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!

金铨达配资These docs were generated from the beta build of TensorFlow 2.0.

金铨达配资You can install the exact version that was used to generate these docs with:

pip install tensorflow==2.0.0-rc0

Modules

audio金铨达配资 module: Public API for tf.audio namespace.

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

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

compat金铨达配资 module: Functions for Python 2 vs. 3 compatibility.

config金铨达配资 module: Public API for tf.config namespace.

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

debugging金铨达配资 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金铨达配资 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金铨达配资 module: Helpers to manipulate a tensor graph in python.

image module: Image processing and decoding ops.

initializers module: Keras initializer serialization / deserialization.

io金铨达配资 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金铨达配资 module: Public API for tf.lite namespace.

lookup module: Public API for tf.lookup namespace.

losses金铨达配资 module: Built-in loss functions.

math金铨达配资 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金铨达配资 module: Built-in optimizer classes.

quantization金铨达配资 module: Public API for tf.quantization namespace.

queue module: Public API for tf.queue namespace.

ragged金铨达配资 module: Ragged Tensors.

random金铨达配资 module: Public API for tf.random namespace.

raw_ops金铨达配资 module: Public API for tf.raw_ops namespace.

saved_model module: Public API for tf.saved_model namespace.

sets module: Tensorflow set operations.

signal金铨达配资 module: Signal processing operations.

sparse金铨达配资 module: Sparse Tensor Representation.

strings金铨达配资 module: Operations for working with string Tensors.

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

sysconfig金铨达配资 module: System configuration library.

test金铨达配资 module: Testing.

tpu module: Ops related to Tensor Processing Units.

train金铨达配资 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金铨达配资: 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金铨达配资: Record operations for automatic differentiation.

class Graph金铨达配资: 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: Represents a graph node that performs computation on tensors.

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

class RaggedTensor金铨达配资: Represents a ragged tensor.

class RaggedTensorSpec: Type specification for a tf.RaggedTensor.

class RegisterGradient金铨达配资: 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: See the .

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

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

class constant_initializer: Initializer that generates tensors with constant values.

class name_scope金铨达配资: A context manager for use when defining a Python op.

class ones_initializer金铨达配资: 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金铨达配资: 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(...): Computes inverse hyperbolic cosine of x element-wise.

add(...)金铨达配资: Returns x + y element-wise.

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

argmax(...): 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(...)金铨达配资: Computes the trignometric inverse sine of x element-wise.

asinh(...)金铨达配资: Computes inverse hyperbolic sine of x element-wise.

assert_equal(...): Assert the condition x == y金铨达配资 holds element-wise.

assert_greater(...): Assert the condition x > y金铨达配资 holds element-wise.

assert_less(...): Assert the condition x < y金铨达配资 holds element-wise.

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

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

atan2(...): Computes arctangent of y/x金铨达配资 element-wise, respecting signs of the arguments.

atanh(...)金铨达配资: Computes inverse hyperbolic tangent of x element-wise.

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

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

boolean_mask(...)金铨达配资: Apply boolean mask to tensor.

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

cast(...): 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(...)金铨达配资: Clips tensor values to a specified min and max.

complex(...)金铨达配资: 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(...)金铨达配资: 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(...)金铨达配资: Decorator to define a function with a custom gradient.

device(...)金铨达配资: 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(...): A generalized contraction between tensors of arbitrary dimension.

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

equal(...)金铨达配资: 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(...)金铨达配资: Construct an identity matrix, or a batch of matrices.

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

fingerprint(...): Generates fingerprint values.

floor(...)金铨达配资: 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金铨达配资 on dimension 0.

function(...)金铨达配资: Creates a callable TensorFlow graph from a Python function.

gather(...)金铨达配资: 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(...): 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(...)金铨达配资: 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(...): 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(...)金铨达配资: Bins the given values for use in a histogram.

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

identity_n(...)金铨达配资: 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金铨达配资. (deprecated arguments)

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

is_tensor(...): Checks whether x金铨达配资 is a tensor or "tensor-like".

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

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

linspace(...)金铨达配资: 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(...): 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 on dimension 0.

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

matrix_square_root(...)金铨达配资: 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(...)金铨达配资: Broadcasts parameters for evaluation on an N-D grid.

minimum(...)金铨达配资: Returns the min of x and y (i.e. x < y ? x : y) element-wise.

multiply(...)金铨达配资: Returns x * y element-wise.

negative(...)金铨达配资: Computes numerical negative value element-wise.

no_gradient(...): Specifies that ops of type op_type金铨达配资 is not differentiable.

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

nondifferentiable_batch_function(...)金铨达配资: Batches the computation done by the decorated function.

norm(...)金铨达配资: Computes the norm of vectors, matrices, and tensors.

not_equal(...)金铨达配资: 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(...)金铨达配资: Pads a tensor.

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

pow(...): 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(...)金铨达配资: Returns the rank of a tensor.

realdiv(...)金铨达配资: 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(...)金铨达配资: Computes log(sum(exp(elements across dimensions of a tensor))).

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

reduce_mean(...)金铨达配资: Computes the mean of elements across dimensions of a tensor.

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

reduce_prod(...)金铨达配资: Computes the product of elements across dimensions of a tensor.

reduce_sum(...)金铨达配资: 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(...)金铨达配资: Calculate padding required to make block_shape divide input_shape.

reshape(...): Reshapes a tensor.

reverse(...)金铨达配资: Reverses specific dimensions of a tensor.

reverse_sequence(...)金铨达配资: Reverses variable length slices.

roll(...)金铨达配资: Rolls the elements of a tensor along an axis.

round(...)金铨达配资: 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金铨达配资 on dimension 0.

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

searchsorted(...)金铨达配资: Searches input tensor for values on the innermost dimension.

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

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

shape_n(...)金铨达配资: Returns shape of tensors.

sigmoid(...): Computes sigmoid of x金铨达配资 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(...)金铨达配资: Extracts a slice from a tensor.

sort(...): Sorts a tensor.

space_to_batch(...): 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(...)金铨达配资: Computes square root of x element-wise.

square(...)金铨达配资: 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(...)金铨达配资: Stops gradient computation.

strided_slice(...)金铨达配资: Extracts a strided slice of a tensor (generalized python array indexing).

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

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

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

tanh(...): Computes hyperbolic tangent of x金铨达配资 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(...)金铨达配资: Constructs a tensor by tiling a given tensor.

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

transpose(...): Transposes a.

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

truncatediv(...)金铨达配资: Returns x / y element-wise for integer types.

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

tuple(...)金铨达配资: Group tensors together.

unique(...)金铨达配资: Finds unique elements in a 1-D tensor.

unique_with_counts(...)金铨达配资: Finds unique elements in a 1-D tensor.

unravel_index(...)金铨达配资: 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(...): 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

results matching ""

    No results matching ""