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[XLA] Fix fallout from CompileOnlyClient et al refactoring. That change broke computation of constants in the XLA2TF bridge, for a couple of reasons, which are described in the comments adjacent to the fixes.

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Change: 155270959
This commit is contained in:
A. Unique TensorFlower 2017-05-05 21:07:29 -08:00 committed by TensorFlower Gardener
parent 166171df59
commit 1959ae333f
2 changed files with 21 additions and 16 deletions
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27
tensorflow/compiler/xla/service/compile_only_service.h
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@ -53,7 +53,10 @@ class CompileOnlyService : public Service {
const tensorflow::gtl::ArraySlice<AotComputationInstance> computations,
const AotCompilationOptions& Options);
// Override Service methods that require an execute backend.
// Override Service methods that require or imply the existence of an
// execute backend. Note that this does not include TransferToClient and
// TransferToClientInProcess, as computing contants produces global data
// that we may wish to transfer.
tensorflow::Status Execute(const ExecuteRequest* arg,
ExecuteResponse* result) override {
return Unimplemented("CompileOnlyService does not support execution.");
@ -76,35 +79,29 @@ class CompileOnlyService : public Service {
WaitForExecutionResponse* result) override {
return Unimplemented("CompileOnlyService does not support execution.");
}
tensorflow::Status TransferToClient(
const TransferToClientRequest* arg,
TransferToClientResponse* result) override {
return Unimplemented("CompileOnlyService does not support data transfers.");
}
tensorflow::Status TransferToClientInProcess(
const TransferToClientInProcessRequest* arg,
TransferToClientInProcessResponse* result) override {
return Unimplemented("CompileOnlyService does not support data transfers.");
}
tensorflow::Status TransferToServer(
const TransferToServerRequest* arg,
TransferToServerResponse* result) override {
return Unimplemented("CompileOnlyService does not support data transfers.");
return Unimplemented(
"CompileOnlyService does not support device data transfers.");
}
tensorflow::Status TransferToInfeed(
const TransferToInfeedRequest* arg,
TransferToInfeedResponse* result) override {
return Unimplemented("CompileOnlyService does not support data transfers.");
return Unimplemented(
"CompileOnlyService does not support device data transfers.");
}
tensorflow::Status TransferFromOutfeed(
const TransferFromOutfeedRequest* arg,
TransferFromOutfeedResponse* result) override {
return Unimplemented("CompileOnlyService does not support data transfers.");
return Unimplemented(
"CompileOnlyService does not support device data transfers.");
}
tensorflow::Status TransferToServerInProcess(
const TransferToServerInProcessRequest* arg,
TransferToServerInProcessResponse* result) override {
return Unimplemented("CompileOnlyService does not support data transfers.");
return Unimplemented(
"CompileOnlyService does not support device data transfers.");
}
tensorflow::Status ResetDevice(const ResetDeviceRequest* arg,
ResetDeviceResponse* result) override {

10
tensorflow/compiler/xla/service/service.cc
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@ -330,7 +330,15 @@ StatusOr<std::unique_ptr<HloModuleConfig>> Service::CreateModuleConfig(
module_config->enable_hlo_profiling(true);
}
module_config->set_replica_count(execute_backend_->Replicas().size());
// TODO(bmoses): Fix this properly. This value is wrong if we are creating a
// module for use with the compute_constant_backend_. However, so long as the
// execute_backend_ exists, it works out because we always use a CPU backend
// for the compute_constant_backend_ and CPU backends ignore this value. We
// do need to ensure that the execute_backend_ exists, however, to avoid a
// segfault when computing constants in a CompileOnlyService.
if (execute_backend_) {
module_config->set_replica_count(execute_backend_->Replicas().size());
}
module_config->set_fast_math_disabled(execution_options.disable_fast_math());
module_config->set_seed(execution_options.seed());