import torch.nn as nn

import colossalai.shardformer.layer as col_nn

from .._utils import getattr_, setattr_
from ..modeling.sam import forward_fn
from .basepolicy import ModulePolicyDescription, Policy, SubModuleReplacementDescription

__all__ = ['SamPolicy', 'SamModelPolicy']


class SamPolicy(Policy):

    def config_sanity_check(self):
        pass

    def preprocess(self):
        return self.model

    def module_policy(self):
        from transformers.models.sam.modeling_sam import (
            SamFeedForward,
            SamTwoWayAttentionBlock,
            SamTwoWayTransformer,
            SamVisionAttention,
            SamVisionLayer,
        )

        policy = {}

        if self.shard_config.enable_tensor_parallelism:
            policy[SamVisionLayer] = ModulePolicyDescription(attribute_replacement={
                "attn.num_attention_heads":
                    self.model.config.vision_config.num_attention_heads // self.shard_config.tensor_parallel_size,
            },
                                                             sub_module_replacement=[
                                                                 SubModuleReplacementDescription(
                                                                     suffix="attn.qkv",
                                                                     target_module=col_nn.FusedLinear1D_Col,
                                                                     kwargs={
                                                                         "n_fused": 3,
                                                                     },
                                                                 ),
                                                                 SubModuleReplacementDescription(
                                                                     suffix="attn.proj",
                                                                     target_module=col_nn.Linear1D_Row,
                                                                 ),
                                                                 SubModuleReplacementDescription(
                                                                     suffix="mlp.lin1",
                                                                     target_module=col_nn.Linear1D_Col,
                                                                 ),
                                                                 SubModuleReplacementDescription(
                                                                     suffix="mlp.lin2",
                                                                     target_module=col_nn.Linear1D_Row,
                                                                 )
                                                             ])
            policy[SamTwoWayAttentionBlock] = ModulePolicyDescription(
                attribute_replacement={
                    "self_attn.num_attention_heads":
                        self.model.config.mask_decoder_config.num_attention_heads //
                        self.shard_config.tensor_parallel_size,
                },
                sub_module_replacement=[
                    SubModuleReplacementDescription(
                        suffix="self_attn.q_proj",
                        target_module=col_nn.Linear1D_Col,
                    ),
                    SubModuleReplacementDescription(
                        suffix="self_attn.k_proj",
                        target_module=col_nn.Linear1D_Col,
                    ),
                    SubModuleReplacementDescription(
                        suffix="self_attn.v_proj",
                        target_module=col_nn.Linear1D_Col,
                    ),
                    SubModuleReplacementDescription(
                        suffix="self_attn.out_proj",
                        target_module=col_nn.Linear1D_Row,
                    ),
                    SubModuleReplacementDescription(
                        suffix="cross_attn_token_to_image.q_proj",
                        target_module=col_nn.Linear1D_Col,
                    ),
                    SubModuleReplacementDescription(
                        suffix="cross_attn_token_to_image.k_proj",
                        target_module=col_nn.Linear1D_Col,
                    ),
                    SubModuleReplacementDescription(
                        suffix="cross_attn_token_to_image.v_proj",
                        target_module=col_nn.Linear1D_Col,
                    ),
                    SubModuleReplacementDescription(
                        suffix="cross_attn_token_to_image.out_proj",
                        target_module=col_nn.Linear1D_Row,
                    ),
                    SubModuleReplacementDescription(
                        suffix="mlp.lin1",
                        target_module=col_nn.Linear1D_Col,
                    ),
                    SubModuleReplacementDescription(
                        suffix="mlp.lin2",
                        target_module=col_nn.Linear1D_Row,
                    ),
                    SubModuleReplacementDescription(
                        suffix="cross_attn_image_to_token.q_proj",
                        target_module=col_nn.Linear1D_Col,
                    ),
                    SubModuleReplacementDescription(
                        suffix="cross_attn_image_to_token.k_proj",
                        target_module=col_nn.Linear1D_Col,
                    ),
                    SubModuleReplacementDescription(
                        suffix="cross_attn_image_to_token.v_proj",
                        target_module=col_nn.Linear1D_Col,
                    ),
                    SubModuleReplacementDescription(
                        suffix="cross_attn_image_to_token.out_proj",
                        target_module=col_nn.Linear1D_Row,
                    ),
                ])
            policy[SamTwoWayTransformer] = ModulePolicyDescription(attribute_replacement={
                "final_attn_token_to_image.num_attention_heads":
                    self.model.config.mask_decoder_config.num_attention_heads // self.shard_config.tensor_parallel_size,
            },
                                                                   sub_module_replacement=[
                                                                       SubModuleReplacementDescription(
                                                                           suffix="final_attn_token_to_image.q_proj",
                                                                           target_module=col_nn.Linear1D_Col,
                                                                       ),
                                                                       SubModuleReplacementDescription(
                                                                           suffix="final_attn_token_to_image.k_proj",
                                                                           target_module=col_nn.Linear1D_Col,
                                                                       ),
                                                                       SubModuleReplacementDescription(
                                                                           suffix="final_attn_token_to_image.v_proj",
                                                                           target_module=col_nn.Linear1D_Col,
                                                                       ),
                                                                       SubModuleReplacementDescription(
                                                                           suffix="final_attn_token_to_image.out_proj",
                                                                           target_module=col_nn.Linear1D_Row,
                                                                       )
                                                                   ])

            # add `DropoutForParallelInput` layer to replace the useage of `nn.functional.dropout`
            policy[SamVisionAttention] = ModulePolicyDescription(attribute_replacement={
                "dropout_layer": col_nn.DropoutForParallelInput(self.model.config.vision_config.attention_dropout)
            },
                                                                 method_replacement={"forward": forward_fn()},
                                                                 sub_module_replacement=[])

        # optimization configuration
        if self.shard_config.enable_fused_normalization:
            # Handle SamVisionLayer
            self.append_or_create_submodule_replacement(description=[
                SubModuleReplacementDescription(
                    suffix="layer_norm1",
                    target_module=col_nn.FusedLayerNorm,
                ),
                SubModuleReplacementDescription(
                    suffix="layer_norm2",
                    target_module=col_nn.FusedLayerNorm,
                )
            ],
                                                        policy=policy,
                                                        target_key=SamVisionLayer)

            # Handle SamTwoWayAttentionBlock
            self.append_or_create_submodule_replacement(description=[
                SubModuleReplacementDescription(
                    suffix="layer_norm1",
                    target_module=col_nn.FusedLayerNorm,
                ),
                SubModuleReplacementDescription(
                    suffix="layer_norm2",
                    target_module=col_nn.FusedLayerNorm,
                ),
                SubModuleReplacementDescription(
                    suffix="layer_norm3",
                    target_module=col_nn.FusedLayerNorm,
                ),
                SubModuleReplacementDescription(
                    suffix="layer_norm4",
                    target_module=col_nn.FusedLayerNorm,
                )
            ],
                                                        policy=policy,
                                                        target_key=SamTwoWayAttentionBlock)

            # Handle SamTwoWayTransformer
            self.append_or_create_submodule_replacement(description=[
                SubModuleReplacementDescription(
                    suffix="layer_norm_final_attn",
                    target_module=col_nn.FusedLayerNorm,
                )
            ],
                                                        policy=policy,
                                                        target_key=SamTwoWayTransformer)

        return policy

    def postprocess(self):
        return self.model


# SamModel
class SamModelPolicy(SamPolicy):

    def __init__(self) -> None:
        super().__init__()
