TFE_DeleteContextOptions(opts);

  TFE_Op* var_op = TFE_NewOp(ctx, "VarHandleOp", status);
  TFE_OpSetAttrType(var_op, "dtype", TF_INT64);
  TFE_OpSetAttrShape(var_op, "shape", {}, 0, status);
  const TFE_OpAttrs* attributes = TFE_OpGetAttrs(var_op);

  TFE_Op* copy_op = TFE_NewOp(ctx, "VarHandleOp", status);
  TFE_OpSetAttrType(copy_op, "dtype", TF_FLOAT);
  TFE_OpAddAttrs(copy_op, attributes);
  unsigned char is_list = 0;

    TF_DeleteStatus(status);
    ASSERT_EQ(TF_OK, code) << status_msg;

    // Test op list.
    TF_Buffer op_list_buf = TF_GetOpList(lib);
    tensorflow::OpList op_list;
    EXPECT_TRUE(op_list.ParseFromArray(op_list_buf.data, op_list_buf.length));
    ASSERT_EQ(op_list.op_size(), 1);
    EXPECT_EQ("TestCApi1", op_list.op(0).name());
    TF_DeleteLibraryHandle(lib);
  }
#endif  // !defined(TENSORFLOW_NO_SHARED_OBJECTS)

  // Sanity check returned OpDef
  string data(static_cast<const char*>(buffer->data), buffer->length);
  OpDef op_def;
  op_def.ParseFromString(data);
  EXPECT_EQ(op_def.name(), func_name_);
  EXPECT_EQ(op_def.input_arg_size(), 1);
  EXPECT_EQ(op_def.output_arg_size(), 1);
  EXPECT_FALSE(op_def.is_stateful());

  TF_DeleteBuffer(buffer);
}

// Returns the serialized OpDef proto with name `op_name`, or a bad status if no
// such op exists. This can return OpDefs of functions copied into the graph.
TF_CAPI_EXPORT extern void TF_GraphGetOpDef(TF_Graph* graph,
                                            const char* op_name,
                                            TF_Buffer* output_op_def,
                                            TF_Status* status);

# addition to this core set of ops, user libraries which are loaded (via
# TF_LoadLibrary/tf.load_op_library) register their ops and kernels with this
# shared object directly.
#
# For example, from Python tf.load_op_library loads a custom op library (via
# dlopen() on Linux), the library finds libtensorflow_framework.so (no

build:mkl_aarch64_threadpool -c opt

# CUDA: This config refers to building CUDA op kernels with nvcc.
build:cuda --repo_env TF_NEED_CUDA=1
build:cuda --crosstool_top=@local_config_cuda//crosstool:toolchain
build:cuda --@local_config_cuda//:enable_cuda

# CUDA: This config refers to building CUDA op kernels with clang.
build:cuda_clang --config=cuda

              "unit": "short"
            },
            "overrides": [
              {
                "matcher": {
                  "id": "byValue",
                  "options": {
                    "op": "gte",
                    "reducer": "allIsZero",
                    "value": 0
                  }
                },
                "properties": [
                  {

  /// been fully persisted.
  ///
  /// DEFAULT IMPLEMENTATION: No op.
  void (*flush)(const TF_WritableFile* file, TF_Status* status);

  /// Syncs contents of `*file` with the filesystem.
  ///
  /// This call should block until filesystem confirms that all buffers have
  /// been flushed and persisted.
  ///
  /// DEFAULT IMPLEMENTATION: No op.
  void (*sync)(const TF_WritableFile* file, TF_Status* status);

		return nil, time.Time{}, err
	}
	defer f.Close()
	stat, err := f.Stat()
	if err != nil {
		return nil, time.Time{}, err
	}
	if stat.IsDir() {
		return nil, time.Time{}, &os.PathError{
			Op:   "open",
			Path: itemPath,
			Err:  syscall.EISDIR,
		}
	}
	buf, err := readXLMetaNoData(f, stat.Size())
	if err != nil {
		return nil, stat.ModTime().UTC(), fmt.Errorf("%w -> %s", err, itemPath)
	}

i&c&nanif!.oc,lpl??os??romem?tnedurp??n&if?oitanretni??t&i&gid!.sppaduolc:.nodnol,,?p&ac?soh???ned?ot???c!.&bog?lim?oc?topsgolb,vog???dil?e&datic?n&ahc?nahc!rehtaew???t!ria?tam??vart??f&8f&pbgo--nx?tbgm--nx??a?n??g!.&gro?moc?oc?ten?ude?xx,zib,??h&d?op??i!.&21k?ca?fdi?gro?inum?oc!.&egapvar,redrotibat,t&ibatym,opsgolb,???ten?vog??a&f?m&e!.psirc.no,?g?toh???m?r??l&a&b&esab?t&eksab!.&sua,zn,??oof???c?mt??e&d?hs??ihmailliw?j??m!.&esserp?gro?moc?ten?ude?v&og?uog????n!.&etisbew321,no&med,rtsic,?oc,pohs...