
from typing import Mapping

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


lowercase__						:Optional[int]					    =       logging.get_logger(__name__)







class 							lowercase						(   SCREAMING_SNAKE_CASE__						):
							lowercase_			:			List[Any]			   ='''mt5'''
							lowercase_			:			Optional[int]			   =['''past_key_values''']




							def __init__(							self  ,A__=2_5_0_1_1_2  ,A__=5_1_2  ,A__=6_4  ,A__=1_0_2_4  ,A__=8  ,A__=None  ,A__=6  ,A__=3_2  ,A__=1_2_8  ,A__=0.1  ,A__=1E-6  ,A__=1.0  ,A__="gated-gelu"  ,A__=True  ,A__=True  ,A__="T5Tokenizer"  ,A__=False  ,A__=0  ,A__=1  ,A__=0  ,**A__  ,):
												super().__init__(
												    is_encoder_decoder=A__  ,tokenizer_class=A__  ,tie_word_embeddings=A__  ,pad_token_id=A__  ,eos_token_id=A__  ,decoder_start_token_id=A__  ,**A__  ,)
												lowercase		      =		vocab_size
												lowercase		      =		d_model
												lowercase		      =		d_kv
												lowercase		      =		d_ff
												lowercase		      =		num_layers
												lowercase		      =		(
												    num_decoder_layers if num_decoder_layers is not None else self.num_layers
												)  # default = symmetry
												lowercase		      =		num_heads
												lowercase		      =		relative_attention_num_buckets
												lowercase		      =		relative_attention_max_distance
												lowercase		      =		dropout_rate
												lowercase		      =		layer_norm_epsilon
												lowercase		      =		initializer_factor
												lowercase		      =		feed_forward_proj
												lowercase		      =		use_cache

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

												if len(A__) > 1 and act_info[0] != "gated" or len(A__) > 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":
																	lowercase		      =		'''gelu_new'''




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




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





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







class 							lowercase						(   SCREAMING_SNAKE_CASE__						):




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

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

												return common_inputs




							@property
							# Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.default_onnx_opset
							def 					A__ (							self):
												return 1_3





							@property
							def 					A__ (							self):
												return 5E-4






# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
from typing import List



def 			UpperCamelCase       (				lowerCAmelCase__					,     lowerCAmelCase__						):
					'''simple docstring'''
					if name != "training_function" and name != "main":
										raise ValueError(f'Incorrect function name passed: {name}, choose either \'main\' or \'training_function\''						)
					lowercase      ,		lowercase		      =		[], False
					for line in lines:
										if not found_start and f'def {name}' in line:
															lowercase		      =		True
															good_lines.append(lowerCAmelCase__						)
															continue
										if found_start:
															if name == "training_function" and "def main" in line:
																				return good_lines
															if name == "main" and "if __name__" in line:
																				return good_lines
															good_lines.append(lowerCAmelCase__						)



def 			UpperCamelCase       (				lowerCAmelCase__						):
					'''simple docstring'''
					return [line for line in lines if not line.lstrip().startswith('''#'''						) and line != "\n"]



def 			UpperCamelCase       (				lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__ = None						):
					'''simple docstring'''
					with open(lowerCAmelCase__					,     '''r'''						) as f:
										lowercase		      =		f.readlines()
					with open(os.path.abspath(os.path.join('''examples'''					,     '''nlp_example.py'''						)						)					,     '''r'''						) as f:
										lowercase		      =		f.readlines()
					with open(lowerCAmelCase__					,     '''r'''						) as f:
										lowercase		      =		f.readlines()
					if secondary_filename is not None:
										with open(lowerCAmelCase__					,     '''r'''						) as f:
															lowercase		      =		f.readlines()

    # This is our base, we remove all the code from here in our `full_filename` and `feature_filename` to find the new content
					if parser_only:
										lowercase		      =		clean_lines(get_function_contents_by_name(lowerCAmelCase__					,     '''main'''						)						)
										lowercase		      =		clean_lines(get_function_contents_by_name(lowerCAmelCase__					,     '''main'''						)						)
										lowercase		      =		clean_lines(get_function_contents_by_name(lowerCAmelCase__					,     '''main'''						)						)
										if secondary_filename is not None:
															lowercase		      =		clean_lines(get_function_contents_by_name(lowerCAmelCase__					,     '''main'''						)						)
					else:
										lowercase		      =		clean_lines(get_function_contents_by_name(lowerCAmelCase__					,     '''training_function'''						)						)
										lowercase		      =		clean_lines(get_function_contents_by_name(lowerCAmelCase__					,     '''training_function'''						)						)
										lowercase		      =		clean_lines(get_function_contents_by_name(lowerCAmelCase__					,     '''training_function'''						)						)
										if secondary_filename is not None:
															lowercase		      =		clean_lines(
															    get_function_contents_by_name(lowerCAmelCase__					,     '''training_function'''						)						)

					lowercase		      =		'''train_dataloader, eval_dataloader = get_dataloaders(accelerator, batch_size)\n'''

					# Specific code in our script that differs from the full version, aka what is new
					lowercase		      =		[]
					lowercase		      =		[]  # We keep track of the idxs just in case it's a repeated statement
					lowercase		      =		iter(lowerCAmelCase__						)
					for i in range(len(lowerCAmelCase__						) - 1						):
										if i not in passed_idxs:
															lowercase		      =		next(lowerCAmelCase__						)
															if (line not in full_file_func) and (line.lstrip() != _dl_line):
																				if "TESTING_MOCKED_DATALOADERS" not in line:
																									new_feature_code.append(lowerCAmelCase__						)
																									passed_idxs.append(lowerCAmelCase__						)
																				else:
																									# Skip over the `config['num_epochs'] = 2` statement
																									lowercase		      =		next(lowerCAmelCase__						)

    # Extract out just the new parts from the full_file_training_func
					lowercase		      =		[]
					lowercase		      =		[]  # We keep track of the idxs just in case it's a repeated statement
					for i, line in enumerate(lowerCAmelCase__						):
										if i not in passed_idxs:
															if (line not in full_file_func) and (line.lstrip() != _dl_line):
																				if "TESTING_MOCKED_DATALOADERS" not in line:
																									new_full_example_parts.append(lowerCAmelCase__						)
																									passed_idxs.append(lowerCAmelCase__						)

    # Finally, get the overall diff
					lowercase		      =		[line for line in new_feature_code if line not in new_full_example_parts]
					if secondary_filename is not None:
										lowercase		      =		[line for line in full_file_contents if line not in secondary_file_func]
										lowercase		      =		[line for line in diff_from_example if line not in diff_from_two]

					return diff_from_example




