




import getopt
import json
import os

# import numpy as np
import sys
from collections import OrderedDict

import datasets
import numpy as np
import torch
from modeling_frcnn import GeneralizedRCNN
from processing_image import Preprocess

from utils import Config
__SCREAMING_SNAKE_CASE			:      Optional[Any]      			=False
__SCREAMING_SNAKE_CASE			:      Dict      			=Config.from_pretrained("""unc-nlp/frcnn-vg-finetuned""")
__SCREAMING_SNAKE_CASE			:      Optional[Any]      			=datasets.Features(
    OrderedDict(
        {
            """attr_ids""": datasets.Sequence(length=CONFIG.MAX_DETECTIONS, feature=datasets.Value("""float32""")),
            """attr_probs""": datasets.Sequence(length=CONFIG.MAX_DETECTIONS, feature=datasets.Value("""float32""")),
            """boxes""": datasets.ArrayaD((CONFIG.MAX_DETECTIONS, 4), dtype="""float32"""),
            """img_id""": datasets.Value("""int32"""),
            """obj_ids""": datasets.Sequence(length=CONFIG.MAX_DETECTIONS, feature=datasets.Value("""float32""")),
            """obj_probs""": datasets.Sequence(length=CONFIG.MAX_DETECTIONS, feature=datasets.Value("""float32""")),
            """roi_features""": datasets.ArrayaD((CONFIG.MAX_DETECTIONS, 2_048), dtype="""float32"""),
            """sizes""": datasets.Sequence(length=2, feature=datasets.Value("""float32""")),
            """preds_per_image""": datasets.Value(dtype="""int32"""),
        }
    )
)






class 	A	:
     """simple docstring"""

     def __init__(			self     :      List[str]		,     A__     :      Tuple=sys.argv[1:]	) ->				List[Any]:
           lowerCamelCase__					     = None
           lowerCamelCase__					     = None
           lowerCamelCase__					     = None
           lowerCamelCase__					     = 1
           lowerCamelCase__     ,						lowerCamelCase__					     = getopt.getopt(A__		,     'i:o:b:s'		,     ['inputdir=', 'outfile=', 'batch_size=', 'subset_list=']	)
           for opt, arg in opts:
                 if opt in ("-i", "--inputdir"):
                       lowerCamelCase__					     = arg
                 elif opt in ("-o", "--outfile"):
                       lowerCamelCase__					     = arg
                 elif opt in ("-b", "--batch_size"):
                       lowerCamelCase__					     = int(A__	)
                 elif opt in ("-s", "--subset_list"):
                       lowerCamelCase__					     = arg

           assert inputdir is not None  # and os.path.isdir(inputdir), f"{inputdir}"
           assert outputfile is not None and not os.path.isfile(A__	), F"""{outputfile}"""
           if subset_list is not None:
                 with open(os.path.realpath(A__	)	) as f:
                       lowerCamelCase__					     = {self._vqa_file_split()[0] for x in tryload(A__	)}
           else:
                 lowerCamelCase__					     = None

           lowerCamelCase__					     = CONFIG
           if torch.cuda.is_available():
                 lowerCamelCase__					     = 'cuda'
           lowerCamelCase__					     = os.path.realpath(A__	)
           lowerCamelCase__					     = os.path.realpath(A__	)
           lowerCamelCase__					     = Preprocess(self.config	)
           lowerCamelCase__					     = GeneralizedRCNN.from_pretrained('unc-nlp/frcnn-vg-finetuned'		,     config=self.config	)
           lowerCamelCase__					     = batch_size if batch_size != 0 else 1
           lowerCamelCase__					     = DEFAULT_SCHEMA




     def        __snake_case      (			self     :      Optional[Any]		,     A__     :      int	) ->				List[str]:
           lowerCamelCase__					     = int(file.split('.'	)[0].split('_'	)[-1]	)
           lowerCamelCase__					     = os.path.join(self.inputdir		,     A__	)
           return (img_id, filepath)




     @property
     def        __snake_case      (			self     :      Any	) ->				List[Any]:
           lowerCamelCase__					     = []
           for i, file in enumerate(os.listdir(self.inputdir	)	):
                 if self.subset_list is not None and i not in self.subset_list:
                       continue
                 batch.append(self._vqa_file_split(A__	)	)
                 if len(A__	) == self.batch:
                       lowerCamelCase__					     = batch
                       lowerCamelCase__					     = []
                       yield list(map(A__		,     zip(*A__	)	)	)

           for i in range(1	):
                 yield list(map(A__		,     zip(*A__	)	)	)




     def __call__(			self     :      Any	) ->				Optional[int]:
           # make writer
           if not TEST:
                 lowerCamelCase__					     = datasets.ArrowWriter(features=self.schema		,     path=self.outputfile	)
           # do file generator
           for i, (img_ids, filepaths) in enumerate(self.file_generator	):
                 lowerCamelCase__     ,						lowerCamelCase__     ,						lowerCamelCase__					     = self.preprocess(A__	)
                 lowerCamelCase__					     = self.model(
                     A__		,     A__		,     scales_yx=A__		,     padding='max_detections'		,     max_detections=self.config.MAX_DETECTIONS		,     pad_value=0		,     return_tensors='np'		,     location='cpu'		,     )
                 lowerCamelCase__					     = output_dict.pop('normalized_boxes'	)
                 if not TEST:
                       lowerCamelCase__					     = np.array(A__	)
                       lowerCamelCase__					     = self.schema.encode_batch(A__	)
                       writer.write_batch(A__	)
                 if TEST:
                       break
                 # finalizer the writer
           if not TEST:
                 lowerCamelCase__     ,						lowerCamelCase__					     = writer.finalize()
                 print(F"""Success! You wrote {num_examples} entry(s) and {num_bytes >> 2_0} mb"""	)

def 	lowerCAmelCase_	(     lowerCamelCase:				Any  )    ->	Optional[Any]:


      '''simple docstring'''




      try:
            lowerCamelCase__					     = json.load(lowerCamelCase  )
            try:
                  lowerCamelCase__					     = list(data.keys()  )
            except Exception:
                  lowerCamelCase__					     = [d['img_id'] for d in data]
      except Exception:
            try:
                  lowerCamelCase__					     = eval(stream.read()  )
            except Exception:
                  lowerCamelCase__					     = stream.read().split('\n'  )
      return data


if __name__ == "__main__":
      __SCREAMING_SNAKE_CASE			:      str      			=Extract(sys.argv[1:])
      extract()
      if not TEST:
            __SCREAMING_SNAKE_CASE			:      str      			=datasets.Dataset.from_file(extract.outputfile)
            # wala!
            # print(np.array(dataset[0:2]["roi_features"]).shape)
# Copyright 2023 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.
import ast
import difflib
from collections.abc import Mapping
from typing import Any, Callable, Dict
class 				a_ (						SCREAMING_SNAKE_CASE						):






 '''simple docstring'''






 pass






def       __lowerCamelCase		(						lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__=None	,  lowerCAmelCase__=False	):
       try:
              lowerCAmelCase__     	=					ast.parse(lowerCAmelCase__	)
       except SyntaxError as e:
              print('The code generated by the agent is not valid.\n'	,  lowerCAmelCase__	)
              return
       if state is None:
              lowerCAmelCase__     	=					{}
       lowerCAmelCase__     	=					None
       for idx, node in enumerate(expression.body	):
              try:
                     lowerCAmelCase__     	=					evaluate_ast(lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	)
              except InterpretorError as e:
                     lowerCAmelCase__     	=					F"""Evaluation of the code stopped at line {idx} before the end because of the following error"""
                     if chat_mode:
                            msg += (
                                F""". Copy paste the following error message and send it back to the agent:\nI get an error: '{e}'"""
                            )
                     else:
                            msg += F""":\n{e}"""
                     print(lowerCAmelCase__	)
                     break
              if line_result is not None:
                     lowerCAmelCase__     	=					line_result

       return result






def       __lowerCamelCase		(						lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	):
       if isinstance(lowerCAmelCase__	,  ast.Assign	):
              # Assignement -> we evaluate the assignement which should update the state
              # We return the variable assigned as it may be used to determine the final result.
              return evaluate_assign(lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	)
       elif isinstance(lowerCAmelCase__	,  ast.Call	):
              # Function call -> we return the value of the function call
              return evaluate_call(lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	)
       elif isinstance(lowerCAmelCase__	,  ast.Constant	):
              # Constant -> just return the value
              return expression.value
       elif isinstance(lowerCAmelCase__	,  ast.Dict	):
              # Dict -> evaluate all keys and values
              lowerCAmelCase__     	=					[evaluate_ast(lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	) for k in expression.keys]
              lowerCAmelCase__     	=					[evaluate_ast(lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	) for v in expression.values]
              return dict(zip(lowerCAmelCase__	,  lowerCAmelCase__	)	)
       elif isinstance(lowerCAmelCase__	,  ast.Expr	):
              # Expression -> evaluate the content
              return evaluate_ast(expression.value	,  lowerCAmelCase__	,  lowerCAmelCase__	)
       elif isinstance(lowerCAmelCase__	,  ast.For	):
              # For loop -> execute the loop
              return evaluate_for(lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	)
       elif isinstance(lowerCAmelCase__	,  ast.FormattedValue	):
              # Formatted value (part of f-string) -> evaluate the content and return
              return evaluate_ast(expression.value	,  lowerCAmelCase__	,  lowerCAmelCase__	)
       elif isinstance(lowerCAmelCase__	,  ast.If	):
              # If -> execute the right branch
              return evaluate_if(lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	)
       elif hasattr(lowerCAmelCase__	,  'Index'	) and isinstance(lowerCAmelCase__	,  ast.Index	):
              return evaluate_ast(expression.value	,  lowerCAmelCase__	,  lowerCAmelCase__	)
       elif isinstance(lowerCAmelCase__	,  ast.JoinedStr	):
              return "".join([str(evaluate_ast(lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	)	) for v in expression.values]	)
       elif isinstance(lowerCAmelCase__	,  ast.List	):
              # List -> evaluate all elements
              return [evaluate_ast(lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	) for elt in expression.elts]
       elif isinstance(lowerCAmelCase__	,  ast.Name	):
              # Name -> pick up the value in the state
              return evaluate_name(lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	)
       elif isinstance(lowerCAmelCase__	,  ast.Subscript	):
              # Subscript -> return the value of the indexing
              return evaluate_subscript(lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	)
       else:
              # For now we refuse anything else. Let's add things as we need them.
              raise InterpretorError(F"""{expression.__class__.__name__} is not supported."""	)






def       __lowerCamelCase		(						lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	):
       lowerCAmelCase__     	=					assign.targets
       lowerCAmelCase__     	=					evaluate_ast(assign.value	,  lowerCAmelCase__	,  lowerCAmelCase__	)

       if len(lowerCAmelCase__	) == 1:
              lowerCAmelCase__     	=					result
       else:
              if len(lowerCAmelCase__	) != len(lowerCAmelCase__	):
                     raise InterpretorError(F"""Expected {len(lowerCAmelCase__	)} values but got {len(lowerCAmelCase__	)}."""	)
              for var_name, r in zip(lowerCAmelCase__	,  lowerCAmelCase__	):
                     lowerCAmelCase__     	=					r
       return result






def       __lowerCamelCase		(						lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	):
       if not isinstance(call.func	,  ast.Name	):
              raise InterpretorError(
                  F"""It is not permitted to evaluate other functions than the provided tools (tried to execute {call.func} of """
                  F"""type {type(call.func	)}."""	)
       lowerCAmelCase__     	=					call.func.id
       if func_name not in tools:
              raise InterpretorError(
                  F"""It is not permitted to evaluate other functions than the provided tools (tried to execute {call.func.id})."""	)

       lowerCAmelCase__     	=					tools[func_name]
       # Todo deal with args
       lowerCAmelCase__     	=					[evaluate_ast(lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	) for arg in call.args]
       lowerCAmelCase__     	=					{keyword.arg: evaluate_ast(keyword.value	,  lowerCAmelCase__	,  lowerCAmelCase__	) for keyword in call.keywords}
       return func(*lowerCAmelCase__	,  **lowerCAmelCase__	)






def       __lowerCamelCase		(						lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	):
       lowerCAmelCase__     	=					evaluate_ast(subscript.slice	,  lowerCAmelCase__	,  lowerCAmelCase__	)
       lowerCAmelCase__     	=					evaluate_ast(subscript.value	,  lowerCAmelCase__	,  lowerCAmelCase__	)
       if isinstance(lowerCAmelCase__	,  (list, tuple)	):
              return value[int(lowerCAmelCase__	)]
       if index in value:
              return value[index]
       if isinstance(lowerCAmelCase__	,  lowerCAmelCase__	) and isinstance(lowerCAmelCase__	,  lowerCAmelCase__	):
              lowerCAmelCase__     	=					difflib.get_close_matches(lowerCAmelCase__	,  list(value.keys()	)	)
              if len(lowerCAmelCase__	) > 0:
                     return value[close_matches[0]]

       raise InterpretorError(F"""Could not index {value} with '{index}'."""	)






def       __lowerCamelCase		(						lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	):
       if name.id in state:
              return state[name.id]
       lowerCAmelCase__     	=					difflib.get_close_matches(name.id	,  list(state.keys()	)	)
       if len(lowerCAmelCase__	) > 0:
              return state[close_matches[0]]
       raise InterpretorError(F"""The variable `{name.id}` is not defined."""	)






def       __lowerCamelCase		(						lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	):
       if len(condition.ops	) > 1:
              raise InterpretorError('Cannot evaluate conditions with multiple operators'	)

       lowerCAmelCase__     	=					evaluate_ast(condition.left	,  lowerCAmelCase__	,  lowerCAmelCase__	)
       lowerCAmelCase__     	=					condition.ops[0]
       lowerCAmelCase__     	=					evaluate_ast(condition.comparators[0]	,  lowerCAmelCase__	,  lowerCAmelCase__	)

       if isinstance(lowerCAmelCase__	,  ast.Eq	):
              return left == right
       elif isinstance(lowerCAmelCase__	,  ast.NotEq	):
              return left != right
       elif isinstance(lowerCAmelCase__	,  ast.Lt	):
              return left < right
       elif isinstance(lowerCAmelCase__	,  ast.LtE	):
              return left <= right
       elif isinstance(lowerCAmelCase__	,  ast.Gt	):
              return left > right
       elif isinstance(lowerCAmelCase__	,  ast.GtE	):
              return left >= right
       elif isinstance(lowerCAmelCase__	,  ast.Is	):
              return left is right
       elif isinstance(lowerCAmelCase__	,  ast.IsNot	):
              return left is not right
       elif isinstance(lowerCAmelCase__	,  ast.In	):
              return left in right
       elif isinstance(lowerCAmelCase__	,  ast.NotIn	):
              return left not in right
       else:
              raise InterpretorError(F"""Operator not supported: {comparator}"""	)






def       __lowerCamelCase		(						lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	):
       lowerCAmelCase__     	=					None
       if evaluate_condition(if_statement.test	,  lowerCAmelCase__	,  lowerCAmelCase__	):
              for line in if_statement.body:
                     lowerCAmelCase__     	=					evaluate_ast(lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	)
                     if line_result is not None:
                            lowerCAmelCase__     	=					line_result
       else:
              for line in if_statement.orelse:
                     lowerCAmelCase__     	=					evaluate_ast(lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	)
                     if line_result is not None:
                            lowerCAmelCase__     	=					line_result
       return result






def       __lowerCamelCase		(						lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	):
       lowerCAmelCase__     	=					None
       lowerCAmelCase__     	=					evaluate_ast(for_loop.iter	,  lowerCAmelCase__	,  lowerCAmelCase__	)
       for counter in iterator:
              lowerCAmelCase__     	=					counter
              for expression in for_loop.body:
                     lowerCAmelCase__     	=					evaluate_ast(lowerCAmelCase__	,  lowerCAmelCase__	,  lowerCAmelCase__	)
                     if line_result is not None:
                            lowerCAmelCase__     	=					line_result
       return result
