tensorflow の API リファレンス

tensorflow (tensorflow/tensorflow) の公開 API 400 件 —— クラス 243、関数 78、メソッド 79。実際のソースを静的解析して抽出した正確なシグネチャを掲載しています。

種別	件数
クラス	243
関数	78
メソッド	79

API 一覧

funcci.official.utilities.extract_resultstore_links.parse_args() -> argparse.Namespace

Parses the commandline args.

funcconfigure.configure_ios(environ_cp)

Configures TensorFlow for iOS builds.

funcconfigure.cygpath(path)

Convert path from posix to windows.

funcconfigure.get_python_major_version(python_bin_path)

Get the python major version.

funcconfigure.get_python_path(environ_cp, python_bin_path)

Get the python site package paths.

funcconfigure.retrieve_clang_version(clang_executable)

Retrieve installed clang version.

funcconfigure.set_clang_cuda_compiler_path(environ_cp)

Set CLANG_CUDA_COMPILER_PATH.

funcconfigure.set_gcc_host_compiler_path(environ_cp)

Set GCC_HOST_COMPILER_PATH.

funcconfigure.set_hermetic_cuda_version(environ_cp)

Set HERMETIC_CUDA_VERSION.

funcconfigure.set_hermetic_cudnn_version(environ_cp)

Set HERMETIC_CUDNN_VERSION.

funcconfigure.set_other_cuda_vars(environ_cp)

Set other CUDA related variables.

funcconfigure.set_system_libs_flag(environ_cp)

Set system libs flags.

funcconfigure.set_tf_cuda_clang(environ_cp)

set TF_CUDA_CLANG action_env.

funcconfigure.set_tf_download_clang(environ_cp)

Set TF_DOWNLOAD_CLANG action_env.

funcconfigure.set_windows_build_flags(environ_cp)

Set Windows specific build options.

funcconfigure.setup_python(environ_cp)

Setup python related env variables.

funcconfigure.symlink_force(target, link_name)

Force symlink, equivalent of 'ln -sf'.

classtensorflow.c.experimental.saved_model.internal.testdata.gen_saved_models.Module

A module with an UninitializedVariable.

classtensorflow.c.experimental.saved_model.internal.testdata.gen_saved_models.SubModule

A module with an UninitializedVariable.

functensorflow.compiler.mlir.quantization.common.python.testing.get_size_ratio(path_a:str, path_b:str) -> float

Return the size ratio of the given paths.

class

tensorflow.compiler.mlir.quantization.stablehlo.python.integration_test.quantize_model_test_base.QuantizedModelTest.EinsumModel

Einsum class.

func

tensorflow.compiler.mlir.quantization.stablehlo.python.quantization.quantize_saved_model(src_saved_model_path:str, dst_saved_model_path:str, config:qc.QuantizationConfig) -> None

Quantizes a saved model.

class

tensorflow.compiler.mlir.quantization.tensorflow.python.integration_test.quantize_model_test_base.QuantizedModelTest.EinsumModel

Einsum class.

class

tensorflow.compiler.mlir.quantization.tensorflow.python.integration_test.quantize_model_test_base.QuantizedModelTest.WhileModel

A model with a while op.

classtensorflow.compiler.mlir.quantization.tensorflow.python.representative_dataset.RepresentativeDatasetLoader

Representative dataset loader.

classtensorflow.compiler.mlir.quantization.tensorflow.python.representative_dataset.RepresentativeDatasetSaver

Representative dataset saver.

func

tensorflow.compiler.mlir.quantization.tensorflow.python.representative_dataset.get_num_samples(repr_ds:RepresentativeDataset) -> Optional[int]

Returns the number of samples if known.

func

tensorflow.compiler.mlir.quantization.tensorflow.python.save_model.create_empty_output_dir(output_directory:str, overwrite:bool=True) -> None

Creates the `output_directory`.

classtensorflow.compiler.mlir.tfr.python.tfr_gen.SymbolTable

Symbol Table for python code.

classtensorflow.compiler.mlir.tfr.python.tfr_gen.TFRGen

Visit the AST and generate MLIR TFR functions.

classtensorflow.compiler.mlir.tfr.python.tfr_gen.TFRTypes

All the supported types.

classtensorflow.compiler.mlir.tfr.python.tfr_gen.TfrGen

Transforms Python objects into TFR MLIR source code.

classtensorflow.core.function.capture.capture_container.MutationAwareDict

A dict with a mutation flag.

classtensorflow.core.function.polymorphism.function_cache.FunctionCache

A container for managing functions.

method

tensorflow.core.function.polymorphism.function_cache.FunctionCache.add(fn:Any, context:Optional[FunctionContext]=None) -> None

Adds a new function using its function_type.

methodtensorflow.core.function.polymorphism.function_cache.FunctionCache.values()

Returns a list of all functions held by this cache.

classtensorflow.core.function.polymorphism.function_type.FunctionType

Represents the type of a TensorFlow function.

method

tensorflow.core.function.polymorphism.function_type.FunctionType.most_specific_common_subtype(others:Sequence['FunctionType']) -> Optional['FunctionType']

Returns a common subtype (if exists).

methodtensorflow.core.function.polymorphism.function_type.FunctionType.unpack_captures(captures) -> List[core.Tensor]

Unpacks captures to flat tensors.

classtensorflow.core.function.polymorphism.function_type.Parameter

Represents a parameter to a function.

methodtensorflow.core.function.polymorphism.function_type.Parameter.from_proto(proto:Any) -> 'Parameter'

Generate a Parameter from the proto representation.

methodtensorflow.core.function.polymorphism.function_type.Parameter.is_subtype_of(other:'Parameter') -> bool

Returns True if self is a supertype of other Parameter.

method

tensorflow.core.function.polymorphism.function_type.Parameter.most_specific_common_supertype(others:Sequence['Parameter']) -> Optional['Parameter']

Returns a common supertype (if exists).

functensorflow.core.function.polymorphism.function_type.sanitize_arg_name(name:str) -> str

Sanitizes function argument names.

classtensorflow.core.function.polymorphism.type_dispatch.TypeDispatchTable

Type dispatch table implementation.

method

tensorflow.core.function.polymorphism.type_dispatch.TypeDispatchTable.add_target(target:function_type.FunctionType) -> None

Adds a new target type.

methodtensorflow.core.function.polymorphism.type_dispatch.TypeDispatchTable.clear() -> None

Deletes all targets in the table.

methodtensorflow.core.function.polymorphism.type_dispatch.TypeDispatchTable.delete(target:function_type.FunctionType) -> None

Deletes a target in the table if it exists.

classtensorflow.core.function.trace_type.default_types.Attrs

Represents a class annotated by attr.s.

method

tensorflow.core.function.trace_type.default_types.Attrs.most_specific_common_supertype(others:Sequence[trace.TraceType]) -> Optional['Attrs']

See base class.

classtensorflow.core.function.trace_type.default_types.Dict

Represents a dictionary of TraceType objects.

methodtensorflow.core.function.trace_type.default_types.Dict.is_subtype_of(other:trace.TraceType) -> bool

See base class.

method

tensorflow.core.function.trace_type.default_types.Dict.most_specific_common_supertype(types:Sequence[trace.TraceType]) -> Optional['Dict']

See base class.

classtensorflow.core.function.trace_type.default_types.List

Represents a list of TraceType objects.

method

tensorflow.core.function.trace_type.default_types.List.most_specific_common_supertype(others:Sequence[trace.TraceType]) -> Optional['Tuple']

See base class.

classtensorflow.core.function.trace_type.default_types.Literal

Represents a Literal type like bool, int or string.

classtensorflow.core.function.trace_type.default_types.NamedTuple

Represents a NamedTuple of TraceType objects.

method

tensorflow.core.function.trace_type.default_types.NamedTuple.most_specific_common_supertype(others:Sequence[trace.TraceType]) -> Optional['NamedTuple']

See base class.

classtensorflow.core.function.trace_type.default_types.Tuple

Represents a tuple of TraceType objects.

method

tensorflow.core.function.trace_type.default_types.Tuple.most_specific_common_supertype(others:Sequence[trace.TraceType]) -> Optional['Tuple']

See base class.

classtensorflow.core.function.trace_type.default_types.Weakref

Represents weakref of an arbitrary Python object.

method

tensorflow.core.function.trace_type.serialization.Serializable.experimental_from_proto(proto:message.Message) -> 'Serializable'

Returns an instance based on a proto.

functensorflow.core.function.trace_type.serialization.serialize(to_serialize:Serializable) -> SerializedTraceType

Converts Serializable to a proto SerializedTraceType.

classtensorflow.core.function.trace_type.trace_type_builder.InternalCastContext

Default casting behaviors.

classtensorflow.core.tfrt.mlrt.kernel.testdata.gen_checkpoint.ToyModule

A toy module for testing checkpoing loading.

functensorflow.dtensor.python.accelerator_util.shutdown_accelerator_system() -> None

Shuts down the accelerator system.

functensorflow.dtensor.python.api.check_layout(tensor:tensor_lib.Tensor, layout:layout_lib.Layout) -> None

Asserts that the layout of the DTensor is `layout`.

functensorflow.dtensor.python.api.device_name() -> str

Returns the singleton DTensor device's name.

functensorflow.dtensor.python.api.fetch_layout(tensor:tensor_lib.Tensor) -> layout_lib.Layout

Fetches the layout of a DTensor.

functensorflow.dtensor.python.api.is_dtensor(tensor) -> bool

Check whether the input tensor is a DTensor.

functensorflow.dtensor.python.api.pack(tensors:Sequence[Any], layout:layout_lib.Layout) -> Any

Packs `tf.Tensor` components into a DTensor.

func

tensorflow.dtensor.python.api.relayout(tensor:tensor_lib.Tensor, layout:layout_lib.Layout, name:Optional[str]=None) -> tensor_lib.Tensor

Changes the layout of `tensor`.

functensorflow.dtensor.python.api.reset_dtensor_device(is_async:bool) -> None

Resets the Eager execution device for DTensor.

functensorflow.dtensor.python.api.unpack(tensor:Any) -> Sequence[Any]

Unpacks a DTensor into `tf.Tensor` components.

functensorflow.dtensor.python.config.client_id() -> int

Returns this client's ID.

functensorflow.dtensor.python.config.is_gpu_present() -> bool

Returns true if TPU devices are present.

functensorflow.dtensor.python.config.is_local_mode() -> bool

Returns true if DTensor shall run in local mode.

functensorflow.dtensor.python.config.is_tpu_present() -> bool

Returns true if TPU devices are present.

functensorflow.dtensor.python.config.num_clients() -> int

Returns the number of clients in this DTensor cluster.

functensorflow.dtensor.python.heartbeat.start(period:int) -> threading.Event

Starts a persistent thread exchanging heartbeats between workers.

classtensorflow.dtensor.python.input_util.DTensorDataset

A dataset of DTensors.

classtensorflow.dtensor.python.input_util.TFDataServiceConfig

Specifies the tf.data service configuration to use.

classtensorflow.dtensor.python.layout.Layout

Represents the layout information of a DTensor.

methodtensorflow.dtensor.python.layout.Layout.batch_sharded(mesh:Mesh, batch_dim:str, rank:int, axis:int=0) -> 'Layout'

Returns a layout sharded on batch dimension.

methodtensorflow.dtensor.python.layout.Layout.delete(dims:List[int]) -> 'Layout'

Returns the layout with the give dimensions deleted.

methodtensorflow.dtensor.python.layout.Layout.from_device(device:str) -> 'Layout'

Constructs a single device layout from a single device mesh.

methodtensorflow.dtensor.python.layout.Layout.from_proto(layout_proto:layout_pb2.LayoutProto) -> 'Layout'

Creates an instance from a LayoutProto.

methodtensorflow.dtensor.python.layout.Layout.from_single_device_mesh(mesh:Mesh) -> 'Layout'

Constructs a single device layout from a single device mesh.

methodtensorflow.dtensor.python.layout.Layout.from_string(layout_str:str) -> 'Layout'

Creates an instance from a human-readable string.

methodtensorflow.dtensor.python.layout.Layout.inner_sharded(mesh:Mesh, inner_dim:str, rank:int) -> 'Layout'

Returns a layout sharded on inner dimension.

methodtensorflow.dtensor.python.layout.Layout.replicated(mesh:Mesh, rank:int) -> 'Layout'

Returns a replicated layout of rank `rank`.

methodtensorflow.dtensor.python.layout.Layout.to_parted() -> 'Layout'

Returns a "parted" layout from a static layout.

methodtensorflow.dtensor.python.layout.Mesh.coords(device_idx:int) -> tensor.Tensor

Converts the device index into a tensor of mesh coordinates.

methodtensorflow.dtensor.python.layout.Mesh.from_device(device:str) -> 'Mesh'

Constructs a single device mesh from a device string.

methodtensorflow.dtensor.python.layout.Mesh.from_proto(proto:layout_pb2.MeshProto) -> 'Mesh'

Construct a mesh instance from input `proto`.

methodtensorflow.dtensor.python.layout.Mesh.global_device_ids() -> np.ndarray

Returns a global device list as an array.

methodtensorflow.dtensor.python.layout.Mesh.host_mesh() -> 'Mesh'

Returns a host mesh.

methodtensorflow.dtensor.python.layout.Mesh.local_device_locations() -> List[Dict[str, int]]

Returns a list of local device locations.

methodtensorflow.dtensor.python.layout.Mesh.strides() -> List[int]

Returns the strides tensor array for this mesh.

func

tensorflow.dtensor.python.mesh_util.barrier(mesh:layout.Mesh, barrier_name:Optional[str]=None, timeout_in_ms:Optional[int]=None)

Runs a barrier on the mesh.

functensorflow.dtensor.python.numpy_util.to_numpy(tensor:TensorLike) -> np.ndarray

Copy `input` DTensor to an equivalent local numpy array.

func

tensorflow.dtensor.python.numpy_util.unpacked_to_numpy(unpacked:List[TensorLike], layout:layout_lib.Layout) -> np.ndarray

Heals local Tensor components to a numpy array.

functensorflow.dtensor.python.tpu_util.shutdown_tpu_system()

Shuts down the TPU system.

classtensorflow.lite.python.analyzer.ModelAnalyzer

Provides a collection of TFLite model analyzer tools.

classtensorflow.lite.python.convert_phase.Component

Enum class defining name of the converter components.

classtensorflow.lite.python.convert_phase.ConverterError

Raised when an error occurs during model conversion.

classtensorflow.lite.python.interpreter.Delegate

Python wrapper class to manage TfLiteDelegate objects.

methodtensorflow.lite.python.interpreter.Interpreter.invoke()

Invoke the interpreter.

classtensorflow.lite.python.interpreter.OpResolverType

Different types of op resolvers for Tensorflow Lite.

classtensorflow.lite.python.lite.RepresentativeDataset

Representative dataset used to optimize the model.

classtensorflow.lite.python.lite.TFLiteConverter

Convert a TensorFlow model into `output_format`.

classtensorflow.lite.python.lite.TFLiteConverterV2

Converts a TensorFlow model into TensorFlow Lite model.

classtensorflow.lite.python.lite.TocoConverter

Convert a TensorFlow model into `output_format`.

classtensorflow.lite.python.lite_v2_test_util.ModelTest

Base test class for TensorFlow Lite 2.x model tests.

classtensorflow.lite.python.lite_v2_test_util.ModelTest.BasicModel

Basic model with multiple functions.

classtensorflow.lite.python.lite_v2_test_util.ModelTest.ConvWrapper

A Wrapper for simulating QAT on Conv2D layers.

classtensorflow.lite.python.lite_v2_test_util.ModelTest.SimpleModelWithOneVariable

Basic model with 1 variable.

classtensorflow.lite.python.metrics.metrics_interface.TFLiteMetricsInterface

Abstract class for TFLiteMetrics.

classtensorflow.lite.python.metrics.metrics_portable.TFLiteMetrics

TFLite metrics helper.

classtensorflow.lite.python.op_hint.OpHint

A class that helps build tflite function invocations.

functensorflow.lite.python.tflite_convert.run_main(_)

Main in tflite_convert.py.

functensorflow.lite.python.util.freeze_graph(sess, input_tensors, output_tensors)

Returns a frozen GraphDef.

functensorflow.lite.python.util.get_dequantize_opcode_idx(model)

Returns the quantize op idx.

functensorflow.lite.python.util.get_quantize_opcode_idx(model)

Returns the quantize op idx.

functensorflow.lite.python.util.get_tensor_name(tensor)

Returns name of the input tensor.

functensorflow.lite.python.util.is_frozen_graph(sess)

Determines if the graph is frozen.

classtensorflow.lite.toco.logging.gen_html.HTMLGenerator

Utility class to generate an HTML report.

classtensorflow.python.autograph.converters.variables.VariableAccessTransformer

Rewrites basic symbol reads.

classtensorflow.python.autograph.core.ag_ctx.NullCtx

Helper substitute for contextlib.nullcontext.

classtensorflow.python.autograph.core.config_lib.Convert

Indicates that this module should be converted.

classtensorflow.python.autograph.core.config_lib.DoNotConvert

Indicates that this module should be not converted.

classtensorflow.python.autograph.core.config_lib.Rule

Base class for conversion rules.

classtensorflow.python.autograph.core.converter.Base

All converters should inherit from this class.

classtensorflow.python.autograph.core.converter.ConversionOptions

Immutable container for global conversion flags.

methodtensorflow.python.autograph.core.converter.Feature.all()

Returns a tuple that enables all options.

classtensorflow.python.autograph.core.converter_testing.TestCase

Base class for unit tests in this module.

classtensorflow.python.autograph.impl.api.AutoGraphError

Base class for all AutoGraph exceptions.

classtensorflow.python.autograph.impl.api.ConversionError

Raised during the conversion process.

classtensorflow.python.autograph.impl.api.PyToTF

The TensorFlow AutoGraph transformer.

classtensorflow.python.autograph.impl.api.StackTraceMapper

Remaps generated code to code it originated from.

classtensorflow.python.autograph.impl.api.StagingError

Raised during the staging (i.e.

functensorflow.python.autograph.impl.api.decorator(f)

Decorator implementation.

functensorflow.python.autograph.operators.data_structures.list_append(list_, x)

The list append function.

functensorflow.python.autograph.operators.data_structures.list_pop(list_, i, opts)

The list pop function.

functensorflow.python.autograph.operators.data_structures.list_stack(list_, opts)

The list stack function.

functensorflow.python.autograph.operators.data_structures.new_list(iterable=None)

The list constructor.

functensorflow.python.autograph.operators.logical.and_(a, b)

Functional form of "and".

functensorflow.python.autograph.operators.logical.eq(a, b)

Functional form of "equal".

functensorflow.python.autograph.operators.logical.not_(a)

Functional form of "not".

functensorflow.python.autograph.operators.logical.not_eq(a, b)

Functional form of "not-equal".

functensorflow.python.autograph.operators.logical.or_(a, b)

Functional form of "or".

functensorflow.python.autograph.operators.slices.get_item(target, i, opts)

The slice read operator (i.e.

functensorflow.python.autograph.operators.slices.set_item(target, i, x)

The slice write operator (i.e.

classtensorflow.python.autograph.operators.variables.Undefined

Represents an undefined symbol in Python.

classtensorflow.python.autograph.operators.variables.UndefinedReturnValue

Represents a return value that is undefined.

functensorflow.python.autograph.operators.variables.ld(v)

Load variable operator.

classtensorflow.python.autograph.pyct.anno.Basic

Container for basic annotation keys.

classtensorflow.python.autograph.pyct.anno.NoValue

Base class for different types of AST annotations.

classtensorflow.python.autograph.pyct.anno.Static

Container for static analysis annotation keys.

classtensorflow.python.autograph.pyct.ast_util.CleanCopier

NodeTransformer-like visitor that copies an AST.

functensorflow.python.autograph.pyct.ast_util.copy_clean(node, preserve_annos=None)

Creates a deep copy of an AST.

functensorflow.python.autograph.pyct.ast_util.matches(node, pattern)

Basic pattern matcher for AST.

functensorflow.python.autograph.pyct.ast_util.parallel_walk(node, other)

Walks two ASTs in parallel.

functensorflow.python.autograph.pyct.ast_util.rename_symbols(node, name_map)

Renames symbols in an AST.

classtensorflow.python.autograph.pyct.cache.CodeObjectCache

A function cache based on code objects.

classtensorflow.python.autograph.pyct.cfg.AstToCfg

Converts an AST to CFGs.

classtensorflow.python.autograph.pyct.cfg.Graph

A Control Flow Graph.

methodtensorflow.python.autograph.pyct.cfg.Graph.as_dot()

Print CFG in DOT format.

classtensorflow.python.autograph.pyct.cfg.GraphBuilder

Builder that constructs a CFG from a given AST.

methodtensorflow.python.autograph.pyct.cfg.GraphBuilder.enter_loop_section(section_id, entry_node)

Enters a loop section.

methodtensorflow.python.autograph.pyct.cfg.GraphBuilder.enter_section(section_id)

Enters a regular section.

methodtensorflow.python.autograph.pyct.cfg.GraphBuilder.exit_loop_section(section_id)

Exits a loop section.

methodtensorflow.python.autograph.pyct.cfg.GraphBuilder.exit_section(section_id)

Exits a regular section.

classtensorflow.python.autograph.pyct.cfg.GraphVisitor

Base class for a CFG visitors.

methodtensorflow.python.autograph.pyct.cfg.GraphVisitor.visit_node(node)

Visitor function.

classtensorflow.python.autograph.pyct.cfg.Node

A node in the CFG.

classtensorflow.python.autograph.pyct.common_transformers.anf.ASTEdgePattern

A pattern defining a type of AST edge.

classtensorflow.python.autograph.pyct.errors.InaccessibleSourceCodeError

Raised when inspect can not access source code.

classtensorflow.python.autograph.pyct.errors.PyCTError

Base class for all exceptions.

functensorflow.python.autograph.pyct.inspect_utils.getdefiningclass(m, owner_class)

Resolves the class (e.g.

classtensorflow.python.autograph.pyct.naming.Namer

Symbol name generator.

classtensorflow.python.autograph.pyct.origin_info.LineLocation

Similar to Location, but without column information.

classtensorflow.python.autograph.pyct.origin_info.Location

Encodes code location information.

classtensorflow.python.autograph.pyct.pretty_printer.PrettyPrinter

Print AST nodes.

classtensorflow.python.autograph.pyct.qual_names.Literal

Represents a Python numeric literal.

classtensorflow.python.autograph.pyct.qual_names.QN

Represents a qualified name.

methodtensorflow.python.autograph.pyct.qual_names.QN.ast()

AST representation.

methodtensorflow.python.autograph.pyct.qual_names.QN.ssf()

Simple symbol form.

classtensorflow.python.autograph.pyct.qual_names.QnResolver

Annotates nodes with QN information.

classtensorflow.python.autograph.pyct.qual_names.Symbol

Represents a Python symbol.

classtensorflow.python.autograph.pyct.static_analysis.activity.ActivityAnalyzer

Annotates nodes with local scope information.

methodtensorflow.python.autograph.pyct.static_analysis.activity.Scope.finalize()

Freezes this scope.

classtensorflow.python.autograph.pyct.templates.ContextAdjuster

Adjusts the ctx field of nodes to ensure consistency.

classtensorflow.python.autograph.pyct.templates.ReplaceTransformer

Replace AST nodes.

classtensorflow.python.autograph.pyct.transformer.Context

Contains information about a source code transformation.

classtensorflow.python.autograph.pyct.transformer.EntityInfo

Contains information about a Python entity.

classtensorflow.python.autograph.pyct.transpiler.GenericTranspiler

A generic transpiler for Python functions.

methodtensorflow.python.autograph.pyct.transpiler.GenericTranspiler.transform_function(fn, user_context)

Transforms a function.

classtensorflow.python.autograph.pyct.transpiler.PyToPy

A generic Python-to-Python transpiler.

methodtensorflow.python.autograph.pyct.transpiler.PyToPy.transform_function(fn, user_context)

Transforms a function.

methodtensorflow.python.autograph.utils.type_registry.TypeRegistry.lookup(obj)

Looks up 'obj'.

classtensorflow.python.checkpoint.async_checkpoint_helper.AsyncCheckpointHelper

Helper class for async checkpoint.

classtensorflow.python.checkpoint.checkpoint.Checkpoint

Manages saving/restoring trackable values to disk.

classtensorflow.python.checkpoint.checkpoint.CheckpointV1

Groups trackable objects, saving and restoring them.

classtensorflow.python.checkpoint.checkpoint_adapter.AbstractCheckpointAdapter

Abstract API for checkpoint adapter.

classtensorflow.python.checkpoint.checkpoint_adapter.ReshardCallback

API to reshard a checkpoint value during restore.

classtensorflow.python.checkpoint.checkpoint_options.CheckpointOptions

Options for constructing a Checkpoint.

classtensorflow.python.checkpoint.checkpoint_view.CheckpointView

Gathers and serializes a checkpoint view.

classtensorflow.python.checkpoint.functional_saver.MultiDeviceSaver

Saves checkpoints directly from multiple devices.

classtensorflow.python.checkpoint.graph_view.ObjectGraphView

Gathers and serializes an object graph.

classtensorflow.python.checkpoint.trackable_view.TrackableView

Gathers and serializes a trackable view.

classtensorflow.python.client.session.BaseSession

A class for interacting with a TensorFlow computation.

methodtensorflow.python.client.session.BaseSession.close()

Closes this session.

classtensorflow.python.client.session.Session

A class for running TensorFlow operations.

classtensorflow.python.client.timeline.StepStatsAnalysis

Stores the step stats analysis output.

classtensorflow.python.compiler.tensorrt.model_tests.model_handler.ModelConfig

Configurations for test models.

classtensorflow.python.compiler.tensorrt.model_tests.model_handler.ModelHandlerV1

Runs a model in TF1.

classtensorflow.python.compiler.tensorrt.model_tests.model_handler.ModelHandlerV2

Runs a model in TF2.

func

tensorflow.python.compiler.tensorrt.model_tests.model_handler.load_meta_graph(saved_model_dir:str, saved_model_tags:str, saved_model_signature_key:str) -> meta_graph_pb2.MetaGraphDef

Loads a `tf.MetaGraphDef` in TF1.

classtensorflow.python.compiler.tensorrt.model_tests.result_analyzer.ResultAnalyzer

Analyzes ModelHandlerManager results.

func

tensorflow.python.compiler.tensorrt.model_tests.result_analyzer.analyze_test_latency(test_results:model_handler.TestResultCollection, use_cpu_baseline:bool) -> DataFrame

Analyzes test latency.

func

tensorflow.python.compiler.tensorrt.model_tests.result_analyzer.analyze_test_numerics(test_results:model_handler.TestResultCollection, use_cpu_baseline:bool) -> (DataFrame, str)

Analyzes test numerics.

func

tensorflow.python.compiler.tensorrt.model_tests.result_analyzer.extract_test_info(test_results:model_handler.TestResultCollection) -> DataFrame

Extracts the test information.

classtensorflow.python.compiler.tensorrt.trt_convert.TrtConversionParams

Parameters that are used for TF-TRT conversion.

classtensorflow.python.data.experimental.ops.grouping.Reducer

A reducer is used for reducing a set of elements.

classtensorflow.python.data.experimental.ops.random_ops.RandomDatasetV1

A `Dataset` of pseudorandom values.

classtensorflow.python.data.experimental.ops.random_ops.RandomDatasetV2

A `Dataset` of pseudorandom values.

classtensorflow.python.data.experimental.ops.writers.TFRecordWriter

Writes a dataset to a TFRecord file.

classtensorflow.python.data.experimental.service.server_lib.DispatchServer

An in-process tf.data service dispatch server.

methodtensorflow.python.data.experimental.service.server_lib.DispatchServer.join() -> None

Blocks until the server has shut down.

methodtensorflow.python.data.experimental.service.server_lib.DispatchServer.start()

Starts this server.

methodtensorflow.python.data.experimental.service.server_lib.DispatchServer.stop() -> None

Stops the server.

classtensorflow.python.data.experimental.service.server_lib.WorkerServer

An in-process tf.data service worker server.

methodtensorflow.python.data.experimental.service.server_lib.WorkerServer.join() -> None

Blocks until the server has shut down.

methodtensorflow.python.data.experimental.service.server_lib.WorkerServer.start() -> None

Starts this server.

methodtensorflow.python.data.experimental.service.server_lib.WorkerServer.stop() -> None

Stops the server.

classtensorflow.python.data.kernel_tests.checkpoint_test_base.CheckpointTestBase

Base test class for checkpointing datasets.

classtensorflow.python.data.kernel_tests.tf_record_test_base.TFRecordTestBase

Base class for TFRecord-based tests.

classtensorflow.python.data.ops.cache_op.CacheDataset

A `Dataset` that caches elements of its input.

classtensorflow.python.data.ops.dataset_ops.DatasetSource

Abstract class representing a dataset with no inputs.

classtensorflow.python.data.ops.dataset_ops.DatasetSpec

Type specification for `tf.data.Dataset`.

methodtensorflow.python.data.ops.dataset_ops.DatasetSpec.element_spec()

The inner element spec.

methodtensorflow.python.data.ops.dataset_ops.DatasetSpec.is_subtype_of(other)

See base class.

methodtensorflow.python.data.ops.dataset_ops.DatasetSpec.most_specific_common_supertype(others)

See base class.

classtensorflow.python.data.ops.dataset_ops.DatasetV1

Represents a potentially large set of elements.

classtensorflow.python.data.ops.dataset_ops.DatasetV2

Represents a potentially large set of elements.

methodtensorflow.python.data.ops.dataset_ops.DatasetV2.cache(filename='', name=None) -> 'DatasetV2'

Caches the elements in this dataset.

methodtensorflow.python.data.ops.dataset_ops.DatasetV2.enumerate(start=0, name=None) -> 'DatasetV2'

Enumerates the elements of this dataset.

methodtensorflow.python.data.ops.dataset_ops.DatasetV2.ignore_errors(log_warning=False, name=None) -> 'DatasetV2'

Drops elements that cause errors.

method

tensorflow.python.data.ops.dataset_ops.DatasetV2.load(path, element_spec=None, compression=None, reader_func=None, wait=False) -> 'DatasetV2'

Loads a previously saved dataset.

methodtensorflow.python.data.ops.dataset_ops.DatasetV2.range(*args, **kwargs) -> 'DatasetV2'

Creates a `Dataset` of a step-separated range of values.

method

tensorflow.python.data.ops.dataset_ops.DatasetV2.window(size, shift=None, stride=1, drop_remainder=False, name=None) -> 'DatasetV2'

Returns a dataset of "windows".

methodtensorflow.python.data.ops.dataset_ops.DatasetV2.zip(*datasets=None, *name=None, *args) -> 'DatasetV2'

Creates a `Dataset` by zipping together the given datasets.

classtensorflow.python.data.ops.dataset_ops.UnaryDataset

Abstract class representing a dataset with one input.

functensorflow.python.data.ops.dataset_ops.apply_rewrite(dataset, rewrite)

Applies a rewrite to a dataset.

func

tensorflow.python.data.ops.dataset_ops.make_initializable_iterator(dataset:DatasetV1, shared_name=None) -> iterator_ops.Iterator

Creates an iterator for elements of `dataset`.

functensorflow.python.data.ops.debug_mode.enable_debug_mode()

Enables debug mode for tf.data.

classtensorflow.python.data.ops.iterator_ops.Iterator

Represents the state of iterating through a `Dataset`.

methodtensorflow.python.data.ops.iterator_ops.Iterator.get_next(name=None)

Returns the next element.

classtensorflow.python.data.ops.iterator_ops.IteratorBase

Represents an iterator of a `tf.data.Dataset`.

methodtensorflow.python.data.ops.iterator_ops.IteratorBase.get_next()

Returns the next element.

classtensorflow.python.data.ops.iterator_ops.IteratorSpec

Type specification for `tf.data.Iterator`.

classtensorflow.python.data.ops.multi_device_iterator_ops.MultiDeviceIterator

An iterator over multiple devices.

classtensorflow.python.data.ops.multi_device_iterator_ops.OwnedMultiDeviceIterator

An iterator over multiple devices.

classtensorflow.python.data.ops.optional_ops.Optional

Represents a value that may or may not be present.

classtensorflow.python.data.ops.optional_ops.OptionalSpec

Type specification for `tf.experimental.Optional`.

classtensorflow.python.data.ops.options.AutoShardPolicy

Represents the type of auto-sharding to use.

classtensorflow.python.data.ops.options.AutotuneAlgorithm

Represents the type of autotuning algorithm to use.

classtensorflow.python.data.ops.options.DistributeOptions

Represents options for distributed data processing.

classtensorflow.python.data.ops.options.OptimizationOptions

Represents options for dataset optimizations.

classtensorflow.python.data.ops.options.Options

Represents options for `tf.data.Dataset`.

classtensorflow.python.data.ops.options.ServiceOptions

Represents options for tf.data service.

classtensorflow.python.data.ops.options.ThreadingOptions

Represents options for dataset threading.

classtensorflow.python.data.util.options.OptionsBase

Base class for representing a set of tf.data options.

functensorflow.python.data.util.options.create_option(name, ty, docstring, default_factory=lambda: None)

Creates a type-checked property.

functensorflow.python.data.util.sparse.any_sparse(classes)

Checks for sparse tensor.

functensorflow.python.data.util.sparse.serialize_sparse_tensors(tensors)

Serializes sparse tensors.

classtensorflow.python.debug.cli.analyzer_cli.DebugAnalyzer

Analyzer for debug data from dump directories.

classtensorflow.python.debug.cli.base_ui.BaseUI

Base class of tfdbg user interface.

classtensorflow.python.debug.cli.command_parser.Interval

Represents an interval between a start and end value.

classtensorflow.python.debug.cli.debugger_cli_common.CommandHandlerRegistry

Registry of command handlers for CLI.

classtensorflow.python.debug.cli.debugger_cli_common.CommandHistory

Keeps command history and supports lookup.

classtensorflow.python.debug.cli.debugger_cli_common.Menu

A class for text-based menu.

methodtensorflow.python.debug.cli.debugger_cli_common.Menu.append(item)

Append an item to the Menu.

classtensorflow.python.debug.cli.debugger_cli_common.MenuItem

A class for an item in a text-based menu.

classtensorflow.python.debug.cli.debugger_cli_common.RichLine

Rich single-line text.

classtensorflow.python.debug.cli.debugger_cli_common.RichTextLines

Rich multi-line text.

methodtensorflow.python.debug.cli.debugger_cli_common.RichTextLines.append(line, font_attr_segs=None)

Append a single line of text.

classtensorflow.python.debug.cli.debugger_cli_common.TabCompletionRegistry

Registry for tab completion responses.

classtensorflow.python.debug.cli.profile_analyzer_cli.ProfileAnalyzer

Analyzer for profiling data.

classtensorflow.python.debug.cli.profile_analyzer_cli.ProfileDataTableView

Table View of profiling data.

classtensorflow.python.debug.cli.readline_ui.ReadlineUI

Readline-based Command-line UI.

classtensorflow.python.debug.cli.tensor_format.HighlightOptions

Options for highlighting elements of a tensor.

classtensorflow.python.debug.lib.debug_data.DebugDumpDir

Data set from a debug-dump directory on filesystem.

methodtensorflow.python.debug.lib.debug_data.DebugDumpDir.devices()

Get the list of device names.

methodtensorflow.python.debug.lib.debug_data.DebugDumpDir.partition_graphs()

Get the partition graphs.

methodtensorflow.python.debug.lib.debug_data.DebugDumpDir.python_graph()

Get the Python graph.

methodtensorflow.python.debug.lib.debug_data.DebugTensorDatum.debug_op()

Name of the debug op.

methodtensorflow.python.debug.lib.debug_data.DebugTensorDatum.dump_size_bytes()

Size of the dump file.

classtensorflow.python.debug.lib.debug_events_monitors.BaseMonitor

Base class for debug event data monitors.

classtensorflow.python.debug.lib.debug_events_monitors.InfNanAlert

Alert for Infinity and NaN values.

classtensorflow.python.debug.lib.debug_events_monitors.InfNanMonitor

Monitor for Infinity and NaN in tensor values.

classtensorflow.python.debug.lib.debug_events_reader.BaseDigest

Base class for digest.

classtensorflow.python.debug.lib.debug_events_reader.DebugEventsReader

Reader class for a tfdbg v2 DebugEvents directory.

classtensorflow.python.debug.lib.debug_events_writer.DebugEventsWriter

A writer for TF debugging events.

methodtensorflow.python.debug.lib.debug_events_writer.DebugEventsWriter.Close()

Close the writer.

classtensorflow.python.debug.lib.debug_gradients.GradientsDebugger

Gradients Debugger.

classtensorflow.python.debug.lib.debug_graphs.DFSGraphTracer

Graph input tracer using depth-first search.

methodtensorflow.python.debug.lib.debug_graphs.DFSGraphTracer.trace(graph_element_name)

Trace inputs.

classtensorflow.python.debug.lib.debug_graphs.DebugGraph

Represents a debugger-decorated graph.

classtensorflow.python.debug.lib.dumping_callback_test_lib.DumpingCallbackTestBase

Base test-case class for tfdbg v2 callbacks.

classtensorflow.python.debug.lib.grpc_debug_server.EventListenerBaseServicer

Base Python class for gRPC debug server.

classtensorflow.python.debug.lib.profiling.ProfileDatum

Profile data point.

classtensorflow.python.debug.wrappers.framework.BaseDebugWrapperSession

Base class of debug-wrapper session classes.

classtensorflow.python.debug.wrappers.framework.OnRunEndRequest

Request to an on-run-end callback.

classtensorflow.python.debug.wrappers.framework.OnRunEndResponse

Response from an on-run-end callback.

classtensorflow.python.debug.wrappers.framework.OnRunStartRequest

Request to an on-run-start callback.

classtensorflow.python.debug.wrappers.framework.OnRunStartResponse

Request from an on-run-start callback.

classtensorflow.python.debug.wrappers.framework.OnSessionInitRequest

Request to an on-session-init callback.

classtensorflow.python.debug.wrappers.framework.OnSessionInitResponse

Response from an on-session-init callback.

classtensorflow.python.debug.wrappers.framework.WatchOptions

Type for return values of watch_fn.

classtensorflow.python.debug.wrappers.hooks.LocalCLIDebugHook

Command-line-interface debugger hook.

classtensorflow.python.distribute.cluster_resolver.kubernetes_cluster_resolver.ExecutableLocation

Defines where the executable runs on.

classtensorflow.python.distribute.cluster_resolver.kubernetes_cluster_resolver.KubernetesClusterResolver

ClusterResolver for Kubernetes.

classtensorflow.python.distribute.cluster_resolver.tpu.tpu_cluster_resolver.TPUClusterResolver

Cluster Resolver for Google Cloud TPUs.

classtensorflow.python.distribute.collective_util.CommunicationImplementation

Cross device communication implementation.

classtensorflow.python.distribute.collective_util.Hints

Hints for collective operations like AllReduce.

classtensorflow.python.distribute.collective_util.Options

Implementation of OptionsInterface.

classtensorflow.python.distribute.combinations.ClusterCombination

Sets up multi worker tests.

classtensorflow.python.distribute.combinations.DistributionCombination

Sets up distribution strategy for tests.

classtensorflow.python.distribute.combinations.DistributionParameter

Transforms arguments of type `NamedDistribution`.

classtensorflow.python.distribute.combinations.TestEnvironment

Holds the test environment information.

functensorflow.python.distribute.combinations.concat(*combined)

Concats combinations.

classtensorflow.python.distribute.coordinator.cluster_coordinator.Closure

Hold a function to be scheduled and its arguments.

classtensorflow.python.distribute.coordinator.cluster_coordinator.ClosureInputError

Wrapper for errors from resource building.

classtensorflow.python.distribute.coordinator.cluster_coordinator.Cluster

A cluster with workers.

classtensorflow.python.distribute.coordinator.cluster_coordinator.ResourceClosure

A closure that builds a resource on a worker.

classtensorflow.python.distribute.coordinator.cluster_coordinator.Worker

A worker in a cluster.

classtensorflow.python.distribute.coordinator.cluster_coordinator.WorkerPreemptionHandler

Handles worker preemptions.

classtensorflow.python.distribute.coordinator.remote_value.RemoteValueStatus

The status of a `RemoteValue` object.

classtensorflow.python.distribute.coordinator.values.PerWorkerValuesTypeSpec

TypeSpec for PerWorkerValues.

classtensorflow.python.distribute.coordinator.values.RemoteValueImpl

Implementation of `RemoteValue`.

classtensorflow.python.distribute.cross_device_ops.AllReduceCrossDeviceOps

All-reduce implementation of CrossDeviceOps.

classtensorflow.python.distribute.cross_device_ops.NcclAllReduce

NCCL all-reduce implementation of CrossDeviceOps.

classtensorflow.python.distribute.cross_device_utils.CollectiveKeys

Class that manages collective keys.

classtensorflow.python.distribute.cross_device_utils.CollectiveReplicaLauncher

Launch collectives on one replica.

method

tensorflow.python.distribute.cross_device_utils.CollectiveReplicaLauncher.all_gather(input_tensor:core.TensorLike, axis:core.TensorLike, options:Optional[collective_util.Options]=None) -> core.Tensor

All-gather a dense tensor.

functensorflow.python.distribute.device_util.canonicalize(d, default=None)

Canonicalize device string.

classtensorflow.python.distribute.distribute_config.DistributeConfig

A config tuple for distribution strategies.

classtensorflow.python.distribute.distribute_coordinator.CoordinatorMode

Specify how distribute coordinator runs.

classtensorflow.python.distribute.distribute_lib.InputReplicationMode

Replication mode for input function.

classtensorflow.python.distribute.distribute_lib.RunOptions

Run options for `strategy.run`.

classtensorflow.python.distribute.experimental.rpc.rpc_ops.Client

Client class for invoking RPCs to the server.

classtensorflow.python.distribute.failure_handling.failure_handling.BorgTPUTerminationConfig

Configurations for Borg.

classtensorflow.python.distribute.failure_handling.failure_handling.BorgTerminationConfig

Configurations for Borg.

classtensorflow.python.distribute.failure_handling.failure_handling.GcpCpuTerminationConfig

Configurations for GCP CPU VM.

classtensorflow.python.distribute.failure_handling.failure_handling.GcpGpuTerminationConfig

Configurations for GCP GPU VM.

classtensorflow.python.distribute.failure_handling.preemption_watcher.PreemptionWatcher

Watch preemption signal and store it.

classtensorflow.python.distribute.input_lib.DistributedDatasetSpec

Type specification for `DistributedDataset.

classtensorflow.python.distribute.input_lib.DistributedDatasetsFromFunction

Inputs created from dataset function.

classtensorflow.python.distribute.input_lib.DistributedIterator

Input Iterator for a distributed dataset.

classtensorflow.python.distribute.input_lib.DistributedIteratorBase

Common implementation for all input iterators.

classtensorflow.python.distribute.input_lib.DistributedIteratorSpec

Type specification for `DistributedIterator`.

classtensorflow.python.distribute.load_context.LoadContext

A context for loading a model.

classtensorflow.python.distribute.mirrored_strategy.MirroredExtended

Implementation of MirroredStrategy.

classtensorflow.python.distribute.multi_process_lib.AbslForkServerProcess

An absl-compatible Forkserver process.

classtensorflow.python.distribute.multi_worker_test_base.IndependentWorkerTestBase

Testing infra for independent workers.

classtensorflow.python.distribute.multi_worker_test_base.MockOsEnv

A class that allows per-thread TF_CONFIG.

classtensorflow.python.distribute.one_device_strategy.OneDeviceExtended

Implementation of OneDeviceStrategy.

classtensorflow.python.distribute.reduce_util.ReduceOp

Indicates how a set of values should be reduced.

classtensorflow.python.distribute.sharded_variable.ShardedVariableMixin

Mixin for ShardedVariable.

methodtensorflow.python.distribute.sharded_variable.ShardedVariableMixin.name()

The name of this object.

classtensorflow.python.distribute.sharded_variable.ShardedVariableSpec

Type specification for a `ShardedVariable`.

classtensorflow.python.distribute.step_fn.Step

Interface for performing each step of a training algorithm.

classtensorflow.python.distribute.strategy_test_lib.RemoteSingleWorkerMirroredStrategyBase

Tests for a Remote single worker.

classtensorflow.python.distribute.tpu_strategy.TPUExtended

Implementation of TPUStrategy.

classtensorflow.python.distribute.tpu_strategy.TPUStrategy

Synchronous training on TPUs and TPU Pods.

methodtensorflow.python.distribute.tpu_strategy.TPUStrategy.run(fn, args=(), kwargs=None, options=None)

See base class.

classtensorflow.python.distribute.tpu_strategy.TPUStrategyV1

TPU distribution strategy implementation.

classtensorflow.python.distribute.tpu_strategy.TPUStrategyV2

Synchronous training on TPUs and TPU Pods.

classtensorflow.python.distribute.tpu_util.LazyVariableTracker

Class to track uninitialized lazy variables.

classtensorflow.python.distribute.tpu_util.TPUUninitializedVariable

UninitializedVariable component for TPU.

classtensorflow.python.distribute.tpu_values.TPUDistributedVariable

DistributedVariable subclass for TPUStrategy.

classtensorflow.python.distribute.tpu_values.TPUVariableMixin

Mixin for TPU variables.

classtensorflow.python.distribute.v1.input_lib.DatasetIterator

Iterator created from input dataset.

classtensorflow.python.distribute.v1.input_lib.DistributedDatasetsFromFunctionV1

Inputs created from dataset function.

classtensorflow.python.distribute.v1.input_lib.DistributedIteratorV1

Input Iterator for a distributed dataset.

classtensorflow.python.distribute.v1.input_lib.InputFunctionIterator

Iterator created from input function.

classtensorflow.python.distribute.values.DistributedValues

Base class for representing distributed values.

classtensorflow.python.distribute.values.DistributedVarOp

A class that looks like `tf.Operation`.

classtensorflow.python.distribute.values.DistributedVariable

Holds a map from replica to variables.

classtensorflow.python.distribute.values.DistributedVariableTraceType

TraceType of DistributedVariable objects.

classtensorflow.python.distribute.values.PerReplica

Holds a map from replica to unsynchronized values.

methodtensorflow.python.distribute.values.PerReplica.values()

Returns the per replica values.

classtensorflow.python.distribute.values.PerReplicaSpec

Type specification for a `PerReplica`.

classtensorflow.python.distribute.values_v2.DistributedVariable

Represents variables that are replicated.

classtensorflow.python.eager.backprop.GradientTape

Record operations for automatic differentiation.

classtensorflow.python.eager.benchmarks_test_base.MicroBenchmarksBase

Run and report benchmark results.

classtensorflow.python.eager.cancellation.CancellationManager

A mechanism for cancelling blocking computation.

classtensorflow.python.eager.context.Context

Environment in which eager operations execute.

この情報について

掲載しているシグネチャは tensorflow/tensorflow の公開ソースコードを Python の ast モジュールで静的解析し、引数名・デフォルト値・型注釈・戻り値型をそのまま抽出したものです。実装コードは保存していません。詳しくは仕組みの解説をご覧ください。

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