code: def execute(cls, ctx, op):
      inputs, device_id, xp = as_same_device(
          [ctx[c.key] for c in op.inputs],
          device=op.device,
          ret_extra=True,
      )
  
      a = inputs[0]
      if len(inputs) > 1:
          repeats = inputs[1]
      else:
          repeats = op.repeats
  
      with device(device_id):
          ctx[op.outputs[0].key] = xp.repeat(
              a, repeats=repeats, axis=op.axis
          )
  
imports: import itertools
  from numbers import Integral
  import numpy
  from ...None import opcodes
  from ...core import recursive_tile
  from ...serialization.serializables import KeyField, AnyField, Int32Field
  from ...utils import has_unknown_shape
  from ..core import Tensor, TENSOR_TYPE, TENSOR_CHUNK_TYPE, TensorOrder
  from ..utils import broadcast_shape, unify_chunks
  from ..operands import TensorHasInput, TensorOperandMixin
  from ..datasource import tensor
  from ..array_utils import as_same_device, device
  from .ravel import ravel
label_desc: Use image node_id 7 for calling the TensorRepeat obj's underlying member method code with example usage: obj.execute(cls, ctx, op) without return types