""" @generated by mypy-protobuf. Do not edit manually! isort:skip_file """ import builtins import collections.abc import sys import google.protobuf.descriptor import google.protobuf.internal.containers import google.protobuf.message import tensorflow.core.framework.attr_value_pb2 import tensorflow.core.framework.full_type_pb2 if sys.version_info >= (3, 8): import typing as typing_extensions else: import typing_extensions DESCRIPTOR: google.protobuf.descriptor.FileDescriptor @typing_extensions.final class NodeDef(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor @typing_extensions.final class AttrEntry(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor KEY_FIELD_NUMBER: builtins.int VALUE_FIELD_NUMBER: builtins.int key: builtins.str @property def value(self) -> tensorflow.core.framework.attr_value_pb2.AttrValue: ... def __init__( self, *, key: builtins.str | None = ..., value: tensorflow.core.framework.attr_value_pb2.AttrValue | None = ..., ) -> None: ... def HasField(self, field_name: typing_extensions.Literal["value", b"value"]) -> builtins.bool: ... def ClearField(self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]) -> None: ... @typing_extensions.final class ExperimentalDebugInfo(google.protobuf.message.Message): DESCRIPTOR: google.protobuf.descriptor.Descriptor ORIGINAL_NODE_NAMES_FIELD_NUMBER: builtins.int ORIGINAL_FUNC_NAMES_FIELD_NUMBER: builtins.int @property def original_node_names(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """Opaque string inserted into error messages created by the runtime. This is intended to store the list of names of the nodes from the original graph that this node was derived. For example if this node, say C, was result of a fusion of 2 nodes A and B, then 'original_node' would be {A, B}. This information can be used to map errors originating at the current node to some top level source code. """ @property def original_func_names(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """This is intended to store the list of names of the functions from the original graph that this node was derived. For example if this node, say C, was result of a fusion of node A in function FA and node B in function FB, then `original_funcs` would be {FA, FB}. If the node is in the top level graph, the `original_func` is empty. This information, with the `original_node_names` can be used to map errors originating at the current ndoe to some top level source code. """ def __init__( self, *, original_node_names: collections.abc.Iterable[builtins.str] | None = ..., original_func_names: collections.abc.Iterable[builtins.str] | None = ..., ) -> None: ... def ClearField(self, field_name: typing_extensions.Literal["original_func_names", b"original_func_names", "original_node_names", b"original_node_names"]) -> None: ... NAME_FIELD_NUMBER: builtins.int OP_FIELD_NUMBER: builtins.int INPUT_FIELD_NUMBER: builtins.int DEVICE_FIELD_NUMBER: builtins.int ATTR_FIELD_NUMBER: builtins.int EXPERIMENTAL_DEBUG_INFO_FIELD_NUMBER: builtins.int EXPERIMENTAL_TYPE_FIELD_NUMBER: builtins.int name: builtins.str """The name given to this operator. Used for naming inputs, logging, visualization, etc. Unique within a single GraphDef. Must match the regexp "[A-Za-z0-9.][A-Za-z0-9_>./]*". """ op: builtins.str """The operation name. There may be custom parameters in attrs. Op names starting with an underscore are reserved for internal use. """ @property def input(self) -> google.protobuf.internal.containers.RepeatedScalarFieldContainer[builtins.str]: """Each input is "node:src_output" with "node" being a string name and "src_output" indicating which output tensor to use from "node". If "src_output" is 0 the ":0" suffix can be omitted. Regular inputs may optionally be followed by control inputs that have the format "^node". """ device: builtins.str """A (possibly partial) specification for the device on which this node should be placed. The expected syntax for this string is as follows: DEVICE_SPEC ::= PARTIAL_SPEC PARTIAL_SPEC ::= ("/" CONSTRAINT) * CONSTRAINT ::= ("job:" JOB_NAME) | ("replica:" [1-9][0-9]*) | ("task:" [1-9][0-9]*) | ("device:" [A-Za-z]* ":" ([1-9][0-9]* | "*") ) Valid values for this string include: * "/job:worker/replica:0/task:1/device:GPU:3" (full specification) * "/job:worker/device:GPU:3" (partial specification) * "" (no specification) If the constraints do not resolve to a single device (or if this field is empty or not present), the runtime will attempt to choose a device automatically. """ @property def attr(self) -> google.protobuf.internal.containers.MessageMap[builtins.str, tensorflow.core.framework.attr_value_pb2.AttrValue]: """Operation-specific graph-construction-time configuration. Note that this should include all attrs defined in the corresponding OpDef, including those with a value matching the default -- this allows the default to change and makes NodeDefs easier to interpret on their own. However, if an attr with a default is not specified in this list, the default will be used. The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and one of the names from the corresponding OpDef's attr field). The values must have a type matching the corresponding OpDef attr's type field. TODO(josh11b): Add some examples here showing best practices. """ @property def experimental_debug_info(self) -> global___NodeDef.ExperimentalDebugInfo: """This stores debug information associated with the node.""" @property def experimental_type(self) -> tensorflow.core.framework.full_type_pb2.FullTypeDef: """The complete type of this node. Experimental and subject to change. Currently, the field only contains the return types of the node. That will extend in the future to contain the entire signature of the node, as a function type. """ def __init__( self, *, name: builtins.str | None = ..., op: builtins.str | None = ..., input: collections.abc.Iterable[builtins.str] | None = ..., device: builtins.str | None = ..., attr: collections.abc.Mapping[builtins.str, tensorflow.core.framework.attr_value_pb2.AttrValue] | None = ..., experimental_debug_info: global___NodeDef.ExperimentalDebugInfo | None = ..., experimental_type: tensorflow.core.framework.full_type_pb2.FullTypeDef | None = ..., ) -> None: ... def HasField(self, field_name: typing_extensions.Literal["experimental_debug_info", b"experimental_debug_info", "experimental_type", b"experimental_type"]) -> builtins.bool: ... def ClearField(self, field_name: typing_extensions.Literal["attr", b"attr", "device", b"device", "experimental_debug_info", b"experimental_debug_info", "experimental_type", b"experimental_type", "input", b"input", "name", b"name", "op", b"op"]) -> None: ... global___NodeDef = NodeDef