code: def tcase_gi(
      self,
      i,
      f,
      o,
      s,
      b,
      flip,
      provide_shape,
      fd=(1, 1),
      expect_error=False,
  ):
      if not dnn_available(test_ctx_name):
          raise SkipTest(dnn_available.msg)
      if fd != (1, 1):
          raise SkipTest("Doesn't have CUDNN implementation")
      mode = mode_with_gpu
  
      if not expect_error:
          self.run_gradinput(
              inputs_shape=i,
              filters_shape=f,
              output_shape=o,
              subsample=s,
              verify_grad=True,
              mode=mode,
              provide_shape=provide_shape,
              border_mode=b,
              filter_flip=flip,
              target_op=GpuDnnConvGradI,
              filter_dilation=fd,
          )
      else:
          assert_raises(
              (RuntimeError, ValueError),
              self.run_gradinput,
              inputs_shape=i,
              filters_shape=f,
              output_shape=o,
              subsample=s,
              verify_grad=False,
              mode=mode,
              provide_shape=provide_shape,
              border_mode=b,
              filter_flip=flip,
              target_op=GpuDnnConvGradI,
              ref=None,
              filter_dilation=fd,
          )
  
imports: from __future__ import absolute_import, print_function, division
  from nose.plugins.skip import SkipTest
  from nose.tools import assert_raises
  import numpy
  from theano.tensor.nnet.tests import test_abstract_conv
  from ..type import GpuArrayType, gpuarray_shared_constructor, get_context
  from ..dnn import dnn_available, GpuDnnConv, GpuDnnConvGradW, GpuDnnConvGradI
  from ..blas import GpuCorrMM, GpuCorrMM_gradWeights, GpuCorrMM_gradInputs, GpuCorr3dMM, GpuCorr3dMM_gradWeights, GpuCorr3dMM_gradInputs
  from .config import mode_with_gpu, test_ctx_name
  from pygpu import gpuarray
label_desc: Use image node_id 3 for calling the TestDnnConv2d obj's underlying member method code with example usage: obj.tcase_gi(i, f, o, s, b, flip, provide_shape, fd, expect_error) without return types