RewriterConfigOrBuilder

 Arithmetic optimizations (default is ON)
 e.g. Simplify arithmetic ops; merge ops with same value (like constants).
 

 Arithmetic optimizations (default is ON)
 e.g. Simplify arithmetic ops; merge ops with same value (like constants).
 

 Optimize data types for CUDA (default is OFF).
 This will try to use float16 on GPU which is faster.
 Note that this can change the numerical stability of the graph and may
 require the use of loss scaling to maintain model convergence.
 

 Optimize data types for MKL (default is OFF).
 This will try to use bfloat16 on CPUs, which is faster.
 Note that this can change the numerical stability of the graph.
 

 Optimize data types for MKL (default is OFF).
 This will try to use bfloat16 on CPUs, which is faster.
 Note that this can change the numerical stability of the graph.
 

 Optimize data types for CUDA (default is OFF).
 This will try to use float16 on GPU which is faster.
 Note that this can change the numerical stability of the graph and may
 require the use of loss scaling to maintain model convergence.
 

 Configures AutoParallel optimization passes either through the
 meta-optimizer or when manually specified through the optimizers field.
 

 Configures AutoParallel optimization passes either through the
 meta-optimizer or when manually specified through the optimizers field.
 

 Common subgraph elimination (default is ON)
 e.g. Simplify arithmetic ops; merge ops with same value (like constants).
 

 Common subgraph elimination (default is ON)
 e.g. Simplify arithmetic ops; merge ops with same value (like constants).
 

 Fold constants (default is ON)
 Statically infer the value of tensors when possible, and materialize the
 result using constants.
 

 Fold constants (default is ON)
 Statically infer the value of tensors when possible, and materialize the
 result using constants.
 

 CPU Conversion settings between NHCW and NCHW.
 

 CPU Conversion settings between NHCW and NCHW.
 

 list of CustomGraphOptimizers to apply.
 

 list of CustomGraphOptimizers to apply.
 

 list of CustomGraphOptimizers to apply.
 

 list of CustomGraphOptimizers to apply.
 

 list of CustomGraphOptimizers to apply.
 

 Strips debug-related nodes from the graph (off by default).
 

 Strips debug-related nodes from the graph (off by default).
 

 Control dependency optimizations (default is ON).
 Remove redundant control dependencies, which may enable other optimization.
 

 Control dependency optimizations (default is ON).
 Remove redundant control dependencies, which may enable other optimization.
 

 Disable the entire meta optimizer (off by default).
 

 If true, don't remove unnecessary ops from the graph
 

 Disable optimizations that assume compressed tensors. Note that this flag
 is experimental and may be removed in the future.
 

 If true, any optimization pass failing will cause the MetaOptimizer to
 stop with an error. By default - or when set to false, failing passes are
 skipped silently.
 

 Function optimizations (default is ON).
 

 Function optimizations (default is ON).
 

 Enable the swap of kernel implementations based on the device placement
 (default is ON).
 

 Enable the swap of kernel implementations based on the device placement
 (default is ON).
 

 VerifierConfig specifying the verifiers to be run after every optimizer.
 

 VerifierConfig specifying the verifiers to be run after every optimizer.
 

 Optimize tensor layouts (default is ON)
 e.g. This will try to use NCHW layout on GPU which is faster.
 

 Optimize tensor layouts (default is ON)
 e.g. This will try to use NCHW layout on GPU which is faster.
 

 Loop optimizations (default is ON).
 

 Loop optimizations (default is ON).
 

 Configures memory optimization passes through the meta-optimizer. Has no
 effect on manually requested memory optimization passes in the optimizers
 field.
 

 Configures memory optimization passes through the meta-optimizer. Has no
 effect on manually requested memory optimization passes in the optimizers
 field.
 

 A node name scope for node names which are valid outputs of recomputations.
 Inputs to nodes that match this scope may be recomputed (subject either to
 manual annotation of those input nodes or to manual annotation and
 heuristics depending on memory_optimization), but the nodes themselves will
 not be recomputed. This matches any sub-scopes as well, meaning the scope
 can appear not just as a top-level scope. For example, if the value is
 "gradients/", the default, it will match node name "gradients/foo",
 "foo/gradients/bar", but not "foo_gradients/"
 

 A node name scope for node names which are valid outputs of recomputations.
 Inputs to nodes that match this scope may be recomputed (subject either to
 manual annotation of those input nodes or to manual annotation and
 heuristics depending on memory_optimization), but the nodes themselves will
 not be recomputed. This matches any sub-scopes as well, meaning the scope
 can appear not just as a top-level scope. For example, if the value is
 "gradients/", the default, it will match node name "gradients/foo",
 "foo/gradients/bar", but not "foo_gradients/"
 

 Controls how many times we run the optimizers in meta optimizer (default
 is once).
 

 Controls how many times we run the optimizers in meta optimizer (default
 is once).
 

 Maximum number of milliseconds to spend optimizing a single graph before
 timing out. If equal to 0 the system picks a default (currently 5 minutes).
 If less than 0 the optimizer will never time out.
 

 The minimum number of nodes in a graph to optimizer. For smaller graphs,
 optimization is skipped.
 0 means the system picks an appropriate number.
 < 0 means do not skip optimization.
 

 If non-empty, will use this as an alternative way to specify a list of
 optimizations to turn on and the order of the optimizations (replacing the
 meta-optimizer).
 Of the RewriterConfig options, only the AutoParallel configuration options
 (the auto_parallel field) apply to manually requested optimization passes
 ("autoparallel"). Memory optimization passes ("memory") invoked here are
 not configurable (in contrast to memory optimization passes through the
 meta-optimizer) and act only on manual op annotations.
 Custom optimizers (see custom_optimizers) that are not part of this
 schedule will be run after - in the order that they were specified.
 

 If non-empty, will use this as an alternative way to specify a list of
 optimizations to turn on and the order of the optimizations (replacing the
 meta-optimizer).
 Of the RewriterConfig options, only the AutoParallel configuration options
 (the auto_parallel field) apply to manually requested optimization passes
 ("autoparallel"). Memory optimization passes ("memory") invoked here are
 not configurable (in contrast to memory optimization passes through the
 meta-optimizer) and act only on manual op annotations.
 Custom optimizers (see custom_optimizers) that are not part of this
 schedule will be run after - in the order that they were specified.
 

 If non-empty, will use this as an alternative way to specify a list of
 optimizations to turn on and the order of the optimizations (replacing the
 meta-optimizer).
 Of the RewriterConfig options, only the AutoParallel configuration options
 (the auto_parallel field) apply to manually requested optimization passes
 ("autoparallel"). Memory optimization passes ("memory") invoked here are
 not configurable (in contrast to memory optimization passes through the
 meta-optimizer) and act only on manual op annotations.
 Custom optimizers (see custom_optimizers) that are not part of this
 schedule will be run after - in the order that they were specified.
 

 If non-empty, will use this as an alternative way to specify a list of
 optimizations to turn on and the order of the optimizations (replacing the
 meta-optimizer).
 Of the RewriterConfig options, only the AutoParallel configuration options
 (the auto_parallel field) apply to manually requested optimization passes
 ("autoparallel"). Memory optimization passes ("memory") invoked here are
 not configurable (in contrast to memory optimization passes through the
 meta-optimizer) and act only on manual op annotations.
 Custom optimizers (see custom_optimizers) that are not part of this
 schedule will be run after - in the order that they were specified.
 

 Force small ops onto the CPU (default is OFF).
 

 Force small ops onto the CPU (default is OFF).
 

 VerifierConfig specifying the verifiers to be run at the end, after all
 optimizers have run.
 

 VerifierConfig specifying the verifiers to be run at the end, after all
 optimizers have run.
 

 Remapping (default is ON)
 Remap subgraphs onto more efficient implementations.
 

 Remapping (default is ON)
 Remap subgraphs onto more efficient implementations.
 

 Try to allocate some independent Op outputs contiguously in order to
 merge or eliminate downstream Ops (off by default).
 

 Try to allocate some independent Op outputs contiguously in order to
 merge or eliminate downstream Ops (off by default).
 

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;

 Shape optimizations (default is ON)
 Simplify computations made on shapes.
 

 Shape optimizations (default is ON)
 Simplify computations made on shapes.
 

 Configures AutoParallel optimization passes either through the
 meta-optimizer or when manually specified through the optimizers field.
 

 VerifierConfig specifying the verifiers to be run after every optimizer.
 

 VerifierConfig specifying the verifiers to be run at the end, after all
 optimizers have run.
 

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;

 Arithmetic optimizations (default is ON)
 e.g. Simplify arithmetic ops; merge ops with same value (like constants).
 

 Arithmetic optimizations (default is ON)
 e.g. Simplify arithmetic ops; merge ops with same value (like constants).
 

 Optimize data types for CUDA (default is OFF).
 This will try to use float16 on GPU which is faster.
 Note that this can change the numerical stability of the graph and may
 require the use of loss scaling to maintain model convergence.
 

 Optimize data types for MKL (default is OFF).
 This will try to use bfloat16 on CPUs, which is faster.
 Note that this can change the numerical stability of the graph.
 

 Optimize data types for MKL (default is OFF).
 This will try to use bfloat16 on CPUs, which is faster.
 Note that this can change the numerical stability of the graph.
 

 Optimize data types for CUDA (default is OFF).
 This will try to use float16 on GPU which is faster.
 Note that this can change the numerical stability of the graph and may
 require the use of loss scaling to maintain model convergence.
 

 Configures AutoParallel optimization passes either through the
 meta-optimizer or when manually specified through the optimizers field.
 

 Configures AutoParallel optimization passes either through the
 meta-optimizer or when manually specified through the optimizers field.
 

 Common subgraph elimination (default is ON)
 e.g. Simplify arithmetic ops; merge ops with same value (like constants).
 

 Common subgraph elimination (default is ON)
 e.g. Simplify arithmetic ops; merge ops with same value (like constants).
 

 Fold constants (default is ON)
 Statically infer the value of tensors when possible, and materialize the
 result using constants.
 

 Fold constants (default is ON)
 Statically infer the value of tensors when possible, and materialize the
 result using constants.
 

 CPU Conversion settings between NHCW and NCHW.
 

 CPU Conversion settings between NHCW and NCHW.
 

 list of CustomGraphOptimizers to apply.
 

 list of CustomGraphOptimizers to apply.
 

 list of CustomGraphOptimizers to apply.
 

 list of CustomGraphOptimizers to apply.
 

 list of CustomGraphOptimizers to apply.
 

 Strips debug-related nodes from the graph (off by default).
 

 Strips debug-related nodes from the graph (off by default).
 

 Control dependency optimizations (default is ON).
 Remove redundant control dependencies, which may enable other optimization.
 

 Control dependency optimizations (default is ON).
 Remove redundant control dependencies, which may enable other optimization.
 

 Disable the entire meta optimizer (off by default).
 

 If true, don't remove unnecessary ops from the graph
 

 Disable optimizations that assume compressed tensors. Note that this flag
 is experimental and may be removed in the future.
 

 If true, any optimization pass failing will cause the MetaOptimizer to
 stop with an error. By default - or when set to false, failing passes are
 skipped silently.
 

 Function optimizations (default is ON).
 

 Function optimizations (default is ON).
 

 Enable the swap of kernel implementations based on the device placement
 (default is ON).
 

 Enable the swap of kernel implementations based on the device placement
 (default is ON).
 

 VerifierConfig specifying the verifiers to be run after every optimizer.
 

 VerifierConfig specifying the verifiers to be run after every optimizer.
 

 Optimize tensor layouts (default is ON)
 e.g. This will try to use NCHW layout on GPU which is faster.
 

 Optimize tensor layouts (default is ON)
 e.g. This will try to use NCHW layout on GPU which is faster.
 

 Loop optimizations (default is ON).
 

 Loop optimizations (default is ON).
 

 Configures memory optimization passes through the meta-optimizer. Has no
 effect on manually requested memory optimization passes in the optimizers
 field.
 

 Configures memory optimization passes through the meta-optimizer. Has no
 effect on manually requested memory optimization passes in the optimizers
 field.
 

 A node name scope for node names which are valid outputs of recomputations.
 Inputs to nodes that match this scope may be recomputed (subject either to
 manual annotation of those input nodes or to manual annotation and
 heuristics depending on memory_optimization), but the nodes themselves will
 not be recomputed. This matches any sub-scopes as well, meaning the scope
 can appear not just as a top-level scope. For example, if the value is
 "gradients/", the default, it will match node name "gradients/foo",
 "foo/gradients/bar", but not "foo_gradients/"
 

 A node name scope for node names which are valid outputs of recomputations.
 Inputs to nodes that match this scope may be recomputed (subject either to
 manual annotation of those input nodes or to manual annotation and
 heuristics depending on memory_optimization), but the nodes themselves will
 not be recomputed. This matches any sub-scopes as well, meaning the scope
 can appear not just as a top-level scope. For example, if the value is
 "gradients/", the default, it will match node name "gradients/foo",
 "foo/gradients/bar", but not "foo_gradients/"
 

 Controls how many times we run the optimizers in meta optimizer (default
 is once).
 

 Controls how many times we run the optimizers in meta optimizer (default
 is once).
 

 Maximum number of milliseconds to spend optimizing a single graph before
 timing out. If equal to 0 the system picks a default (currently 5 minutes).
 If less than 0 the optimizer will never time out.
 

 The minimum number of nodes in a graph to optimizer. For smaller graphs,
 optimization is skipped.
 0 means the system picks an appropriate number.
 < 0 means do not skip optimization.
 

 If non-empty, will use this as an alternative way to specify a list of
 optimizations to turn on and the order of the optimizations (replacing the
 meta-optimizer).
 Of the RewriterConfig options, only the AutoParallel configuration options
 (the auto_parallel field) apply to manually requested optimization passes
 ("autoparallel"). Memory optimization passes ("memory") invoked here are
 not configurable (in contrast to memory optimization passes through the
 meta-optimizer) and act only on manual op annotations.
 Custom optimizers (see custom_optimizers) that are not part of this
 schedule will be run after - in the order that they were specified.
 

 If non-empty, will use this as an alternative way to specify a list of
 optimizations to turn on and the order of the optimizations (replacing the
 meta-optimizer).
 Of the RewriterConfig options, only the AutoParallel configuration options
 (the auto_parallel field) apply to manually requested optimization passes
 ("autoparallel"). Memory optimization passes ("memory") invoked here are
 not configurable (in contrast to memory optimization passes through the
 meta-optimizer) and act only on manual op annotations.
 Custom optimizers (see custom_optimizers) that are not part of this
 schedule will be run after - in the order that they were specified.
 

 If non-empty, will use this as an alternative way to specify a list of
 optimizations to turn on and the order of the optimizations (replacing the
 meta-optimizer).
 Of the RewriterConfig options, only the AutoParallel configuration options
 (the auto_parallel field) apply to manually requested optimization passes
 ("autoparallel"). Memory optimization passes ("memory") invoked here are
 not configurable (in contrast to memory optimization passes through the
 meta-optimizer) and act only on manual op annotations.
 Custom optimizers (see custom_optimizers) that are not part of this
 schedule will be run after - in the order that they were specified.
 

 If non-empty, will use this as an alternative way to specify a list of
 optimizations to turn on and the order of the optimizations (replacing the
 meta-optimizer).
 Of the RewriterConfig options, only the AutoParallel configuration options
 (the auto_parallel field) apply to manually requested optimization passes
 ("autoparallel"). Memory optimization passes ("memory") invoked here are
 not configurable (in contrast to memory optimization passes through the
 meta-optimizer) and act only on manual op annotations.
 Custom optimizers (see custom_optimizers) that are not part of this
 schedule will be run after - in the order that they were specified.
 

 Force small ops onto the CPU (default is OFF).
 

 Force small ops onto the CPU (default is OFF).
 

 VerifierConfig specifying the verifiers to be run at the end, after all
 optimizers have run.
 

 VerifierConfig specifying the verifiers to be run at the end, after all
 optimizers have run.
 

 Remapping (default is ON)
 Remap subgraphs onto more efficient implementations.
 

 Remapping (default is ON)
 Remap subgraphs onto more efficient implementations.
 

 Try to allocate some independent Op outputs contiguously in order to
 merge or eliminate downstream Ops (off by default).
 

 Try to allocate some independent Op outputs contiguously in order to
 merge or eliminate downstream Ops (off by default).
 

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;

 Shape optimizations (default is ON)
 Simplify computations made on shapes.
 

 Shape optimizations (default is ON)
 Simplify computations made on shapes.
 

 Configures AutoParallel optimization passes either through the
 meta-optimizer or when manually specified through the optimizers field.
 

 VerifierConfig specifying the verifiers to be run after every optimizer.
 

 VerifierConfig specifying the verifiers to be run at the end, after all
 optimizers have run.
 

.tensorflow.ScopedAllocatorOptions scoped_allocator_opts = 16;