)金坛期货配资: Returns the truth value of x AND y element-wise.

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

logical_or(...)金坛期货配资: Returns the truth value of x OR y element-wise.

make_ndarray(...)金坛期货配资: Create a numpy ndarray from a tensor.

make_tensor_proto(...): Create a TensorProto.

map_fn(...): map on the list of tensors unpacked from elems金坛期货配资 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(...)金坛期货配资: Broadcasts parameters for evaluation on an N-D grid.

minimum(...)金坛期货配资: Returns the min of x and y (i.e. x < y ? x : y) element-wise.

multiply(...)金坛期货配资: Returns x * y element-wise.

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

no_gradient(...): Specifies that ops of type op_type金坛期货配资 is not differentiable.

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

nondifferentiable_batch_function(...): 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(...)金坛期货配资: Returns a one-hot tensor.

ones(...)金坛期货配资: Creates a tensor with all elements set to 1.

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

pad(...)金坛期货配资: Pads a tensor.

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

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

print(...)金坛期货配资: 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(...)金坛期货配资: Returns x / y element-wise for real types.

recompute_grad(...): An eager-compatible version of recompute_grad.

reduce_all(...): 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(...): Computes log(sum(exp(elements across dimensions of a tensor))).

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

reduce_mean(...)金坛期货配资: Computes the mean of elements across dimensions of a tensor.

reduce_min(...)金坛期货配资: Computes the minimum of elements across dimensions of a tensor.

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

reduce_sum(...)金坛期货配资: 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(...)金坛期货配资: Calculate padding required to make block_shape divide input_shape.

reshape(...): Reshapes a tensor.

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

reverse_sequence(...): Reverses variable length slices.

roll(...)金坛期货配资: 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 on dimension 0.

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

searchsorted(...)金坛期货配资: Searches input tensor for values on the innermost dimension.

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

shape(...)金坛期货配资: 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(...)金坛期货配资: Computes sine of x element-wise.

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

size(...)

slice(...)金坛期货配资: Extracts a slice from a tensor.

sort(...): Sorts a tensor.

space_to_batch(...)金坛期货配资: SpaceToBatch for N-D tensors of type T.

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

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

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

square(...)金坛期货配资: 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(...)金坛期货配资: Stops gradient computation.

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

subtract(...): Returns x - y element-wise.

switch_case(...)金坛期货配资: Create a switch/case operation, i.e. an integer-indexed conditional.

tan(...)金坛期货配资: 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(...): Tensor contraction of a and b along specified axes.

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

timestamp(...)金坛期货配资: Provides the time since epoch in seconds.

transpose(...): Transposes a.

truediv(...)金坛期货配资: 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(...)金坛期货配资: Group tensors together.

unique(...)金坛期货配资: Finds unique elements in a 1-D tensor.

unique_with_counts(...)金坛期货配资: Finds unique elements in a 1-D tensor.

unravel_index(...)金坛期货配资: 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(...)金坛期货配资: 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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