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tf.nn.nce_loss View source on GitHub Computes and returns the noise-contrastive estimation training loss.
tf.nn.nce_loss(
weights, biases, labels, inputs, num_sampled, num_classes, num_true=1,
sampled_values=None, remove_accidental_hits=False, name='nce_loss'
)
See Noise-contrastive estimation: A new e... | tensorflow.nn.nce_loss |
tf.nn.normalize_moments View source on GitHub Calculate the mean and variance of based on the sufficient statistics. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.nn.normalize_moments
tf.nn.normalize_moments(
counts, mean_ss, variance_ss, shift, name=None
)... | tensorflow.nn.normalize_moments |
tf.nn.pool View source on GitHub Performs an N-D pooling operation.
tf.nn.pool(
input, window_shape, pooling_type, strides=None, padding='VALID',
data_format=None, dilations=None, name=None
)
In the case that data_format does not start with "NC", computes for 0 <= b < batch_size, 0 <= x[i] < output_spa... | tensorflow.nn.pool |
tf.nn.relu Computes rectified linear: max(features, 0). View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.nn.relu
tf.nn.relu(
features, name=None
)
See: https://en.wikipedia.org/wiki/Rectifier_(neural_networks) Example usage: >>> tf.nn.relu([-2., 0., -0., 3.]).numpy(... | tensorflow.nn.relu |
tf.nn.relu6 View source on GitHub Computes Rectified Linear 6: min(max(features, 0), 6). View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.nn.relu6
tf.nn.relu6(
features, name=None
)
Args
features A Tensor with type float, double, int32, int64, uint8,... | tensorflow.nn.relu6 |
tf.nn.RNNCellDeviceWrapper Operator that ensures an RNNCell runs on a particular device. Inherits From: AbstractRNNCell, Layer, Module
tf.nn.RNNCellDeviceWrapper(
*args, **kwargs
)
Args
cell An instance of RNNCell.
device A device string or function, for passing to tf.device.
**kwargs dict of... | tensorflow.nn.rnncelldevicewrapper |
tf.nn.RNNCellDropoutWrapper Operator adding dropout to inputs and outputs of the given cell. Inherits From: AbstractRNNCell, Layer, Module
tf.nn.RNNCellDropoutWrapper(
*args, **kwargs
)
Args
cell an RNNCell, a projection to output_size is added to it.
input_keep_prob unit Tensor or float between 0 ... | tensorflow.nn.rnncelldropoutwrapper |
tf.nn.RNNCellResidualWrapper RNNCell wrapper that ensures cell inputs are added to the outputs. Inherits From: AbstractRNNCell, Layer, Module
tf.nn.RNNCellResidualWrapper(
*args, **kwargs
)
Args
cell An instance of RNNCell.
residual_fn (Optional) The function to map raw cell inputs and raw cell out... | tensorflow.nn.rnncellresidualwrapper |
tf.nn.safe_embedding_lookup_sparse View source on GitHub Lookup embedding results, accounting for invalid IDs and empty features.
tf.nn.safe_embedding_lookup_sparse(
embedding_weights, sparse_ids, sparse_weights=None, combiner='mean',
default_id=None, max_norm=None, name=None
)
The partitioned embeddin... | tensorflow.nn.safe_embedding_lookup_sparse |
tf.nn.sampled_softmax_loss View source on GitHub Computes and returns the sampled softmax training loss.
tf.nn.sampled_softmax_loss(
weights, biases, labels, inputs, num_sampled, num_classes, num_true=1,
sampled_values=None, remove_accidental_hits=True, seed=None,
name='sampled_softmax_loss'
)
This... | tensorflow.nn.sampled_softmax_loss |
tf.nn.scale_regularization_loss View source on GitHub Scales the sum of the given regularization losses by number of replicas. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.nn.scale_regularization_loss
tf.nn.scale_regularization_loss(
regularization_loss
)
... | tensorflow.nn.scale_regularization_loss |
tf.nn.selu Computes scaled exponential linear: scale * alpha * (exp(features) - 1) View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.nn.selu
tf.nn.selu(
features, name=None
)
if < 0, scale * features otherwise. To be used together with initializer = tf.variance_scali... | tensorflow.nn.selu |
tf.nn.separable_conv2d View source on GitHub 2-D convolution with separable filters.
tf.nn.separable_conv2d(
input, depthwise_filter, pointwise_filter, strides, padding, data_format=None,
dilations=None, name=None
)
Performs a depthwise convolution that acts separately on channels followed by a pointwi... | tensorflow.nn.separable_conv2d |
tf.nn.sigmoid_cross_entropy_with_logits View source on GitHub Computes sigmoid cross entropy given logits.
tf.nn.sigmoid_cross_entropy_with_logits(
labels=None, logits=None, name=None
)
Measures the probability error in discrete classification tasks in which each class is independent and not mutually exclu... | tensorflow.nn.sigmoid_cross_entropy_with_logits |
tf.nn.silu Computes the SiLU or Swish activation function: x * sigmoid(x). View aliases Main aliases
tf.nn.swish Compat aliases for migration See Migration guide for more details. tf.compat.v1.nn.silu, tf.compat.v1.nn.swish
tf.nn.silu(
features
)
The SiLU activation function was introduced in "Gaussian Error ... | tensorflow.nn.silu |
tf.nn.softmax View source on GitHub Computes softmax activations. View aliases Main aliases
tf.math.softmax
tf.nn.softmax(
logits, axis=None, name=None
)
This function performs the equivalent of softmax = tf.exp(logits) / tf.reduce_sum(tf.exp(logits), axis)
Args
logits A non-empty Tensor. Mus... | tensorflow.nn.softmax |
tf.nn.softmax_cross_entropy_with_logits View source on GitHub Computes softmax cross entropy between logits and labels.
tf.nn.softmax_cross_entropy_with_logits(
labels, logits, axis=-1, name=None
)
Measures the probability error in discrete classification tasks in which the classes are mutually exclusive (... | tensorflow.nn.softmax_cross_entropy_with_logits |
tf.nn.softsign Computes softsign: features / (abs(features) + 1). View aliases Main aliases
tf.math.softsign Compat aliases for migration See Migration guide for more details. tf.compat.v1.math.softsign, tf.compat.v1.nn.softsign
tf.nn.softsign(
features, name=None
)
Args
features A Tensor. Must be on... | tensorflow.nn.softsign |
tf.nn.space_to_depth View source on GitHub SpaceToDepth for tensors of type T.
tf.nn.space_to_depth(
input, block_size, data_format='NHWC', name=None
)
Rearranges blocks of spatial data, into depth. More specifically, this op outputs a copy of the input tensor where values from the height and width dimensi... | tensorflow.nn.space_to_depth |
tf.nn.sparse_softmax_cross_entropy_with_logits View source on GitHub Computes sparse softmax cross entropy between logits and labels.
tf.nn.sparse_softmax_cross_entropy_with_logits(
labels, logits, name=None
)
Measures the probability error in discrete classification tasks in which the classes are mutually... | tensorflow.nn.sparse_softmax_cross_entropy_with_logits |
tf.nn.sufficient_statistics View source on GitHub Calculate the sufficient statistics for the mean and variance of x.
tf.nn.sufficient_statistics(
x, axes, shift=None, keepdims=False, name=None
)
These sufficient statistics are computed using the one pass algorithm on an input that's optionally shifted. Se... | tensorflow.nn.sufficient_statistics |
tf.nn.weighted_cross_entropy_with_logits View source on GitHub Computes a weighted cross entropy.
tf.nn.weighted_cross_entropy_with_logits(
labels, logits, pos_weight, name=None
)
This is like sigmoid_cross_entropy_with_logits() except that pos_weight, allows one to trade off recall and precision by up- or... | tensorflow.nn.weighted_cross_entropy_with_logits |
tf.nn.weighted_moments View source on GitHub Returns the frequency-weighted mean and variance of x.
tf.nn.weighted_moments(
x, axes, frequency_weights, keepdims=False, name=None
)
Args
x A tensor.
axes 1-d tensor of int32 values; these are the axes along which to compute mean and variance. ... | tensorflow.nn.weighted_moments |
tf.nn.with_space_to_batch View source on GitHub Performs op on the space-to-batch representation of input. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.nn.with_space_to_batch
tf.nn.with_space_to_batch(
input, dilation_rate, padding, op, filter_shape=None, ... | tensorflow.nn.with_space_to_batch |
tf.nondifferentiable_batch_function View source on GitHub Batches the computation done by the decorated function. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.nondifferentiable_batch_function
tf.nondifferentiable_batch_function(
num_batch_threads, max_batc... | tensorflow.nondifferentiable_batch_function |
tf.norm View source on GitHub Computes the norm of vectors, matrices, and tensors. View aliases Main aliases
tf.linalg.norm
tf.norm(
tensor, ord='euclidean', axis=None, keepdims=None, name=None
)
This function can compute several different vector norms (the 1-norm, the Euclidean or 2-norm, the inf-norm... | tensorflow.norm |
tf.no_gradient View source on GitHub Specifies that ops of type op_type is not differentiable. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.NoGradient, tf.compat.v1.NotDifferentiable, tf.compat.v1.no_gradient
tf.no_gradient(
op_type
)
This function should... | tensorflow.no_gradient |
tf.no_op Does nothing. Only useful as a placeholder for control edges. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.no_op
tf.no_op(
name=None
)
Args
name A name for the operation (optional).
Returns The created Operation. | tensorflow.no_op |
tf.numpy_function View source on GitHub Wraps a python function and uses it as a TensorFlow op. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.numpy_function
tf.numpy_function(
func, inp, Tout, name=None
)
Given a python function func wrap this function as ... | tensorflow.numpy_function |
tf.ones View source on GitHub Creates a tensor with all elements set to one (1). View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.ones
tf.ones(
shape, dtype=tf.dtypes.float32, name=None
)
See also tf.ones_like, tf.zeros, tf.fill, tf.eye. This operation return... | tensorflow.ones |
tf.ones_initializer Initializer that generates tensors initialized to 1. Initializers allow you to pre-specify an initialization strategy, encoded in the Initializer object, without knowing the shape and dtype of the variable being initialized. Examples:
def make_variables(k, initializer):
return (tf.Variable(initia... | tensorflow.ones_initializer |
tf.ones_like View source on GitHub Creates a tensor of all ones that has the same shape as the input.
tf.ones_like(
input, dtype=None, name=None
)
See also tf.ones. Given a single tensor (tensor), this operation returns a tensor of the same type and shape as tensor with all elements set to 1. Optionally, y... | tensorflow.ones_like |
tf.one_hot View source on GitHub Returns a one-hot tensor. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.one_hot
tf.one_hot(
indices, depth, on_value=None, off_value=None, axis=None, dtype=None, name=None
)
See also tf.fill, tf.eye. The locations represent... | tensorflow.one_hot |
tf.Operation View source on GitHub Represents a graph node that performs computation on tensors. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.Operation
tf.Operation(
node_def, g, inputs=None, output_types=None, control_inputs=None,
input_types=None, or... | tensorflow.operation |
tf.OptionalSpec View source on GitHub Type specification for tf.experimental.Optional. Inherits From: TypeSpec View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.OptionalSpec, tf.compat.v1.data.experimental.OptionalStructure
tf.OptionalSpec(
element_spec
)
For ... | tensorflow.optionalspec |
tf.pad View source on GitHub Pads a tensor.
tf.pad(
tensor, paddings, mode='CONSTANT', constant_values=0, name=None
)
This operation pads a tensor according to the paddings you specify. paddings is an integer tensor with shape [n, 2], where n is the rank of tensor. For each dimension D of input, paddings[D... | tensorflow.pad |
tf.parallel_stack View source on GitHub Stacks a list of rank-R tensors into one rank-(R+1) tensor in parallel. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.parallel_stack
tf.parallel_stack(
values, name='parallel_stack'
)
Requires that the shape of input... | tensorflow.parallel_stack |
tf.print View source on GitHub Print the specified inputs. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.print
tf.print(
*inputs, **kwargs
)
A TensorFlow operator that prints the specified inputs to a desired output stream or logging level. The inputs may ... | tensorflow.print |
Module: tf.profiler Public API for tf.profiler namespace. Modules experimental module: Public API for tf.profiler.experimental namespace. | tensorflow.profiler |
Module: tf.profiler.experimental Public API for tf.profiler.experimental namespace. Modules client module: Public API for tf.profiler.experimental.client namespace. server module: Public API for tf.profiler.experimental.server namespace. Classes class Profile: Context-manager profile API. class ProfilerOptions: Options... | tensorflow.profiler.experimental |
Module: tf.profiler.experimental.client Public API for tf.profiler.experimental.client namespace. Functions monitor(...): Sends grpc requests to profiler server to perform on-demand monitoring. trace(...): Sends gRPC requests to one or more profiler servers to perform on-demand profiling. | tensorflow.profiler.experimental.client |
tf.profiler.experimental.client.monitor Sends grpc requests to profiler server to perform on-demand monitoring.
tf.profiler.experimental.client.monitor(
service_addr, duration_ms, level=1
)
The monitoring result is a light weight performance summary of your model execution. This method will block the caller threa... | tensorflow.profiler.experimental.client.monitor |
tf.profiler.experimental.client.trace Sends gRPC requests to one or more profiler servers to perform on-demand profiling.
tf.profiler.experimental.client.trace(
service_addr, logdir, duration_ms, worker_list='',
num_tracing_attempts=3, options=None
)
This method will block the calling thread until it receiv... | tensorflow.profiler.experimental.client.trace |
tf.profiler.experimental.Profile Context-manager profile API.
tf.profiler.experimental.Profile(
logdir, options=None
)
Profiling will start when entering the scope, and stop and save the results to the logdir when exits the scope. Open TensorBoard profile tab to view results. Example usage: with tf.profiler.exper... | tensorflow.profiler.experimental.profile |
tf.profiler.experimental.ProfilerOptions Options for finer control over the profiler.
tf.profiler.experimental.ProfilerOptions(
host_tracer_level=2, python_tracer_level=0, device_tracer_level=1, delay_ms=None
)
Use tf.profiler.ProfilerOptions to control tf.profiler behavior. Fields:
host_tracer_level: Adjust CP... | tensorflow.profiler.experimental.profileroptions |
Module: tf.profiler.experimental.server Public API for tf.profiler.experimental.server namespace. Functions start(...): Start a profiler grpc server that listens to given port. | tensorflow.profiler.experimental.server |
tf.profiler.experimental.server.start Start a profiler grpc server that listens to given port.
tf.profiler.experimental.server.start(
port
)
The profiler server will exit when the process finishes. The service is defined in tensorflow/core/profiler/profiler_service.proto.
Args
port port profiler server l... | tensorflow.profiler.experimental.server.start |
tf.profiler.experimental.start Start profiling TensorFlow performance.
tf.profiler.experimental.start(
logdir, options=None
)
Args
logdir Profiling results log directory.
options ProfilerOptions namedtuple to specify miscellaneous profiler options. See example usage below.
Raises
AlreadyE... | tensorflow.profiler.experimental.start |
tf.profiler.experimental.stop Stops the current profiling session.
tf.profiler.experimental.stop(
save=True
)
The profiler session will be stopped and profile results can be saved.
Args
save An optional variable to save the results to TensorBoard. Default True.
Raises
UnavailableError If ther... | tensorflow.profiler.experimental.stop |
tf.profiler.experimental.Trace Context manager that generates a trace event in the profiler.
tf.profiler.experimental.Trace(
name, **kwargs
)
A trace event will start when entering the context, and stop and save the result to the profiler when exiting the context. Open TensorBoard Profile tab and choose trace vie... | tensorflow.profiler.experimental.trace |
tf.py_function View source on GitHub Wraps a python function into a TensorFlow op that executes it eagerly. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.py_function
tf.py_function(
func, inp, Tout, name=None
)
This function allows expressing computations ... | tensorflow.py_function |
Module: tf.quantization Public API for tf.quantization namespace. Functions dequantize(...): Dequantize the 'input' tensor into a float or bfloat16 Tensor. fake_quant_with_min_max_args(...): Fake-quantize the 'inputs' tensor, type float to 'outputs' tensor of same type. fake_quant_with_min_max_args_gradient(...): Compu... | tensorflow.quantization |
tf.quantization.dequantize View source on GitHub Dequantize the 'input' tensor into a float or bfloat16 Tensor. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.dequantize, tf.compat.v1.quantization.dequantize
tf.quantization.dequantize(
input, min_range, max_... | tensorflow.quantization.dequantize |
tf.quantization.fake_quant_with_min_max_args Fake-quantize the 'inputs' tensor, type float to 'outputs' tensor of same type. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.fake_quant_with_min_max_args, tf.compat.v1.quantization.fake_quant_with_min_max_args
tf.quantizat... | tensorflow.quantization.fake_quant_with_min_max_args |
tf.quantization.fake_quant_with_min_max_args_gradient Compute gradients for a FakeQuantWithMinMaxArgs operation. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.fake_quant_with_min_max_args_gradient, tf.compat.v1.quantization.fake_quant_with_min_max_args_gradient
tf.qua... | tensorflow.quantization.fake_quant_with_min_max_args_gradient |
tf.quantization.fake_quant_with_min_max_vars Fake-quantize the 'inputs' tensor of type float via global float scalars View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.fake_quant_with_min_max_vars, tf.compat.v1.quantization.fake_quant_with_min_max_vars
tf.quantization.fak... | tensorflow.quantization.fake_quant_with_min_max_vars |
tf.quantization.fake_quant_with_min_max_vars_gradient Compute gradients for a FakeQuantWithMinMaxVars operation. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.fake_quant_with_min_max_vars_gradient, tf.compat.v1.quantization.fake_quant_with_min_max_vars_gradient
tf.qua... | tensorflow.quantization.fake_quant_with_min_max_vars_gradient |
tf.quantization.fake_quant_with_min_max_vars_per_channel Fake-quantize the 'inputs' tensor of type float via per-channel floats View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.fake_quant_with_min_max_vars_per_channel, tf.compat.v1.quantization.fake_quant_with_min_max_vars... | tensorflow.quantization.fake_quant_with_min_max_vars_per_channel |
tf.quantization.fake_quant_with_min_max_vars_per_channel_gradient Compute gradients for a FakeQuantWithMinMaxVarsPerChannel operation. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.fake_quant_with_min_max_vars_per_channel_gradient, tf.compat.v1.quantization.fake_quant_w... | tensorflow.quantization.fake_quant_with_min_max_vars_per_channel_gradient |
tf.quantization.quantize View source on GitHub Quantize the 'input' tensor of type float to 'output' tensor of type 'T'. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.quantization.quantize, tf.compat.v1.quantize
tf.quantization.quantize(
input, min_range, m... | tensorflow.quantization.quantize |
tf.quantization.quantized_concat Concatenates quantized tensors along one dimension. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.quantization.quantized_concat, tf.compat.v1.quantized_concat
tf.quantization.quantized_concat(
concat_dim, values, input_mins, input_... | tensorflow.quantization.quantized_concat |
tf.quantization.quantize_and_dequantize View source on GitHub Quantizes then dequantizes a tensor. (deprecated) View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.quantization.quantize_and_dequantize
tf.quantization.quantize_and_dequantize(
input, input_min, inp... | tensorflow.quantization.quantize_and_dequantize |
tf.quantization.quantize_and_dequantize_v2 Quantizes then dequantizes a tensor. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.quantization.quantize_and_dequantize_v2
tf.quantization.quantize_and_dequantize_v2(
input, input_min, input_max, signed_input=True, num_bi... | tensorflow.quantization.quantize_and_dequantize_v2 |
tf.quantize_and_dequantize_v4 Returns the gradient of QuantizeAndDequantizeV4. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.quantize_and_dequantize_v4
tf.quantize_and_dequantize_v4(
input, input_min, input_max, signed_input=True, num_bits=8, range_given=False,
... | tensorflow.quantize_and_dequantize_v4 |
Module: tf.queue Public API for tf.queue namespace. Classes class FIFOQueue: A queue implementation that dequeues elements in first-in first-out order. class PaddingFIFOQueue: A FIFOQueue that supports batching variable-sized tensors by padding. class PriorityQueue: A queue implementation that dequeues elements in prio... | tensorflow.queue |
tf.queue.FIFOQueue View source on GitHub A queue implementation that dequeues elements in first-in first-out order. Inherits From: QueueBase View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.FIFOQueue, tf.compat.v1.queue.FIFOQueue
tf.queue.FIFOQueue(
capacity, ... | tensorflow.queue.fifoqueue |
tf.queue.PaddingFIFOQueue View source on GitHub A FIFOQueue that supports batching variable-sized tensors by padding. Inherits From: QueueBase View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.PaddingFIFOQueue, tf.compat.v1.io.PaddingFIFOQueue, tf.compat.v1.queue.Pad... | tensorflow.queue.paddingfifoqueue |
tf.queue.PriorityQueue View source on GitHub A queue implementation that dequeues elements in prioritized order. Inherits From: QueueBase View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.PriorityQueue, tf.compat.v1.io.PriorityQueue, tf.compat.v1.queue.PriorityQueue ... | tensorflow.queue.priorityqueue |
tf.queue.QueueBase View source on GitHub Base class for queue implementations. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.QueueBase, tf.compat.v1.io.QueueBase, tf.compat.v1.queue.QueueBase
tf.queue.QueueBase(
dtypes, shapes, names, queue_ref
)
A queue i... | tensorflow.queue.queuebase |
tf.queue.RandomShuffleQueue View source on GitHub A queue implementation that dequeues elements in a random order. Inherits From: QueueBase View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.RandomShuffleQueue, tf.compat.v1.io.RandomShuffleQueue, tf.compat.v1.queue.Ra... | tensorflow.queue.randomshufflequeue |
Module: tf.ragged Ragged Tensors. This package defines ops for manipulating ragged tensors (tf.RaggedTensor), which are tensors with non-uniform shapes. In particular, each RaggedTensor has one or more ragged dimensions, which are dimensions whose slices may have different lengths. For example, the inner (column) dimen... | tensorflow.ragged |
tf.ragged.boolean_mask View source on GitHub Applies a boolean mask to data without flattening the mask dimensions. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.ragged.boolean_mask
tf.ragged.boolean_mask(
data, mask, name=None
)
Returns a potentially ragg... | tensorflow.ragged.boolean_mask |
tf.ragged.constant View source on GitHub Constructs a constant RaggedTensor from a nested Python list. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.ragged.constant
tf.ragged.constant(
pylist, dtype=None, ragged_rank=None, inner_shape=None, name=None,
r... | tensorflow.compat.v1.ragged.constant |
tf.ragged.constant View source on GitHub Constructs a constant RaggedTensor from a nested Python list. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.ragged.constant
tf.ragged.constant(
pylist, dtype=None, ragged_rank=None, inner_shape=None, name=None,
r... | tensorflow.ragged.constant |
tf.ragged.cross Generates feature cross from a list of tensors. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.ragged.cross
tf.ragged.cross(
inputs, name=None
)
The input tensors must have rank=2, and must all have the same number of rows. The result is a RaggedTe... | tensorflow.ragged.cross |
tf.ragged.cross_hashed Generates hashed feature cross from a list of tensors. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.ragged.cross_hashed
tf.ragged.cross_hashed(
inputs, num_buckets=0, hash_key=None, name=None
)
The input tensors must have rank=2, and must ... | tensorflow.ragged.cross_hashed |
tf.ragged.map_flat_values View source on GitHub Applies op to the values of one or more RaggedTensors. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.ragged.map_flat_values
tf.ragged.map_flat_values(
op, *args, **kwargs
)
Replaces any RaggedTensor in args o... | tensorflow.ragged.map_flat_values |
tf.ragged.range View source on GitHub Returns a RaggedTensor containing the specified sequences of numbers. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.ragged.range
tf.ragged.range(
starts, limits=None, deltas=1, dtype=None, name=None,
row_splits_dtyp... | tensorflow.ragged.range |
tf.ragged.row_splits_to_segment_ids View source on GitHub Generates the segmentation corresponding to a RaggedTensor row_splits. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.ragged.row_splits_to_segment_ids
tf.ragged.row_splits_to_segment_ids(
splits, name... | tensorflow.ragged.row_splits_to_segment_ids |
tf.ragged.segment_ids_to_row_splits View source on GitHub Generates the RaggedTensor row_splits corresponding to a segmentation. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.ragged.segment_ids_to_row_splits
tf.ragged.segment_ids_to_row_splits(
segment_ids,... | tensorflow.ragged.segment_ids_to_row_splits |
tf.ragged.stack View source on GitHub Stacks a list of rank-R tensors into one rank-(R+1) RaggedTensor. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.ragged.stack
tf.ragged.stack(
values, axis=0, name=None
)
Given a list of tensors or ragged tensors with t... | tensorflow.ragged.stack |
tf.ragged.stack_dynamic_partitions View source on GitHub Stacks dynamic partitions of a Tensor or RaggedTensor. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.ragged.stack_dynamic_partitions
tf.ragged.stack_dynamic_partitions(
data, partitions, num_partition... | tensorflow.ragged.stack_dynamic_partitions |
tf.RaggedTensor View source on GitHub Represents a ragged tensor. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.RaggedTensor A RaggedTensor is a tensor with one or more ragged dimensions, which are dimensions whose slices may have different lengths. For exampl... | tensorflow.raggedtensor |
tf.RaggedTensorSpec View source on GitHub Type specification for a tf.RaggedTensor. Inherits From: TypeSpec View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.RaggedTensorSpec
tf.RaggedTensorSpec(
shape=None, dtype=tf.dtypes.float32, ragged_rank=None,
row_sp... | tensorflow.raggedtensorspec |
Module: tf.random Public API for tf.random namespace. Modules experimental module: Public API for tf.random.experimental namespace. Classes class Algorithm: An enumeration. class Generator: Random-number generator. Functions all_candidate_sampler(...): Generate the set of all classes. categorical(...): Draws samples fr... | tensorflow.random |
tf.random.Algorithm An enumeration. View aliases Main aliases
tf.random.experimental.Algorithm Compat aliases for migration See Migration guide for more details. tf.compat.v1.random.Algorithm, tf.compat.v1.random.experimental.Algorithm
Class Variables
PHILOX tf.random.Algorithm
THREEFRY tf.random.Alg... | tensorflow.random.algorithm |
tf.random.all_candidate_sampler View source on GitHub Generate the set of all classes. View aliases Main aliases
tf.nn.all_candidate_sampler Compat aliases for migration See Migration guide for more details. tf.compat.v1.nn.all_candidate_sampler, tf.compat.v1.random.all_candidate_sampler
tf.random.all_candi... | tensorflow.random.all_candidate_sampler |
tf.random.categorical View source on GitHub Draws samples from a categorical distribution. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.random.categorical
tf.random.categorical(
logits, num_samples, dtype=None, seed=None, name=None
)
Example: # samples ha... | tensorflow.random.categorical |
tf.random.create_rng_state Creates a RNG state from an integer or a vector. View aliases Main aliases
tf.random.experimental.create_rng_state Compat aliases for migration See Migration guide for more details. tf.compat.v1.random.create_rng_state, tf.compat.v1.random.experimental.create_rng_state
tf.random.create_r... | tensorflow.random.create_rng_state |
Module: tf.random.experimental Public API for tf.random.experimental namespace. Classes class Algorithm: An enumeration. class Generator: Random-number generator. Functions create_rng_state(...): Creates a RNG state from an integer or a vector. get_global_generator(...): Retrieves the global generator. set_global_gener... | tensorflow.random.experimental |
tf.random.experimental.stateless_fold_in Folds in data to an RNG seed to form a new RNG seed. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.random.experimental.stateless_fold_in
tf.random.experimental.stateless_fold_in(
seed, data
)
For example, in a distributed-... | tensorflow.random.experimental.stateless_fold_in |
tf.random.experimental.stateless_split Splits an RNG seed into num new seeds by adding a leading axis. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.random.experimental.stateless_split
tf.random.experimental.stateless_split(
seed, num=2
)
Example:
seed = [1, 2]
... | tensorflow.random.experimental.stateless_split |
tf.random.fixed_unigram_candidate_sampler View source on GitHub Samples a set of classes using the provided (fixed) base distribution. View aliases Main aliases
tf.nn.fixed_unigram_candidate_sampler Compat aliases for migration See Migration guide for more details. tf.compat.v1.nn.fixed_unigram_candidate_samp... | tensorflow.random.fixed_unigram_candidate_sampler |
tf.random.gamma View source on GitHub Draws shape samples from each of the given Gamma distribution(s). View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.random.gamma, tf.compat.v1.random_gamma
tf.random.gamma(
shape, alpha, beta=None, dtype=tf.dtypes.float32, ... | tensorflow.random.gamma |
tf.random.Generator Random-number generator. View aliases Main aliases
tf.random.experimental.Generator Compat aliases for migration See Migration guide for more details. tf.compat.v1.random.Generator, tf.compat.v1.random.experimental.Generator
tf.random.Generator(
copy_from=None, state=None, alg=None
)
Examp... | tensorflow.random.generator |
tf.random.get_global_generator Retrieves the global generator. View aliases Main aliases
tf.random.experimental.get_global_generator Compat aliases for migration See Migration guide for more details. tf.compat.v1.random.experimental.get_global_generator, tf.compat.v1.random.get_global_generator
tf.random.get_globa... | tensorflow.random.get_global_generator |
tf.random.learned_unigram_candidate_sampler View source on GitHub Samples a set of classes from a distribution learned during training. View aliases Main aliases
tf.nn.learned_unigram_candidate_sampler Compat aliases for migration See Migration guide for more details. tf.compat.v1.nn.learned_unigram_candidate... | tensorflow.random.learned_unigram_candidate_sampler |
tf.random.log_uniform_candidate_sampler View source on GitHub Samples a set of classes using a log-uniform (Zipfian) base distribution. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.nn.log_uniform_candidate_sampler, tf.compat.v1.random.log_uniform_candidate_sampl... | tensorflow.random.log_uniform_candidate_sampler |
tf.random.normal View source on GitHub Outputs random values from a normal distribution. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.random.normal, tf.compat.v1.random_normal
tf.random.normal(
shape, mean=0.0, stddev=1.0, dtype=tf.dtypes.float32, seed=Non... | tensorflow.random.normal |
tf.random.poisson View source on GitHub Draws shape samples from each of the given Poisson distribution(s).
tf.random.poisson(
shape, lam, dtype=tf.dtypes.float32, seed=None, name=None
)
lam is the rate parameter describing the distribution(s). Example: samples = tf.random.poisson([10], [0.5, 1.5])
# sampl... | tensorflow.random.poisson |
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