[Relax][Frontend][TFLite] Support StableHLO shape ops

[Aharrypotter]

Summary

This PR adds Relax TFLite frontend support for the remaining StableHLO shape
operators tracked by #19519:

• STABLEHLO_RESHAPE -> R.reshape
• STABLEHLO_SLICE -> R.strided_slice
• STABLEHLO_TRANSPOSE -> R.permute_dims

It carries forward the implementation from #19869 by @Mohxen onto the current
main branch and addresses the outstanding review feedback by using explicit
ValueError checks for the input and output arity of all three new converters.

Design

StableHLO reshape

STABLEHLO_RESHAPE has one tensor input and a statically described result
shape. The converter reads that shape from the TFLite output tensor metadata
and emits relax.op.reshape.

StableHLO slice

STABLEHLO_SLICE stores start_indices, limit_indices, and strides in
StablehloSliceOptions. The converter parses those vectors, applies them to all
input axes, and emits relax.op.strided_slice.

StableHLO transpose

STABLEHLO_TRANSPOSE stores its permutation in
StablehloTransposeOptions. The converter parses the permutation and emits
relax.op.permute_dims.

Operator Support

Operator	TFLite metadata	Relax lowering	Supported subset
STABLEHLO_RESHAPE	output tensor shape	R.reshape	static result shape
STABLEHLO_SLICE	start, limit, and stride vectors	R.strided_slice	static slice attributes
STABLEHLO_TRANSPOSE	permutation vector	R.permute_dims	static permutation

Tests

The tests manually build minimal TFLite flatbuffers for each StableHLO
operator and compare the imported Relax IR with
tvm.ir.assert_structural_equal. The slice fixture exercises non-unit strides,
and the transpose fixture uses a nontrivial three-dimensional permutation.

Local validation:

python -m ruff format --check \
  python/tvm/relax/frontend/tflite/tflite_frontend.py \
  tests/python/relax/test_frontend_tflite.py

python -m ruff check \
  python/tvm/relax/frontend/tflite/tflite_frontend.py \
  tests/python/relax/test_frontend_tflite.py

python -m py_compile \
  python/tvm/relax/frontend/tflite/tflite_frontend.py \
  tests/python/relax/test_frontend_tflite.py

python -m pytest tests/python/relax/test_frontend_tflite.py \
  -k "stablehlo_reshape or stablehlo_slice or stablehlo_transpose" -q

Result:

ruff format --check: 2 files already formatted
ruff check: All checks passed
py_compile: passed
targeted StableHLO shape tests: 3 passed, 551 deselected

References

• Completes the remaining StableHLO shape-operator items in [Tracking Issue][TFLite] Remaining builtin operator coverage beyond #19412 #19519.
• Continues and supersedes [Relax][Frontend][TFLite] Support StableHLO shape ops #19869 by @Mohxen.

[Aharrypotter]

@tlopex cc

[tlopex]

Overall this looks good, but there are a couple of missing edge cases around COMPLEX64. Relax represents complex tensors with an extra trailing size-2 axis, so reshape needs to use _get_relax_tensor_shape, and transpose needs to append that pair axis to the permutation. Using the raw TFLite output shape also breaks rank-0 reshape outputs. Could we handle those cases and add scalar/complex tests?

[Aharrypotter]

Overall this looks good, but there are a couple of missing edge cases around COMPLEX64. Relax represents complex tensors with an extra trailing size-2 axis, so reshape needs to use _get_relax_tensor_shape, and transpose needs to append that pair axis to the permutation. Using the raw TFLite output shape also breaks rank-0 reshape outputs. Could we handle those cases and add scalar/complex tests?

Done.