doc_content stringlengths 1 386k | doc_id stringlengths 5 188 |
|---|---|
Module: tf.compat.v1.config.threading Public API for tf.config.threading namespace. Functions get_inter_op_parallelism_threads(...): Get number of threads used for parallelism between independent operations. get_intra_op_parallelism_threads(...): Get number of threads used within an individual op for parallelism. set_i... | tensorflow.compat.v1.config.threading |
tf.compat.v1.ConfigProto A ProtocolMessage
Attributes
allow_soft_placement bool allow_soft_placement
cluster_def ClusterDef cluster_def
device_count repeated DeviceCountEntry device_count
device_filters repeated string device_filters
experimental Experimental experimental
gpu_option... | tensorflow.compat.v1.configproto |
tf.compat.v1.ConfigProto.DeviceCountEntry A ProtocolMessage
Attributes
key string key
value int32 value | tensorflow.compat.v1.configproto.devicecountentry |
tf.compat.v1.ConfigProto.Experimental A ProtocolMessage
Attributes
collective_deterministic_sequential_execution bool collective_deterministic_sequential_execution
collective_group_leader string collective_group_leader
collective_nccl bool collective_nccl
disable_output_partition_graphs bool ... | tensorflow.compat.v1.configproto.experimental |
tf.compat.v1.confusion_matrix Computes the confusion matrix from predictions and labels. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.math.confusion_matrix
tf.compat.v1.confusion_matrix(
labels, predictions, num_classes=None, dtype=tf.dtypes.int32, name=None,
... | tensorflow.compat.v1.confusion_matrix |
tf.compat.v1.constant Creates a constant tensor.
tf.compat.v1.constant(
value, dtype=None, shape=None, name='Const', verify_shape=False
)
The resulting tensor is populated with values of type dtype, as specified by arguments value and (optionally) shape (see examples below). The argument value can be a constant v... | tensorflow.compat.v1.constant |
tf.compat.v1.container Wrapper for Graph.container() using the default graph.
tf.compat.v1.container(
container_name
)
Args
container_name The container string to use in the context.
Returns A context manager that specifies the default container to use for newly created stateful ops. | tensorflow.compat.v1.container |
tf.compat.v1.control_flow_v2_enabled Returns True if v2 control flow is enabled.
tf.compat.v1.control_flow_v2_enabled()
Note: v2 control flow is always enabled inside of tf.function. | tensorflow.compat.v1.control_flow_v2_enabled |
tf.compat.v1.convert_to_tensor Converts the given value to a Tensor.
tf.compat.v1.convert_to_tensor(
value, dtype=None, name=None, preferred_dtype=None, dtype_hint=None
)
This function converts Python objects of various types to Tensor objects. It accepts Tensor objects, numpy arrays, Python lists, and Python sca... | tensorflow.compat.v1.convert_to_tensor |
tf.compat.v1.convert_to_tensor_or_indexed_slices Converts the given object to a Tensor or an IndexedSlices.
tf.compat.v1.convert_to_tensor_or_indexed_slices(
value, dtype=None, name=None
)
If value is an IndexedSlices or SparseTensor it is returned unmodified. Otherwise, it is converted to a Tensor using convert_... | tensorflow.compat.v1.convert_to_tensor_or_indexed_slices |
tf.compat.v1.convert_to_tensor_or_sparse_tensor Converts value to a SparseTensor or Tensor.
tf.compat.v1.convert_to_tensor_or_sparse_tensor(
value, dtype=None, name=None
)
Args
value A SparseTensor, SparseTensorValue, or an object whose type has a registered Tensor conversion function.
dtype Option... | tensorflow.compat.v1.convert_to_tensor_or_sparse_tensor |
tf.compat.v1.count_nonzero Computes number of nonzero elements across dimensions of a tensor. (deprecated arguments) (deprecated arguments) View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.math.count_nonzero
tf.compat.v1.count_nonzero(
input_tensor=None, axis=None, k... | tensorflow.compat.v1.count_nonzero |
tf.compat.v1.count_up_to Increments 'ref' until it reaches 'limit'. (deprecated)
tf.compat.v1.count_up_to(
ref, limit, name=None
)
Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Prefer Dataset.range instead.
Args
ref A Variable. Must be one of the... | tensorflow.compat.v1.count_up_to |
tf.compat.v1.create_partitioned_variables Create a list of partitioned variables according to the given slicing. (deprecated)
tf.compat.v1.create_partitioned_variables(
shape, slicing, initializer, dtype=tf.dtypes.float32, trainable=True,
collections=None, name=None, reuse=None
)
Warning: THIS FUNCTION IS DEP... | tensorflow.compat.v1.create_partitioned_variables |
Module: tf.compat.v1.data tf.data.Dataset API for input pipelines. See Importing Data for an overview. Modules experimental module: Experimental API for building input pipelines. Classes class Dataset: Represents a potentially large set of elements. class DatasetSpec: Type specification for tf.data.Dataset. class Fixed... | tensorflow.compat.v1.data |
tf.compat.v1.data.Dataset Represents a potentially large set of elements. Inherits From: Dataset
tf.compat.v1.data.Dataset()
A Dataset can be used to represent an input pipeline as a collection of elements and a "logical plan" of transformations that act on those elements.
Args
variant_tensor A DT_VARIANT te... | tensorflow.compat.v1.data.dataset |
Module: tf.compat.v1.data.experimental Experimental API for building input pipelines. This module contains experimental Dataset sources and transformations that can be used in conjunction with the tf.data.Dataset API. Note that the tf.data.experimental API is not subject to the same backwards compatibility guarantees a... | tensorflow.compat.v1.data.experimental |
tf.compat.v1.data.experimental.choose_from_datasets Creates a dataset that deterministically chooses elements from datasets.
tf.compat.v1.data.experimental.choose_from_datasets(
datasets, choice_dataset
)
For example, given the following datasets: datasets = [tf.data.Dataset.from_tensors("foo").repeat(),
... | tensorflow.compat.v1.data.experimental.choose_from_datasets |
tf.compat.v1.data.experimental.Counter Creates a Dataset that counts from start in steps of size step.
tf.compat.v1.data.experimental.Counter(
start=0, step=1, dtype=tf.dtypes.int64
)
For example: Dataset.count() == [0, 1, 2, ...)
Dataset.count(2) == [2, 3, ...)
Dataset.count(2, 5) == [2, 7, 12, ...)
Dataset.coun... | tensorflow.compat.v1.data.experimental.counter |
tf.compat.v1.data.experimental.CsvDataset A Dataset comprising lines from one or more CSV files. Inherits From: Dataset, Dataset
tf.compat.v1.data.experimental.CsvDataset(
filenames, record_defaults, compression_type=None, buffer_size=None,
header=False, field_delim=',', use_quote_delim=True,
na_value='', ... | tensorflow.compat.v1.data.experimental.csvdataset |
tf.compat.v1.data.experimental.make_batched_features_dataset Returns a Dataset of feature dictionaries from Example protos.
tf.compat.v1.data.experimental.make_batched_features_dataset(
file_pattern, batch_size, features, reader=None, label_key=None,
reader_args=None, num_epochs=None, shuffle=True, shuffle_buf... | tensorflow.compat.v1.data.experimental.make_batched_features_dataset |
tf.compat.v1.data.experimental.make_csv_dataset Reads CSV files into a dataset.
tf.compat.v1.data.experimental.make_csv_dataset(
file_pattern, batch_size, column_names=None, column_defaults=None,
label_name=None, select_columns=None, field_delim=',',
use_quote_delim=True, na_value='', header=True, num_epoc... | tensorflow.compat.v1.data.experimental.make_csv_dataset |
tf.compat.v1.data.experimental.map_and_batch_with_legacy_function Fused implementation of map and batch. (deprecated)
tf.compat.v1.data.experimental.map_and_batch_with_legacy_function(
map_func, batch_size, num_parallel_batches=None, drop_remainder=False,
num_parallel_calls=None
)
Warning: THIS FUNCTION IS DE... | tensorflow.compat.v1.data.experimental.map_and_batch_with_legacy_function |
tf.compat.v1.data.experimental.RaggedTensorStructure DEPRECATED FUNCTION
tf.compat.v1.data.experimental.RaggedTensorStructure(
dtype, shape, ragged_rank
)
Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Use tf.RaggedTensorSpec instead. | tensorflow.compat.v1.data.experimental.raggedtensorstructure |
tf.compat.v1.data.experimental.RandomDataset A Dataset of pseudorandom values. Inherits From: Dataset, Dataset
tf.compat.v1.data.experimental.RandomDataset(
seed=None
)
Attributes
element_spec The type specification of an element of this dataset.
dataset = tf.data.Dataset.from_tensor_slices([1, 2, 3])
d... | tensorflow.compat.v1.data.experimental.randomdataset |
tf.compat.v1.data.experimental.sample_from_datasets Samples elements at random from the datasets in datasets.
tf.compat.v1.data.experimental.sample_from_datasets(
datasets, weights=None, seed=None
)
Args
datasets A list of tf.data.Dataset objects with compatible structure.
weights (Optional.) A lis... | tensorflow.compat.v1.data.experimental.sample_from_datasets |
Module: tf.compat.v1.data.experimental.service API for using the tf.data service. This module contains: tf.data server implementations for running the tf.data service. A distribute dataset transformation that moves a dataset's preprocessing to happen in the tf.data service. The tf.data service offers a way to improve... | tensorflow.compat.v1.data.experimental.service |
tf.compat.v1.data.experimental.SparseTensorStructure DEPRECATED FUNCTION
tf.compat.v1.data.experimental.SparseTensorStructure(
dtype, shape
)
Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Use tf.SparseTensorSpec instead. | tensorflow.compat.v1.data.experimental.sparsetensorstructure |
tf.compat.v1.data.experimental.SqlDataset A Dataset consisting of the results from a SQL query. Inherits From: Dataset, Dataset
tf.compat.v1.data.experimental.SqlDataset(
driver_name, data_source_name, query, output_types
)
Args
driver_name A 0-D tf.string tensor containing the database type. Currently, ... | tensorflow.compat.v1.data.experimental.sqldataset |
tf.compat.v1.data.experimental.StatsAggregator A stateful resource that aggregates statistics from one or more iterators.
tf.compat.v1.data.experimental.StatsAggregator()
To record statistics, use one of the custom transformation functions defined in this module when defining your tf.data.Dataset. All statistics will... | tensorflow.compat.v1.data.experimental.statsaggregator |
tf.compat.v1.data.experimental.TensorArrayStructure DEPRECATED FUNCTION
tf.compat.v1.data.experimental.TensorArrayStructure(
dtype, element_shape, dynamic_size, infer_shape
)
Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Use tf.TensorArraySpec instead. | tensorflow.compat.v1.data.experimental.tensorarraystructure |
tf.compat.v1.data.experimental.TensorStructure DEPRECATED FUNCTION
tf.compat.v1.data.experimental.TensorStructure(
dtype, shape
)
Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Use tf.TensorSpec instead. | tensorflow.compat.v1.data.experimental.tensorstructure |
tf.compat.v1.data.FixedLengthRecordDataset A Dataset of fixed-length records from one or more binary files. Inherits From: Dataset, Dataset
tf.compat.v1.data.FixedLengthRecordDataset(
filenames, record_bytes, header_bytes=None, footer_bytes=None, buffer_size=None,
compression_type=None, num_parallel_reads=None... | tensorflow.compat.v1.data.fixedlengthrecorddataset |
tf.compat.v1.data.get_output_classes Returns the output classes for elements of the input dataset / iterator.
tf.compat.v1.data.get_output_classes(
dataset_or_iterator
)
Args
dataset_or_iterator A tf.data.Dataset or tf.data.Iterator.
Returns A nested structure of Python type objects matching th... | tensorflow.compat.v1.data.get_output_classes |
tf.compat.v1.data.get_output_shapes Returns the output shapes for elements of the input dataset / iterator.
tf.compat.v1.data.get_output_shapes(
dataset_or_iterator
)
Args
dataset_or_iterator A tf.data.Dataset or tf.data.Iterator.
Returns A nested structure of tf.TensorShape objects matching th... | tensorflow.compat.v1.data.get_output_shapes |
tf.compat.v1.data.get_output_types Returns the output shapes for elements of the input dataset / iterator.
tf.compat.v1.data.get_output_types(
dataset_or_iterator
)
Args
dataset_or_iterator A tf.data.Dataset or tf.data.Iterator.
Returns A nested structure of tf.DType objects objects matching th... | tensorflow.compat.v1.data.get_output_types |
tf.compat.v1.data.Iterator Represents the state of iterating through a Dataset.
tf.compat.v1.data.Iterator(
iterator_resource, initializer, output_types, output_shapes, output_classes
)
Args
iterator_resource A tf.resource scalar tf.Tensor representing the iterator.
initializer A tf.Operation that ... | tensorflow.compat.v1.data.iterator |
tf.compat.v1.data.make_initializable_iterator Creates an iterator for elements of dataset.
tf.compat.v1.data.make_initializable_iterator(
dataset, shared_name=None
)
Note: The returned iterator will be in an uninitialized state, and you must run the iterator.initializer operation before using it:
dataset = ...
... | tensorflow.compat.v1.data.make_initializable_iterator |
tf.compat.v1.data.make_one_shot_iterator Creates an iterator for elements of dataset.
tf.compat.v1.data.make_one_shot_iterator(
dataset
)
Note: The returned iterator will be initialized automatically. A "one-shot" iterator does not support re-initialization.
Args
dataset A tf.data.Dataset.
Retu... | tensorflow.compat.v1.data.make_one_shot_iterator |
tf.compat.v1.data.TextLineDataset A Dataset comprising lines from one or more text files. Inherits From: Dataset, Dataset
tf.compat.v1.data.TextLineDataset(
filenames, compression_type=None, buffer_size=None, num_parallel_reads=None
)
Args
filenames A tf.string tensor or tf.data.Dataset containing one or... | tensorflow.compat.v1.data.textlinedataset |
tf.compat.v1.data.TFRecordDataset A Dataset comprising records from one or more TFRecord files. Inherits From: Dataset, Dataset
tf.compat.v1.data.TFRecordDataset(
filenames, compression_type=None, buffer_size=None, num_parallel_reads=None
)
Args
filenames A tf.string tensor or tf.data.Dataset containing ... | tensorflow.compat.v1.data.tfrecorddataset |
Module: tf.compat.v1.debugging Public API for tf.debugging namespace. Modules experimental module: Public API for tf.debugging.experimental namespace. Functions Assert(...): Asserts that the given condition is true. assert_all_finite(...): Assert that the tensor does not contain any NaN's or Inf's. assert_equal(...): A... | tensorflow.compat.v1.debugging |
tf.compat.v1.debugging.assert_shapes Assert tensor shapes and dimension size relationships between tensors.
tf.compat.v1.debugging.assert_shapes(
shapes, data=None, summarize=None, message=None, name=None
)
This Op checks that a collection of tensors shape relationships satisfies given constraints. Example:
n = ... | tensorflow.compat.v1.debugging.assert_shapes |
Module: tf.compat.v1.debugging.experimental Public API for tf.debugging.experimental namespace. Functions disable_dump_debug_info(...): Disable the currently-enabled debugging dumping. enable_dump_debug_info(...): Enable dumping debugging information from a TensorFlow program. | tensorflow.compat.v1.debugging.experimental |
tf.compat.v1.decode_csv Convert CSV records to tensors. Each column maps to one tensor. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.io.decode_csv
tf.compat.v1.decode_csv(
records, record_defaults, field_delim=',', use_quote_delim=True,
name=None, na_value=''... | tensorflow.compat.v1.decode_csv |
tf.compat.v1.decode_raw Convert raw byte strings into tensors. (deprecated arguments) View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.io.decode_raw
tf.compat.v1.decode_raw(
input_bytes=None, out_type=None, little_endian=True, name=None, bytes=None
)
Warning: SOME A... | tensorflow.compat.v1.decode_raw |
tf.compat.v1.delete_session_tensor Delete the tensor for the given tensor handle.
tf.compat.v1.delete_session_tensor(
handle, name=None
)
This is EXPERIMENTAL and subject to change. Delete the tensor of a given tensor handle. The tensor is produced in a previous run() and stored in the state of the session.
... | tensorflow.compat.v1.delete_session_tensor |
tf.compat.v1.depth_to_space DepthToSpace for tensors of type T. View aliases Compat aliases for migration
See Migration guide for more details. tf.compat.v1.nn.depth_to_space
tf.compat.v1.depth_to_space(
input, block_size, name=None, data_format='NHWC'
)
Rearranges data from depth into blocks of spatial data.... | tensorflow.compat.v1.depth_to_space |
tf.compat.v1.device Wrapper for Graph.device() using the default graph.
tf.compat.v1.device(
device_name_or_function
)
See tf.Graph.device for more details.
Args
device_name_or_function The device name or function to use in the context.
Returns A context manager that specifies the default devic... | tensorflow.compat.v1.device |
tf.compat.v1.DeviceSpec Represents a (possibly partial) specification for a TensorFlow device. Inherits From: DeviceSpec
tf.compat.v1.DeviceSpec(
job=None, replica=None, task=None, device_type=None, device_index=None
)
DeviceSpecs are used throughout TensorFlow to describe where state is stored and computations o... | tensorflow.compat.v1.devicespec |
tf.compat.v1.Dimension Represents the value of one dimension in a TensorShape.
tf.compat.v1.Dimension(
value
)
Attributes
value The value of this dimension, or None if it is unknown. Methods assert_is_compatible_with View source
assert_is_compatible_with(
other
)
Raises an exception if other is ... | tensorflow.compat.v1.dimension |
tf.compat.v1.disable_control_flow_v2 Opts out of control flow v2.
tf.compat.v1.disable_control_flow_v2()
Note: v2 control flow is always enabled inside of tf.function. Calling this function has no effect in that case.
If your code needs tf.disable_control_flow_v2() to be called to work properly please file a bug. | tensorflow.compat.v1.disable_control_flow_v2 |
tf.compat.v1.disable_eager_execution Disables eager execution.
tf.compat.v1.disable_eager_execution()
This function can only be called before any Graphs, Ops, or Tensors have been created. It can be used at the beginning of the program for complex migration projects from TensorFlow 1.x to 2.x. | tensorflow.compat.v1.disable_eager_execution |
tf.compat.v1.disable_resource_variables Opts out of resource variables. (deprecated)
tf.compat.v1.disable_resource_variables()
Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: non-resource variables are not supported in the long term If your code needs tf.disabl... | tensorflow.compat.v1.disable_resource_variables |
tf.compat.v1.disable_tensor_equality Compare Tensors by their id and be hashable.
tf.compat.v1.disable_tensor_equality()
This is a legacy behaviour of TensorFlow and is highly discouraged. | tensorflow.compat.v1.disable_tensor_equality |
tf.compat.v1.disable_v2_behavior Disables TensorFlow 2.x behaviors.
tf.compat.v1.disable_v2_behavior()
This function can be called at the beginning of the program (before Tensors, Graphs or other structures have been created, and before devices have been initialized. It switches all global behaviors that are differen... | tensorflow.compat.v1.disable_v2_behavior |
tf.compat.v1.disable_v2_tensorshape Disables the V2 TensorShape behavior and reverts to V1 behavior.
tf.compat.v1.disable_v2_tensorshape()
See docstring for enable_v2_tensorshape for details about the new behavior. | tensorflow.compat.v1.disable_v2_tensorshape |
Module: tf.compat.v1.distribute Library for running a computation across multiple devices. The intent of this library is that you can write an algorithm in a stylized way and it will be usable with a variety of different tf.distribute.Strategy implementations. Each descendant will implement a different strategy for dis... | tensorflow.compat.v1.distribute |
Module: tf.compat.v1.distribute.cluster_resolver Library imports for ClusterResolvers. This library contains all implementations of ClusterResolvers. ClusterResolvers are a way of specifying cluster information for distributed execution. Built on top of existing ClusterSpec framework, ClusterResolvers are a way for Ten... | tensorflow.compat.v1.distribute.cluster_resolver |
Module: tf.compat.v1.distribute.experimental Public API for tf.distribute.experimental namespace. Classes class CentralStorageStrategy: A one-machine strategy that puts all variables on a single device. class CollectiveCommunication: Cross device communication implementation. class CollectiveHints: Hints for collective... | tensorflow.compat.v1.distribute.experimental |
tf.compat.v1.distribute.experimental.CentralStorageStrategy A one-machine strategy that puts all variables on a single device. Inherits From: Strategy
tf.compat.v1.distribute.experimental.CentralStorageStrategy(
compute_devices=None, parameter_device=None
)
Variables are assigned to local CPU or the only GPU. If ... | tensorflow.compat.v1.distribute.experimental.centralstoragestrategy |
tf.compat.v1.distribute.experimental.MultiWorkerMirroredStrategy A distribution strategy for synchronous training on multiple workers. Inherits From: Strategy
tf.compat.v1.distribute.experimental.MultiWorkerMirroredStrategy(
communication=tf.distribute.experimental.CollectiveCommunication.AUTO,
cluster_resolve... | tensorflow.compat.v1.distribute.experimental.multiworkermirroredstrategy |
tf.compat.v1.distribute.experimental.ParameterServerStrategy An asynchronous multi-worker parameter server tf.distribute strategy. Inherits From: Strategy
tf.compat.v1.distribute.experimental.ParameterServerStrategy(
cluster_resolver=None
)
This strategy requires two roles: workers and parameter servers. Variable... | tensorflow.compat.v1.distribute.experimental.parameterserverstrategy |
tf.compat.v1.distribute.experimental.TPUStrategy TPU distribution strategy implementation. Inherits From: Strategy
tf.compat.v1.distribute.experimental.TPUStrategy(
tpu_cluster_resolver=None, steps_per_run=None, device_assignment=None
)
Args
tpu_cluster_resolver A tf.distribute.cluster_resolver.TPUCluste... | tensorflow.compat.v1.distribute.experimental.tpustrategy |
tf.compat.v1.distribute.get_loss_reduction tf.distribute.ReduceOp corresponding to the last loss reduction.
tf.compat.v1.distribute.get_loss_reduction()
This is used to decide whether loss should be scaled in optimizer (used only for estimator + v1 optimizer use case).
Returns tf.distribute.ReduceOp correspond... | tensorflow.compat.v1.distribute.get_loss_reduction |
tf.compat.v1.distribute.MirroredStrategy Synchronous training across multiple replicas on one machine. Inherits From: Strategy
tf.compat.v1.distribute.MirroredStrategy(
devices=None, cross_device_ops=None
)
This strategy is typically used for training on one machine with multiple GPUs. For TPUs, use tf.distribute... | tensorflow.compat.v1.distribute.mirroredstrategy |
tf.compat.v1.distribute.OneDeviceStrategy A distribution strategy for running on a single device. Inherits From: Strategy
tf.compat.v1.distribute.OneDeviceStrategy(
device
)
Using this strategy will place any variables created in its scope on the specified device. Input distributed through this strategy will be p... | tensorflow.compat.v1.distribute.onedevicestrategy |
tf.compat.v1.distribute.ReplicaContext A class with a collection of APIs that can be called in a replica context.
tf.compat.v1.distribute.ReplicaContext(
strategy, replica_id_in_sync_group
)
You can use tf.distribute.get_replica_context to get an instance of ReplicaContext, which can only be called inside the fun... | tensorflow.compat.v1.distribute.replicacontext |
tf.compat.v1.distribute.Strategy A list of devices with a state & compute distribution policy.
tf.compat.v1.distribute.Strategy(
extended
)
See the guide for overview and examples.
Note: Not all tf.distribute.Strategy implementations currently support TensorFlow's partitioned variables (where a single variable i... | tensorflow.compat.v1.distribute.strategy |
tf.compat.v1.distribute.StrategyExtended Additional APIs for algorithms that need to be distribution-aware. Inherits From: StrategyExtended
tf.compat.v1.distribute.StrategyExtended(
container_strategy
)
Note: For most usage of tf.distribute.Strategy, there should be no need to call these methods, since TensorFlo... | tensorflow.compat.v1.distribute.strategyextended |
Module: tf.compat.v1.distributions Core module for TensorFlow distribution objects and helpers. Classes class Bernoulli: Bernoulli distribution. class Beta: Beta distribution. class Categorical: Categorical distribution. class Dirichlet: Dirichlet distribution. class DirichletMultinomial: Dirichlet-Multinomial compound... | tensorflow.compat.v1.distributions |
tf.compat.v1.distributions.Bernoulli Bernoulli distribution. Inherits From: Distribution
tf.compat.v1.distributions.Bernoulli(
logits=None, probs=None, dtype=tf.dtypes.int32, validate_args=False,
allow_nan_stats=True, name='Bernoulli'
)
The Bernoulli distribution with probs parameter, i.e., the probability of... | tensorflow.compat.v1.distributions.bernoulli |
tf.compat.v1.distributions.Beta Beta distribution. Inherits From: Distribution
tf.compat.v1.distributions.Beta(
concentration1=None, concentration0=None, validate_args=False,
allow_nan_stats=True, name='Beta'
)
The Beta distribution is defined over the (0, 1) interval using parameters concentration1 (aka "alp... | tensorflow.compat.v1.distributions.beta |
tf.compat.v1.distributions.Categorical Categorical distribution. Inherits From: Distribution
tf.compat.v1.distributions.Categorical(
logits=None, probs=None, dtype=tf.dtypes.int32, validate_args=False,
allow_nan_stats=True, name='Categorical'
)
The Categorical distribution is parameterized by either probabili... | tensorflow.compat.v1.distributions.categorical |
tf.compat.v1.distributions.Dirichlet Dirichlet distribution. Inherits From: Distribution
tf.compat.v1.distributions.Dirichlet(
concentration, validate_args=False, allow_nan_stats=True,
name='Dirichlet'
)
The Dirichlet distribution is defined over the (k-1)-simplex using a positive, length-k vector concentrati... | tensorflow.compat.v1.distributions.dirichlet |
tf.compat.v1.distributions.DirichletMultinomial Dirichlet-Multinomial compound distribution. Inherits From: Distribution
tf.compat.v1.distributions.DirichletMultinomial(
total_count, concentration, validate_args=False, allow_nan_stats=True,
name='DirichletMultinomial'
)
The Dirichlet-Multinomial distribution ... | tensorflow.compat.v1.distributions.dirichletmultinomial |
tf.compat.v1.distributions.Distribution A generic probability distribution base class.
tf.compat.v1.distributions.Distribution(
dtype, reparameterization_type, validate_args, allow_nan_stats, parameters=None,
graph_parents=None, name=None
)
Distribution is a base class for constructing and organizing properti... | tensorflow.compat.v1.distributions.distribution |
tf.compat.v1.distributions.Exponential Exponential distribution. Inherits From: Gamma, Distribution
tf.compat.v1.distributions.Exponential(
rate, validate_args=False, allow_nan_stats=True, name='Exponential'
)
The Exponential distribution is parameterized by an event rate parameter. Mathematical Details The proba... | tensorflow.compat.v1.distributions.exponential |
tf.compat.v1.distributions.Gamma Gamma distribution. Inherits From: Distribution
tf.compat.v1.distributions.Gamma(
concentration, rate, validate_args=False, allow_nan_stats=True,
name='Gamma'
)
The Gamma distribution is defined over positive real numbers using parameters concentration (aka "alpha") and rate (... | tensorflow.compat.v1.distributions.gamma |
tf.compat.v1.distributions.kl_divergence Get the KL-divergence KL(distribution_a || distribution_b). (deprecated)
tf.compat.v1.distributions.kl_divergence(
distribution_a, distribution_b, allow_nan_stats=True, name=None
)
Warning: THIS FUNCTION IS DEPRECATED. It will be removed after 2019-01-01. Instructions for ... | tensorflow.compat.v1.distributions.kl_divergence |
tf.compat.v1.distributions.Laplace The Laplace distribution with location loc and scale parameters. Inherits From: Distribution
tf.compat.v1.distributions.Laplace(
loc, scale, validate_args=False, allow_nan_stats=True, name='Laplace'
)
Mathematical details The probability density function (pdf) of this distributi... | tensorflow.compat.v1.distributions.laplace |
tf.compat.v1.distributions.Multinomial Multinomial distribution. Inherits From: Distribution
tf.compat.v1.distributions.Multinomial(
total_count, logits=None, probs=None, validate_args=False, allow_nan_stats=True,
name='Multinomial'
)
This Multinomial distribution is parameterized by probs, a (batch of) lengt... | tensorflow.compat.v1.distributions.multinomial |
tf.compat.v1.distributions.Normal The Normal distribution with location loc and scale parameters. Inherits From: Distribution
tf.compat.v1.distributions.Normal(
loc, scale, validate_args=False, allow_nan_stats=True, name='Normal'
)
Mathematical details The probability density function (pdf) is, pdf(x; mu, sigma) ... | tensorflow.compat.v1.distributions.normal |
tf.compat.v1.distributions.RegisterKL Decorator to register a KL divergence implementation function.
tf.compat.v1.distributions.RegisterKL(
dist_cls_a, dist_cls_b
)
Usage: @distributions.RegisterKL(distributions.Normal, distributions.Normal) def _kl_normal_mvn(norm_a, norm_b): # Return KL(norm_a || norm_b)
A... | tensorflow.compat.v1.distributions.registerkl |
tf.compat.v1.distributions.ReparameterizationType Instances of this class represent how sampling is reparameterized.
tf.compat.v1.distributions.ReparameterizationType(
rep_type
)
Two static instances exist in the distributions library, signifying one of two possible properties for samples from a distribution: FUL... | tensorflow.compat.v1.distributions.reparameterizationtype |
tf.compat.v1.distributions.StudentT Student's t-distribution. Inherits From: Distribution
tf.compat.v1.distributions.StudentT(
df, loc, scale, validate_args=False, allow_nan_stats=True,
name='StudentT'
)
This distribution has parameters: degree of freedom df, location loc, and scale. Mathematical details The ... | tensorflow.compat.v1.distributions.studentt |
tf.compat.v1.distributions.Uniform Uniform distribution with low and high parameters. Inherits From: Distribution
tf.compat.v1.distributions.Uniform(
low=0.0, high=1.0, validate_args=False, allow_nan_stats=True,
name='Uniform'
)
Mathematical Details The probability density function (pdf) is, pdf(x; a, b) = I[... | tensorflow.compat.v1.distributions.uniform |
Module: tf.compat.v1.dtypes Public API for tf.dtypes namespace. Classes class DType: Represents the type of the elements in a Tensor. Functions as_dtype(...): Converts the given type_value to a DType. as_string(...): Converts each entry in the given tensor to strings. cast(...): Casts a tensor to a new type. complex(..... | tensorflow.compat.v1.dtypes |
tf.compat.v1.enable_control_flow_v2 Use control flow v2.
tf.compat.v1.enable_control_flow_v2()
control flow v2 (cfv2) is an improved version of control flow in TensorFlow with support for higher order derivatives. Enabling cfv2 will change the graph/function representation of control flow, e.g., tf.while_loop and tf.... | tensorflow.compat.v1.enable_control_flow_v2 |
tf.compat.v1.enable_eager_execution Enables eager execution for the lifetime of this program.
tf.compat.v1.enable_eager_execution(
config=None, device_policy=None, execution_mode=None
)
Eager execution provides an imperative interface to TensorFlow. With eager execution enabled, TensorFlow functions execute opera... | tensorflow.compat.v1.enable_eager_execution |
tf.compat.v1.enable_resource_variables Creates resource variables by default.
tf.compat.v1.enable_resource_variables()
Resource variables are improved versions of TensorFlow variables with a well-defined memory model. Accessing a resource variable reads its value, and all ops which access a specific read value of the... | tensorflow.compat.v1.enable_resource_variables |
tf.compat.v1.enable_tensor_equality Compare Tensors with element-wise comparison and thus be unhashable.
tf.compat.v1.enable_tensor_equality()
Comparing tensors with element-wise allows comparisons such as tf.Variable(1.0) == 1.0. Element-wise equality implies that tensors are unhashable. Thus tensors can no longer b... | tensorflow.compat.v1.enable_tensor_equality |
tf.compat.v1.enable_v2_behavior Enables TensorFlow 2.x behaviors.
tf.compat.v1.enable_v2_behavior()
This function can be called at the beginning of the program (before Tensors, Graphs or other structures have been created, and before devices have been initialized. It switches all global behaviors that are different b... | tensorflow.compat.v1.enable_v2_behavior |
tf.compat.v1.enable_v2_tensorshape In TensorFlow 2.0, iterating over a TensorShape instance returns values.
tf.compat.v1.enable_v2_tensorshape()
This enables the new behavior. Concretely, tensor_shape[i] returned a Dimension instance in V1, but it V2 it returns either an integer, or None. Examples: ##################... | tensorflow.compat.v1.enable_v2_tensorshape |
Module: tf.compat.v1.errors Exception types for TensorFlow errors. Classes class AbortedError: The operation was aborted, typically due to a concurrent action. class AlreadyExistsError: Raised when an entity that we attempted to create already exists. class CancelledError: Raised when an operation or step is cancelled.... | tensorflow.compat.v1.errors |
tf.compat.v1.errors.error_code_from_exception_type
tf.compat.v1.errors.error_code_from_exception_type() | tensorflow.compat.v1.errors.error_code_from_exception_type |
tf.compat.v1.errors.exception_type_from_error_code
tf.compat.v1.errors.exception_type_from_error_code(
error_code
) | tensorflow.compat.v1.errors.exception_type_from_error_code |
tf.compat.v1.errors.raise_exception_on_not_ok_status Context manager to check for C API status. Methods __enter__ View source
__enter__()
__exit__ View source
__exit__(
type_arg, value_arg, traceback_arg
) | tensorflow.compat.v1.errors.raise_exception_on_not_ok_status |
Module: tf.compat.v1.estimator Estimator: High level tools for working with models. Modules experimental module: Public API for tf.estimator.experimental namespace. export module: All public utility methods for exporting Estimator to SavedModel. inputs module: Utility methods to create simple input_fns. tpu module: Pub... | tensorflow.compat.v1.estimator |
tf.compat.v1.estimator.BaselineClassifier A classifier that can establish a simple baseline. Inherits From: Estimator
tf.compat.v1.estimator.BaselineClassifier(
model_dir=None, n_classes=2, weight_column=None, label_vocabulary=None,
optimizer='Ftrl', config=None,
loss_reduction=tf.compat.v1.losses.Reductio... | tensorflow.compat.v1.estimator.baselineclassifier |
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