


import unittest
from unittest.util import safe_repr

from transformers import AutoTokenizer, RwkvConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device

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


if is_torch_available():
	import torch

	from transformers import (
	    RWKV_PRETRAINED_MODEL_ARCHIVE_LIST,
	    RwkvForCausalLM,
	    RwkvModel,
	)
	from transformers.pytorch_utils import is_torch_greater_or_equal_than_2_0
else:
	A :	str												=     False



class 							A					:
					'''simple docstring'''






					def __init__(self					:		Dict   ,      _UpperCAmelCase					:		Union[str, Any]   ,      _UpperCAmelCase					:		Optional[Any]=14   ,      _UpperCAmelCase					:		List[Any]=7   ,      _UpperCAmelCase					:		Union[str, Any]=True   ,      _UpperCAmelCase					:		Tuple=False   ,      _UpperCAmelCase					:		List[str]=True   ,      _UpperCAmelCase					:		Optional[Any]=True   ,      _UpperCAmelCase					:		Union[str, Any]=True   ,      _UpperCAmelCase					:		Union[str, Any]=99   ,      _UpperCAmelCase					:		Optional[Any]=32   ,      _UpperCAmelCase					:		int=5   ,      _UpperCAmelCase					:		int=37   ,      _UpperCAmelCase					:		Dict="gelu"   ,      _UpperCAmelCase					:		Optional[int]=0.1   ,      _UpperCAmelCase					:		Any=0.1   ,      _UpperCAmelCase					:		List[str]=512   ,      _UpperCAmelCase					:		List[str]=16   ,      _UpperCAmelCase					:		Tuple=2   ,      _UpperCAmelCase					:		Any=3   ,      _UpperCAmelCase					:		str=4   ,      _UpperCAmelCase					:		Dict=None   ,      )		->     str:




							"""simple docstring"""


							lowercase__      =	parent
							lowercase__      =	batch_size
							lowercase__      =	seq_length
							lowercase__      =	is_training
							lowercase__      =	use_token_type_ids
							lowercase__      =	use_input_mask
							lowercase__      =	use_labels
							lowercase__      =	use_mc_token_ids
							lowercase__      =	vocab_size
							lowercase__      =	hidden_size
							lowercase__      =	num_hidden_layers
							lowercase__      =	intermediate_size
							lowercase__      =	hidden_act
							lowercase__      =	hidden_dropout_prob
							lowercase__      =	attention_probs_dropout_prob
							lowercase__      =	max_position_embeddings
							lowercase__      =	type_vocab_size
							lowercase__      =	type_sequence_label_size
							lowercase__      =	num_labels
							lowercase__      =	num_choices
							lowercase__      =	scope
							lowercase__      =	vocab_size - 1
							lowercase__      =	vocab_size - 1
							lowercase__      =	vocab_size - 1

					def 						lowerCamelCase__  (self					:		Optional[Any]	)		->     str:




							"""simple docstring"""


							return RwkvConfig.from_pretrained("""sgugger/rwkv-4-pile-7b"""	)

					def 						lowerCamelCase__  (self					:		Tuple   ,      _UpperCAmelCase					:		List[Any]=False   ,      _UpperCAmelCase					:		Tuple=False   ,      _UpperCAmelCase					:		int=False	)		->     Optional[int]:




							"""simple docstring"""


							lowercase__      =	ids_tensor([self.batch_size, self.seq_length]   ,      self.vocab_size	)

							lowercase__      =	None
							if self.use_input_mask:
									lowercase__      =	random_attention_mask([self.batch_size, self.seq_length]	)

							lowercase__      =	None
							if self.use_token_type_ids:
									lowercase__      =	ids_tensor([self.batch_size, self.seq_length]   ,      self.type_vocab_size	)

							lowercase__      =	None
							if self.use_mc_token_ids:
									lowercase__      =	ids_tensor([self.batch_size, self.num_choices]   ,      self.seq_length	)

							lowercase__      =	None
							lowercase__      =	None
							lowercase__      =	None
							if self.use_labels:
									lowercase__      =	ids_tensor([self.batch_size]   ,      self.type_sequence_label_size	)
									lowercase__      =	ids_tensor([self.batch_size, self.seq_length]   ,      self.num_labels	)
									lowercase__      =	ids_tensor([self.batch_size]   ,      self.num_choices	)

							lowercase__      =	self.get_config(
							    gradient_checkpointing=_UpperCAmelCase   ,      scale_attn_by_inverse_layer_idx=_UpperCAmelCase   ,      reorder_and_upcast_attn=_UpperCAmelCase   ,      )

							return (
							    config,
							    input_ids,
							    input_mask,
							    None,
							    token_type_ids,
							    mc_token_ids,
							    sequence_labels,
							    token_labels,
							    choice_labels,
							)

					def 						lowerCamelCase__  (self					:		List[str]   ,      _UpperCAmelCase					:		Optional[int]=False   ,      _UpperCAmelCase					:		List[str]=False   ,      _UpperCAmelCase					:		List[Any]=False	)		->     int:




							"""simple docstring"""


							return RwkvConfig(
							    vocab_size=self.vocab_size   ,      hidden_size=self.hidden_size   ,      num_hidden_layers=self.num_hidden_layers   ,      intermediate_size=self.intermediate_size   ,      activation_function=self.hidden_act   ,      resid_pdrop=self.hidden_dropout_prob   ,      attn_pdrop=self.attention_probs_dropout_prob   ,      n_positions=self.max_position_embeddings   ,      type_vocab_size=self.type_vocab_size   ,      use_cache=_UpperCAmelCase   ,      bos_token_id=self.bos_token_id   ,      eos_token_id=self.eos_token_id   ,      pad_token_id=self.pad_token_id   ,      gradient_checkpointing=_UpperCAmelCase   ,      scale_attn_by_inverse_layer_idx=_UpperCAmelCase   ,      reorder_and_upcast_attn=_UpperCAmelCase   ,      )

					def 						lowerCamelCase__  (self					:		Union[str, Any]	)		->     str:




							"""simple docstring"""


							lowercase__      =	self.get_config()
							lowercase__      =	300
							return config

					def 						lowerCamelCase__  (self					:		Tuple	)		->     Dict:




							"""simple docstring"""


							(
							    (
							    lowercase__
							)    ,			(
							    lowercase__
							)    ,			(
							    lowercase__
							)    ,			(
							    lowercase__
							)    ,			(
							    lowercase__
							)    ,			(
							    lowercase__
							)    ,			(
							    lowercase__
							)    ,			(
							    lowercase__
							)    ,			(
							    lowercase__
							)    ,			
							)      =	self.prepare_config_and_inputs()

							lowercase__      =	floats_tensor([self.batch_size, self.seq_length, self.hidden_size]	)
							lowercase__      =	ids_tensor([self.batch_size, self.seq_length]   ,      vocab_size=2	)

							return (
							    config,
							    input_ids,
							    input_mask,
							    head_mask,
							    token_type_ids,
							    sequence_labels,
							    token_labels,
							    choice_labels,
							    encoder_hidden_states,
							    encoder_attention_mask,
							)

					def 						lowerCamelCase__  (self					:		List[str]   ,      _UpperCAmelCase					:		Tuple   ,      _UpperCAmelCase					:		int   ,      _UpperCAmelCase					:		List[Any]   ,      _UpperCAmelCase					:		Any   ,      _UpperCAmelCase					:		Optional[int]   ,      *_UpperCAmelCase					:		Any	)		->     Optional[Any]:




							"""simple docstring"""


							lowercase__      =	True
							lowercase__      =	RwkvModel(config=_UpperCAmelCase	)
							model.to(_UpperCAmelCase	)
							model.eval()

							lowercase__      =	model(_UpperCAmelCase	)

							self.parent.assertEqual(result.last_hidden_state.shape   ,      (self.batch_size, self.seq_length, self.hidden_size)	)
							self.parent.assertEqual(len(result.hidden_states	)   ,      config.num_hidden_layers + 1	)

					def 						lowerCamelCase__  (self					:		List[Any]   ,      _UpperCAmelCase					:		Union[str, Any]   ,      _UpperCAmelCase					:		str   ,      _UpperCAmelCase					:		int   ,      _UpperCAmelCase					:		str   ,      _UpperCAmelCase					:		int   ,      *_UpperCAmelCase					:		str	)		->     Tuple:




							"""simple docstring"""


							lowercase__      =	RwkvForCausalLM(_UpperCAmelCase	)
							model.to(_UpperCAmelCase	)
							model.eval()

							lowercase__      =	model(_UpperCAmelCase   ,      labels=_UpperCAmelCase	)
							self.parent.assertEqual(result.loss.shape   ,      ()	)
							self.parent.assertEqual(result.logits.shape   ,      (self.batch_size, self.seq_length, self.vocab_size)	)

					def 						lowerCamelCase__  (self					:		int   ,      _UpperCAmelCase					:		Optional[int]   ,      _UpperCAmelCase					:		Union[str, Any]   ,      _UpperCAmelCase					:		Dict   ,      _UpperCAmelCase					:		Dict   ,      _UpperCAmelCase					:		Optional[int]   ,      *_UpperCAmelCase					:		str	)		->     str:




							"""simple docstring"""


							lowercase__      =	RwkvModel(config=_UpperCAmelCase	)
							model.to(_UpperCAmelCase	)
							model.eval()

							lowercase__      =	model(_UpperCAmelCase	)
							lowercase__      =	outputs.last_hidden_state

							lowercase__      =	model(input_ids[:, :2]	)
							lowercase__      =	outputs.last_hidden_state

							# Using the state computed on the first inputs, we will get the same output
							lowercase__      =	model(input_ids[:, 2:]   ,      state=outputs.state	)
							lowercase__      =	outputs.last_hidden_state

							self.parent.assertTrue(torch.allclose(torch.cat([output_one, output_two]   ,      dim=1	)   ,      _UpperCAmelCase   ,      atol=1E-5	)	)

					def 						lowerCamelCase__  (self					:		Union[str, Any]   ,      _UpperCAmelCase					:		Dict   ,      _UpperCAmelCase					:		Optional[int]   ,      _UpperCAmelCase					:		Union[str, Any]   ,      _UpperCAmelCase					:		List[Any]   ,      _UpperCAmelCase					:		List[str]   ,      *_UpperCAmelCase					:		List[Any]   ,      _UpperCAmelCase					:		Optional[Any]=False	)		->     int:




							"""simple docstring"""


							lowercase__      =	RwkvForCausalLM(_UpperCAmelCase	)
							model.to(_UpperCAmelCase	)
							if gradient_checkpointing:
									model.gradient_checkpointing_enable()

							lowercase__      =	model(_UpperCAmelCase   ,      labels=_UpperCAmelCase	)
							self.parent.assertEqual(result.loss.shape   ,      ()	)
							self.parent.assertEqual(result.logits.shape   ,      (self.batch_size, self.seq_length, self.vocab_size)	)
							result.loss.backward()


					def 						lowerCamelCase__  (self					:		Tuple	)		->     Optional[Any]:




							"""simple docstring"""


							lowercase__      =	self.prepare_config_and_inputs()

							(
							    (
							    lowercase__
							)    ,			(
							    lowercase__
							)    ,			(
							    lowercase__
							)    ,			(
							    lowercase__
							)    ,			(
							    lowercase__
							)    ,			(
							    lowercase__
							)    ,			(
							    lowercase__
							)    ,			(
							    lowercase__
							)    ,			(
							    lowercase__
							)    ,			
							)      =	config_and_inputs

							lowercase__      =	{"""input_ids""": input_ids}

							return config, inputs_dict






@unittest.skipIf(
    not is_torch_greater_or_equal_than_2_0				,						reason='''See https://github.com/huggingface/transformers/pull/24204'''							)
@require_torch
class 							A					( UpperCAmelCase__				,						UpperCAmelCase__				,						UpperCAmelCase__				,						unittest.TestCase							):
					'''simple docstring'''






					A__    =				(RwkvModel, RwkvForCausalLM) if is_torch_available() else ()
					A__    =				(
					    {'''feature-extraction''': RwkvModel, '''text-generation''': RwkvForCausalLM} if is_torch_available() else {}
					)
					# all_generative_model_classes = (RwkvForCausalLM,) if is_torch_available() else ()
					A__    =				False
					A__    =				False
					A__    =				False
					A__    =				False
					A__    =				False  # Rwkv does not support head masking

					def 						lowerCamelCase__  (self					:		str	)		->     str:




							"""simple docstring"""


							lowercase__      =	RwkvModelTester(self	)
							lowercase__      =	ConfigTester(
							    self   ,      config_class=_UpperCAmelCase   ,      n_embd=37   ,      common_properties=["""hidden_size""", """num_hidden_layers"""]	)

					def 						lowerCamelCase__  (self					:		List[Any]   ,      _UpperCAmelCase					:		List[str]   ,      _UpperCAmelCase					:		int   ,      _UpperCAmelCase					:		Optional[Any]=None	)		->     Union[str, Any]:




							"""simple docstring"""


							if isinstance(_UpperCAmelCase   ,      torch.Tensor	):
									lowercase__    ,			lowercase__      =	member.max().item(), member.min().item()
							elif isinstance(_UpperCAmelCase   ,      _UpperCAmelCase	) or isinstance(_UpperCAmelCase   ,      _UpperCAmelCase	):
									lowercase__    ,			lowercase__      =	max(_UpperCAmelCase	), min(_UpperCAmelCase	)

							if not isinstance(_UpperCAmelCase   ,      _UpperCAmelCase	):
									raise TypeError("""container should be a list or tuple"""	)
							elif len(_UpperCAmelCase	) != 2:
									raise ValueError("""container should have 2 elements"""	)

							lowercase__    ,			lowercase__      =	container

							lowercase__      =	(min_value >= expected_min) and (max_value <= expected_max)

							if not is_inside_interval:
									lowercase__      =	"""%s not found in %s""" % (safe_repr(_UpperCAmelCase	), safe_repr(_UpperCAmelCase	))
									self.fail(self._formatMessage(_UpperCAmelCase   ,      _UpperCAmelCase	)	)

					def 						lowerCamelCase__  (self					:		str	)		->     List[str]:




							"""simple docstring"""


							self.config_tester.run_common_tests()

					def 						lowerCamelCase__  (self					:		Tuple	)		->     str:




							"""simple docstring"""


							lowercase__      =	self.model_tester.prepare_config_and_inputs()
							self.model_tester.create_and_check_rwkv_model(*_UpperCAmelCase	)

					def 						lowerCamelCase__  (self					:		Union[str, Any]	)		->     Any:




							"""simple docstring"""


							lowercase__      =	self.model_tester.prepare_config_and_inputs()
							self.model_tester.create_and_check_causl_lm(*_UpperCAmelCase	)

					def 						lowerCamelCase__  (self					:		List[str]	)		->     List[str]:




							"""simple docstring"""


							lowercase__      =	self.model_tester.prepare_config_and_inputs()
							self.model_tester.create_and_check_state_equivalency(*_UpperCAmelCase	)

					def 						lowerCamelCase__  (self					:		Optional[int]	)		->     Optional[Any]:




							"""simple docstring"""


							lowercase__    ,			lowercase__      =	self.model_tester.prepare_config_and_inputs_for_common()

							for model_class in self.all_model_classes:
									lowercase__      =	model_class(config=_UpperCAmelCase	)
									for name, param in model.named_parameters():
											if "time_decay" in name:
													if param.requires_grad:
															self.assertTrue(param.data.max().item() == 3.0	)
															self.assertTrue(param.data.min().item() == -5.0	)
											elif "time_first" in name:
													if param.requires_grad:
															# check if it's a ones like
															self.assertTrue(torch.allclose(param.data   ,      torch.ones_like(param.data	)   ,      atol=1E-5   ,      rtol=1E-5	)	)
											elif any(x in name for x in ["""time_mix_key""", """time_mix_receptance"""]	):
													if param.requires_grad:
															self.assertInterval(
															    param.data   ,      [0.0, 1.0]   ,      msg=f'''Parameter {name} of model {model_class} seems not properly initialized'''   ,      )
											elif "time_mix_value" in name:
													if param.requires_grad:
															self.assertInterval(
															    param.data   ,      [0.0, 1.3]   ,      msg=f'''Parameter {name} of model {model_class} seems not properly initialized'''   ,      )

					def 						lowerCamelCase__  (self					:		Union[str, Any]	)		->     int:




							"""simple docstring"""


							lowercase__    ,			lowercase__      =	self.model_tester.prepare_config_and_inputs_for_common()
							lowercase__      =	True

							lowercase__      =	getattr(self.model_tester   ,      """seq_length"""   ,      _UpperCAmelCase	)

							for model_class in self.all_model_classes:
									lowercase__      =	True
									lowercase__      =	False
									lowercase__      =	True
									lowercase__      =	model_class(_UpperCAmelCase	)
									model.to(_UpperCAmelCase	)
									model.eval()

									lowercase__      =	self._prepare_for_class(_UpperCAmelCase   ,      _UpperCAmelCase	)
									lowercase__      =	inputs["""input_ids"""].shape[0]
									with torch.no_grad():
											lowercase__      =	model(**_UpperCAmelCase	)
									lowercase__      =	outputs.attentions
									self.assertEqual(len(_UpperCAmelCase	)   ,      self.model_tester.num_hidden_layers	)

									# check that output_attentions also work using config
									del inputs_dict["output_attentions"]
									lowercase__      =	True
									lowercase__      =	model_class(_UpperCAmelCase	)
									model.to(_UpperCAmelCase	)
									model.eval()

									lowercase__      =	self._prepare_for_class(_UpperCAmelCase   ,      _UpperCAmelCase	)
									lowercase__      =	inputs["""input_ids"""].shape[0]
									with torch.no_grad():
											lowercase__      =	model(**_UpperCAmelCase	)
									lowercase__      =	outputs.attentions
									self.assertEqual(len(_UpperCAmelCase	)   ,      self.model_tester.num_hidden_layers	)

									self.assertListEqual(
									    list(attentions[0].shape[-3:]	)   ,      [batch_size, seq_len, config.hidden_size]   ,      )
									lowercase__      =	len(_UpperCAmelCase	)

									# Check attention is always last and order is fine
									lowercase__      =	True
									lowercase__      =	True
									lowercase__      =	model_class(_UpperCAmelCase	)
									model.to(_UpperCAmelCase	)
									model.eval()

									lowercase__      =	self._prepare_for_class(_UpperCAmelCase   ,      _UpperCAmelCase	)
									lowercase__      =	inputs["""input_ids"""].shape[0]
									with torch.no_grad():
											lowercase__      =	model(**_UpperCAmelCase	)

									lowercase__      =	1
									self.assertEqual(out_len + added_hidden_states   ,      len(_UpperCAmelCase	)	)

									lowercase__      =	outputs.attentions

									self.assertEqual(len(_UpperCAmelCase	)   ,      self.model_tester.num_hidden_layers	)
									self.assertListEqual(
									    list(self_attentions[0].shape[-3:]	)   ,      [batch_size, seq_len, config.hidden_size]   ,      )


					@slow
					def 						lowerCamelCase__  (self					:		List[Any]	)		->     Optional[int]:




							"""simple docstring"""


							for model_name in RWKV_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
									lowercase__      =	RwkvModel.from_pretrained(_UpperCAmelCase	)
									self.assertIsNotNone(_UpperCAmelCase	)






@unittest.skipIf(
    not is_torch_greater_or_equal_than_2_0				,						reason='''See https://github.com/huggingface/transformers/pull/24204'''							)
@slow
class 							A					( unittest.TestCase							):
					'''simple docstring'''






					def 						lowerCamelCase__  (self					:		List[Any]	)		->     List[Any]:




							"""simple docstring"""


							lowercase__      =	"""RWKV/rwkv-4-169m-pile"""
							lowercase__      =	AutoTokenizer.from_pretrained(self.model_id	)

					def 						lowerCamelCase__  (self					:		Optional[Any]	)		->     Union[str, Any]:




							"""simple docstring"""


							lowercase__      =	"""Hello my name is Jasmine and I am a newbie to the"""
							lowercase__      =	RwkvForCausalLM.from_pretrained(self.model_id	).to(_UpperCAmelCase	)

							lowercase__      =	self.tokenizer("""Hello my name is"""   ,      return_tensors="""pt"""	).input_ids.to(_UpperCAmelCase	)
							lowercase__      =	model.generate(_UpperCAmelCase   ,      max_new_tokens=10	)
							lowercase__      =	self.tokenizer.decode(output[0].tolist()	)

							self.assertEqual(_UpperCAmelCase   ,      _UpperCAmelCase	)


					def 						lowerCamelCase__  (self					:		Dict	)		->     Any:




							"""simple docstring"""


							lowercase__      =	"""Hello my name is Jasmine and I am a newbie to the"""

							lowercase__      =	self.tokenizer("""Hello my name is"""   ,      return_tensors="""pt"""	).input_ids.to(_UpperCAmelCase	)
							lowercase__      =	RwkvForCausalLM.from_pretrained(self.model_id   ,      torch_dtype=torch.bfloataa	).to(_UpperCAmelCase	)

							lowercase__      =	model.generate(_UpperCAmelCase   ,      max_new_tokens=10	)
							lowercase__      =	self.tokenizer.decode(output[0].tolist()	)

							self.assertEqual(_UpperCAmelCase   ,      _UpperCAmelCase	)





from __future__ import annotations






def 				UpperCamelCase      (			__magic_name__  :							list[list[int]]					,					__magic_name__  :							list[list[int]]  )     ->						list[int]:
		"""simple docstring"""




		assert len(__magic_name__  ) == len(__magic_name__  )

		lowercase__      =	len(__magic_name__  )
		lowercase__      =	list(range(__magic_name__  )  )
		lowercase__      =	[-1] * n  # who the donor has donated to
		lowercase__      =	[-1] * n  # who the recipient has received from
		lowercase__      =	[0] * n

		while unmatched_donors:
				lowercase__      =	unmatched_donors[0]
				lowercase__      =	donor_pref[donor]
				lowercase__      =	donor_preference[num_donations[donor]]
				num_donations[donor] += 1
				lowercase__      =	recipient_pref[recipient]
				lowercase__      =	rec_record[recipient]

				if prev_donor != -1:
						if rec_preference.index(__magic_name__  ) > rec_preference.index(__magic_name__  ):
								lowercase__      =	donor
								lowercase__      =	recipient
								unmatched_donors.append(__magic_name__  )
								unmatched_donors.remove(__magic_name__  )
				else:
						lowercase__      =	donor
						lowercase__      =	recipient
						unmatched_donors.remove(__magic_name__  )
		return donor_record

