Module: tf

TensorFlow 2.0 RC

免费成长做爱直播有哪些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!

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

免费成长做爱直播有哪些You can install the exact version that was used to generate these docs with:

pip install tensorflow==2.0.0-rc0

Modules

audio免费成长做爱直播有哪些 module: Public API for tf.audio namespace.

autograph免费成长做爱直播有哪些 module: Conversion of plain Python into TensorFlow graph code.

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

compat免费成长做爱直播有哪些 module: Functions for Python 2 vs. 3 compatibility.

config免费成长做爱直播有哪些 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免费成长做爱直播有哪些 module: Estimator: High level tools for working with models.

experimental module: Public API for tf.experimental namespace.

feature_column免费成长做爱直播有哪些 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免费成长做爱直播有哪些 module: Operations for linear algebra.

lite免费成长做爱直播有哪些 module: Public API for tf.lite namespace.

lookup module: Public API for tf.lookup namespace.

losses module: Built-in loss functions.

math免费成长做爱直播有哪些 module: Math Operations.

metrics免费成长做爱直播有哪些 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免费成长做爱直播有哪些 module: Public API for tf.random namespace.

raw_ops module: Public API for tf.raw_ops namespace.

saved_model免费成长做爱直播有哪些 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免费成长做爱直播有哪些 module: System configuration library.

test module: Testing.

tpu module: Ops related to Tensor Processing Units.

train免费成长做爱直播有哪些 module: Support for training models.

version module: Public API for tf.version namespace.

xla module: Public API for tf.xla namespace.

Classes

class AggregationMethod免费成长做爱直播有哪些: A class listing aggregation methods used to combine gradients.

class CriticalSection免费成长做爱直播有哪些: 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: Represents a graph node that performs computation on tensors.

class OptionalSpec免费成长做爱直播有哪些: Represents an optional potentially containing a structured value.

class RaggedTensor免费成长做爱直播有哪些: 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免费成长做爱直播有哪些: 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免费成长做爱直播有哪些: 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免费成长做爱直播有哪些: Indicates how a distributed variable will be aggregated.

class VariableSynchronization免费成长做爱直播有哪些: Indicates when a distributed variable will be synced.

class constant_initializer免费成长做爱直播有哪些: Initializer that generates tensors with constant values.

class name_scope: 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免费成长做爱直播有哪些: Initializer that generates tensors initialized to 0.

Functions

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

abs(...)免费成长做爱直播有哪些: Computes the absolute value of a tensor.

acos(...)免费成长做爱直播有哪些: Computes acos of x element-wise.

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

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

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

argmax(...)免费成长做爱直播有哪些: 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(...)免费成长做爱直播有哪些: 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 holds element-wise.

assert_less(...): Assert the condition x < y 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免费成长做爱直播有哪些 element-wise, respecting signs of the arguments.

atanh(...): 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(...)免费成长做爱直播有哪些: Apply boolean mask to tensor.

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

broadcast_static_shape(...)免费成长做爱直播有哪些: Computes the shape of a broadcast given known shapes.

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

case(...)免费成长做爱直播有哪些: 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(...)免费成长做爱直播有哪些: Clips tensor values to a maximum L2-norm.

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

complex(...)免费成长做爱直播有哪些: 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(...): Computes cos of x element-wise.

cosh(...)免费成长做爱直播有哪些: 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免费成长做爱直播有哪些 tensors into a single tensor.

edit_distance(...): 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(...)免费成长做爱直播有哪些: Computes exponential of x element-wise. \(y = e^x\).

expand_dims(...)免费成长做爱直播有哪些: 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(...)免费成长做爱直播有哪些: 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免费成长做爱直播有哪些 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(...): 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(...)免费成长做爱直播有哪些: Returns the truth value of (x >= y) element-wise.

group(...)免费成长做爱直播有哪些: Create an op that groups multiple operations.

guarantee_const(...)免费成长做爱直播有哪些: 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(...)免费成长做爱直播有哪些: Return histogram of values.

histogram_fixed_width_bins(...)免费成长做爱直播有哪些: Bins the given values for use in a histogram.

identity(...)免费成长做爱直播有哪些: 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. (deprecated arguments)

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

is_tensor(...): Checks whether x免费成长做爱直播有哪些 is a tensor or "tensor-like".

less(...)免费成长做爱直播有哪些: Returns the truth value of (x < y) element-wise.

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

linspace(...)免费成长做爱直播有哪些: 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(...)免费成长做爱直播有哪些: Returns the truth value of x AND y element-wise.

logical_not(...)免费成长做爱直播有哪些: Returns the truth value of NOT x element-wise.

logical_or(...)免费成长做爱直播有哪些: Returns the truth value of x OR y element-wise.

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

make_tensor_proto(...)免费成长做爱直播有哪些: Create a TensorProto.

map_fn(...): map on the list of tensors unpacked from elems免费成长做爱直播有哪些 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(...): Broadcasts parameters for evaluation on an N-D grid.

minimum(...)免费成长做爱直播有哪些: Returns the min of x and y (i.e. x < y ? x : y) element-wise.

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

negative(...)免费成长做爱直播有哪些: Computes numerical negative value element-wise.

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

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

nondifferentiable_batch_function(...)免费成长做爱直播有哪些: 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(...)免费成长做爱直播有哪些: Creates a tensor with all elements set to zero.

pad(...)免费成长做爱直播有哪些: Pads a tensor.

parallel_stack(...): Stacks a list of rank-R tensors into one rank-(R+1)免费成长做爱直播有哪些 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(...): Returns the rank of a tensor.

realdiv(...): 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(...)免费成长做爱直播有哪些: 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(...)免费成长做爱直播有哪些: Computes the maximum of elements across dimensions of a tensor.

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

reduce_min(...)免费成长做爱直播有哪些: Computes the minimum of elements across dimensions of a tensor.

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

reduce_sum(...)免费成长做爱直播有哪些: 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(...)免费成长做爱直播有哪些: Calculate padding required to make block_shape divide input_shape.

reshape(...): Reshapes a tensor.

reverse(...)免费成长做爱直播有哪些: Reverses specific dimensions of a tensor.

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

roll(...)免费成长做爱直播有哪些: Rolls the elements of a tensor along an axis.

round(...)免费成长做爱直播有哪些: 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免费成长做爱直播有哪些 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免费成长做爱直播有哪些 element-wise.

sign(...)免费成长做爱直播有哪些: Returns an element-wise indication of the sign of a number.

sin(...)免费成长做爱直播有哪些: Computes sine of x element-wise.

sinh(...)免费成长做爱直播有哪些: Computes hyperbolic sine of x element-wise.

size(...)

slice(...)免费成长做爱直播有哪些: 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(...)免费成长做爱直播有哪些: SpaceToBatch for N-D tensors of type T.

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

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

square(...)免费成长做爱直播有哪些: 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(...)免费成长做爱直播有哪些: Stops gradient computation.

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

subtract(...)免费成长做爱直播有哪些: Returns x - y element-wise.

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

tan(...)免费成长做爱直播有哪些: 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(...)免费成长做爱直播有哪些: Constructs a tensor by tiling a given tensor.

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

transpose(...): Transposes a.

truediv(...)免费成长做爱直播有哪些: Divides x / y elementwise (using Python 3 division operator semantics).

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

truncatemod(...)免费成长做爱直播有哪些: Returns element-wise remainder of division. This emulates C semantics in that

tuple(...)免费成长做爱直播有哪些: Group tensors together.

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

unique_with_counts(...)免费成长做爱直播有哪些: Finds unique elements in a 1-D tensor.

unravel_index(...)免费成长做爱直播有哪些: 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免费成长做爱直播有哪些 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(...)免费成长做爱直播有哪些: 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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