tensorflow:: ClientSession
#include <client_session.h>
A ClientSession
object lets the caller drive the evaluation of the TensorFlow graph constructed with the C++ API.
Summary
Example:
Scope root = Scope::NewRootScope(); auto a = Placeholder(root, DT_INT32); auto c = Add(root, a, {41}); ClientSession session(root); std::vectoroutputs; Status s = session.Run({ {a, {1} } }, {c}, &outputs); if (!s.ok()) { ... }
Constructors and Destructors |
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ClientSession(const Scope & scope, const string & target)
Create a new session to evaluate the graph contained in
scope by connecting to the TensorFlow runtime specified by target . |
|
ClientSession(const Scope & scope)
Same as above, but use the empty string ("") as the target specification.
|
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ClientSession(const Scope & scope, const SessionOptions & session_options)
Create a new session, configuring it with
session_options . |
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~ClientSession()
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Public types |
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CallableHandle
|
typedefint64_t
A handle to a subgraph, created with ClientSession::MakeCallable() . |
FeedType
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typedefstd::unordered_map< Output, Input::Initializer, OutputHash >
A data type to represent feeds to a Run call. |
Public functions |
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MakeCallable(const CallableOptions & callable_options, CallableHandle *out_handle)
|
Status
Creates a
handle for invoking the subgraph defined by callable_options . |
ReleaseCallable(CallableHandle handle)
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Status
Releases resources associated with the given
handle in this session. |
Run(const std::vector< Output > & fetch_outputs, std::vector< Tensor > *outputs) const
|
Status
Evaluate the tensors in
fetch_outputs . |
Run(const FeedType & inputs, const std::vector< Output > & fetch_outputs, std::vector< Tensor > *outputs) const
|
Status
Same as above, but use the mapping in
inputs as feeds. |
Run(const FeedType & inputs, const std::vector< Output > & fetch_outputs, const std::vector< Operation > & run_outputs, std::vector< Tensor > *outputs) const
|
Status
Same as above. Additionally runs the operations ins
run_outputs . |
Run(const RunOptions & run_options, const FeedType & inputs, const std::vector< Output > & fetch_outputs, const std::vector< Operation > & run_outputs, std::vector< Tensor > *outputs, RunMetadata *run_metadata) const
|
Status
Use
run_options to turn on performance profiling. |
Run(const RunOptions & run_options, const FeedType & inputs, const std::vector< Output > & fetch_outputs, const std::vector< Operation > & run_outputs, std::vector< Tensor > *outputs, RunMetadata *run_metadata, const thread::ThreadPoolOptions & threadpool_options) const
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Status
Same as above.
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RunCallable(CallableHandle handle, const std::vector< Tensor > & feed_tensors, std::vector< Tensor > *fetch_tensors, RunMetadata *run_metadata)
|
Status
Invokes the subgraph named by
handle with the given options and input tensors. |
RunCallable(CallableHandle handle, const std::vector< Tensor > & feed_tensors, std::vector< Tensor > *fetch_tensors, RunMetadata *run_metadata, const thread::ThreadPoolOptions & options)
|
Status
Invokes the subgraph named by
handle with the given options and input tensors. |
Public types
CallableHandle
int64_t CallableHandle
A handle to a subgraph, created with ClientSession::MakeCallable()
.
FeedType
std::unordered_map< Output, Input::Initializer, OutputHash > FeedType
A data type to represent feeds to a Run call.
This is a map of Output
objects returned by op-constructors to the value to feed them with. See Input::Initializer
for details on what can be used as feed values.
Public functions
ClientSession
ClientSession( const Scope & scope, const string & target )
Create a new session to evaluate the graph contained in scope
by connecting to the TensorFlow runtime specified by target
.
ClientSession
ClientSession( const Scope & scope )
Same as above, but use the empty string ("") as the target specification.
ClientSession
ClientSession( const Scope & scope, const SessionOptions & session_options )
Create a new session, configuring it with session_options
.
MakeCallable
Status MakeCallable( const CallableOptions & callable_options, CallableHandle *out_handle )
Creates a handle
for invoking the subgraph defined by callable_options
.
NOTE: This API is still experimental and may change.
ReleaseCallable
Status ReleaseCallable( CallableHandle handle )
Releases resources associated with the given handle
in this session.
NOTE: This API is still experimental and may change.
Run
Status Run( const std::vector< Output > & fetch_outputs, std::vector< Tensor > *outputs ) const
Evaluate the tensors in fetch_outputs
.
The values are returned as Tensor
objects in outputs
. The number and order of outputs
will match fetch_outputs
.
Run
Status Run( const FeedType & inputs, const std::vector< Output > & fetch_outputs, std::vector< Tensor > *outputs ) const
Same as above, but use the mapping in inputs
as feeds.
Run
Status Run( const FeedType & inputs, const std::vector< Output > & fetch_outputs, const std::vector< Operation > & run_outputs, std::vector< Tensor > *outputs ) const
Same as above. Additionally runs the operations ins run_outputs
.
Run
Status Run( const RunOptions & run_options, const FeedType & inputs, const std::vector< Output > & fetch_outputs, const std::vector< Operation > & run_outputs, std::vector< Tensor > *outputs, RunMetadata *run_metadata ) const
Use run_options
to turn on performance profiling.
run_metadata
, if not null, is filled in with the profiling results.
Run
Status Run( const RunOptions & run_options, const FeedType & inputs, const std::vector< Output > & fetch_outputs, const std::vector< Operation > & run_outputs, std::vector< Tensor > *outputs, RunMetadata *run_metadata, const thread::ThreadPoolOptions & threadpool_options ) const
Same as above.
Additionally allows user to provide custom threadpool implementation via ThreadPoolOptions.
RunCallable
Status RunCallable( CallableHandle handle, const std::vector< Tensor > & feed_tensors, std::vector< Tensor > *fetch_tensors, RunMetadata *run_metadata )
Invokes the subgraph named by handle
with the given options and input tensors.
The order of tensors in feed_tensors
must match the order of names in CallableOptions::feed()
and the order of tensors in fetch_tensors
will match the order of names in CallableOptions::fetch()
when this subgraph was created. NOTE: This API is still experimental and may change.
RunCallable
Status RunCallable( CallableHandle handle, const std::vector< Tensor > & feed_tensors, std::vector< Tensor > *fetch_tensors, RunMetadata *run_metadata, const thread::ThreadPoolOptions & options )
Invokes the subgraph named by handle
with the given options and input tensors.
The order of tensors in feed_tensors
must match the order of names in CallableOptions::feed()
and the order of tensors in fetch_tensors
will match the order of names in CallableOptions::fetch()
when this subgraph was created. NOTE: This API is still experimental and may change.
~ClientSession
~ClientSession()