


import unittest

from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow


if is_flax_available():
			import optax
			from flax.training.common_utils import onehot

			from transformers import AutoTokenizer, FlaxMTaForConditionalGeneration
			from transformers.models.ta.modeling_flax_ta import shift_tokens_right

@require_torch
@require_sentencepiece
@require_tokenizers
@require_flax
class 							a						(unittest.TestCase ):




							"""simple docstring"""


							@slow
							def        __snake_case   (				self			:    Optional[Any]							)      ->       List[Any]:
														__snake_case						:     List[str]									=  FlaxMTaForConditionalGeneration.from_pretrained("google/mt5-small"							)
														__snake_case						:     Tuple									=  AutoTokenizer.from_pretrained("google/mt5-small"							)

														__snake_case						:     Optional[Any]									=  tokenizer("Hello there"       ,      return_tensors="np"							).input_ids
														__snake_case						:     List[Any]									=  tokenizer("Hi I am"       ,      return_tensors="np"							).input_ids

														__snake_case						:     Union[str, Any]									=  shift_tokens_right(lowerCamelCase       ,      model.config.pad_token_id       ,      model.config.decoder_start_token_id							)

														__snake_case						:     List[str]									=  model(lowerCamelCase       ,      decoder_input_ids=lowerCamelCase							).logits
														__snake_case						:     List[str]									=  optax.softmax_cross_entropy(lowerCamelCase       ,      onehot(lowerCamelCase       ,      logits.shape[-1]							)							).mean()

														__snake_case						:     Optional[int]									=  -(labels.shape[-1] * loss.item())

														__snake_case						:     List[Any]									=  -84.91_27
														self.assertTrue(abs(mtf_score - EXPECTED_SCORE							) < 1E-4							)





from __future__ import annotations
class 						lowerCamelCase_							:



					'''simple docstring'''







					def __init__(					self			,							snake_case_    ) ->      None:







								'''simple docstring'''

								__lowercase			       = order

								# a_{0} ... a_{k}
								__lowercase			       = [1.0] + [0.0] * order
								# b_{0} ... b_{k}
								__lowercase			       = [1.0] + [0.0] * order

								# x[n-1] ... x[n-k]
								__lowercase			       = [0.0] * self.order
								# y[n-1] ... y[n-k]
								__lowercase			       = [0.0] * self.order






					def A   (					self			,							snake_case_			,							snake_case_    ) ->      None:







								'''simple docstring'''

								if len(snake_case_    ) < self.order:
											__lowercase			       = [1.0, *a_coeffs]

								if len(snake_case_    ) != self.order + 1:
											__lowercase			       = (
											    F'Expected a_coeffs to have {self.order + 1} elements '
											    F'for {self.order}-order filter, got {len(snake_case_    )}'
											)
											raise ValueError(snake_case_    )

								if len(snake_case_    ) != self.order + 1:
											__lowercase			       = (
											    F'Expected b_coeffs to have {self.order + 1} elements '
											    F'for {self.order}-order filter, got {len(snake_case_    )}'
											)
											raise ValueError(snake_case_    )

								__lowercase			       = a_coeffs
								__lowercase			       = b_coeffs






					def A   (					self			,							snake_case_    ) ->      float:







								'''simple docstring'''

								__lowercase			       = 0.0

								# Start at index 1 and do index 0 at the end.
								for i in range(1			,							self.order + 1    ):
											result += (
											    self.b_coeffs[i] * self.input_history[i - 1]
											    - self.a_coeffs[i] * self.output_history[i - 1]
											)

								__lowercase			       = (result + self.b_coeffs[0] * sample) / self.a_coeffs[0]

								__lowercase			       = self.input_history[:-1]
								__lowercase			       = self.output_history[:-1]

								__lowercase			       = sample
								__lowercase			       = result

								return result


