::tensorflow::DumpMlirOpToFile(
        DEBUG_DATA_DUMPER()->GetDumpFilename(module_name.str(), kDebugGroupMain,
                                             dump_prefix.str() + "_after"),
        module, llvm::StringRef(), &bridge);
  }

  return diag_handler.ConsumeStatus();
}

tensorflow::Status RecordIfErrorStatus(const std::string error_prefix,

    ::tensorflow::DumpMlirOpToFile(DEBUG_DATA_DUMPER()->GetDumpFilename(
                                       module_name.str(), kDebugGroupMain,
                                       "_" + dump_prefix.str() + "_after"),
                                   module, llvm::StringRef(), &bridge);
  }

  return diag_handler.ConsumeStatus();
}

}  // namespace

    }
  }

  void runAfterPass(mlir::Pass* pass, mlir::Operation* op) override {
    if (RE2::FullMatch(pass->getName(), *dump_pass_re_)) {
      Dump(absl::StrCat(absl::string_view(pass->getName()), "_after"), op,
           absl::StrCat(absl::Hex(pass_counter_++, absl::kZeroPad8)));
    }
  }

 private:
  // Dumps the given op. `name` is used as part of the filename to help

      ::tensorflow::DumpMlirOpToFile(DEBUG_DATA_DUMPER()->GetDumpFilename(
                                         function_name, kDebugGroupMain,
                                         llvm::formatv("mlir_{0}_after", name)),
                                     *module_ref, llvm::StringRef(), nullptr);
    }
  }

  if (!is_module_updated) {
    VLOG(2) << "MLIR module is not updated. Using the original graph. "

private FastMap$EntryImpl _before; private FastMap$EntryImpl _after; private void FastMap$EntryImpl(); public Object getKey(); public Object getValue(); public Object setValue(Object); public boolean equals(Object); public int hashCode(); public String toString(); } org/codehaus/plexus/util/FastMap$EntrySet$1.class package org.codehaus.plexus.util; synchronized class FastMap$EntrySet$1 implements java.util.Iterator { FastMap$EntryImpl after; FastMap$EntryImpl before; void FastMap$EntrySet$1(FastMap$EntrySet);...

Slawomir Jaranowski <******@****.***> 1694625617 +0200

Guillaume Nodet <******@****.***> 1715601879 +0200

A. Unique TensorFlower <******@****.***> 1704479080 -0800

        then:
        result.groupedOutput.task(':a:log').output == 'Before\nAfter'
        result.groupedOutput.task(':a:log').outcome == 'FAILED'
        result.groupedOutput.task(':b:log').output == 'Interrupting output'
        result.groupedOutput.task(':b:log').outcome == null
    }

    def "long running task output are flushed after delay"() {
        server.start()

        given:
        buildFile << """

  // its outside. This may cause the op to fail to verify after the cluster is
  // outlined, as the constant operand is replaced by an argument.
  pm.addPass(mlir::createInlinerPass({}, NoCanonicalization));
  // Lift resource operations out of device computation. This step needs to be
  // done after inlining.
  pm.addPass(mlir::TFDevice::CreateResourceOpLiftingPass());