
import ast
import difflib
from collections.abc import Mapping
from typing import Any, Callable, Dict





class       __lowerCAmelCase				(  lowerCAmelCase_ ):
				pass


def 	_UpperCAmelCase       (   snake_case			,		snake_case			,		snake_case=None			,		snake_case=False    ):





					"""simple docstring"""

					try:
										_lowerCAmelCase      			=					ast.parse(_SCREAMING_SNAKE_CASE    )
					except SyntaxError as e:
										print("""The code generated by the agent is not valid.\n"""			,		_SCREAMING_SNAKE_CASE    )
										return
					if state is None:
										_lowerCAmelCase      			=					{}
					_lowerCAmelCase      			=					None
					for idx, node in enumerate(expression.body    ):
										try:
															_lowerCAmelCase      			=					evaluate_ast(_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE    )
										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(_SCREAMING_SNAKE_CASE    )
															break
										if line_result is not None:
															_lowerCAmelCase      			=					line_result

					return result


def 	_UpperCAmelCase       (   snake_case			,		snake_case			,		snake_case    ):





					"""simple docstring"""

					if isinstance(_SCREAMING_SNAKE_CASE			,		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(_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE    )
					elif isinstance(_SCREAMING_SNAKE_CASE			,		ast.Call    ):
										# Function call -> we return the value of the function call
										return evaluate_call(_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE    )
					elif isinstance(_SCREAMING_SNAKE_CASE			,		ast.Constant    ):
										# Constant -> just return the value
										return expression.value
					elif isinstance(_SCREAMING_SNAKE_CASE			,		ast.Dict    ):
										# Dict -> evaluate all keys and values
										_lowerCAmelCase      			=					[evaluate_ast(_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE    ) for k in expression.keys]
										_lowerCAmelCase      			=					[evaluate_ast(_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE    ) for v in expression.values]
										return dict(zip(_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE    )    )
					elif isinstance(_SCREAMING_SNAKE_CASE			,		ast.Expr    ):
										# Expression -> evaluate the content
										return evaluate_ast(expression.value			,		_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE    )
					elif isinstance(_SCREAMING_SNAKE_CASE			,		ast.For    ):
										# For loop -> execute the loop
										return evaluate_for(_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE    )
					elif isinstance(_SCREAMING_SNAKE_CASE			,		ast.FormattedValue    ):
										# Formatted value (part of f-string) -> evaluate the content and return
										return evaluate_ast(expression.value			,		_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE    )
					elif isinstance(_SCREAMING_SNAKE_CASE			,		ast.If    ):
										# If -> execute the right branch
										return evaluate_if(_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE    )
					elif hasattr(_SCREAMING_SNAKE_CASE			,		"""Index"""    ) and isinstance(_SCREAMING_SNAKE_CASE			,		ast.Index    ):
										return evaluate_ast(expression.value			,		_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE    )
					elif isinstance(_SCREAMING_SNAKE_CASE			,		ast.JoinedStr    ):
										return "".join([str(evaluate_ast(_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE    )    ) for v in expression.values]    )
					elif isinstance(_SCREAMING_SNAKE_CASE			,		ast.List    ):
										# List -> evaluate all elements
										return [evaluate_ast(_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE    ) for elt in expression.elts]
					elif isinstance(_SCREAMING_SNAKE_CASE			,		ast.Name    ):
										# Name -> pick up the value in the state
										return evaluate_name(_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE    )
					elif isinstance(_SCREAMING_SNAKE_CASE			,		ast.Subscript    ):
										# Subscript -> return the value of the indexing
										return evaluate_subscript(_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE    )
					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 	_UpperCAmelCase       (   snake_case			,		snake_case			,		snake_case    ):





					"""simple docstring"""

					_lowerCAmelCase      			=					assign.targets
					_lowerCAmelCase      			=					evaluate_ast(assign.value			,		_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE    )

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


def 	_UpperCAmelCase       (   snake_case			,		snake_case			,		snake_case    ):





					"""simple docstring"""

					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(_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE    ) for arg in call.args]
					_lowerCAmelCase      			=					{keyword.arg: evaluate_ast(keyword.value			,		_SCREAMING_SNAKE_CASE			,		_SCREAMING_SNAKE_CASE    ) for keyword in call.keywords}
					return func(*_SCREAMING_SNAKE_CASE			,		**_SCREAMING_SNAKE_CASE    )


def 	_UpperCAmelCase       (   snake_case			,		snake_case			,		snake_case    ):





					"""simple docstring"""

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

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


def 	_UpperCAmelCase       (   snake_case			,		snake_case			,		snake_case    ):





					"""simple docstring"""

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


def 	_UpperCAmelCase       (   snake_case			,		snake_case			,		snake_case    ):





					"""simple docstring"""

					if len(condition.ops    ) > 1:
										raise InterpretorError("""Cannot evaluate conditions with multiple operators"""    )

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

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


def 	_UpperCAmelCase       (   snake_case			,		snake_case			,		snake_case    ):





					"""simple docstring"""

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


def 	_UpperCAmelCase       (   snake_case			,		snake_case			,		snake_case    ):





					"""simple docstring"""

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








import unittest

from transformers import SpeechaTextaConfig
from transformers.testing_utils import is_torch_available, require_torch, torch_device

from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_torch_available():
	import torch

	from transformers.models.speech_to_text_a.modeling_speech_to_text_a import (
	    SpeechaTextaDecoder,
	    SpeechaTextaForCausalLM,
	)





@require_torch
class       __lowerCAmelCase				:




				def __init__(							self		,       _snake_case		,       _snake_case=99		,       _snake_case=13		,       _snake_case=16		,       _snake_case=7		,       _snake_case=True		,       _snake_case=True		,       _snake_case=True		,       _snake_case=False		,       _snake_case=True		,       _snake_case=2		,       _snake_case=32		,       _snake_case=4		,       _snake_case=4		,       _snake_case=30		,       _snake_case=0		,       _snake_case=1		,       _snake_case=2		,       _snake_case=None		,       ):



									"""simple docstring"""





									_lowerCAmelCase      			=					parent
									_lowerCAmelCase      			=					batch_size
									_lowerCAmelCase      			=					decoder_seq_length
									# For common tests
									_lowerCAmelCase      			=					self.decoder_seq_length
									_lowerCAmelCase      			=					is_training
									_lowerCAmelCase      			=					use_attention_mask
									_lowerCAmelCase      			=					use_labels

									_lowerCAmelCase      			=					vocab_size
									_lowerCAmelCase      			=					d_model
									_lowerCAmelCase      			=					d_model
									_lowerCAmelCase      			=					decoder_layers
									_lowerCAmelCase      			=					decoder_layers
									_lowerCAmelCase      			=					decoder_ffn_dim
									_lowerCAmelCase      			=					decoder_attention_heads
									_lowerCAmelCase      			=					decoder_attention_heads
									_lowerCAmelCase      			=					eos_token_id
									_lowerCAmelCase      			=					bos_token_id
									_lowerCAmelCase      			=					pad_token_id
									_lowerCAmelCase      			=					decoder_start_token_id
									_lowerCAmelCase      			=					use_cache
									_lowerCAmelCase      			=					max_position_embeddings

									_lowerCAmelCase      			=					None
									_lowerCAmelCase      			=					decoder_seq_length
									_lowerCAmelCase      			=					2
									_lowerCAmelCase      			=					1




				def 							snake_case     (							self	):



									"""simple docstring"""





									_lowerCAmelCase      			=					ids_tensor([self.batch_size, self.decoder_seq_length]		,       self.vocab_size	)

									_lowerCAmelCase      			=					None
									if self.use_attention_mask:
														_lowerCAmelCase      			=					ids_tensor([self.batch_size, self.decoder_seq_length]		,       vocab_size=2	)

									_lowerCAmelCase      			=					None
									if self.use_labels:
														_lowerCAmelCase      			=					ids_tensor([self.batch_size, self.decoder_seq_length]		,       self.vocab_size	)

									_lowerCAmelCase      			=					SpeechaTextaConfig(
									    vocab_size=self.vocab_size		,       d_model=self.d_model		,       decoder_layers=self.decoder_layers		,       decoder_ffn_dim=self.decoder_ffn_dim		,       decoder_attention_heads=self.decoder_attention_heads		,       eos_token_id=self.eos_token_id		,       bos_token_id=self.bos_token_id		,       use_cache=self.use_cache		,       pad_token_id=self.pad_token_id		,       decoder_start_token_id=self.decoder_start_token_id		,       max_position_embeddings=self.max_position_embeddings		,       )

									return (
									    config,
									    input_ids,
									    attention_mask,
									    lm_labels,
									)




				def 							snake_case     (							self		,       _snake_case		,       _snake_case		,       _snake_case		,       _snake_case		,       ):



									"""simple docstring"""





									_lowerCAmelCase      			=					True
									_lowerCAmelCase      			=					SpeechaTextaDecoder(config=_snake_case	).to(_snake_case	).eval()
									_lowerCAmelCase      			=					input_ids[:2]

									input_ids[input_ids == 0] += 1
									# first forward pass
									_lowerCAmelCase      			=					model(_snake_case		,       use_cache=_snake_case	)
									_lowerCAmelCase      			=					model(_snake_case	)
									_lowerCAmelCase      			=					model(_snake_case		,       use_cache=_snake_case	)

									self.parent.assertTrue(len(_snake_case	) == len(_snake_case	)	)
									self.parent.assertTrue(len(_snake_case	) == len(_snake_case	) + 1	)

									_lowerCAmelCase      			=					outputs["""past_key_values"""]

									# create hypothetical next token and extent to next_input_ids
									_lowerCAmelCase      			=					ids_tensor((2, 1)		,       config.vocab_size - 1	) + 1

									# append to next input_ids and
									_lowerCAmelCase      			=					torch.cat([input_ids, next_tokens]		,       dim=-1	)

									print(_snake_case	)

									_lowerCAmelCase      			=					model(_snake_case	)["""last_hidden_state"""]
									_lowerCAmelCase      			=					model(_snake_case		,       past_key_values=_snake_case	)["""last_hidden_state"""]

									# select random slice
									_lowerCAmelCase      			=					ids_tensor((1,)		,       output_from_past.shape[-1]	).item()
									_lowerCAmelCase      			=					output_from_no_past[:, next_input_ids.shape[-1] - 1, random_slice_idx].detach()
									_lowerCAmelCase      			=					output_from_past[:, 0, random_slice_idx].detach()

									# test that outputs are equal for slice
									assert torch.allclose(_snake_case		,       _snake_case		,       atol=1e-3	)




				def 							snake_case     (							self	):



									"""simple docstring"""





									_lowerCAmelCase      			=					self.prepare_config_and_inputs()
									(
									    (
									    _lowerCAmelCase
									)			,			(
									    _lowerCAmelCase
									)			,			(
									    _lowerCAmelCase
									)			,			(
									    _lowerCAmelCase
									)			,			
									)      			=					config_and_inputs

									_lowerCAmelCase      			=					{
									    """input_ids""": input_ids,
									    """attention_mask""": attention_mask,
									}
									return config, inputs_dict





@require_torch
class       __lowerCAmelCase				(  lowerCamelCase__ ,		lowerCamelCase__ ,		lowerCamelCase__ ,		unittest.TestCase ):
				__lowerCamelCase				=       (SpeechaTextaDecoder, SpeechaTextaForCausalLM) if is_torch_available() else ()
				__lowerCamelCase				=       (SpeechaTextaForCausalLM,) if is_torch_available() else ()
				__lowerCamelCase				=       {'''text-generation''': SpeechaTextaForCausalLM} if is_torch_available() else {}
				__lowerCamelCase				=       True
				__lowerCamelCase				=       False




				def 							snake_case     (							self		,       ):



									"""simple docstring"""





									_lowerCAmelCase      			=					SpeechaTextaStandaloneDecoderModelTester(self		,       is_training=_snake_case	)
									_lowerCAmelCase      			=					ConfigTester(self		,       config_class=_snake_case	)




				def 							snake_case     (							self	):



									"""simple docstring"""





									pass




				def 							snake_case     (							self	):



									"""simple docstring"""





									pass




				def 							snake_case     (							self	):



									"""simple docstring"""





									pass




				def 							snake_case     (							self	):



									"""simple docstring"""





									self.config_tester.run_common_tests()




				def 							snake_case     (							self	):



									"""simple docstring"""





									_lowerCAmelCase      			=					self.model_tester.prepare_config_and_inputs()
									self.model_tester.create_and_check_decoder_model_past(*_snake_case	)




				def 							snake_case     (							self	):



									"""simple docstring"""





									return



