






# 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 	lowerCamelCase__				(							UpperCAmelCase ):
      pass




def       _a   (							lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__=None ,			lowerCamelCase__=False				)  ->      int:
 try:
  lowerCamelCase_							:    Any							=     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_							:    Any							=     {}
 lowerCamelCase_							:    Dict							=     None
 for idx, node in enumerate(expression.body				):
  try:
   lowerCamelCase_							:    List[Any]							=     evaluate_ast(lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)
  except InterpretorError as e:
   lowerCamelCase_							:    List[str]							=     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_							:    str							=     line_result

 return result




def       _a   (							lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)  ->      List[str]:
 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_							:    Union[str, Any]							=     [evaluate_ast(lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				) for k in expression.keys]
  lowerCamelCase_							:    Any							=     [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       _a   (							lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)  ->      Optional[Any]:
 lowerCamelCase_							:    List[Any]							=     assign.targets
 lowerCamelCase_							:    Optional[Any]							=     evaluate_ast(assign.value ,			lowerCamelCase__ ,			lowerCamelCase__				)

 if len(lowerCamelCase__				) == 1:
  lowerCamelCase_							:    Optional[int]							=     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_							:    Union[str, Any]							=     r
 return result




def       _a   (							lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)  ->      Union[str, Any]:
 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_							:    Optional[int]							=     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_							:    str							=     tools[func_name]
 # Todo deal with args
 lowerCamelCase_							:    Dict							=     [evaluate_ast(lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				) for arg in call.args]
 lowerCamelCase_							:    List[Any]							=     {keyword.arg: evaluate_ast(keyword.value ,			lowerCamelCase__ ,			lowerCamelCase__				) for keyword in call.keywords}
 return func(*lowerCamelCase__ ,			**lowerCamelCase__				)




def       _a   (							lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)  ->      List[str]:
 lowerCamelCase_							:    Dict							=     evaluate_ast(subscript.slice ,			lowerCamelCase__ ,			lowerCamelCase__				)
 lowerCamelCase_							:    Optional[Any]							=     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_							:    Optional[int]							=     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       _a   (							lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)  ->      Tuple:
 if name.id in state:
  return state[name.id]
 lowerCamelCase_							:    Optional[int]							=     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       _a   (							lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)  ->      Tuple:
 if len(condition.ops				) > 1:
  raise InterpretorError('Cannot evaluate conditions with multiple operators'				)

 lowerCamelCase_							:    str							=     evaluate_ast(condition.left ,			lowerCamelCase__ ,			lowerCamelCase__				)
 lowerCamelCase_							:    Any							=     condition.ops[0]
 lowerCamelCase_							:    Optional[int]							=     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       _a   (							lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)  ->      Any:
 lowerCamelCase_							:    str							=     None
 if evaluate_condition(if_statement.test ,			lowerCamelCase__ ,			lowerCamelCase__				):
  for line in if_statement.body:
   lowerCamelCase_							:    str							=     evaluate_ast(lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)
   if line_result is not None:
    lowerCamelCase_							:    Dict							=     line_result
 else:
  for line in if_statement.orelse:
   lowerCamelCase_							:    Dict							=     evaluate_ast(lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)
   if line_result is not None:
    lowerCamelCase_							:    Optional[int]							=     line_result
 return result





def       _a   (							lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)  ->      List[Any]:
 lowerCamelCase_							:    Optional[Any]							=     None
 lowerCamelCase_							:    Optional[int]							=     evaluate_ast(for_loop.iter ,			lowerCamelCase__ ,			lowerCamelCase__				)
 for counter in iterator:
  lowerCamelCase_							:    List[str]							=     counter
  for expression in for_loop.body:
   lowerCamelCase_							:    Optional[int]							=     evaluate_ast(lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)
   if line_result is not None:
    lowerCamelCase_							:    Tuple							=     line_result
 return result








from functools import partial
from typing import Any, Callable, Dict, List, Type, TypeVar, Union, overload

import torch
import torch.nn as nn
import torch.types




def       _a   (							lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)  ->      torch.Tensor:
 # The first operation in a checkpoint can't be in-place, but it's
 # nice to have in-place addition during inference. Thus...
 if not inplace:
  lowerCamelCase_							:    Tuple							=     ma + ma
 else:
  ma += ma

 return ma




def       _a   (							lowerCamelCase__ ,			lowerCamelCase__				)  ->      torch.Tensor:
 lowerCamelCase_							:    Union[str, Any]							=     -1 * len(lowerCamelCase__				)
 lowerCamelCase_							:    Optional[Any]							=     list(range(len(tensor.shape[:zero_index]				)				)				)
 return tensor.permute(first_inds + [zero_index + i for i in inds]				)




def       _a   (							lowerCamelCase__ ,			lowerCamelCase__				)  ->      torch.Tensor:
 return t.reshape(t.shape[:-no_dims] + (-1,)				)




def       _a   (							lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__ = 1e-4				)  ->      torch.Tensor:
 lowerCamelCase_							:    Optional[int]							=     mask.expand(*value.shape				)
 return torch.sum(mask * value ,			dim=lowerCamelCase__				) / (eps + torch.sum(lowerCamelCase__ ,			dim=lowerCamelCase__				))




def       _a   (							lowerCamelCase__ ,			lowerCamelCase__ = 2.3125 ,			lowerCamelCase__ = 21.6875 ,			lowerCamelCase__ = 64				)  ->      torch.Tensor:
 lowerCamelCase_							:    int							=     torch.linspace(lowerCamelCase__ ,			lowerCamelCase__ ,			no_bins - 1 ,			device=pts.device				)
 lowerCamelCase_							:    Tuple							=     torch.sqrt(torch.sum((pts.unsqueeze(-2				) - pts.unsqueeze(-3				)) ** 2 ,			dim=-1				)				)
 return torch.bucketize(lowerCamelCase__ ,			lowerCamelCase__				)




def       _a   (							lowerCamelCase__ ,			lowerCamelCase__				)  ->      dict:
 lowerCamelCase_							:    Optional[Any]							=     dicts[0]
 lowerCamelCase_							:    Optional[Any]							=     {}
 for k, v in first.items():
  lowerCamelCase_							:    Tuple							=     [d[k] for d in dicts]
  if isinstance(lowerCamelCase__ ,			lowerCamelCase__				):
   lowerCamelCase_							:    Optional[int]							=     dict_multimap(lowerCamelCase__ ,			lowerCamelCase__				)
  else:
   lowerCamelCase_							:    List[Any]							=     fn(lowerCamelCase__				)

 return new_dict




def       _a   (							lowerCamelCase__ ,			lowerCamelCase__				)  ->      torch.Tensor:
 lowerCamelCase_							:    str							=     v_bins.view(((1,) * len(x.shape				)) + (len(lowerCamelCase__				),)				)
 lowerCamelCase_							:    List[Any]							=     x[..., None] - reshaped_bins
 lowerCamelCase_							:    List[Any]							=     torch.argmin(torch.abs(lowerCamelCase__				) ,			dim=-1				)
 return nn.functional.one_hot(lowerCamelCase__ ,			num_classes=len(lowerCamelCase__				)				).float()




def       _a   (							lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__ = 0 ,			lowerCamelCase__ = 0				)  ->      torch.Tensor:
 lowerCamelCase_							:    List[Union[slice, torch.Tensor]]							=     []
 for i, s in enumerate(data.shape[:no_batch_dims]				):
  lowerCamelCase_							:    int							=     torch.arange(lowerCamelCase__				)
  lowerCamelCase_							:    Any							=     r.view(*(*((1,) * i), -1, *((1,) * (len(inds.shape				) - i - 1)))				)
  ranges.append(lowerCamelCase__				)

 lowerCamelCase_							:    List[Union[slice, torch.Tensor]]							=     [slice(lowerCamelCase__				) for _ in range(len(data.shape				) - no_batch_dims				)]
 lowerCamelCase_							:    Optional[int]							=     inds
 ranges.extend(lowerCamelCase__				)
 # Matt note: Editing this to get around the behaviour of using a list as an array index changing
 # in recent Numpy versions
 return data[tuple(lowerCamelCase__				)]


UpperCamelCase											=      TypeVar('''T''')




def       _a   (							lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)  ->      Dict[Any, Union[dict, list, tuple, Any]]:
 lowerCamelCase_							:    Dict[Any, Union[dict, list, tuple, Any]]							=     {}
 for k, v in dic.items():
  if isinstance(lowerCamelCase__ ,			lowerCamelCase__				):
   lowerCamelCase_							:    Optional[Any]							=     dict_map(lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)
  else:
   lowerCamelCase_							:    Dict							=     tree_map(lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)

 return new_dict




@overload
def       _a   (							lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)  ->      Any:
 ...




@overload
def       _a   (							lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)  ->      dict:
 ...




@overload
def       _a   (							lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)  ->      list:
 ...




@overload
def       _a   (							lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)  ->      tuple:
 ...




def       _a   (							lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)  ->      Any:
 if isinstance(lowerCamelCase__ ,			lowerCamelCase__				):
  return dict_map(lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				)
 elif isinstance(lowerCamelCase__ ,			lowerCamelCase__				):
  return [tree_map(lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				) for x in tree]
 elif isinstance(lowerCamelCase__ ,			lowerCamelCase__				):
  return tuple(tree_map(lowerCamelCase__ ,			lowerCamelCase__ ,			lowerCamelCase__				) for x in tree				)
 elif isinstance(lowerCamelCase__ ,			lowerCamelCase__				):
  return fn(lowerCamelCase__				)
 else:
  print(type(lowerCamelCase__				)				)
  raise ValueError('Not supported'				)





UpperCamelCase											=      partial(tree_map, leaf_type=torch.Tensor)
