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#
# 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.
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from ...loaders import Flux2LoraLoaderMixin
from ...utils import logging
from ..modular_pipeline import ModularPipeline


logger = logging.get_logger(__name__)  # pylint: disable=invalid-name


class Flux2ModularPipeline(ModularPipeline, Flux2LoraLoaderMixin):
    """
    A ModularPipeline for Flux2.

    > [!WARNING] > This is an experimental feature and is likely to change in the future.
    """

    default_blocks_name = "Flux2AutoBlocks"

    @property
    def default_height(self):
        return self.default_sample_size * self.vae_scale_factor

    @property
    def default_width(self):
        return self.default_sample_size * self.vae_scale_factor

    @property
    def default_sample_size(self):
        return 128

    @property
    def vae_scale_factor(self):
        vae_scale_factor = 8
        if getattr(self, "vae", None) is not None:
            vae_scale_factor = 2 ** (len(self.vae.config.block_out_channels) - 1)
        return vae_scale_factor

    @property
    def num_channels_latents(self):
        num_channels_latents = 32
        if getattr(self, "transformer", None):
            num_channels_latents = self.transformer.config.in_channels // 4
        return num_channels_latents


class Flux2KleinModularPipeline(Flux2ModularPipeline):
    """
    A ModularPipeline for Flux2-Klein (distilled model).

    > [!WARNING] > This is an experimental feature and is likely to change in the future.
    """

    default_blocks_name = "Flux2KleinAutoBlocks"

    @property
    def requires_unconditional_embeds(self):
        if hasattr(self.config, "is_distilled") and self.config.is_distilled:
            return False

        requires_unconditional_embeds = False
        if hasattr(self, "guider") and self.guider is not None:
            requires_unconditional_embeds = self.guider._enabled and self.guider.num_conditions > 1

        return requires_unconditional_embeds


class Flux2KleinBaseModularPipeline(Flux2ModularPipeline):
    """
    A ModularPipeline for Flux2-Klein (base model).

    > [!WARNING] > This is an experimental feature and is likely to change in the future.
    """

    default_blocks_name = "Flux2KleinBaseAutoBlocks"

    @property
    def requires_unconditional_embeds(self):
        if hasattr(self.config, "is_distilled") and self.config.is_distilled:
            return False

        requires_unconditional_embeds = False
        if hasattr(self, "guider") and self.guider is not None:
            requires_unconditional_embeds = self.guider._enabled and self.guider.num_conditions > 1

        return requires_unconditional_embeds