# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0

"""CPU-only unit tests for the diffusion LoRA trainer's pure helpers.

The training loop needs a GPU + weights, but dataset discovery, config normalisation,
the SDXL add-time-ids, and the dict->config adapter are pure and tested here.
"""

from __future__ import annotations

import json

import pytest

from core.training.diffusion_lora_trainer import (
    DEFAULT_LORA_TARGETS,
    DiffusionLoraConfig,
    _config_from_dict,
    compute_sdxl_add_time_ids,
    discover_image_caption_pairs,
)


def _touch(p):
    p.write_bytes(b"")


def test_discover_prefers_metadata_then_sidecar_then_instance(tmp_path):
    _touch(tmp_path / "a.png")
    _touch(tmp_path / "b.jpg")
    _touch(tmp_path / "c.webp")
    # a.png captioned via metadata.jsonl
    (tmp_path / "metadata.jsonl").write_text(
        json.dumps({"file_name": "a.png", "text": "from metadata"}) + "\n", encoding = "utf-8"
    )
    # b.jpg captioned via sidecar
    (tmp_path / "b.txt").write_text("from sidecar", encoding = "utf-8")
    # c.webp falls back to the instance prompt
    pairs = dict(discover_image_caption_pairs(tmp_path, instance_prompt = "from instance"))
    assert pairs[str(tmp_path / "a.png")] == "from metadata"
    assert pairs[str(tmp_path / "b.jpg")] == "from sidecar"
    assert pairs[str(tmp_path / "c.webp")] == "from instance"


def test_discover_skips_uncaptioned_without_instance_prompt(tmp_path):
    _touch(tmp_path / "cap.png")
    _touch(tmp_path / "nocap.png")
    (tmp_path / "cap.caption").write_text("a caption", encoding = "utf-8")
    pairs = discover_image_caption_pairs(tmp_path)
    assert pairs == [(str(tmp_path / "cap.png"), "a caption")]


def test_discover_captions_jsonl_and_image_key(tmp_path):
    _touch(tmp_path / "x.png")
    (tmp_path / "captions.jsonl").write_text(
        json.dumps({"image": "x.png", "text": "hi"}) + "\n", encoding = "utf-8"
    )
    assert discover_image_caption_pairs(tmp_path) == [(str(tmp_path / "x.png"), "hi")]


def test_discover_custom_caption_column(tmp_path):
    _touch(tmp_path / "x.png")
    (tmp_path / "metadata.jsonl").write_text(
        json.dumps({"file_name": "x.png", "caption": "col"}) + "\n", encoding = "utf-8"
    )
    assert discover_image_caption_pairs(tmp_path, caption_column = "caption")[0][1] == "col"


def test_discover_empty_raises(tmp_path):
    _touch(tmp_path / "x.png")  # no captions anywhere, no instance prompt
    with pytest.raises(ValueError, match = "No captioned images"):
        discover_image_caption_pairs(tmp_path)


def test_discover_missing_dir_raises(tmp_path):
    with pytest.raises(FileNotFoundError):
        discover_image_caption_pairs(tmp_path / "nope")


def test_config_normalized_defaults():
    cfg = DiffusionLoraConfig(base_model = "b", data_dir = "d", output_dir = "o").normalized()
    assert cfg.lora_alpha == cfg.lora_rank  # alpha defaults to rank
    assert cfg.lora_target_modules == DEFAULT_LORA_TARGETS


@pytest.mark.parametrize(
    "kw",
    [
        {"train_steps": 0},
        {"train_batch_size": 0},
        {"gradient_accumulation_steps": 0},
        {"lora_rank": 0},
        {"resolution": 100},  # not a multiple of 8
        {"resolution": 32},  # too small
        {"mixed_precision": "int4"},
    ],
)
def test_config_normalized_validation(kw):
    with pytest.raises(ValueError):
        DiffusionLoraConfig(base_model = "b", data_dir = "d", output_dir = "o", **kw).normalized()


def test_compute_sdxl_add_time_ids():
    assert compute_sdxl_add_time_ids(1024) == (1024, 1024, 0, 0, 1024, 1024)


def test_config_from_dict_ignores_unknown_and_tuples_targets():
    cfg = _config_from_dict(
        {
            "base_model": "b",
            "data_dir": "d",
            "output_dir": "o",
            "lora_target_modules": ["to_q", "to_v"],
            "unknown_field": 123,  # must be ignored, not crash
        }
    )
    assert cfg.lora_target_modules == ("to_q", "to_v")
    assert not hasattr(cfg, "unknown_field")