[Relax][Frontend][TFLite] Add missing TFLite operator mappings

[Aharrypotter]

Summary

Adds Relax TFLite frontend coverage for a batch of builtin operators tracked in
#19412. All lowerings reuse existing Relax ops; the change is limited to the
TFLite frontend converter and its tests.

Changes

Grouped by the #19412 checklist section:

Section A — drop-in operator mappings

• SIGN -> relax.op.sign
• BITWISE_XOR -> relax.op.bitwise_xor
• RIGHT_SHIFT -> relax.op.right_shift
• RELU_0_TO_1 -> relax.op.clip
• BUCKETIZE -> relax.op.bucketize
• UNIQUE -> relax.op.unique (unique values + inverse indices)

Section B — compose with existing Relax ops

• RANK -> scalar rank constant for statically-ranked inputs
• UNSORTED_SEGMENT_SUM -> extends the existing scatter-based segment lowering
  (scatter_nd, reduction="add")
• UNSORTED_SEGMENT_MAX -> same, reduction="max"

Section C — fix partial implementation

• FAKE_QUANT: the handler called the non-existent relax.op.const and raised
  AttributeError on every invocation; switch to relax.const so the op works.
  (The builtin op carries only scalar min/max, so there is no per-channel/vector
  min/max path.)

Tests

Adds coverage in tests/python/relax/test_frontend_tflite.py for the new
mappings and the FAKE_QUANT narrow-range vector path. Most tests use
structural-equal Relax IR checks; data-dependent and numeric regression cases
add focused output checks for UNIQUE and FAKE_QUANT.

python -m ruff format 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 pytest tests/python/relax/test_frontend_tflite.py -k "unique or sign or bitwise_xor or right_shift or bucketize or relu_0_to_1 or rank or unsorted_segment_sum or unsorted_segment_max or fake_quant"
python -m pytest tests/python/relax/test_frontend_tflite.py

Result:

• ruff format: 2 files left unchanged
• ruff check: All checks passed
• target pytest: 22 passed, 523 deselected
• full TFLite pytest: 545 passed

References

• Issue [Tracking Issue][TFlite] Expand Missing / Partial Operator Coverage #19412: TFLite missing/partial operator coverage (sections A, B, C)

[gemini-code-assist]

Code Review

This pull request addresses several Relax TFLite frontend gaps by implementing mappings for operators such as SIGN, BITWISE_XOR, RIGHT_SHIFT, BUCKETIZE, RELU_0_TO_1, UNIQUE, RANK, UNSORTED_SEGMENT_SUM, and UNSORTED_SEGMENT_MAX, along with fixing FAKE_QUANT narrow-range vector conversion. Feedback suggests simplifying the RANK conversion by passing the Python integer directly to relax.const rather than wrapping it in a NumPy array, and using positional arguments instead of keyword arguments in relax.op.clip for consistency and compatibility.

Important

The consumer version of Gemini Code Assist on GitHub is being sunset. Starting June 18, 2026, new organization installations will be blocked, and all code review activity will officially cease on July 17, 2026.
For more details on the timeline and next steps, please review the Help Documentation.

[gemini-code-assist]

We can simplify this by passing the Python integer rank directly to relax.const instead of wrapping it in a np.array. relax.const natively supports Python scalars with a specified dtype.

Suggested change

	return relax.const(np.array(rank, dtype=output_dtype), dtype=output_dtype)
	return relax.const(rank, dtype=output_dtype)

[Aharrypotter]

Addressed by returning relax.const(rank, dtype=output_dtype).

[gemini-code-assist]

For consistency with other uses of relax.op.clip in this file (e.g., in convert_fake_quant), and to ensure compatibility with TVM's FFI wrappers, it is recommended to use positional arguments instead of keyword arguments (min and max).

Suggested change

	if input_tensor.qnn_params:
	in_f32 = self.dequantize(in_expr, input_tensor)
	out = relax.op.clip(in_f32, min=0, max=1)
	out = self.quantize(out, output_tensor)
	else:
	out = relax.op.clip(in_expr, min=0, max=1)
	if input_tensor.qnn_params:
	in_f32 = self.dequantize(in_expr, input_tensor)
	out = relax.op.clip(in_f32, 0, 1)
	out = self.quantize(out, output_tensor)
	else:
	out = relax.op.clip(in_expr, 0, 1)

[Aharrypotter]

Addressed by switching the new relax.op.clip calls to positional arguments.

[tlopex]

Could you resolve the conflict so that we can merge it in?

[Aharrypotter]

Rebased the PR onto the latest main and resolved the branch conflict in the
TFLite converter map.

Also refreshed the PR description with the post-rebase validation results.

[Aharrypotter]

Updated the PR description for clearer scope: the changes are now grouped by the
#19412 checklist section — Section A (drop-in mappings: SIGN, BITWISE_XOR,
RIGHT_SHIFT, RELU_0_TO_1, BUCKETIZE, UNIQUE), Section B (RANK,
UNSORTED_SEGMENT_SUM/MAX), and Section C (the FAKE_QUANT crash fix:
relax.op.const → relax.const) —
with a link back to the tracking issue. No code change; this only makes it
clearer which tracked items this PR covers.