code: def _execute_tensor(cls, ctx, op):
      (x,), device_id, xp = as_same_device(
          [ctx[inp.key] for inp in op.inputs],
          device=op.device,
          ret_extra=True,
      )
  
      with device(device_id):
          if issparse(x) and x.nnz == 0:
              x_min = 0
          else:
              x_min = xp.min(x)
  
          if x_min < 0:
              raise ValueError(op.err_msg)
  
          ctx[op.outputs[0].key] = np.array(True)
  
imports: import numpy
  from ...None import opcodes
  from ...None import tensor
  from ...core import ENTITY_TYPE, get_output_types, recursive_tile
  from ...core.operand import OperandStage
  from ...config import options
  from ...serialization.serializables import KeyField, StringField, BoolField, DataTypeField
  from ...tensor.core import TensorOrder, TENSOR_CHUNK_TYPE
  from ...tensor.array_utils import as_same_device, device, issparse, get_array_module
  from ...utils import ceildiv
  from ..operands import LearnOperand, LearnOperandMixin, OutputType
label_desc: Use image node_id 3 for calling the CheckNonNegative obj's underlying member method code with example usage: obj._execute_tensor(cls, ctx, op) without return types