パブリック インターフェイスGraphOptionsOrBuilder
| 既知の間接サブクラス |
パブリックメソッド
| 抽象的な長い | getBuildCostModel () The number of steps to run before returning a cost model detailing the memory usage and performance of each node of the graph. |
| 抽象的な長い | getBuildCostModelAfter () The number of steps to skip before collecting statistics for the cost model. |
| 抽象ブール値 | getEnableBfloat16Sendrecv () If true, transfer float values between processes as bfloat16. |
| 抽象ブール値 | getEnableRecvScheduling () If true, use control flow to schedule the activation of Recv nodes. |
| 抽象ブール値 | getInferShapes () Annotate each Node with Op output shape data, to the extent it can be statically inferred. |
| 抽象的なオプティマイザーオプション | getOptimizerOptions () Options controlling how graph is optimized. |
| 抽象OptimizerOptionsOrBuilder | getOptimizerOptionsOrBuilder () Options controlling how graph is optimized. |
| 抽象ブール値 | getPlacePrunedGraph () Only place the subgraphs that are run, rather than the entire graph. |
| 抽象RewriterConfig | getRewriteOptions () Options that control the type and amount of graph rewriting. |
| 抽象RewriterConfigOrBuilder | getRewriteOptionsOrBuilder () Options that control the type and amount of graph rewriting. |
| 抽象整数 | getTimelineStep () If > 0, record a timeline every this many steps. |
| 抽象ブール値 | hasOptimizerOptions () Options controlling how graph is optimized. |
| 抽象ブール値 | hasRewriteOptions () Options that control the type and amount of graph rewriting. |
パブリックメソッド
パブリック抽象ロングgetBuildCostModel ()
The number of steps to run before returning a cost model detailing the memory usage and performance of each node of the graph. 0 means no cost model.
int64 build_cost_model = 4; パブリック抽象ロングgetBuildCostModelAfter ()
The number of steps to skip before collecting statistics for the cost model.
int64 build_cost_model_after = 9; パブリック抽象ブール値getEnableBfloat16Sendrecv ()
If true, transfer float values between processes as bfloat16.
bool enable_bfloat16_sendrecv = 7; public abstract boolean getEnableRecvScheduling ()
If true, use control flow to schedule the activation of Recv nodes. (Currently ignored.)
bool enable_recv_scheduling = 2; パブリック抽象ブール値getInferShapes ()
Annotate each Node with Op output shape data, to the extent it can be statically inferred.
bool infer_shapes = 5; public abstract OptimizerOptions getOptimizerOptions ()
Options controlling how graph is optimized.
.tensorflow.OptimizerOptions optimizer_options = 3; パブリック抽象OptimizerOptionsOrBuilder getOptimizerOptionsOrBuilder ()
Options controlling how graph is optimized.
.tensorflow.OptimizerOptions optimizer_options = 3; public abstract boolean getPlacePrunedGraph ()
Only place the subgraphs that are run, rather than the entire graph. This is useful for interactive graph building, where one might produce graphs that cannot be placed during the debugging process. In particular, it allows the client to continue work in a session after adding a node to a graph whose placement constraints are unsatisfiable.
bool place_pruned_graph = 6; public abstract RewriterConfig getRewriteOptions ()
Options that control the type and amount of graph rewriting. Not currently configurable via the public Python API (i.e. there is no API stability guarantee if you import RewriterConfig explicitly).
.tensorflow.RewriterConfig rewrite_options = 10; パブリック抽象RewriterConfigOrBuilder getRewriteOptionsOrBuilder ()
Options that control the type and amount of graph rewriting. Not currently configurable via the public Python API (i.e. there is no API stability guarantee if you import RewriterConfig explicitly).
.tensorflow.RewriterConfig rewrite_options = 10; public abstract int getTimelineStep ()
If > 0, record a timeline every this many steps. EXPERIMENTAL: This currently has no effect in MasterSession.
int32 timeline_step = 8; public abstract boolean hasOptimizerOptions ()
Options controlling how graph is optimized.
.tensorflow.OptimizerOptions optimizer_options = 3; public abstract boolean hasRewriteOptions ()
Options that control the type and amount of graph rewriting. Not currently configurable via the public Python API (i.e. there is no API stability guarantee if you import RewriterConfig explicitly).
.tensorflow.RewriterConfig rewrite_options = 10;