



class 				__snake_case						:




							def __init__(       self     :       str				,				A_     :       Dict				,				A_     :       Optional[int]):
									lowerCAmelCase_			:     str									= name
									lowerCAmelCase_			:     List[Any]									= val




							def __str__(       self     :       List[str]):
									return F"""{self.__class__.__name__}({self.name}, {self.val})"""







							def __lt__(       self     :       List[str]				,				A_     :       Tuple):
									return self.val < other.val





class 				__snake_case						:




							def __init__(       self     :       int				,				A_     :       Dict):
									lowerCAmelCase_			:     List[str]									= {}
									lowerCAmelCase_			:     Any									= {}
									lowerCAmelCase_			:     Dict									= self.build_heap(A_)




							def __getitem__(       self     :       List[str]				,				A_     :       List[Any]):
									return self.get_value(A_)




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




							def    UpperCAmelCase__			(       self     :       int				,				A_     :       List[str]):
									return idx * 2 + 1




							def    UpperCAmelCase__			(       self     :       str				,				A_     :       List[Any]):
									return idx * 2 + 2




							def    UpperCAmelCase__			(       self     :       Optional[Any]				,				A_     :       Tuple):
									return self.heap_dict[key]




							def    UpperCAmelCase__			(       self     :       Union[str, Any]				,				A_     :       Tuple):
									lowerCAmelCase_			:     Dict									= len(A_) - 1
									lowerCAmelCase_			:     List[Any]									= self.get_parent_idx(A_)

									for idx, i in enumerate(A_):
											lowerCAmelCase_			:     List[str]									= idx
											lowerCAmelCase_			:     Any									= i.val

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




							def    UpperCAmelCase__			(       self     :       List[str]				,				A_     :       int				,				A_     :       Tuple):
									while True:
											lowerCAmelCase_			:     Union[str, Any]									= self.get_left_child_idx(A_)  # noqa: E741
											lowerCAmelCase_			:     int									= self.get_right_child_idx(A_)

											lowerCAmelCase_			:     int									= idx
											if l < len(A_) and array[l] < array[idx]:
													lowerCAmelCase_			:     Any									= l
											if r < len(A_) and array[r] < array[smallest]:
													lowerCAmelCase_			:     List[str]									= r

											if smallest != idx:
													lowerCAmelCase_					,  lowerCAmelCase_			:     List[Any]									= array[smallest], array[idx]
													(
													    (
													    lowerCAmelCase_
													)					,  (
													    lowerCAmelCase_
													)					,  
													)			:     List[Any]									= (
													    self.idx_of_element[array[smallest]],
													    self.idx_of_element[array[idx]],
													)
													lowerCAmelCase_			:     Union[str, Any]									= smallest
											else:
													break




							def    UpperCAmelCase__			(       self     :       Tuple				,				A_     :       List[str]):
									lowerCAmelCase_			:     Any									= self.get_parent_idx(A_)
									while p >= 0 and self.heap[p] > self.heap[idx]:
											lowerCAmelCase_					,  lowerCAmelCase_			:     Optional[Any]									= self.heap[idx], self.heap[p]
											lowerCAmelCase_					,  lowerCAmelCase_			:     Optional[Any]									= (
											    self.idx_of_element[self.heap[idx]],
											    self.idx_of_element[self.heap[p]],
											)
											lowerCAmelCase_			:     int									= p
											lowerCAmelCase_			:     Tuple									= self.get_parent_idx(A_)




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




							def    UpperCAmelCase__			(       self     :       Tuple):
									lowerCAmelCase_					,  lowerCAmelCase_			:     Optional[int]									= self.heap[-1], self.heap[0]
									lowerCAmelCase_					,  lowerCAmelCase_			:     Any									= (
									    self.idx_of_element[self.heap[-1]],
									    self.idx_of_element[self.heap[0]],
									)

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




							def    UpperCAmelCase__			(       self     :       Any				,				A_     :       Any):
									self.heap.append(A_)
									lowerCAmelCase_			:     Optional[int]									= len(self.heap) - 1
									lowerCAmelCase_			:     Optional[int]									= node.val
									self.sift_up(len(self.heap) - 1)




							def    UpperCAmelCase__			(       self     :       List[Any]):
									return len(self.heap) == 0







							def    UpperCAmelCase__			(       self     :       Optional[int]				,				A_     :       Optional[Any]				,				A_     :       int):
									assert (
									    self.heap[self.idx_of_element[node]].val > new_value
									), "newValue must be less that current value"
									lowerCAmelCase_			:     Tuple									= new_value
									lowerCAmelCase_			:     Tuple									= new_value
									self.sift_up(self.idx_of_element[node])





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

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

# Generating Min-Heap from array
A__  :  Optional[Any]								=					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()










import json
import os
import subprocess
import unittest
from ast import literal_eval

import pytest
from parameterized import parameterized_class

from . import is_sagemaker_available


if is_sagemaker_available():
						from sagemaker import Session, TrainingJobAnalytics
						from sagemaker.huggingface import HuggingFace



@pytest.mark.skipif(
    literal_eval(os.getenv('''TEST_SAGEMAKER'''						,'''False'''						)						) is not True						,reason='''Skipping test because should only be run when releasing minor transformers version'''						,)
@pytest.mark.usefixtures('''sm_env'''						)
@parameterized_class(
    [
        {
            '''framework''': '''pytorch''',
            '''script''': '''run_glue.py''',
            '''model_name_or_path''': '''distilbert-base-cased''',
            '''instance_type''': '''ml.g4dn.xlarge''',
            '''results''': {'''train_runtime''': 650, '''eval_accuracy''': 0.6, '''eval_loss''': 0.9},
        },
        {
            '''framework''': '''tensorflow''',
            '''script''': '''run_tf.py''',
            '''model_name_or_path''': '''distilbert-base-cased''',
            '''instance_type''': '''ml.g4dn.xlarge''',
            '''results''': {'''train_runtime''': 600, '''eval_accuracy''': 0.3, '''eval_loss''': 0.9},
        },
    ]						)
class 				__snake_case						(     unittest.TestCase						):




							def    UpperCAmelCase__			(       self     :       int):
									if self.framework == "pytorch":
											subprocess.run(
											    F"""cp ./examples/pytorch/text-classification/run_glue.py {self.env.test_path}/run_glue.py""".split()				,				encoding='''utf-8'''				,				check=A_				,				)
									assert hasattr(self				,				'''env''')




							def    UpperCAmelCase__			(       self     :       Union[str, Any]				,				A_     :       str=1):
									# creates estimator
									return HuggingFace(
									    entry_point=self.script				,				source_dir=self.env.test_path				,				role=self.env.role				,				image_uri=self.env.image_uri				,				base_job_name=F"""{self.env.base_job_name}-single"""				,				instance_count=A_				,				instance_type=self.instance_type				,				debugger_hook_config=A_				,				hyperparameters={**self.env.hyperparameters, '''model_name_or_path''': self.model_name_or_path}				,				metric_definitions=self.env.metric_definitions				,				py_version='''py36'''				,				)




							def    UpperCAmelCase__			(       self     :       List[str]				,				A_     :       Optional[Any]):
									TrainingJobAnalytics(A_).export_csv(F"""{self.env.test_path}/{job_name}_metrics.csv""")







							def    UpperCAmelCase__			(       self     :       int):
									# create estimator
									lowerCAmelCase_			:     List[Any]									= self.create_estimator()

									# run training
									estimator.fit()

									# result dataframe
									lowerCAmelCase_			:     Union[str, Any]									= TrainingJobAnalytics(estimator.latest_training_job.name).dataframe()

									# extract kpis
									lowerCAmelCase_			:     Optional[Any]									= list(result_metrics_df[result_metrics_df.metric_name == '''eval_accuracy''']['''value'''])
									lowerCAmelCase_			:     Optional[int]									= list(result_metrics_df[result_metrics_df.metric_name == '''eval_loss''']['''value'''])
									# get train time from SageMaker job, this includes starting, preprocessing, stopping
									lowerCAmelCase_			:     Dict									= (
									    Session().describe_training_job(estimator.latest_training_job.name).get('''TrainingTimeInSeconds'''				,				9_9_9_9_9_9)
									)

									# assert kpis
									assert train_runtime <= self.results["train_runtime"]
									assert all(t >= self.results['''eval_accuracy'''] for t in eval_accuracy)
									assert all(t <= self.results['''eval_loss'''] for t in eval_loss)

									# dump tests result into json file to share in PR
									with open(F"""{estimator.latest_training_job.name}.json"""				,				'''w''') as outfile:
											json.dump({'''train_time''': train_runtime, '''eval_accuracy''': eval_accuracy, '''eval_loss''': eval_loss}				,				A_)





