#!/usr/bin/env python

# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from lerobot.policies import factory
from lerobot.policies.pi0_fast import processor_pi0_fast
from lerobot.policies.pi0_fast.configuration_pi0_fast import PI0FastConfig
from lerobot.policies.pi052 import fit_fast_tokenizer as fit_module


def test_pi0_fast_resolves_dataset_specific_tokenizer(monkeypatch, tmp_path):
    config = PI0FastConfig(
        auto_fit_fast_tokenizer=True,
        action_tokenizer_name="base-tokenizer",
        fast_tokenizer_cache_dir=str(tmp_path),
        fast_tokenizer_fit_samples=17,
        chunk_size=12,
        n_action_steps=12,
    )
    received = {}

    def fake_fit(**kwargs):
        received.update(kwargs)
        return "/cache/fitted-tokenizer"

    monkeypatch.setattr(fit_module, "fit_fast_tokenizer", fake_fit)

    assert fit_module.resolve_fast_tokenizer(config, "user/dataset") == "/cache/fitted-tokenizer"
    assert received == {
        "dataset_repo_id": "user/dataset",
        "cache_dir": tmp_path,
        "base_tokenizer_name": "base-tokenizer",
        "n_samples": 17,
        "chunk_size": 12,
    }


def test_pretrained_pi0_fast_rebuilds_processor_only_during_dataset_fit(monkeypatch):
    config = PI0FastConfig(auto_fit_fast_tokenizer=True)
    expected = (object(), object())

    monkeypatch.setattr(processor_pi0_fast, "make_pi0_fast_pre_post_processors", lambda **_: expected)

    assert (
        factory.make_pre_post_processors(
            config,
            pretrained_path="checkpoint",
            dataset_repo_id="user/dataset",
        )
        == expected
    )