



import inspect
import unittest

class 				snake_case__(unittest.TestCase      ):

					"""simple docstring"""






					def 			snake_case					(							self :     str					):
									try:
													import diffusers  # noqa: F401
									except ImportError:
													assert False







					def 			snake_case					(							self :     Dict					):
									import diffusers
									from diffusers.dependency_versions_table import deps

									lowercase__					:   Any													=					inspect.getmembers(SCREAMING_SNAKE_CASE				,       inspect.isclass					)

									for cls_name, cls_module in all_classes:
													if "dummy_" in cls_module.__module__:
																	for backend in cls_module._backends:
																					if backend == "k_diffusion":
																									lowercase__					:   Dict													=					"k-diffusion"
																					elif backend == "invisible_watermark":
																									lowercase__					:   List[Any]													=					"invisible-watermark"
																					assert backend in deps, f"""{backend} is not in the deps table!"""









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 				snake_case__(unittest.TestCase      ):

					"""simple docstring"""






					@slow
					def 			snake_case					(							self :     Optional[int]					):
									lowercase__					:   Dict													=					FlaxMTaForConditionalGeneration.from_pretrained("google/mt5-small"					)
									lowercase__					:   Dict													=					AutoTokenizer.from_pretrained("google/mt5-small"					)

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

									lowercase__					:   int													=					shift_tokens_right(SCREAMING_SNAKE_CASE				,       model.config.pad_token_id				,       model.config.decoder_start_token_id					)

									lowercase__					:   Tuple													=					model(SCREAMING_SNAKE_CASE				,       decoder_input_ids=SCREAMING_SNAKE_CASE					).logits
									lowercase__					:   Dict													=					optax.softmax_cross_entropy(SCREAMING_SNAKE_CASE				,       onehot(SCREAMING_SNAKE_CASE				,       logits.shape[-1]					)					).mean()

									lowercase__					:   Union[str, Any]													=					-(labels.shape[-1] * loss.item())

									lowercase__					:   Union[str, Any]													=					-84.9_127
									self.assertTrue(abs(mtf_score - EXPECTED_SCORE					) < 1E-4					)




