





"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory

from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
    convert,
    ensure_valid_input,
    generate_identified_filename,
    infer_shapes,
    quantize,
)
from transformers.testing_utils import require_tf, require_tokenizers, require_torch, slow






class 					_UpperCAmelCase   :


					def 	lowerCamelCase       (					self			:List[str]     ,       __UpperCamelCase			:Union[str, Any]     ,       __UpperCamelCase			:Any     ,       __UpperCamelCase			:Union[str, Any]		):
												return None







class 					_UpperCAmelCase   :


					def 	lowerCamelCase       (					self			:Optional[int]     ,       __UpperCamelCase			:Any     ,       __UpperCamelCase			:Union[str, Any]     ,       __UpperCamelCase			:Optional[int]     ,       __UpperCamelCase			:List[Any]		):
												return None







class 					_UpperCAmelCase   (	unittest.TestCase ):
					UpperCamelCase      =							[
					    # (model_name, model_kwargs)
					    ('''bert-base-cased''', {}),
					    ('''gpt2''', {'''use_cache''': False}),  # We don't support exporting GPT2 past keys anymore
					]


					@require_tf
					@slow
					def 	lowerCamelCase       (					self			:Tuple		):
												for model, model_kwargs in OnnxExportTestCase.MODEL_TO_TEST:
																			self._test_export(__UpperCamelCase     ,       "tf"     ,       12     ,       **__UpperCamelCase		)


					@require_torch
					@slow
					def 	lowerCamelCase       (					self			:List[str]		):
												for model, model_kwargs in OnnxExportTestCase.MODEL_TO_TEST:
																			self._test_export(__UpperCamelCase     ,       "pt"     ,       12     ,       **__UpperCamelCase		)


					@require_torch
					@slow
					def 	lowerCamelCase       (					self			:str		):
												from transformers import BertModel

												A		=  ["[UNK]", "[SEP]", "[CLS]", "[PAD]", "[MASK]", "some", "other", "words"]
												with NamedTemporaryFile(mode="w+t"		) as vocab_file:
																			vocab_file.write("\n".join(__UpperCamelCase		)		)
																			vocab_file.flush()
																			A		=  BertTokenizerFast(vocab_file.name		)

												with TemporaryDirectory() as bert_save_dir:
																			A		=  BertModel(BertConfig(vocab_size=len(__UpperCamelCase		)		)		)
																			model.save_pretrained(__UpperCamelCase		)
																			self._test_export(__UpperCamelCase     ,       "pt"     ,       12     ,       __UpperCamelCase		)


					@require_tf
					@slow
					def 	lowerCamelCase       (					self			:Dict		):
												for model, model_kwargs in OnnxExportTestCase.MODEL_TO_TEST:
																			A		=  self._test_export(__UpperCamelCase     ,       "tf"     ,       12     ,       **__UpperCamelCase		)
																			A		=  quantize(Path(__UpperCamelCase		)		)

																			# Ensure the actual quantized model is not bigger than the original one
																			if quantized_path.stat().st_size >= Path(__UpperCamelCase		).stat().st_size:
																										self.fail("Quantized model is bigger than initial ONNX model"		)


					@require_torch
					@slow
					def 	lowerCamelCase       (					self			:List[Any]		):
												for model, model_kwargs in OnnxExportTestCase.MODEL_TO_TEST:
																			A		=  self._test_export(__UpperCamelCase     ,       "pt"     ,       12     ,       **__UpperCamelCase		)
																			A		=  quantize(__UpperCamelCase		)

																			# Ensure the actual quantized model is not bigger than the original one
																			if quantized_path.stat().st_size >= Path(__UpperCamelCase		).stat().st_size:
																										self.fail("Quantized model is bigger than initial ONNX model"		)


					def 	lowerCamelCase       (					self			:Union[str, Any]     ,       __UpperCamelCase			:str     ,       __UpperCamelCase			:List[Any]     ,       __UpperCamelCase			:Tuple     ,       __UpperCamelCase			:str=None     ,       **__UpperCamelCase			:int		):
												try:
																			# Compute path
																			with TemporaryDirectory() as tempdir:
																										A		=  Path(__UpperCamelCase		).joinpath("model.onnx"		)

																			# Remove folder if exists
																			if path.parent.exists():
																										path.parent.rmdir()

																			# Export
																			convert(__UpperCamelCase     ,       __UpperCamelCase     ,       __UpperCamelCase     ,       __UpperCamelCase     ,       __UpperCamelCase     ,       **__UpperCamelCase		)

																			return path
												except Exception as e:
																			self.fail(__UpperCamelCase		)


					@require_torch
					@require_tokenizers
					@slow
					def 	lowerCamelCase       (					self			:List[Any]		):
												from transformers import BertModel

												A		=  BertModel(BertConfig.from_pretrained("lysandre/tiny-bert-random"		)		)
												A		=  BertTokenizerFast.from_pretrained("lysandre/tiny-bert-random"		)
												self._test_infer_dynamic_axis(__UpperCamelCase     ,       __UpperCamelCase     ,       "pt"		)


					@require_tf
					@require_tokenizers
					@slow
					def 	lowerCamelCase       (					self			:List[Any]		):
												from transformers import TFBertModel

												A		=  TFBertModel(BertConfig.from_pretrained("lysandre/tiny-bert-random"		)		)
												A		=  BertTokenizerFast.from_pretrained("lysandre/tiny-bert-random"		)
												self._test_infer_dynamic_axis(__UpperCamelCase     ,       __UpperCamelCase     ,       "tf"		)


					def 	lowerCamelCase       (					self			:Optional[Any]     ,       __UpperCamelCase			:Tuple     ,       __UpperCamelCase			:Optional[Any]     ,       __UpperCamelCase			:Optional[Any]		):
												A		=  FeatureExtractionPipeline(__UpperCamelCase     ,       __UpperCamelCase		)

												A		=  ["input_ids", "token_type_ids", "attention_mask", "output_0", "output_1"]
												A,	A,	A,	A		=  infer_shapes(__UpperCamelCase     ,       __UpperCamelCase		)

												# Assert all variables are present
												self.assertEqual(len(__UpperCamelCase		)     ,       len(__UpperCamelCase		)		)
												self.assertTrue(all(var_name in shapes for var_name in variable_names		)		)
												self.assertSequenceEqual(variable_names[:3]     ,       __UpperCamelCase		)
												self.assertSequenceEqual(variable_names[3:]     ,       __UpperCamelCase		)

												# Assert inputs are {0: batch, 1: sequence}
												for var_name in ["input_ids", "token_type_ids", "attention_mask"]:
																			self.assertDictEqual(shapes[var_name]     ,       {0: "batch", 1: "sequence"}		)

												# Assert outputs are {0: batch, 1: sequence} and {0: batch}
												self.assertDictEqual(shapes["output_0"]     ,       {0: "batch", 1: "sequence"}		)
												self.assertDictEqual(shapes["output_1"]     ,       {0: "batch"}		)


					def 	lowerCamelCase       (					self			:List[str]		):
												A		=  ["input_ids", "attention_mask", "token_type_ids"]
												A		=  {"input_ids": [1, 2, 3, 4], "attention_mask": [0, 0, 0, 0], "token_type_ids": [1, 1, 1, 1]}
												A,	A		=  ensure_valid_input(FuncContiguousArgs()     ,       __UpperCamelCase     ,       __UpperCamelCase		)

												# Should have exactly the same number of args (all are valid)
												self.assertEqual(len(__UpperCamelCase		)     ,       3		)

												# Should have exactly the same input names
												self.assertEqual(set(__UpperCamelCase		)     ,       set(__UpperCamelCase		)		)

												# Parameter should be reordered according to their respective place in the function:
												# (input_ids, token_type_ids, attention_mask)
												self.assertEqual(__UpperCamelCase     ,       (tokens["input_ids"], tokens["token_type_ids"], tokens["attention_mask"])		)

												# Generated args are interleaved with another args (for instance parameter "past" in GPT2)
												A,	A		=  ensure_valid_input(FuncNonContiguousArgs()     ,       __UpperCamelCase     ,       __UpperCamelCase		)

												# Should have exactly the one arg (all before the one not provided "some_other_args")
												self.assertEqual(len(__UpperCamelCase		)     ,       1		)
												self.assertEqual(len(__UpperCamelCase		)     ,       1		)

												# Should have only "input_ids"
												self.assertEqual(inputs_args[0]     ,       tokens["input_ids"]		)
												self.assertEqual(ordered_input_names[0]     ,       "input_ids"		)


					def 	lowerCamelCase       (					self			:Any		):
												A		=  generate_identified_filename(Path("/home/something/my_fake_model.onnx"		)     ,       "-test"		)
												self.assertEqual("/home/something/my_fake_model-test.onnx"     ,       generated.as_posix()		)









"""simple docstring"""
class 					_UpperCAmelCase   :


					def __init__(					self			:List[str]     ,       __UpperCamelCase			:Union[str, Any]     ,       __UpperCamelCase			:Tuple		):
												A		=  name
												A		=  val


					def __str__(					self			:str		):
												return f"{self.__class__.__name__}({self.name}, {self.val})"


					def __lt__(					self			:List[Any]     ,       __UpperCamelCase			:Union[str, Any]		):
												return self.val < other.val







class 					_UpperCAmelCase   :


					def __init__(					self			:List[str]     ,       __UpperCamelCase			:Optional[Any]		):
												A		=  {}
												A		=  {}
												A		=  self.build_heap(__UpperCamelCase		)


					def __getitem__(					self			:int     ,       __UpperCamelCase			:Optional[int]		):
												return self.get_value(__UpperCamelCase		)


					def 	lowerCamelCase       (					self			:List[Any]     ,       __UpperCamelCase			:str		):
												return (idx - 1) // 2


					def 	lowerCamelCase       (					self			:int     ,       __UpperCamelCase			:Optional[Any]		):
												return idx * 2 + 1


					def 	lowerCamelCase       (					self			:Union[str, Any]     ,       __UpperCamelCase			:Optional[int]		):
												return idx * 2 + 2


					def 	lowerCamelCase       (					self			:Optional[Any]     ,       __UpperCamelCase			:str		):
												return self.heap_dict[key]


					def 	lowerCamelCase       (					self			:int     ,       __UpperCamelCase			:Optional[Any]		):
												A		=  len(__UpperCamelCase		) - 1
												A		=  self.get_parent_idx(__UpperCamelCase		)

												for idx, i in enumerate(__UpperCamelCase		):
																			A		=  idx
																			A		=  i.val

												for i in range(__UpperCamelCase     ,       -1     ,       -1		):
																			self.sift_down(__UpperCamelCase     ,       __UpperCamelCase		)
												return array


					def 	lowerCamelCase       (					self			:str     ,       __UpperCamelCase			:Optional[Any]     ,       __UpperCamelCase			:Dict		):
												while True:
																			A		=  self.get_left_child_idx(__UpperCamelCase		)  # noqa: E741
																			A		=  self.get_right_child_idx(__UpperCamelCase		)

																			A		=  idx
																			if l < len(__UpperCamelCase		) and array[l] < array[idx]:
																										A		=  l
																			if r < len(__UpperCamelCase		) and array[r] < array[smallest]:
																										A		=  r

																			if smallest != idx:
																										A,	A		=  array[smallest], array[idx]
																										(
																										    (
																										    A
																										),	(
																										    A
																										),	
																										)		=  (
																										    self.idx_of_element[array[smallest]],
																										    self.idx_of_element[array[idx]],
																										)
																										A		=  smallest
																			else:
																										break


					def 	lowerCamelCase       (					self			:Optional[Any]     ,       __UpperCamelCase			:Optional[int]		):
												A		=  self.get_parent_idx(__UpperCamelCase		)
												while p >= 0 and self.heap[p] > self.heap[idx]:
																			A,	A		=  self.heap[idx], self.heap[p]
																			A,	A		=  (
																			    self.idx_of_element[self.heap[idx]],
																			    self.idx_of_element[self.heap[p]],
																			)
																			A		=  p
																			A		=  self.get_parent_idx(__UpperCamelCase		)


					def 	lowerCamelCase       (					self			:Any		):
												return self.heap[0]


					def 	lowerCamelCase       (					self			:Tuple		):
												A,	A		=  self.heap[-1], self.heap[0]
												A,	A		=  (
												    self.idx_of_element[self.heap[-1]],
												    self.idx_of_element[self.heap[0]],
												)

												A		=  self.heap.pop()
												del self.idx_of_element[x]
												self.sift_down(0     ,       self.heap		)
												return x


					def 	lowerCamelCase       (					self			:Optional[int]     ,       __UpperCamelCase			:Optional[int]		):
												self.heap.append(__UpperCamelCase		)
												A		=  len(self.heap		) - 1
												A		=  node.val
												self.sift_up(len(self.heap		) - 1		)


					def 	lowerCamelCase       (					self			:Tuple		):
												return len(self.heap		) == 0


					def 	lowerCamelCase       (					self			:Any     ,       __UpperCamelCase			:str     ,       __UpperCamelCase			:Dict		):
												assert (
												    self.heap[self.idx_of_element[node]].val > new_value
												), "newValue must be less that current value"
												A		=  new_value
												A		=  new_value
												self.sift_up(self.idx_of_element[node]		)







_snake_case     :		Optional[int]       						= Node('R', -1)
_snake_case     :		Tuple       						= Node('B', 6)
_snake_case     :		Tuple       						= Node('A', 3)
_snake_case     :		Optional[int]       						= Node('X', 1)
_snake_case     :		List[Any]       						= Node('E', 4)

# Use one of these two ways to generate Min-Heap

# Generating Min-Heap from array
_snake_case     :		Tuple       						= MinHeap([r, b, a, x, e])

# Generating Min-Heap by Insert method
# myMinHeap.insert(a)
# myMinHeap.insert(b)
# myMinHeap.insert(x)
# myMinHeap.insert(r)
# myMinHeap.insert(e)

# Before
print('Min Heap - before decrease key')
for i in my_min_heap.heap:
		print(i)

print('Min Heap - After decrease key of node [B -> -17]')
my_min_heap.decrease_key(b, -17)

# After
for i in my_min_heap.heap:
		print(i)

if __name__ == "__main__":
		import doctest

		doctest.testmod()


