Python代码:
import os
import sys
from subprocess import check_call
import tensorflow as tf
CC_NAME = "tf-resource-op.cc"
SO_NAME = "tf-resource-op.so"
def compile_so():
use_cxx11_abi = hasattr(tf,'CXX11_ABI_flaG') and tf.CXX11_ABI_flaG
common_opts = ["-shared","-O2"]
common_opts += ["-std=c++11"]
if sys.platform == "darwin":
common_opts += ["-undefined","dynamic_lookup"]
tf_include = tf.sysconfig.get_include() # e.g. "...python2.7/site-packages/tensorflow/include"
tf_include_nsync = tf_include + "/external/nsync/public" # https://github.com/tensorflow/tensorflow/issues/2412
include_paths = [tf_include,tf_include_nsync]
for include_path in include_paths:
common_opts += ["-I",include_path]
common_opts += ["-fPIC","-v"]
common_opts += ["-D_GLIBCXX_USE_CXX11_ABI=%i" % (1 if use_cxx11_abi else 0)]
common_opts += ["-g"]
opts = common_opts + [CC_NAME,"-o",SO_NAME]
ld_flags = ["-L%s" % tf.sysconfig.get_lib(),"-ltensorflow_framework"]
opts += ld_flags
cmd_bin = "g++"
cmd_args = [cmd_bin] + opts
print("$ %s" % " ".join(cmd_args))
check_call(cmd_args)
def main():
if not os.path.exists(SO_NAME):
compile_so()
mod = tf.load_op_library(SO_NAME)
handle = mod.open_fst_load(filename="foo.bar")
new_states,scores = mod.open_fst_transition(handle=handle,inputs=[0],states=[0])
with tf.Session() as session:
# InternalError: ndarray was 1 bytes but TF_Tensor was 98 bytes
# print("fst:",session.run(handle))
out_new_states,out_scores = session.run((new_states,scores))
print("output new states:",out_new_states)
print("output scores:",out_scores)
# When session unloads,crashes with assertion:
# F .../site-packages/tensorflow/include/tensorflow/core/lib/core/refcount.h:79] Check failed: ref_.load() == 0 (1 vs. 0) # nopep8
if __name__ == '__main__':
import better_exchook
better_exchook.install()
main()
C ++代码:
#include <exception>
#include "tensorflow/core/framework/op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/shape_inference.h"
#include "tensorflow/core/framework/resource_mgr.h"
#include "tensorflow/core/framework/resource_op_kernel.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/platform/macros.h"
#include "tensorflow/core/platform/mutex.h"
#include "tensorflow/core/platform/types.h"
using namespace tensorflow;
REGISTER_OP("OpenFstLoad")
.Attr("filename: string")
.Attr("container: string = ''")
.Attr("shared_name: string = ''")
.Output("handle: resource")
.SetIsStateful()
.SetShapeFn(shape_inference::ScalarShape)
.Doc("OpenFstLoad: loads FST,creates TF resource,persistent across runs in the session");
REGISTER_OP("OpenFstTransition")
.Input("handle: resource")
.Input("states: int32")
.Input("inputs: int32")
.Output("new_states: int32")
.Output("scores: float32")
.SetShapeFn([](::tensorflow::shape_inference::InferenceContext* c) {
c->set_output(0,c->input(1));
c->set_output(1,c->input(1));
return Status::OK();
})
.Doc("OpenFstTransition: performs a transition");
struct OpenFstInstance : public ResourceBase {
explicit OpenFstInstance(const string& filename) : filename_(filename) {}
string DebugString() override {
return strings::StrCat("OpenFstInstance[",filename_,"]");
}
const string filename_;
};
// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/resource_op_kernel.h
// TFUtil.TFArrayContainer
class OpenFstLoadOp : public ResourceOpKernel<OpenFstInstance> {
public:
explicit OpenFstLoadOp(OpKernelConstruction* context)
: ResourceOpKernel(context) {
OP_REQUIRES_OK(context,context->Getattr("filename",&filename_));
}
private:
virtual bool IsCancellable() const { return false; }
virtual void Cancel() {}
Status CreateResource(OpenFstInstance** ret) override EXCLUSIVE_LOCKS_REQUIRED(mu_) {
try {
*ret = new OpenFstInstance(filename_);
} catch (std::exception& exc) {
return errors::Internal("Could not load OpenFst ",",exception: ",exc.what());
}
if(*ret == nullptr)
return errors::ResourceExhausted("Failed to allocate");
return Status::OK();
}
Status VerifyResource(OpenFstInstance* fst) override {
if(fst->filename_ != filename_)
return errors::InvalidArgument("Filename mismatch: expected "," but got ",fst->filename_,".");
return Status::OK();
}
string filename_;
};
REGISTER_KERNEL_BUILDER(Name("OpenFstLoad").Device(DEVICE_CPU),OpenFstLoadOp);
class OpenFstTransitionOp : public OpKernel {
public:
using OpKernel::OpKernel;
void Compute(OpKernelContext* context) override {
OpenFstInstance* fst;
OP_REQUIRES_OK(context,GetResourceFromContext(context,"handle",&fst));
core::ScopedUnref unref(fst);
const Tensor& states_tensor = context->input(1);
auto states_flat = states_tensor.flat<int32>();
const Tensor& inputs_tensor = context->input(2);
auto inputs_flat = inputs_tensor.flat<int32>();
OP_REQUIRES(
context,TensorShapeUtils::IsVector(states_tensor.shape()) &&
TensorShapeUtils::IsVector(inputs_tensor.shape()) &&
states_flat.size() == inputs_flat.size(),errors::InvalidArgument(
"Shape mismatch. states ",states_tensor.shape().DebugString()," vs inputs ",inputs_tensor.shape().DebugString()));
Tensor* output_new_states_tensor = NULL;
OP_REQUIRES_OK(context,context->allocate_output(0,states_tensor.shape(),&output_new_states_tensor));
auto output_new_states_flat = output_new_states_tensor->flat<int32>();
Tensor* output_scores_tensor = NULL;
OP_REQUIRES_OK(context,context->allocate_output(1,&output_scores_tensor));
auto output_scores_flat = output_scores_tensor->flat<float>();
for(int i = 0; i < inputs_flat.size(); ++i) {
output_new_states_flat(i) = -1; // TODO
output_scores_flat(i) = -1.; // TODO
}
}
};
REGISTER_KERNEL_BUILDER(Name("OpenFstTransition").Device(DEVICE_CPU),OpenFstTransitionOp);
一些问题:
运行print("fst:",session.run(handle))
会引发异常InternalError: ndarray was 1 bytes but TF_Tensor was 98 bytes
。为什么?什么意思?
当会话卸载时,它会因断言而崩溃:
F .../site-packages/tensorflow/include/tensorflow/core/lib/core/refcount.h:79] Check failed: ref_.load() == 0 (1 vs. 0)
。
堆栈跟踪:
2 libsystem_c.dylib 0x00007fff6687d1ae abort + 127
3 libtensorflow_framework.so 0x0000000107382e70 tensorflow::internal::LogMessageFatal::~LogMessageFatal() + 32
4 libtensorflow_framework.so 0x0000000107382e80 tensorflow::internal::LogMessageFatal::~LogMessageFatal() + 16
5 tf-resource-op.so 0x0000000128093d82 tensorflow::core::RefCounted::~RefCounted() + 162
6 tf-resource-op.so 0x0000000128095e2e OpenFstInstance::~OpenFstInstance() + 46 (tf-resource-op.cc:40)
7 libtensorflow_framework.so 0x000000010726a1f3 tensorflow::ResourceMgr::DoDelete(std::__1::basic_string<char,std::__1::char_traits<char>,std::__1::allocator<char> > const&,unsigned long long,std::__1::basic_string<char,std::__1::allocator<char> > const&) + 307
8 libtensorflow_framework.so 0x000000010726a433 tensorflow::ResourceMgr::DoDelete(std::__1::basic_string<char,std::__1::type_index,std::__1::allocator<char> > const&) + 99
9 tf-resource-op.so 0x000000012809457b tensorflow::ResourceOpKernel<OpenFstInstance>::~ResourceOpKernel() + 91 (resource_op_kernel.h:60)
10 tf-resource-op.so 0x0000000128094694 OpenFstLoadOp::~OpenFstLoadOp() + 52 (tf-resource-op.cc:53)
11 libtensorflow_framework.so 0x0000000107264d4f tensorflow::OpSegment::Item::~Item() + 63
12 libtensorflow_framework.so 0x000000010726558f tensorflow::OpSegment::RemoveHold(std::__1::basic_string<char,std::__1::allocator<char> > const&) + 303
13 _pywrap_tensorflow_internal.so 0x0000000113b7b712 tensorflow::DirectSession::~DirectSession() + 274
14 _pywrap_tensorflow_internal.so 0x0000000113b7bade tensorflow::DirectSession::~DirectSession() + 14
我猜想OpenFstInstance
对象的引用计数有些混乱。但为什么?我该如何解决?
(相关的是this question。)