[Relax][TFLite] Fix MIRROR_PAD/ONE_HOT converters and add tests for PAD, PADV2, MIRROR_PAD, TOPK_V2, ONE_HOT

[swjng]

Part of #18971

Two bugs in the TFLite Relax frontend converters are fixed, and unit tests
are added for the Padding / Sparse / Other category operators claimed in
that tracking issue.

Bug fixes

convert_mirror_pad

Called relax.op.nn.mirror_pad which does not exist in the Relax op
namespace. Replaced with relax.op.nn.pad using pad_mode="reflect" for
REFLECT mode (the modes are semantically equivalent). SYMMETRIC mode raises
OpAttributeUnImplemented as there is no direct Relax equivalent.

convert_one_hot

• on_value and off_value were passed as Expr (constant tensor nodes),
  but relax.op.one_hot requires PrimValue arguments.
• An extra dtype positional argument was passed, which the function
  signature does not accept.

Fixed by extracting the scalar from each tensor buffer and wrapping it in
relax.PrimValue with the correct dtype via tvm.tirx.FloatImm /
tvm.tirx.IntImm.

Tests added

Each test uses the verify() + tf.Module pattern and includes an explicit
expected IRModule verified with tvm.ir.assert_structural_equal.

Operator	TFLite op	Notes
test_pad	PAD	constant zero padding
test_pad_v2	PADV2	explicit constant_values=5.0
test_mirror_pad	MIRROR_PAD	REFLECT mode
test_topk_v2	TOPK_V2	returns top-k values
test_one_hot	ONE_HOT	float32 on/off values, depth=4

[gemini-code-assist]

Code Review

This pull request updates the TFLite frontend in TVM Relax by refactoring the MIRROR_PAD and ONE_HOT operators. MIRROR_PAD now utilizes relax.op.nn.pad for reflection padding, while ONE_HOT has been updated to wrap its on/off values as PrimValue. Additionally, several new tests were added to cover padding and one-hot operations. Review feedback suggests casting padding values to Python integers for better compatibility and simplifying the extraction of scalar values from numpy arrays in the one-hot conversion.

[tlopex]

LGTM Thanks!