public final class ConfigProto extends org.nd4j.shade.protobuf.GeneratedMessageV3 implements ConfigProtoOrBuilder
Session configuration parameters. The system picks appropriate values for fields that are not set.Protobuf type
tensorflow.ConfigProto
Modifier and Type | Class and Description |
---|---|
static class |
ConfigProto.Builder
Session configuration parameters.
|
static class |
ConfigProto.Experimental
Everything inside Experimental is subject to change and is not subject
to API stability guarantees in
https://www.tensorflow.org/guide/version_compat.
|
static interface |
ConfigProto.ExperimentalOrBuilder |
org.nd4j.shade.protobuf.GeneratedMessageV3.BuilderParent, org.nd4j.shade.protobuf.GeneratedMessageV3.ExtendableBuilder<MessageType extends org.nd4j.shade.protobuf.GeneratedMessageV3.ExtendableMessage,BuilderType extends org.nd4j.shade.protobuf.GeneratedMessageV3.ExtendableBuilder<MessageType,BuilderType>>, org.nd4j.shade.protobuf.GeneratedMessageV3.ExtendableMessage<MessageType extends org.nd4j.shade.protobuf.GeneratedMessageV3.ExtendableMessage>, org.nd4j.shade.protobuf.GeneratedMessageV3.ExtendableMessageOrBuilder<MessageType extends org.nd4j.shade.protobuf.GeneratedMessageV3.ExtendableMessage>, org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTable, org.nd4j.shade.protobuf.GeneratedMessageV3.UnusedPrivateParameter
Modifier and Type | Field and Description |
---|---|
static int |
ALLOW_SOFT_PLACEMENT_FIELD_NUMBER |
static int |
CLUSTER_DEF_FIELD_NUMBER |
static int |
DEVICE_COUNT_FIELD_NUMBER |
static int |
DEVICE_FILTERS_FIELD_NUMBER |
static int |
EXPERIMENTAL_FIELD_NUMBER |
static int |
GPU_OPTIONS_FIELD_NUMBER |
static int |
GRAPH_OPTIONS_FIELD_NUMBER |
static int |
INTER_OP_PARALLELISM_THREADS_FIELD_NUMBER |
static int |
INTRA_OP_PARALLELISM_THREADS_FIELD_NUMBER |
static int |
ISOLATE_SESSION_STATE_FIELD_NUMBER |
static int |
LOG_DEVICE_PLACEMENT_FIELD_NUMBER |
static int |
OPERATION_TIMEOUT_IN_MS_FIELD_NUMBER |
static int |
PLACEMENT_PERIOD_FIELD_NUMBER |
static int |
RPC_OPTIONS_FIELD_NUMBER |
static int |
SESSION_INTER_OP_THREAD_POOL_FIELD_NUMBER |
static int |
USE_PER_SESSION_THREADS_FIELD_NUMBER |
Modifier and Type | Method and Description |
---|---|
boolean |
containsDeviceCount(String key)
Map from device type name (e.g., "CPU" or "GPU" ) to maximum
number of devices of that type to use.
|
boolean |
equals(Object obj) |
boolean |
getAllowSoftPlacement()
Whether soft placement is allowed.
|
ClusterDef |
getClusterDef()
Optional list of all workers to use in this session.
|
ClusterDefOrBuilder |
getClusterDefOrBuilder()
Optional list of all workers to use in this session.
|
static ConfigProto |
getDefaultInstance() |
ConfigProto |
getDefaultInstanceForType() |
static org.nd4j.shade.protobuf.Descriptors.Descriptor |
getDescriptor() |
Map<String,Integer> |
getDeviceCount()
Deprecated.
|
int |
getDeviceCountCount()
Map from device type name (e.g., "CPU" or "GPU" ) to maximum
number of devices of that type to use.
|
Map<String,Integer> |
getDeviceCountMap()
Map from device type name (e.g., "CPU" or "GPU" ) to maximum
number of devices of that type to use.
|
int |
getDeviceCountOrDefault(String key,
int defaultValue)
Map from device type name (e.g., "CPU" or "GPU" ) to maximum
number of devices of that type to use.
|
int |
getDeviceCountOrThrow(String key)
Map from device type name (e.g., "CPU" or "GPU" ) to maximum
number of devices of that type to use.
|
String |
getDeviceFilters(int index)
When any filters are present sessions will ignore all devices which do not
match the filters.
|
org.nd4j.shade.protobuf.ByteString |
getDeviceFiltersBytes(int index)
When any filters are present sessions will ignore all devices which do not
match the filters.
|
int |
getDeviceFiltersCount()
When any filters are present sessions will ignore all devices which do not
match the filters.
|
org.nd4j.shade.protobuf.ProtocolStringList |
getDeviceFiltersList()
When any filters are present sessions will ignore all devices which do not
match the filters.
|
ConfigProto.Experimental |
getExperimental()
.tensorflow.ConfigProto.Experimental experimental = 16; |
ConfigProto.ExperimentalOrBuilder |
getExperimentalOrBuilder()
.tensorflow.ConfigProto.Experimental experimental = 16; |
GPUOptions |
getGpuOptions()
Options that apply to all GPUs.
|
GPUOptionsOrBuilder |
getGpuOptionsOrBuilder()
Options that apply to all GPUs.
|
GraphOptions |
getGraphOptions()
Options that apply to all graphs.
|
GraphOptionsOrBuilder |
getGraphOptionsOrBuilder()
Options that apply to all graphs.
|
int |
getInterOpParallelismThreads()
Nodes that perform blocking operations are enqueued on a pool of
inter_op_parallelism_threads available in each process.
|
int |
getIntraOpParallelismThreads()
The execution of an individual op (for some op types) can be
parallelized on a pool of intra_op_parallelism_threads.
|
boolean |
getIsolateSessionState()
If true, any resources such as Variables used in the session will not be
shared with other sessions.
|
boolean |
getLogDevicePlacement()
Whether device placements should be logged.
|
long |
getOperationTimeoutInMs()
Global timeout for all blocking operations in this session.
|
org.nd4j.shade.protobuf.Parser<ConfigProto> |
getParserForType() |
int |
getPlacementPeriod()
Assignment of Nodes to Devices is recomputed every placement_period
steps until the system warms up (at which point the recomputation
typically slows down automatically).
|
RPCOptions |
getRpcOptions()
Options that apply when this session uses the distributed runtime.
|
RPCOptionsOrBuilder |
getRpcOptionsOrBuilder()
Options that apply when this session uses the distributed runtime.
|
int |
getSerializedSize() |
ThreadPoolOptionProto |
getSessionInterOpThreadPool(int index)
This option is experimental - it may be replaced with a different mechanism
in the future.
|
int |
getSessionInterOpThreadPoolCount()
This option is experimental - it may be replaced with a different mechanism
in the future.
|
List<ThreadPoolOptionProto> |
getSessionInterOpThreadPoolList()
This option is experimental - it may be replaced with a different mechanism
in the future.
|
ThreadPoolOptionProtoOrBuilder |
getSessionInterOpThreadPoolOrBuilder(int index)
This option is experimental - it may be replaced with a different mechanism
in the future.
|
List<? extends ThreadPoolOptionProtoOrBuilder> |
getSessionInterOpThreadPoolOrBuilderList()
This option is experimental - it may be replaced with a different mechanism
in the future.
|
org.nd4j.shade.protobuf.UnknownFieldSet |
getUnknownFields() |
boolean |
getUsePerSessionThreads()
If true, use a new set of threads for this session rather than the global
pool of threads.
|
boolean |
hasClusterDef()
Optional list of all workers to use in this session.
|
boolean |
hasExperimental()
.tensorflow.ConfigProto.Experimental experimental = 16; |
boolean |
hasGpuOptions()
Options that apply to all GPUs.
|
boolean |
hasGraphOptions()
Options that apply to all graphs.
|
int |
hashCode() |
boolean |
hasRpcOptions()
Options that apply when this session uses the distributed runtime.
|
protected org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTable |
internalGetFieldAccessorTable() |
protected org.nd4j.shade.protobuf.MapField |
internalGetMapField(int number) |
boolean |
isInitialized() |
static ConfigProto.Builder |
newBuilder() |
static ConfigProto.Builder |
newBuilder(ConfigProto prototype) |
ConfigProto.Builder |
newBuilderForType() |
protected ConfigProto.Builder |
newBuilderForType(org.nd4j.shade.protobuf.GeneratedMessageV3.BuilderParent parent) |
protected Object |
newInstance(org.nd4j.shade.protobuf.GeneratedMessageV3.UnusedPrivateParameter unused) |
static ConfigProto |
parseDelimitedFrom(InputStream input) |
static ConfigProto |
parseDelimitedFrom(InputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) |
static ConfigProto |
parseFrom(byte[] data) |
static ConfigProto |
parseFrom(byte[] data,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) |
static ConfigProto |
parseFrom(ByteBuffer data) |
static ConfigProto |
parseFrom(ByteBuffer data,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) |
static ConfigProto |
parseFrom(org.nd4j.shade.protobuf.ByteString data) |
static ConfigProto |
parseFrom(org.nd4j.shade.protobuf.ByteString data,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) |
static ConfigProto |
parseFrom(org.nd4j.shade.protobuf.CodedInputStream input) |
static ConfigProto |
parseFrom(org.nd4j.shade.protobuf.CodedInputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) |
static ConfigProto |
parseFrom(InputStream input) |
static ConfigProto |
parseFrom(InputStream input,
org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) |
static org.nd4j.shade.protobuf.Parser<ConfigProto> |
parser() |
ConfigProto.Builder |
toBuilder() |
void |
writeTo(org.nd4j.shade.protobuf.CodedOutputStream output) |
canUseUnsafe, computeStringSize, computeStringSizeNoTag, emptyBooleanList, emptyDoubleList, emptyFloatList, emptyIntList, emptyLongList, getAllFields, getDescriptorForType, getField, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, hasField, hasOneof, makeExtensionsImmutable, mutableCopy, mutableCopy, mutableCopy, mutableCopy, mutableCopy, newBooleanList, newBuilderForType, newDoubleList, newFloatList, newIntList, newLongList, parseDelimitedWithIOException, parseDelimitedWithIOException, parseUnknownField, parseUnknownFieldProto3, parseWithIOException, parseWithIOException, parseWithIOException, parseWithIOException, serializeBooleanMapTo, serializeIntegerMapTo, serializeLongMapTo, serializeStringMapTo, writeReplace, writeString, writeStringNoTag
findInitializationErrors, getInitializationErrorString, hashBoolean, hashEnum, hashEnumList, hashFields, hashLong, toString
addAll, addAll, checkByteStringIsUtf8, getSerializedSizeInternal, isInitializedInternal, makeImmutableInternal, mergeFromInternal, toByteArray, toByteString, writeDelimitedTo, writeTo, writeToInternal
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
public static final int DEVICE_COUNT_FIELD_NUMBER
public static final int INTRA_OP_PARALLELISM_THREADS_FIELD_NUMBER
public static final int INTER_OP_PARALLELISM_THREADS_FIELD_NUMBER
public static final int USE_PER_SESSION_THREADS_FIELD_NUMBER
public static final int SESSION_INTER_OP_THREAD_POOL_FIELD_NUMBER
public static final int PLACEMENT_PERIOD_FIELD_NUMBER
public static final int DEVICE_FILTERS_FIELD_NUMBER
public static final int GPU_OPTIONS_FIELD_NUMBER
public static final int ALLOW_SOFT_PLACEMENT_FIELD_NUMBER
public static final int LOG_DEVICE_PLACEMENT_FIELD_NUMBER
public static final int GRAPH_OPTIONS_FIELD_NUMBER
public static final int OPERATION_TIMEOUT_IN_MS_FIELD_NUMBER
public static final int RPC_OPTIONS_FIELD_NUMBER
public static final int CLUSTER_DEF_FIELD_NUMBER
public static final int ISOLATE_SESSION_STATE_FIELD_NUMBER
public static final int EXPERIMENTAL_FIELD_NUMBER
protected Object newInstance(org.nd4j.shade.protobuf.GeneratedMessageV3.UnusedPrivateParameter unused)
newInstance
in class org.nd4j.shade.protobuf.GeneratedMessageV3
public final org.nd4j.shade.protobuf.UnknownFieldSet getUnknownFields()
getUnknownFields
in interface org.nd4j.shade.protobuf.MessageOrBuilder
getUnknownFields
in class org.nd4j.shade.protobuf.GeneratedMessageV3
public static final org.nd4j.shade.protobuf.Descriptors.Descriptor getDescriptor()
protected org.nd4j.shade.protobuf.MapField internalGetMapField(int number)
internalGetMapField
in class org.nd4j.shade.protobuf.GeneratedMessageV3
protected org.nd4j.shade.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
internalGetFieldAccessorTable
in class org.nd4j.shade.protobuf.GeneratedMessageV3
public int getDeviceCountCount()
ConfigProtoOrBuilder
Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use. If a particular device type is not found in the map, the system picks an appropriate number.
map<string, int32> device_count = 1;
getDeviceCountCount
in interface ConfigProtoOrBuilder
public boolean containsDeviceCount(String key)
Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use. If a particular device type is not found in the map, the system picks an appropriate number.
map<string, int32> device_count = 1;
containsDeviceCount
in interface ConfigProtoOrBuilder
@Deprecated public Map<String,Integer> getDeviceCount()
getDeviceCountMap()
instead.getDeviceCount
in interface ConfigProtoOrBuilder
public Map<String,Integer> getDeviceCountMap()
Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use. If a particular device type is not found in the map, the system picks an appropriate number.
map<string, int32> device_count = 1;
getDeviceCountMap
in interface ConfigProtoOrBuilder
public int getDeviceCountOrDefault(String key, int defaultValue)
Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use. If a particular device type is not found in the map, the system picks an appropriate number.
map<string, int32> device_count = 1;
getDeviceCountOrDefault
in interface ConfigProtoOrBuilder
public int getDeviceCountOrThrow(String key)
Map from device type name (e.g., "CPU" or "GPU" ) to maximum number of devices of that type to use. If a particular device type is not found in the map, the system picks an appropriate number.
map<string, int32> device_count = 1;
getDeviceCountOrThrow
in interface ConfigProtoOrBuilder
public int getIntraOpParallelismThreads()
The execution of an individual op (for some op types) can be parallelized on a pool of intra_op_parallelism_threads. 0 means the system picks an appropriate number.
int32 intra_op_parallelism_threads = 2;
getIntraOpParallelismThreads
in interface ConfigProtoOrBuilder
public int getInterOpParallelismThreads()
Nodes that perform blocking operations are enqueued on a pool of inter_op_parallelism_threads available in each process. 0 means the system picks an appropriate number. Note that the first Session created in the process sets the number of threads for all future sessions unless use_per_session_threads is true or session_inter_op_thread_pool is configured.
int32 inter_op_parallelism_threads = 5;
getInterOpParallelismThreads
in interface ConfigProtoOrBuilder
public boolean getUsePerSessionThreads()
If true, use a new set of threads for this session rather than the global pool of threads. Only supported by direct sessions. If false, use the global threads created by the first session, or the per-session thread pools configured by session_inter_op_thread_pool. This option is deprecated. The same effect can be achieved by setting session_inter_op_thread_pool to have one element, whose num_threads equals inter_op_parallelism_threads.
bool use_per_session_threads = 9;
getUsePerSessionThreads
in interface ConfigProtoOrBuilder
public List<ThreadPoolOptionProto> getSessionInterOpThreadPoolList()
This option is experimental - it may be replaced with a different mechanism in the future. Configures session thread pools. If this is configured, then RunOptions for a Run call can select the thread pool to use. The intended use is for when some session invocations need to run in a background pool limited to a small number of threads: - For example, a session may be configured to have one large pool (for regular compute) and one small pool (for periodic, low priority work); using the small pool is currently the mechanism for limiting the inter-op parallelism of the low priority work. Note that it does not limit the parallelism of work spawned by a single op kernel implementation. - Using this setting is normally not needed in training, but may help some serving use cases. - It is also generally recommended to set the global_name field of this proto, to avoid creating multiple large pools. It is typically better to run the non-low-priority work, even across sessions, in a single large pool.
repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12;
getSessionInterOpThreadPoolList
in interface ConfigProtoOrBuilder
public List<? extends ThreadPoolOptionProtoOrBuilder> getSessionInterOpThreadPoolOrBuilderList()
This option is experimental - it may be replaced with a different mechanism in the future. Configures session thread pools. If this is configured, then RunOptions for a Run call can select the thread pool to use. The intended use is for when some session invocations need to run in a background pool limited to a small number of threads: - For example, a session may be configured to have one large pool (for regular compute) and one small pool (for periodic, low priority work); using the small pool is currently the mechanism for limiting the inter-op parallelism of the low priority work. Note that it does not limit the parallelism of work spawned by a single op kernel implementation. - Using this setting is normally not needed in training, but may help some serving use cases. - It is also generally recommended to set the global_name field of this proto, to avoid creating multiple large pools. It is typically better to run the non-low-priority work, even across sessions, in a single large pool.
repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12;
getSessionInterOpThreadPoolOrBuilderList
in interface ConfigProtoOrBuilder
public int getSessionInterOpThreadPoolCount()
This option is experimental - it may be replaced with a different mechanism in the future. Configures session thread pools. If this is configured, then RunOptions for a Run call can select the thread pool to use. The intended use is for when some session invocations need to run in a background pool limited to a small number of threads: - For example, a session may be configured to have one large pool (for regular compute) and one small pool (for periodic, low priority work); using the small pool is currently the mechanism for limiting the inter-op parallelism of the low priority work. Note that it does not limit the parallelism of work spawned by a single op kernel implementation. - Using this setting is normally not needed in training, but may help some serving use cases. - It is also generally recommended to set the global_name field of this proto, to avoid creating multiple large pools. It is typically better to run the non-low-priority work, even across sessions, in a single large pool.
repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12;
getSessionInterOpThreadPoolCount
in interface ConfigProtoOrBuilder
public ThreadPoolOptionProto getSessionInterOpThreadPool(int index)
This option is experimental - it may be replaced with a different mechanism in the future. Configures session thread pools. If this is configured, then RunOptions for a Run call can select the thread pool to use. The intended use is for when some session invocations need to run in a background pool limited to a small number of threads: - For example, a session may be configured to have one large pool (for regular compute) and one small pool (for periodic, low priority work); using the small pool is currently the mechanism for limiting the inter-op parallelism of the low priority work. Note that it does not limit the parallelism of work spawned by a single op kernel implementation. - Using this setting is normally not needed in training, but may help some serving use cases. - It is also generally recommended to set the global_name field of this proto, to avoid creating multiple large pools. It is typically better to run the non-low-priority work, even across sessions, in a single large pool.
repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12;
getSessionInterOpThreadPool
in interface ConfigProtoOrBuilder
public ThreadPoolOptionProtoOrBuilder getSessionInterOpThreadPoolOrBuilder(int index)
This option is experimental - it may be replaced with a different mechanism in the future. Configures session thread pools. If this is configured, then RunOptions for a Run call can select the thread pool to use. The intended use is for when some session invocations need to run in a background pool limited to a small number of threads: - For example, a session may be configured to have one large pool (for regular compute) and one small pool (for periodic, low priority work); using the small pool is currently the mechanism for limiting the inter-op parallelism of the low priority work. Note that it does not limit the parallelism of work spawned by a single op kernel implementation. - Using this setting is normally not needed in training, but may help some serving use cases. - It is also generally recommended to set the global_name field of this proto, to avoid creating multiple large pools. It is typically better to run the non-low-priority work, even across sessions, in a single large pool.
repeated .tensorflow.ThreadPoolOptionProto session_inter_op_thread_pool = 12;
getSessionInterOpThreadPoolOrBuilder
in interface ConfigProtoOrBuilder
public int getPlacementPeriod()
Assignment of Nodes to Devices is recomputed every placement_period steps until the system warms up (at which point the recomputation typically slows down automatically).
int32 placement_period = 3;
getPlacementPeriod
in interface ConfigProtoOrBuilder
public org.nd4j.shade.protobuf.ProtocolStringList getDeviceFiltersList()
When any filters are present sessions will ignore all devices which do not match the filters. Each filter can be partially specified, e.g. "/job:ps" "/job:worker/replica:3", etc.
repeated string device_filters = 4;
getDeviceFiltersList
in interface ConfigProtoOrBuilder
public int getDeviceFiltersCount()
When any filters are present sessions will ignore all devices which do not match the filters. Each filter can be partially specified, e.g. "/job:ps" "/job:worker/replica:3", etc.
repeated string device_filters = 4;
getDeviceFiltersCount
in interface ConfigProtoOrBuilder
public String getDeviceFilters(int index)
When any filters are present sessions will ignore all devices which do not match the filters. Each filter can be partially specified, e.g. "/job:ps" "/job:worker/replica:3", etc.
repeated string device_filters = 4;
getDeviceFilters
in interface ConfigProtoOrBuilder
public org.nd4j.shade.protobuf.ByteString getDeviceFiltersBytes(int index)
When any filters are present sessions will ignore all devices which do not match the filters. Each filter can be partially specified, e.g. "/job:ps" "/job:worker/replica:3", etc.
repeated string device_filters = 4;
getDeviceFiltersBytes
in interface ConfigProtoOrBuilder
public boolean hasGpuOptions()
Options that apply to all GPUs.
.tensorflow.GPUOptions gpu_options = 6;
hasGpuOptions
in interface ConfigProtoOrBuilder
public GPUOptions getGpuOptions()
Options that apply to all GPUs.
.tensorflow.GPUOptions gpu_options = 6;
getGpuOptions
in interface ConfigProtoOrBuilder
public GPUOptionsOrBuilder getGpuOptionsOrBuilder()
Options that apply to all GPUs.
.tensorflow.GPUOptions gpu_options = 6;
getGpuOptionsOrBuilder
in interface ConfigProtoOrBuilder
public boolean getAllowSoftPlacement()
Whether soft placement is allowed. If allow_soft_placement is true, an op will be placed on CPU if 1. there's no GPU implementation for the OP or 2. no GPU devices are known or registered or 3. need to co-locate with reftype input(s) which are from CPU.
bool allow_soft_placement = 7;
getAllowSoftPlacement
in interface ConfigProtoOrBuilder
public boolean getLogDevicePlacement()
Whether device placements should be logged.
bool log_device_placement = 8;
getLogDevicePlacement
in interface ConfigProtoOrBuilder
public boolean hasGraphOptions()
Options that apply to all graphs.
.tensorflow.GraphOptions graph_options = 10;
hasGraphOptions
in interface ConfigProtoOrBuilder
public GraphOptions getGraphOptions()
Options that apply to all graphs.
.tensorflow.GraphOptions graph_options = 10;
getGraphOptions
in interface ConfigProtoOrBuilder
public GraphOptionsOrBuilder getGraphOptionsOrBuilder()
Options that apply to all graphs.
.tensorflow.GraphOptions graph_options = 10;
getGraphOptionsOrBuilder
in interface ConfigProtoOrBuilder
public long getOperationTimeoutInMs()
Global timeout for all blocking operations in this session. If non-zero, and not overridden on a per-operation basis, this value will be used as the deadline for all blocking operations.
int64 operation_timeout_in_ms = 11;
getOperationTimeoutInMs
in interface ConfigProtoOrBuilder
public boolean hasRpcOptions()
Options that apply when this session uses the distributed runtime.
.tensorflow.RPCOptions rpc_options = 13;
hasRpcOptions
in interface ConfigProtoOrBuilder
public RPCOptions getRpcOptions()
Options that apply when this session uses the distributed runtime.
.tensorflow.RPCOptions rpc_options = 13;
getRpcOptions
in interface ConfigProtoOrBuilder
public RPCOptionsOrBuilder getRpcOptionsOrBuilder()
Options that apply when this session uses the distributed runtime.
.tensorflow.RPCOptions rpc_options = 13;
getRpcOptionsOrBuilder
in interface ConfigProtoOrBuilder
public boolean hasClusterDef()
Optional list of all workers to use in this session.
.tensorflow.ClusterDef cluster_def = 14;
hasClusterDef
in interface ConfigProtoOrBuilder
public ClusterDef getClusterDef()
Optional list of all workers to use in this session.
.tensorflow.ClusterDef cluster_def = 14;
getClusterDef
in interface ConfigProtoOrBuilder
public ClusterDefOrBuilder getClusterDefOrBuilder()
Optional list of all workers to use in this session.
.tensorflow.ClusterDef cluster_def = 14;
getClusterDefOrBuilder
in interface ConfigProtoOrBuilder
public boolean getIsolateSessionState()
If true, any resources such as Variables used in the session will not be shared with other sessions.
bool isolate_session_state = 15;
getIsolateSessionState
in interface ConfigProtoOrBuilder
public boolean hasExperimental()
.tensorflow.ConfigProto.Experimental experimental = 16;
hasExperimental
in interface ConfigProtoOrBuilder
public ConfigProto.Experimental getExperimental()
.tensorflow.ConfigProto.Experimental experimental = 16;
getExperimental
in interface ConfigProtoOrBuilder
public ConfigProto.ExperimentalOrBuilder getExperimentalOrBuilder()
.tensorflow.ConfigProto.Experimental experimental = 16;
getExperimentalOrBuilder
in interface ConfigProtoOrBuilder
public final boolean isInitialized()
isInitialized
in interface org.nd4j.shade.protobuf.MessageLiteOrBuilder
isInitialized
in class org.nd4j.shade.protobuf.GeneratedMessageV3
public void writeTo(org.nd4j.shade.protobuf.CodedOutputStream output) throws IOException
writeTo
in interface org.nd4j.shade.protobuf.MessageLite
writeTo
in class org.nd4j.shade.protobuf.GeneratedMessageV3
IOException
public int getSerializedSize()
getSerializedSize
in interface org.nd4j.shade.protobuf.MessageLite
getSerializedSize
in class org.nd4j.shade.protobuf.GeneratedMessageV3
public boolean equals(Object obj)
equals
in interface org.nd4j.shade.protobuf.Message
equals
in class org.nd4j.shade.protobuf.AbstractMessage
public int hashCode()
hashCode
in interface org.nd4j.shade.protobuf.Message
hashCode
in class org.nd4j.shade.protobuf.AbstractMessage
public static ConfigProto parseFrom(ByteBuffer data) throws org.nd4j.shade.protobuf.InvalidProtocolBufferException
org.nd4j.shade.protobuf.InvalidProtocolBufferException
public static ConfigProto parseFrom(ByteBuffer data, org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) throws org.nd4j.shade.protobuf.InvalidProtocolBufferException
org.nd4j.shade.protobuf.InvalidProtocolBufferException
public static ConfigProto parseFrom(org.nd4j.shade.protobuf.ByteString data) throws org.nd4j.shade.protobuf.InvalidProtocolBufferException
org.nd4j.shade.protobuf.InvalidProtocolBufferException
public static ConfigProto parseFrom(org.nd4j.shade.protobuf.ByteString data, org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) throws org.nd4j.shade.protobuf.InvalidProtocolBufferException
org.nd4j.shade.protobuf.InvalidProtocolBufferException
public static ConfigProto parseFrom(byte[] data) throws org.nd4j.shade.protobuf.InvalidProtocolBufferException
org.nd4j.shade.protobuf.InvalidProtocolBufferException
public static ConfigProto parseFrom(byte[] data, org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) throws org.nd4j.shade.protobuf.InvalidProtocolBufferException
org.nd4j.shade.protobuf.InvalidProtocolBufferException
public static ConfigProto parseFrom(InputStream input) throws IOException
IOException
public static ConfigProto parseFrom(InputStream input, org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
IOException
public static ConfigProto parseDelimitedFrom(InputStream input) throws IOException
IOException
public static ConfigProto parseDelimitedFrom(InputStream input, org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
IOException
public static ConfigProto parseFrom(org.nd4j.shade.protobuf.CodedInputStream input) throws IOException
IOException
public static ConfigProto parseFrom(org.nd4j.shade.protobuf.CodedInputStream input, org.nd4j.shade.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
IOException
public ConfigProto.Builder newBuilderForType()
newBuilderForType
in interface org.nd4j.shade.protobuf.Message
newBuilderForType
in interface org.nd4j.shade.protobuf.MessageLite
public static ConfigProto.Builder newBuilder()
public static ConfigProto.Builder newBuilder(ConfigProto prototype)
public ConfigProto.Builder toBuilder()
toBuilder
in interface org.nd4j.shade.protobuf.Message
toBuilder
in interface org.nd4j.shade.protobuf.MessageLite
protected ConfigProto.Builder newBuilderForType(org.nd4j.shade.protobuf.GeneratedMessageV3.BuilderParent parent)
newBuilderForType
in class org.nd4j.shade.protobuf.GeneratedMessageV3
public static ConfigProto getDefaultInstance()
public static org.nd4j.shade.protobuf.Parser<ConfigProto> parser()
public org.nd4j.shade.protobuf.Parser<ConfigProto> getParserForType()
getParserForType
in interface org.nd4j.shade.protobuf.Message
getParserForType
in interface org.nd4j.shade.protobuf.MessageLite
getParserForType
in class org.nd4j.shade.protobuf.GeneratedMessageV3
public ConfigProto getDefaultInstanceForType()
getDefaultInstanceForType
in interface org.nd4j.shade.protobuf.MessageLiteOrBuilder
getDefaultInstanceForType
in interface org.nd4j.shade.protobuf.MessageOrBuilder
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