
"""simple docstring"""


from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging


A_						       =				logging.get_logger(__name__)




class    __lowerCamelCase     (   lowerCAmelCase ):
				a__:			Any									=						'mt5'
				a__:			List[str]									=						['past_key_values']




				def __init__(							self       ,	UpperCAmelCase=25_0112       ,	UpperCAmelCase=512       ,	UpperCAmelCase=64       ,	UpperCAmelCase=1024       ,	UpperCAmelCase=8       ,	UpperCAmelCase=None       ,	UpperCAmelCase=6       ,	UpperCAmelCase=32       ,	UpperCAmelCase=128       ,	UpperCAmelCase=0.1       ,	UpperCAmelCase=1e-6       ,	UpperCAmelCase=1.0       ,	UpperCAmelCase="gated-gelu"       ,	UpperCAmelCase=True       ,	UpperCAmelCase=True       ,	UpperCAmelCase="T5Tokenizer"       ,	UpperCAmelCase=False       ,	UpperCAmelCase=0       ,	UpperCAmelCase=1       ,	UpperCAmelCase=0       ,	**UpperCAmelCase       ,	):
							super().__init__(
							    is_encoder_decoder=UpperCAmelCase       ,	tokenizer_class=UpperCAmelCase       ,	tie_word_embeddings=UpperCAmelCase       ,	pad_token_id=UpperCAmelCase       ,	eos_token_id=UpperCAmelCase       ,	decoder_start_token_id=UpperCAmelCase       ,	**UpperCAmelCase       ,	)
							lowerCamelCase_ 		=     vocab_size
							lowerCamelCase_ 		=     d_model
							lowerCamelCase_ 		=     d_kv
							lowerCamelCase_ 		=     d_ff
							lowerCamelCase_ 		=     num_layers
							lowerCamelCase_ 		=     (
							    num_decoder_layers if num_decoder_layers is not None else self.num_layers
							)  # default = symmetry
							lowerCamelCase_ 		=     num_heads
							lowerCamelCase_ 		=     relative_attention_num_buckets
							lowerCamelCase_ 		=     relative_attention_max_distance
							lowerCamelCase_ 		=     dropout_rate
							lowerCamelCase_ 		=     layer_norm_epsilon
							lowerCamelCase_ 		=     initializer_factor
							lowerCamelCase_ 		=     feed_forward_proj
							lowerCamelCase_ 		=     use_cache

							lowerCamelCase_ 		=     self.feed_forward_proj.split('''-'''      )
							lowerCamelCase_ 		=     act_info[-1]
							lowerCamelCase_ 		=     act_info[0] == '''gated'''

							if len(UpperCAmelCase      ) > 1 and act_info[0] != "gated" or len(UpperCAmelCase      ) > 2:
										raise ValueError(
										    f"`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer."
										    '''Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. '''
										    '''\'gated-gelu\' or \'relu\''''      )

							# for backwards compatibility
							if feed_forward_proj == "gated-gelu":
										lowerCamelCase_ 		=     '''gelu_new'''




				@property
				def 					UpperCAmelCase__	(							self      ):
							return self.d_model




				@property
				def 					UpperCAmelCase__	(							self      ):
							return self.num_heads





				@property
				def 					UpperCAmelCase__	(							self      ):
							return self.num_layers




class    __lowerCamelCase     (   lowerCAmelCase ):




				@property
				# Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.inputs
				def 					UpperCAmelCase__	(							self      ):
							lowerCamelCase_ 		=     {
							    '''input_ids''': {0: '''batch''', 1: '''encoder_sequence'''},
							    '''attention_mask''': {0: '''batch''', 1: '''encoder_sequence'''},
							}
							if self.use_past:
										lowerCamelCase_ 		=     '''past_encoder_sequence + sequence'''
										lowerCamelCase_ 		=     {0: '''batch'''}
										lowerCamelCase_ 		=     {0: '''batch''', 1: '''past_decoder_sequence + sequence'''}
							else:
										lowerCamelCase_ 		=     {0: '''batch''', 1: '''decoder_sequence'''}
										lowerCamelCase_ 		=     {0: '''batch''', 1: '''decoder_sequence'''}

							if self.use_past:
										self.fill_with_past_key_values_(UpperCAmelCase       ,	direction='''inputs'''      )

							return common_inputs




				@property
				# Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.default_onnx_opset
				def 					UpperCAmelCase__	(							self      ):
							return 13





				@property
				def 					UpperCAmelCase__	(							self      ):
							return 5e-4





"""simple docstring"""


import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from unittest.mock import Mock, patch

import diffusers.utils.hub_utils




class    __lowerCamelCase     (   unittest.TestCase ):




				@patch('''diffusers.utils.hub_utils.get_full_repo_name'''      )
				def 					UpperCAmelCase__	(							self       ,	UpperCAmelCase      ):
							lowerCamelCase_ 		=     '''full_repo_name'''
							with TemporaryDirectory() as tmpdir:
										# Dummy args values
										lowerCamelCase_ 		=     Mock()
										lowerCamelCase_ 		=     tmpdir
										lowerCamelCase_ 		=     0
										lowerCamelCase_ 		=     '''hub_token'''
										lowerCamelCase_ 		=     '''dataset_name'''
										lowerCamelCase_ 		=     0.0_1
										lowerCamelCase_ 		=     10_0000
										lowerCamelCase_ 		=     1_0000
										lowerCamelCase_ 		=     0.0_1
										lowerCamelCase_ 		=     0.0_2
										lowerCamelCase_ 		=     0.0_3
										lowerCamelCase_ 		=     0.0_0_0_5
										lowerCamelCase_ 		=     0.0_0_0_0_0_1
										lowerCamelCase_ 		=     1
										lowerCamelCase_ 		=     10
										lowerCamelCase_ 		=     0.0_0_1
										lowerCamelCase_ 		=     0.1
										lowerCamelCase_ 		=     0.2
										lowerCamelCase_ 		=     True

										# Model card mush be rendered and saved
										diffusers.utils.hub_utils.create_model_card(UpperCAmelCase       ,	model_name='''model_name'''      )
										self.assertTrue((Path(UpperCAmelCase      ) / '''README.md''').is_file()      )



