




import argparse
import re

import torch
from CLAP import create_model

from transformers import AutoFeatureExtractor, ClapConfig, ClapModel


lowerCamelCase__			:       Optional[int]         =							{
    'text_branch': 'text_model',
    'audio_branch': 'audio_model.audio_encoder',
    'attn': 'attention.self',
    'self.proj': 'output.dense',
    'attention.self_mask': 'attn_mask',
    'mlp.fc1': 'intermediate.dense',
    'mlp.fc2': 'output.dense',
    'norm1': 'layernorm_before',
    'norm2': 'layernorm_after',
    'bn0': 'batch_norm',
}

lowerCamelCase__			:       str         =							AutoFeatureExtractor.from_pretrained('laion/clap-htsat-unfused', truncation='rand_trunc')

def  UpperCAmelCase_							(				__UpperCAmelCase						:     Any      ,      __UpperCAmelCase						:     Optional[Any]=False							) ->			Dict:
      SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_     						=      create_model(
          'HTSAT-tiny'      ,      'roberta'      ,      __UpperCAmelCase      ,      precision='fp32'      ,      device='cuda:0' if torch.cuda.is_available() else 'cpu'      ,      enable_fusion=__UpperCAmelCase      ,      fusion_type='aff_2d' if enable_fusion else None      ,      )
      return model, model_cfg

def  UpperCAmelCase_							(				__UpperCAmelCase						:     Tuple							) ->			List[Any]:
      SCREAMING_SNAKE_CASE_     						=      {}

      SCREAMING_SNAKE_CASE_     						=      r'.*sequential.(\d+).*'
      SCREAMING_SNAKE_CASE_     						=      r'.*_projection.(\d+).*'

      for key, value in state_dict.items():
            # check if any key needs to be modified
            for key_to_modify, new_key in KEYS_TO_MODIFY_MAPPING.items():
                  if key_to_modify in key:
                        SCREAMING_SNAKE_CASE_     						=      key.replace(__UpperCAmelCase      ,      __UpperCAmelCase							)

            if re.match(__UpperCAmelCase      ,      __UpperCAmelCase							):
                  # replace sequential layers with list
                  SCREAMING_SNAKE_CASE_     						=      re.match(__UpperCAmelCase      ,      __UpperCAmelCase							).group(1							)

                  SCREAMING_SNAKE_CASE_     						=      key.replace(f"sequential.{sequential_layer}."      ,      f"layers.{int(__UpperCAmelCase							)//3}.linear."							)
            elif re.match(__UpperCAmelCase      ,      __UpperCAmelCase							):
                  SCREAMING_SNAKE_CASE_     						=      int(re.match(__UpperCAmelCase      ,      __UpperCAmelCase							).group(1							)							)

                  # Because in CLAP they use `nn.Sequential`...
                  SCREAMING_SNAKE_CASE_     						=      1 if projecton_layer == 0 else 2

                  SCREAMING_SNAKE_CASE_     						=      key.replace(f"_projection.{projecton_layer}."      ,      f"_projection.linear{transformers_projection_layer}."							)

            if "audio" and "qkv" in key:
                  # split qkv into query key and value
                  SCREAMING_SNAKE_CASE_     						=      value
                  SCREAMING_SNAKE_CASE_     						=      mixed_qkv.size(0							) // 3

                  SCREAMING_SNAKE_CASE_     						=      mixed_qkv[:qkv_dim]
                  SCREAMING_SNAKE_CASE_     						=      mixed_qkv[qkv_dim : qkv_dim * 2]
                  SCREAMING_SNAKE_CASE_     						=      mixed_qkv[qkv_dim * 2 :]

                  SCREAMING_SNAKE_CASE_     						=      query_layer
                  SCREAMING_SNAKE_CASE_     						=      key_layer
                  SCREAMING_SNAKE_CASE_     						=      value_layer
            else:
                  SCREAMING_SNAKE_CASE_     						=      value

      return model_state_dict

def  UpperCAmelCase_							(				__UpperCAmelCase						:     List[Any]      ,      __UpperCAmelCase						:     List[str]      ,      __UpperCAmelCase						:     List[Any]      ,      __UpperCAmelCase						:     Optional[Any]=False							) ->			List[Any]:
      SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_     						=      init_clap(__UpperCAmelCase      ,      enable_fusion=__UpperCAmelCase							)

      clap_model.eval()
      SCREAMING_SNAKE_CASE_     						=      clap_model.state_dict()
      SCREAMING_SNAKE_CASE_     						=      rename_state_dict(__UpperCAmelCase							)

      SCREAMING_SNAKE_CASE_     						=      ClapConfig()
      SCREAMING_SNAKE_CASE_     						=      enable_fusion
      SCREAMING_SNAKE_CASE_     						=      ClapModel(__UpperCAmelCase							)

      # ignore the spectrogram embedding layer
      model.load_state_dict(__UpperCAmelCase      ,      strict=__UpperCAmelCase							)

      model.save_pretrained(__UpperCAmelCase							)
      transformers_config.save_pretrained(__UpperCAmelCase							)


if __name__ == "__main__":
      lowerCamelCase__			:       Optional[int]         =							argparse.ArgumentParser()
      parser.add_argument('--pytorch_dump_folder_path', default=None, type=str, help='Path to the output PyTorch model.')
      parser.add_argument('--checkpoint_path', default=None, type=str, help='Path to fairseq checkpoint')
      parser.add_argument('--config_path', default=None, type=str, help='Path to hf config.json of model to convert')
      parser.add_argument('--enable_fusion', action='store_true', help='Whether to enable fusion or not')
      lowerCamelCase__			:       List[str]         =							parser.parse_args()

      convert_clap_checkpoint(args.checkpoint_path, args.pytorch_dump_folder_path, args.config_path, args.enable_fusion)





from __future__ import annotations

from sys import maxsize
from typing import Generic, TypeVar

lowerCamelCase__			:       Dict         =							TypeVar('T')

def  UpperCAmelCase_							(				__UpperCAmelCase						:     int							) ->			int:
      return (position - 1) // 2

def  UpperCAmelCase_							(				__UpperCAmelCase						:     int							) ->			int:
      return (2 * position) + 1

def  UpperCAmelCase_							(				__UpperCAmelCase						:     int							) ->			int:
      return (2 * position) + 2





class 	lowerCamelCase_							(				Generic[T] ):


 '''simple docstring'''







 def __init__(							self  :		Optional[Any]						):
       SCREAMING_SNAKE_CASE_     						=      []
       SCREAMING_SNAKE_CASE_     						=      {}
       SCREAMING_SNAKE_CASE_     						=      0



 def __len__(							self  :		Optional[Any]						):
       return self.elements



 def __repr__(							self  :		Optional[int]						):
       return str(self.heap						)



 def 				lowerCAmelCase_  (							self  :		Union[str, Any]						):
       # Check if the priority queue is empty
       return self.elements == 0



 def 				lowerCAmelCase_  (							self  :		Tuple    ,    _lowerCAmelCase  :		T    ,    _lowerCAmelCase  :		int						):
       # Add an element with given priority to the queue
       self.heap.append((elem, weight)						)
       SCREAMING_SNAKE_CASE_     						=      self.elements
       self.elements += 1
       self._bubble_up(_lowerCAmelCase						)



 def 				lowerCAmelCase_  (							self  :		Optional[int]						):
       # Remove and return the element with lowest weight (highest priority)
       if self.elements > 1:
             self._swap_nodes(0    ,    self.elements - 1						)
       SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_     						=      self.heap.pop()
       del self.position_map[elem]
       self.elements -= 1
       if self.elements > 0:
             SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_     						=      self.heap[0]
             self._bubble_down(_lowerCAmelCase						)
       return elem



 def 				lowerCAmelCase_  (							self  :		Optional[int]    ,    _lowerCAmelCase  :		T    ,    _lowerCAmelCase  :		int						):
       # Update the weight of the given key
       SCREAMING_SNAKE_CASE_     						=      self.position_map[elem]
       SCREAMING_SNAKE_CASE_     						=      (elem, weight)
       if position > 0:
             SCREAMING_SNAKE_CASE_     						=      get_parent_position(_lowerCAmelCase						)
             SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_     						=      self.heap[parent_position]
             if parent_weight > weight:
                   self._bubble_up(_lowerCAmelCase						)
             else:
                   self._bubble_down(_lowerCAmelCase						)
       else:
             self._bubble_down(_lowerCAmelCase						)



 def 				lowerCAmelCase_  (							self  :		Union[str, Any]    ,    _lowerCAmelCase  :		T						):
       # Place a node at the proper position (upward movement) [to be used internally
       # only]
       SCREAMING_SNAKE_CASE_     						=      self.position_map[elem]
       if curr_pos == 0:
             return None
       SCREAMING_SNAKE_CASE_     						=      get_parent_position(_lowerCAmelCase						)
       SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_     						=      self.heap[curr_pos]
       SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_     						=      self.heap[parent_position]
       if parent_weight > weight:
             self._swap_nodes(_lowerCAmelCase    ,    _lowerCAmelCase						)
             return self._bubble_up(_lowerCAmelCase						)
       return None



 def 				lowerCAmelCase_  (							self  :		List[Any]    ,    _lowerCAmelCase  :		T						):
       # Place a node at the proper position (downward movement) [to be used
       # internally only]
       SCREAMING_SNAKE_CASE_     						=      self.position_map[elem]
       SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_     						=      self.heap[curr_pos]
       SCREAMING_SNAKE_CASE_     						=      get_child_left_position(_lowerCAmelCase						)
       SCREAMING_SNAKE_CASE_     						=      get_child_right_position(_lowerCAmelCase						)
       if child_left_position < self.elements and child_right_position < self.elements:
             SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_     						=      self.heap[child_left_position]
             SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_     						=      self.heap[child_right_position]
             if child_right_weight < child_left_weight and child_right_weight < weight:
                   self._swap_nodes(_lowerCAmelCase    ,    _lowerCAmelCase						)
                   return self._bubble_down(_lowerCAmelCase						)
       if child_left_position < self.elements:
             SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_     						=      self.heap[child_left_position]
             if child_left_weight < weight:
                   self._swap_nodes(_lowerCAmelCase    ,    _lowerCAmelCase						)
                   return self._bubble_down(_lowerCAmelCase						)
       else:
             return None
       if child_right_position < self.elements:
             SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_     						=      self.heap[child_right_position]
             if child_right_weight < weight:
                   self._swap_nodes(_lowerCAmelCase    ,    _lowerCAmelCase						)
                   return self._bubble_down(_lowerCAmelCase						)
       return None




 def 				lowerCAmelCase_  (							self  :		Optional[Any]    ,    _lowerCAmelCase  :		int    ,    _lowerCAmelCase  :		int						):
       # Swap the nodes at the given positions
       SCREAMING_SNAKE_CASE_     						=      self.heap[nodea_pos][0]
       SCREAMING_SNAKE_CASE_     						=      self.heap[nodea_pos][0]
       SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_     						=      (
           self.heap[nodea_pos],
           self.heap[nodea_pos],
       )
       SCREAMING_SNAKE_CASE_     						=      nodea_pos
       SCREAMING_SNAKE_CASE_     						=      nodea_pos





class 	lowerCamelCase_							(				Generic[T] ):


 '''simple docstring'''







 def __init__(							self  :		Union[str, Any]						):
       SCREAMING_SNAKE_CASE_     						=      {}
       SCREAMING_SNAKE_CASE_     						=      0



 def __repr__(							self  :		Optional[int]						):
       return str(self.connections						)



 def __len__(							self  :		Tuple						):
       return self.nodes



 def 				lowerCAmelCase_  (							self  :		Dict    ,    _lowerCAmelCase  :		T						):
       # Add a node in the graph if it is not in the graph
       if node not in self.connections:
             SCREAMING_SNAKE_CASE_     						=      {}
             self.nodes += 1




 def 				lowerCAmelCase_  (							self  :		List[Any]    ,    _lowerCAmelCase  :		T    ,    _lowerCAmelCase  :		T    ,    _lowerCAmelCase  :		int						):
       # Add an edge between 2 nodes in the graph
       self.add_node(_lowerCAmelCase						)
       self.add_node(_lowerCAmelCase						)
       SCREAMING_SNAKE_CASE_     						=      weight
       SCREAMING_SNAKE_CASE_     						=      weight


def  UpperCAmelCase_							(				__UpperCAmelCase						:     GraphUndirectedWeighted[T]      ,      ) ->			tuple[dict[T, int], dict[T, T | None]]:
      SCREAMING_SNAKE_CASE_     						=      {node: maxsize for node in graph.connections}
      SCREAMING_SNAKE_CASE_     						=      {node: None for node in graph.connections}

      SCREAMING_SNAKE_CASE_     						=      MinPriorityQueue()
      for node, weight in dist.items():
            priority_queue.push(__UpperCAmelCase      ,      __UpperCAmelCase							)

      if priority_queue.is_empty():
            return dist, parent

      # initialization
      SCREAMING_SNAKE_CASE_     						=      priority_queue.extract_min()
      SCREAMING_SNAKE_CASE_     						=      0
      for neighbour in graph.connections[node]:
            if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
                  SCREAMING_SNAKE_CASE_     						=      dist[node] + graph.connections[node][neighbour]
                  priority_queue.update_key(__UpperCAmelCase      ,      dist[neighbour]							)
                  SCREAMING_SNAKE_CASE_     						=      node

    # running prim's algorithm
      while not priority_queue.is_empty():
            SCREAMING_SNAKE_CASE_     						=      priority_queue.extract_min()
            for neighbour in graph.connections[node]:
                  if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
                        SCREAMING_SNAKE_CASE_     						=      dist[node] + graph.connections[node][neighbour]
                        priority_queue.update_key(__UpperCAmelCase      ,      dist[neighbour]							)
                        SCREAMING_SNAKE_CASE_     						=      node
      return dist, parent