from typing import Dict, Tuple, overload

import torch
import torch.types
from torch import nn

from . import residue_constants as rc
from .rigid_utils import Rigid, Rotation
from .tensor_utils import batched_gather






@overload
def    __lowerCamelCase	(		lowerCAmelCase__			,						lowerCAmelCase__			,						lowerCAmelCase__			):
							...






@overload
def    __lowerCamelCase	(		lowerCAmelCase__			,						lowerCAmelCase__			,						lowerCAmelCase__			):
							...






def    __lowerCamelCase	(		lowerCAmelCase__			,						lowerCAmelCase__			,						lowerCAmelCase__			):
							lowerCAmelCase__  			=      aatype == rc.restype_order['G']
							lowerCAmelCase__  			=      rc.atom_order['CA']
							lowerCAmelCase__  			=      rc.atom_order['CB']
							lowerCAmelCase__  			=      torch.where(
							    is_gly[..., None].expand(*((-1,) * len(is_gly.shape			))			,						3			)			,						all_atom_positions[..., ca_idx, :]			,						all_atom_positions[..., cb_idx, :]			,						)

							if all_atom_masks is not None:
														lowerCAmelCase__  			=      torch.where(
														    lowerCAmelCase__			,						all_atom_masks[..., ca_idx]			,						all_atom_masks[..., cb_idx]			,						)
														return pseudo_beta, pseudo_beta_mask
							else:
														return pseudo_beta






def    __lowerCamelCase	(		lowerCAmelCase__			,						lowerCAmelCase__			):
							lowerCAmelCase__  			=      batched_gather(
							    lowerCAmelCase__			,						batch['residx_atom37_to_atom14']			,						dim=-2			,						no_batch_dims=len(atomaa.shape[:-2]			)			,						)

							lowerCAmelCase__  			=      atomaa_data * batch['atom37_atom_exists'][..., None]

							return atomaa_data






def    __lowerCamelCase	(		lowerCAmelCase__			):
							lowerCAmelCase__  			=      template_feats['template_aatype']
							lowerCAmelCase__  			=      template_feats['template_torsion_angles_sin_cos']
							lowerCAmelCase__  			=      template_feats['template_alt_torsion_angles_sin_cos']
							lowerCAmelCase__  			=      template_feats['template_torsion_angles_mask']
							lowerCAmelCase__  			=      torch.cat(
							    [
							        nn.functional.one_hot(lowerCAmelCase__			,						2_2			),
							        torsion_angles_sin_cos.reshape(*torsion_angles_sin_cos.shape[:-2]			,						1_4			),
							        alt_torsion_angles_sin_cos.reshape(*alt_torsion_angles_sin_cos.shape[:-2]			,						1_4			),
							        torsion_angles_mask,
							    ]			,						dim=-1			,						)

							return template_angle_feat






def    __lowerCamelCase	(		lowerCAmelCase__			,						lowerCAmelCase__			,						lowerCAmelCase__			,						lowerCAmelCase__			,						lowerCAmelCase__ = False			,						lowerCAmelCase__ = 1e-2_0			,						lowerCAmelCase__ = 1e8			,						):
							lowerCAmelCase__  			=      batch['template_pseudo_beta_mask']
							lowerCAmelCase__  			=      template_mask[..., None] * template_mask[..., None, :]

							# Compute distogram (this seems to differ slightly from Alg. 5)
							lowerCAmelCase__  			=      batch['template_pseudo_beta']
							lowerCAmelCase__  			=      torch.sum((tpb[..., None, :] - tpb[..., None, :, :]) ** 2			,						dim=-1			,						keepdim=lowerCAmelCase__			)
							lowerCAmelCase__  			=      torch.linspace(lowerCAmelCase__			,						lowerCAmelCase__			,						lowerCAmelCase__			,						device=tpb.device			) ** 2
							lowerCAmelCase__  			=      torch.cat([lower[1:], lower.new_tensor([inf]			)]			,						dim=-1			)
							lowerCAmelCase__  			=      ((dgram > lower) * (dgram < upper)).type(dgram.dtype			)

							lowerCAmelCase__  			=      [dgram, template_mask_ad[..., None]]

							lowerCAmelCase__  			=      nn.functional.one_hot(
							    batch['template_aatype']			,						rc.restype_num + 2			,						)

							lowerCAmelCase__  			=      batch['template_aatype'].shape[-1]
							to_concat.append(aatype_one_hot[..., None, :, :].expand(*aatype_one_hot.shape[:-2]			,						lowerCAmelCase__			,						-1			,						-1			)			)
							to_concat.append(aatype_one_hot[..., None, :].expand(*aatype_one_hot.shape[:-2]			,						-1			,						lowerCAmelCase__			,						-1			)			)

							lowerCAmelCase__			,      lowerCAmelCase__			,      lowerCAmelCase__  			=      [rc.atom_order[a] for a in ['N', 'CA', 'C']]
							lowerCAmelCase__  			=      Rigid.make_transform_from_reference(
							    n_xyz=batch['template_all_atom_positions'][..., n, :]			,						ca_xyz=batch['template_all_atom_positions'][..., ca, :]			,						c_xyz=batch['template_all_atom_positions'][..., c, :]			,						eps=lowerCAmelCase__			,						)
							lowerCAmelCase__  			=      rigids.get_trans()[..., None, :, :]
							lowerCAmelCase__  			=      rigids[..., None].invert_apply(lowerCAmelCase__			)

							lowerCAmelCase__  			=      torch.rsqrt(eps + torch.sum(rigid_vec**2			,						dim=-1			)			)

							lowerCAmelCase__  			=      batch['template_all_atom_mask']
							lowerCAmelCase__  			=      t_aa_masks[..., n] * t_aa_masks[..., ca] * t_aa_masks[..., c]
							lowerCAmelCase__  			=      template_mask[..., None] * template_mask[..., None, :]

							lowerCAmelCase__  			=      inv_distance_scalar * template_mask_ad
							lowerCAmelCase__  			=      rigid_vec * inv_distance_scalar[..., None]

							if not use_unit_vector:
														lowerCAmelCase__  			=      unit_vector * 0.0

							to_concat.extend(torch.unbind(unit_vector[..., None, :]			,						dim=-1			)			)
							to_concat.append(template_mask_ad[..., None]			)

							lowerCAmelCase__  			=      torch.cat(lowerCAmelCase__			,						dim=-1			)
							lowerCAmelCase__  			=      act * template_mask_ad[..., None]

							return act






def    __lowerCamelCase	(		lowerCAmelCase__			):
							lowerCAmelCase__  			=      nn.functional.one_hot(batch['extra_msa']			,						2_3			)
							lowerCAmelCase__  			=      [
							    msa_ahot,
							    batch['extra_has_deletion'].unsqueeze(-1			),
							    batch['extra_deletion_value'].unsqueeze(-1			),
							]
							return torch.cat(lowerCAmelCase__			,						dim=-1			)






def    __lowerCamelCase	(		lowerCAmelCase__			,						lowerCAmelCase__			,						lowerCAmelCase__			,						lowerCAmelCase__			,						):
							# [*, N, 8, 4, 4]
							lowerCAmelCase__  			=      rrgdf[aatype, ...]

							# [*, N, 8] transformations, i.e.
							#   One [*, N, 8, 3, 3] rotation matrix and
							#   One [*, N, 8, 3]    translation matrix
							lowerCAmelCase__  			=      r.from_tensor_axa(lowerCAmelCase__			)

							lowerCAmelCase__  			=      alpha.new_zeros((*((1,) * len(alpha.shape[:-1]			)), 2)			)
							lowerCAmelCase__  			=      1

							# [*, N, 8, 2]
							lowerCAmelCase__  			=      torch.cat([bb_rot.expand(*alpha.shape[:-2]			,						-1			,						-1			), alpha]			,						dim=-2			)

							# [*, N, 8, 3, 3]
							# Produces rotation matrices of the form:
							# [
							#   [1, 0  , 0  ],
							#   [0, a_2,-a_1],
							#   [0, a_1, a_2]
							# ]
							# This follows the original code rather than the supplement, which uses
							# different indices.

							lowerCAmelCase__  			=      alpha.new_zeros(default_r.get_rots().get_rot_mats().shape			)
							lowerCAmelCase__  			=      1
							lowerCAmelCase__  			=      alpha[..., 1]
							lowerCAmelCase__  			=      -alpha[..., 0]
							lowerCAmelCase__  			=      alpha

							lowerCAmelCase__  			=      default_r.compose(Rigid(Rotation(rot_mats=lowerCAmelCase__			)			,						lowerCAmelCase__			)			)

							lowerCAmelCase__  			=      all_frames[..., 5]
							lowerCAmelCase__  			=      all_frames[..., 6]
							lowerCAmelCase__  			=      all_frames[..., 7]

							lowerCAmelCase__  			=      all_frames[..., 4]
							lowerCAmelCase__  			=      chia_frame_to_bb.compose(lowerCAmelCase__			)
							lowerCAmelCase__  			=      chia_frame_to_bb.compose(lowerCAmelCase__			)
							lowerCAmelCase__  			=      chia_frame_to_bb.compose(lowerCAmelCase__			)

							lowerCAmelCase__  			=      Rigid.cat(
							    [
							        all_frames[..., :5],
							        chia_frame_to_bb.unsqueeze(-1			),
							        chia_frame_to_bb.unsqueeze(-1			),
							        chia_frame_to_bb.unsqueeze(-1			),
							    ]			,						dim=-1			,						)

							lowerCAmelCase__  			=      r[..., None].compose(lowerCAmelCase__			)

							return all_frames_to_global






def    __lowerCamelCase	(		lowerCAmelCase__			,						lowerCAmelCase__			,						lowerCAmelCase__			,						lowerCAmelCase__			,						lowerCAmelCase__			,						lowerCAmelCase__			,						):
							# [*, N, 14]
							lowerCAmelCase__  			=      group_idx[aatype, ...]

							# [*, N, 14, 8]
							lowerCAmelCase__  			=      nn.functional.one_hot(
							    lowerCAmelCase__			,						num_classes=default_frames.shape[-3]			,						)

							# [*, N, 14, 8]
							lowerCAmelCase__  			=      r[..., None, :] * group_mask_one_hot

							# [*, N, 14]
							lowerCAmelCase__  			=      t_atoms_to_global.map_tensor_fn(lambda lowerCAmelCase__			: torch.sum(lowerCAmelCase__			,						dim=-1			)			)

							# [*, N, 14, 1]
							lowerCAmelCase__  			=      atom_mask[aatype, ...].unsqueeze(-1			)

							# [*, N, 14, 3]
							lowerCAmelCase__  			=      lit_positions[aatype, ...]
							lowerCAmelCase__  			=      t_atoms_to_global.apply(lowerCAmelCase__			)
							lowerCAmelCase__  			=      pred_positions * atom_mask

							return pred_positions

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase__					=				logging.get_logger(__name__)

lowerCAmelCase__					=				{
    'ZinengTang/tvlt-base': 'https://huggingface.co/ZinengTang/tvlt-base/blob/main/config.json',
}
class        a_				(		SCREAMING_SNAKE_CASE		):






 '''simple docstring'''






 UpperCAmelCase_							=      'tvlt'




 def __init__(    self      :						Dict    ,					lowercase__      :						str=224    ,					lowercase__      :						int=2_048    ,					lowercase__      :						int=128    ,					lowercase__      :						Optional[Any]=[16, 16]    ,					lowercase__      :						List[str]=[16, 16]    ,					lowercase__      :						Optional[int]=3    ,					lowercase__      :						Tuple=1    ,					lowercase__      :						Union[str, Any]=8    ,					lowercase__      :						int=768    ,					lowercase__      :						Tuple=12    ,					lowercase__      :						List[str]=12    ,					lowercase__      :						Union[str, Any]=3_072    ,					lowercase__      :						Union[str, Any]="gelu"    ,					lowercase__      :						Dict=0.0    ,					lowercase__      :						Tuple=0.0    ,					lowercase__      :						Union[str, Any]=0.02    ,					lowercase__      :						Any=1e-6    ,					lowercase__      :						Dict=True    ,					lowercase__      :						int=False    ,					lowercase__      :						Tuple=16    ,					lowercase__      :						Optional[int]=512    ,					lowercase__      :						int=8    ,					lowercase__      :						List[Any]=2_048    ,					lowercase__      :						Optional[int]=0.75    ,					lowercase__      :						Union[str, Any]=0.15    ,					lowercase__      :						List[str]="frame-level"    ,					lowercase__      :						Dict=True    ,					lowercase__      :						Tuple=True    ,					lowercase__      :						Any="classification"    ,					**lowercase__      :						Union[str, Any]    ,					):







        '''simple docstring'''



        super().__init__(**lowercase__)

        if audio_mask_type not in ("frame-level", "patch_level"):
               raise ValueError(
                   'audio_mask_type must be one of two acceptable strategies - {\'frame_level\', \'patch-level\') '
                   F"""got {audio_mask_type}""")

        lowerCAmelCase__  			=      image_size
        lowerCAmelCase__  			=      spectrogram_length
        lowerCAmelCase__  			=      frequency_length
        lowerCAmelCase__  			=      image_patch_size
        lowerCAmelCase__  			=      audio_patch_size
        lowerCAmelCase__  			=      num_image_channels
        lowerCAmelCase__  			=      num_audio_channels
        lowerCAmelCase__  			=      num_frames

        lowerCAmelCase__  			=      hidden_size
        lowerCAmelCase__  			=      num_hidden_layers
        lowerCAmelCase__  			=      num_attention_heads
        lowerCAmelCase__  			=      intermediate_size
        lowerCAmelCase__  			=      hidden_act
        lowerCAmelCase__  			=      hidden_dropout_prob
        lowerCAmelCase__  			=      attention_probs_dropout_prob
        lowerCAmelCase__  			=      initializer_range
        lowerCAmelCase__  			=      layer_norm_eps
        lowerCAmelCase__  			=      qkv_bias
        lowerCAmelCase__  			=      use_mean_pooling

        lowerCAmelCase__  			=      decoder_num_attention_heads
        lowerCAmelCase__  			=      decoder_hidden_size
        lowerCAmelCase__  			=      decoder_num_hidden_layers
        lowerCAmelCase__  			=      decoder_intermediate_size
        lowerCAmelCase__  			=      pixel_mask_ratio
        lowerCAmelCase__  			=      audio_mask_ratio
        lowerCAmelCase__  			=      audio_mask_type

        lowerCAmelCase__  			=      task_matching
        lowerCAmelCase__  			=      task_mae
        lowerCAmelCase__  			=      loss_type
