blacklist:
# Disabled in favour of `aten::index_put` which supports optional indices via `hacked_twin` JIT hack.
# It also doesn't have confusing `unsafe` argument.
- _index_put_impl

# Ops with list of tensors output
- split.Tensor
- split_with_sizes
- unbind.int
- chunk

# Additional ops which autogen is supported for but don't compile yet
- _convolution
- detach
- item
- size
- copy_

# Disabled for consistency with TS backend
- lift_fresh_copy
- new_empty
- rsub
- slice.Tensor  # Disabled in favour of slice_copy.Tensor
- zeros
- ones
- arange
- arange.start
- arange.start_step
- fill.Scalar
- scalar_tensor

# Disabled in favour of functionalized alternatives
- _reshape_alias
- expand
- permute
- select.int
- squeeze
- squeeze.dim
- t
- transpose.int
- unsqueeze
- view

whitelist:
# Enabled for consistency with TS backend
- arange.start_out

# List of supported ops that we don't want to do the full codegen for
supported:
# - bernoulli
# - bernoulli_
- _to_copy
- clone
- empty.memory_format
- empty_strided
- fill_.Scalar
- _unsafe_view
- unbind_copy.int
- split_copy.Tensor
- split_with_sizes_copy
- index.Tensor
- index_put

# ops required for functionalization
- lift
- lift_fresh
# Below are all operators that are "composite" in core,
# but require us to explicitly re-enable functionalization in order to use them.
# Why? These operators are all CompositeExplicitAutograd, which mean that they run
# after functionalization,
# but their implementations call view operators (which we need to functionalize away).
- block_diag
- new_empty_strided
- narrow_copy
- pixel_shuffle
- pixel_unshuffle
- select_backward
- slice_backward
- diagonal_backward
- _trilinear
- linalg_pinv.atol_rtol_tensor
- logsumexp.out

# List of ops that will take in symints for the size instead of ints
symint:
- empty.memory_format
- new_empty_strided
- expand_copy
- narrow_copy
- slice_backward
- slice_copy.Tensor
- split_copy.Tensor
- slice_scatter
- view
- view_copy
- as_strided_copy
- as_strided_scatter
- split_with_sizes_copy


additional_ops:
# Additional ops to support that are not supported by Torch-MLIR explicitly
- _copy_from
- _copy_from_and_resize

# List of non native ops that we only want to do IR node class generation for
non_native:
  - func: scalar(Scalar value, ScalarType type) -> Tensor
    opkind: at::prim::Constant
    properties:
      - ShapeCompute
      - TreatScalarsAsConstants
  - func: expand(Tensor input, int[] size, bool is_scalar_expand) -> Tensor
  - func: cast(Tensor input, ScalarType dtype, ScalarType? stype) -> Tensor
    opkind: ltc_cast
    properties:
      - ShapeCompute