const char tensor1[] = {5, 7};
  const int64_t dims1[] = {1, 2};
  const size_t ndims1 = TF_ARRAYSIZE(dims1);

  const char tensor2[] = {2, 4, 6, 8};
  const int64_t dims2[] = {2, 2};
  const size_t ndims2 = TF_ARRAYSIZE(dims2);

  auto desc = init("list(tensor)");
  TF_Tensor* tmp[] = {
      Int8Tensor(dims1, ndims1, tensor1),
      Int8Tensor(dims2, ndims2, tensor2),
  };

    return a;
  }
  int64_t rank = a.getRank();
  SmallVector<int64_t, 4> dims;
  dims.resize(rank);
  for (int i = 0, e = rank; i != e; i++) {
    int64_t dim0 = a.getDimSize(i);
    int64_t dim1 = b.getDimSize(i);
    dims[i] = (dim0 == ShapedType::kDynamic) ? dim1 : dim0;
  }
  return RankedTensorType::get(dims, a.getElementType());
}
}  // namespace detail

  constexpr int64_t dims[] = {100, 100};
  constexpr int num_elements = dims[0] * dims[1];
  float data[num_elements];
  for (int i = 0; i < num_elements; ++i) {
    data[i] = 1.0f;
  }
  TF_Status* status = TF_NewStatus();
  TF_Tensor* t = TFE_AllocateHostTensor(ctx, TF_FLOAT, &dims[0],
                                        sizeof(dims) / sizeof(int64_t), status);

  %1 = stablehlo.transpose %0, dims = [1, 0] : (tensor<2x3xi32>) -> tensor<3x2xi32>
  return %1 : tensor<3x2xi32>
}
// CHECK: transpose

// -----

// Tests that transposing an argument cannot be folded.

// CHECK-LABEL: transpose_arg
func.func @transpose_arg(%arg0: tensor<2x3xf32>) -> tensor<3x2xf32> {
  %0 = stablehlo.transpose %arg0, dims = [1, 0] : (tensor<2x3xf32>) -> tensor<3x2xf32>

  }
  float& arg0(size_t dim0, size_t dim1) {
    return (*static_cast<float(*)[1][2]>(
        arg_data(0)))[dim0][dim1];
  }
  const float* arg0_data() const {
    return static_cast<const float*>(arg_data(0));
  }
  const float& arg0(size_t dim0, size_t dim1) const {
    return (*static_cast<const float(*)[1][2]>(
        arg_data(0)))[dim0][dim1];
  }
  int arg0_size() const {

    - mikedanese
  sig-auth-authorizers-reviewers:
    - deads2k
    - dims
    - enj
    - liggitt
    - mikedanese
    - ncdc
    - smarterclayton
    - sttts
    - thockin
    - wojtek-t
  sig-auth-certificates-approvers:
    - liggitt
    - mikedanese
    - smarterclayton
  sig-auth-certificates-reviewers:
    - deads2k
    - dims
    - enj
    - liggitt
    - mikedanese

  static char empty;
  int64_t nelems = 1;
  std::vector<int64_t> dims;
  auto shape_dims = shape.dims();
  dims.reserve(shape_dims);
  for (int i = 0; i < shape_dims; ++i) {
    dims.push_back(shape.dim_size(i));
    nelems *= shape.dim_size(i);
  }
  CHECK_EQ(nelems, 0);
  return TF_NewTensor(
      dtype, reinterpret_cast<const int64_t*>(dims.data()), shape.dims(),

# See the OWNERS docs at https://go.k8s.io/owners

reviewers:
  - bentheelder
  - dims
  - pohly
approvers:
  - dims
  - pohly
labels:

# See the OWNERS docs at https://go.k8s.io/owners

reviewers:
  - aojea
  - bentheelder
  - dims
  - liggitt
  - pohly
approvers:
  - dims
  - liggitt
labels:

  %1 = stablehlo.transpose %arg0, dims = [0, 3, 1, 2] : (tensor<1x3x3x4xf32>) -> tensor<1x4x3x3xf32>
  %2 = stablehlo.add %1, %0 : tensor<1x4x3x3xf32>
  return %2 : tensor<1x4x3x3xf32>
}
// CHECK-SAME: (%[[ARG_0:.+]]: tensor<1x3x3x4xf32>) -> tensor<1x4x3x3xf32>
// CHECK-DAG: %[[CONST_0:.+]] = stablehlo.constant