我正在C ++中定义一个新的自定义Op,它接受一个张量类型的属性和一个输入张量变量。操作码的摘录版本如下:
#include "tensorflow/core/framework/op.h"
#include "tensorflow/core/framework/op_kernel.h"
using namespace tensorflow;
REGISTER_OP("DoStuff")
.Attr("attr: tensor = { dtype: DT_FLOAT }")
.Input("in: float")
.Output("out: float");
class DoStuffOp : public OpKernel {
public:
explicit DoStuffOp(OpKernelConstruction *context) : OpKernel(context) {
OP_REQUIRES_OK(context, context->GetAttr("attr", &attr_));
// ...
}
void Compute(OpKernelContext *context) override {
// ...
}
private:
Tensor attr_;
};
REGISTER_KERNEL_BUILDER(Name("DoStuff").Device(DEVICE_CPU), DoStuffOp);
我可以将Op编译成.so文件。现在,将运行以下代码。
import tensorflow as tf
dostufflib = tf.load_op_library('build/do_stuff.so')
sess = tf.InteractiveSession()
sample_in = np.random.rand(3,3)
sample_in_t = tf.convert_to_tensor(sample_in, dtype=np.float32)
sample_atrr = np.zeros([3,3], dtype=np.float32)
sample_attr_t = tf.contrib.util.make_tensor_proto(sample_atrr)
Y = dostufflib.do_stuff(in=sample_in_t, attr=sample_attr_t)
但是,如果我尝试使用积极的执行模式,即
import tensorflow as tf
tf.compat.v1.enable_eager_execution()
dostufflib = tf.load_op_library('build/do_stuff.so')
sample_in = np.random.rand(3,3)
sample_in_t = tf.convert_to_tensor(sample_in, dtype=np.float32)
sample_atrr = np.zeros([3,3], dtype=np.float32)
sample_attr_t = tf.contrib.util.make_tensor_proto(sample_atrr)
Y = dostufflib.do_stuff(in=sample_in_t, attr=sample_attr_t)
出现以下错误,
tensorflow.python.framework.errors_impl.UnimplementedError: Attr sample_locs has unhandled type 6