





import csv
import json
import logging
import os
import re
import subprocess
import tempfile
import unittest
import zipfile
from pathlib import Path
from typing import Optional
from unittest import mock

import torch

# We use TF to parse the logs
from accelerate import Accelerator
from accelerate.test_utils.testing import (
    MockingTestCase,
    TempDirTestCase,
    require_comet_ml,
    require_tensorboard,
    require_wandb,
    skip,
)
from accelerate.tracking import CometMLTracker, GeneralTracker
from accelerate.utils import ProjectConfiguration, is_comet_ml_available, is_tensorboard_available


if is_comet_ml_available():
      from comet_ml import OfflineExperiment

if is_tensorboard_available():
      import struct

      import tensorboard.compat.proto.event_pba as event_pba

__UpperCAmelCase			:  Any										=				logging.getLogger(__name__)







@require_tensorboard
class        __snake_case			(				unittest.TestCase     ):





       '''simple docstring'''







       def 				UpperCAmelCase__					(    self					:       str						):
         __snake_case:		Any					    =		"""test_project_with_config"""
         with tempfile.TemporaryDirectory() as dirpath:
           __snake_case:		str					    =		Accelerator(log_with="""tensorboard"""				,							project_dir=UpperCamelCase__						)
           __snake_case:		Optional[int]					    =		{"""num_iterations""": 12, """learning_rate""": 1E-2, """some_boolean""": False, """some_string""": """some_value"""}
           accelerator.init_trackers(UpperCamelCase__				,							UpperCamelCase__						)
           accelerator.end_training()
           for child in Path(f'''{dirpath}/{project_name}'''						).glob("""*/**"""						):
             __snake_case:		Union[str, Any]					    =		list(filter(lambda A						: x.is_file()				,							child.iterdir()						)						)[0]
           self.assertNotEqual(str(UpperCamelCase__						)				,							""""""						)




       def 				UpperCAmelCase__					(    self					:       int						):
         __snake_case:		Tuple					    =		"""test_project_with_log"""
         with tempfile.TemporaryDirectory() as dirpath:
           __snake_case:		Tuple					    =		Accelerator(log_with="""tensorboard"""				,							project_dir=UpperCamelCase__						)
           accelerator.init_trackers(UpperCamelCase__						)
           __snake_case:		List[str]					    =		{"""total_loss""": 0.1, """iteration""": 1, """my_text""": """some_value"""}
           accelerator.log(UpperCamelCase__				,							step=0						)
           accelerator.end_training()
           # Logged values are stored in the outermost-tfevents file and can be read in as a TFRecord
           # Names are randomly generated each time
           __snake_case:		Union[str, Any]					    =		list(filter(lambda A						: x.is_file()				,							Path(f'''{dirpath}/{project_name}'''						).iterdir()						)						)[0]
           self.assertNotEqual(str(UpperCamelCase__						)				,							""""""						)




       def 				UpperCAmelCase__					(    self					:       str						):
         __snake_case:		Optional[Any]					    =		"""test_project_with_log"""
         with tempfile.TemporaryDirectory() as dirpath:
           __snake_case:		Tuple					    =		Accelerator(log_with="""tensorboard"""				,							project_dir=UpperCamelCase__						)
           accelerator.init_trackers(UpperCamelCase__						)
           __snake_case:		Any					    =		{"""tensor""": torch.tensor(1						)}
           accelerator.log(UpperCamelCase__				,							step=0						)
           accelerator.end_training()
           # Logged values are stored in the outermost-tfevents file and can be read in as a TFRecord
           # Names are randomly generated each time
           __snake_case:		Union[str, Any]					    =		list(filter(lambda A						: x.is_file()				,							Path(f'''{dirpath}/{project_name}'''						).iterdir()						)						)[0]
           # Reading implementation based on https://github.com/pytorch/pytorch/issues/45327#issuecomment-703757685
           with open(UpperCamelCase__				,							"""rb"""						) as f:
             __snake_case:		List[str]					    =		f.read()
           __snake_case:		List[Any]					    =		False
           while data:
             __snake_case:		List[str]					    =		struct.unpack("""Q"""				,							data[:8]						)

             __snake_case:		Optional[Any]					    =		data[12 : 12 + int(header[0]						)]  # 8+4
             __snake_case:		Optional[Any]					    =		data[12 + int(header[0]						) + 4 :]
             __snake_case:		Any					    =		event_pba.Event()

             event.ParseFromString(UpperCamelCase__						)
             if event.HasField("""summary"""						):
               for value in event.summary.value:
                 if value.simple_value == 1.0 and value.tag == "tensor":
                   __snake_case:		str					    =		True
           self.assertTrue(UpperCamelCase__				,							"""Converted tensor was not found in the log file!"""						)




       def 				UpperCAmelCase__					(    self					:       Optional[Any]						):
         with self.assertRaisesRegex(UpperCamelCase__				,							"""Logging with `tensorboard` requires a `logging_dir`"""						):
           __snake_case:		Dict					    =		Accelerator(log_with="""tensorboard"""						)
         with tempfile.TemporaryDirectory() as dirpath:
           __snake_case:		Optional[Any]					    =		Accelerator(log_with="""tensorboard"""				,							project_dir=UpperCamelCase__						)






       def 				UpperCAmelCase__					(    self					:       Tuple						):
         __snake_case:		str					    =		ProjectConfiguration(total_limit=30						)
         with tempfile.TemporaryDirectory() as dirpath:
           __snake_case:		int					    =		Accelerator(log_with="""tensorboard"""				,							project_dir=UpperCamelCase__				,							project_config=UpperCamelCase__						)







@require_wandb
@mock.patch.dict(os.environ  ,     {"""WANDB_MODE""": """offline"""}     )
class        __snake_case			(				_lowercase  ,     _lowercase     ):





       '''simple docstring'''







       def 				UpperCAmelCase__					(    self					:       Optional[Any]						):
         super().setUp()
         # wandb let's us override where logs are stored to via the WANDB_DIR env var
         self.add_mocks(mock.patch.dict(os.environ				,							{"""WANDB_DIR""": self.tmpdir}						)						)




       @staticmethod
       def 				UpperCAmelCase__					(    A					:       str				,							A					:       str				,							A					:       bool = True						):
         __snake_case:		List[str]					    =		rf'''{section} ([\S\s]*?)\n\n'''
         if record:
           __snake_case:		Any					    =		rf'''Record: {pattern}'''
         __snake_case:		Tuple					    =		re.findall(UpperCamelCase__				,							UpperCamelCase__						)[0]
         # A config
         if section == "config" or section == "history":
           __snake_case:		Optional[Any]					    =		re.findall(r"""\"([a-zA-Z0-9_.,]+)"""				,							UpperCamelCase__						)
           return {key: val for key, val in zip(cleaned_record[0::2]				,							cleaned_record[1::2]						)}
         # Everything else
         else:
           return dict(re.findall(r"""(\w+): \"([^\s]+)\""""				,							UpperCamelCase__						)						)






       @skip
       def 				UpperCAmelCase__					(    self					:       List[str]						):
         __snake_case:		Any					    =		"""test_project_with_config"""
         __snake_case:		int					    =		Accelerator(log_with="""wandb"""						)
         __snake_case:		str					    =		{"""num_iterations""": 12, """learning_rate""": 1E-2, """some_boolean""": False, """some_string""": """some_value"""}
         __snake_case:		Tuple					    =		{"""wandb""": {"""tags""": ["""my_tag"""]}}
         accelerator.init_trackers(UpperCamelCase__				,							UpperCamelCase__				,							UpperCamelCase__						)
         __snake_case:		str					    =		{"""total_loss""": 0.1, """iteration""": 1, """my_text""": """some_value"""}
         accelerator.log(UpperCamelCase__				,							step=0						)
         accelerator.end_training()
         # The latest offline log is stored at wandb/latest-run/*.wandb
         for child in Path(f'''{self.tmpdir}/wandb/latest-run'''						).glob("""*"""						):
           if child.is_file() and child.suffix == ".wandb":
             __snake_case:		str					    =		subprocess.check_output(
                 ["""wandb""", """sync""", """--view""", """--verbose""", str(UpperCamelCase__						)]				,							env=os.environ.copy()						).decode("""utf8"""				,							"""ignore"""						)
             break

        # Check HPS through careful parsing and cleaning
         __snake_case:		List[str]					    =		self.parse_log(UpperCamelCase__				,							"""config"""						)
         self.assertEqual(logged_items["""num_iterations"""]				,							"""12"""						)
         self.assertEqual(logged_items["""learning_rate"""]				,							"""0.01"""						)
         self.assertEqual(logged_items["""some_boolean"""]				,							"""false"""						)
         self.assertEqual(logged_items["""some_string"""]				,							"""some_value"""						)
         self.assertEqual(logged_items["""some_string"""]				,							"""some_value"""						)

         # Run tags
         __snake_case:		str					    =		self.parse_log(UpperCamelCase__				,							"""run"""				,							UpperCamelCase__						)
         self.assertEqual(logged_items["""tags"""]				,							"""my_tag"""						)

         # Actual logging
         __snake_case:		Dict					    =		self.parse_log(UpperCamelCase__				,							"""history"""						)
         self.assertEqual(logged_items["""total_loss"""]				,							"""0.1"""						)
         self.assertEqual(logged_items["""iteration"""]				,							"""1"""						)
         self.assertEqual(logged_items["""my_text"""]				,							"""some_value"""						)
         self.assertEqual(logged_items["""_step"""]				,							"""0"""						)







def      A__				(       self   ,   SCREAMING_SNAKE_CASE__   ,   SCREAMING_SNAKE_CASE__)  ->       str:
  __snake_case:		int					    =		run_name
  __snake_case:		str					    =		OfflineExperiment(project_name=SCREAMING_SNAKE_CASE__   ,   offline_directory=SCREAMING_SNAKE_CASE__)
  logger.info(F'''Initialized offline CometML project {self.run_name}''')
  logger.info("""Make sure to log any initial configurations with `self.store_init_configuration` before training!""")







@require_comet_ml
@mock.patch.object(_lowercase  ,     """__init__"""  ,     _lowercase     )
class        __snake_case			(				unittest.TestCase     ):





       '''simple docstring'''







       @staticmethod
       def 				UpperCAmelCase__					(    A					:       Tuple				,							A					:       str				,							A					:       bool = False						):
         for log in log_list:
           __snake_case:		Union[str, Any]					    =		json.loads(UpperCamelCase__						)["""payload"""]
           if is_param and "param" in j.keys():
             if j["param"]["paramName"] == key:
               return j["param"]["paramValue"]
           if "log_other" in j.keys():
             if j["log_other"]["key"] == key:
               return j["log_other"]["val"]
           if "metric" in j.keys():
             if j["metric"]["metricName"] == key:
               return j["metric"]["metricValue"]




       def 				UpperCAmelCase__					(    self					:       Union[str, Any]						):
         with tempfile.TemporaryDirectory() as d:
           __snake_case:		Tuple					    =		CometMLTracker("""test_project_with_config"""				,							UpperCamelCase__						)
           __snake_case:		str					    =		Accelerator(log_with=UpperCamelCase__						)
           __snake_case:		Optional[int]					    =		{"""num_iterations""": 12, """learning_rate""": 1E-2, """some_boolean""": False, """some_string""": """some_value"""}
           accelerator.init_trackers(UpperCamelCase__				,							UpperCamelCase__						)
           accelerator.end_training()
           __snake_case:		Optional[int]					    =		os.listdir(UpperCamelCase__						)[0]  # Comet is nice, it's just a zip file here
           # We parse the raw logs
           __snake_case:		Dict					    =		os.path.join(UpperCamelCase__				,							UpperCamelCase__						)
           __snake_case:		Union[str, Any]					    =		zipfile.ZipFile(UpperCamelCase__				,							"""r"""						)
           __snake_case:		Union[str, Any]					    =		archive.open("""messages.json"""						).read().decode("""utf-8"""						)
         __snake_case:		Optional[Any]					    =		log.split("""\n"""						)[:-1]
         self.assertEqual(self.get_value_from_key(UpperCamelCase__				,							"""num_iterations"""				,							UpperCamelCase__						)				,							12						)
         self.assertEqual(self.get_value_from_key(UpperCamelCase__				,							"""learning_rate"""				,							UpperCamelCase__						)				,							0.01						)
         self.assertEqual(self.get_value_from_key(UpperCamelCase__				,							"""some_boolean"""				,							UpperCamelCase__						)				,							UpperCamelCase__						)
         self.assertEqual(self.get_value_from_key(UpperCamelCase__				,							"""some_string"""				,							UpperCamelCase__						)				,							"""some_value"""						)






       def 				UpperCAmelCase__					(    self					:       List[str]						):
         with tempfile.TemporaryDirectory() as d:
           __snake_case:		Tuple					    =		CometMLTracker("""test_project_with_config"""				,							UpperCamelCase__						)
           __snake_case:		List[str]					    =		Accelerator(log_with=UpperCamelCase__						)
           accelerator.init_trackers(UpperCamelCase__						)
           __snake_case:		Dict					    =		{"""total_loss""": 0.1, """iteration""": 1, """my_text""": """some_value"""}
           accelerator.log(UpperCamelCase__				,							step=0						)
           accelerator.end_training()
           __snake_case:		List[str]					    =		os.listdir(UpperCamelCase__						)[0]  # Comet is nice, it's just a zip file here
           # We parse the raw logs
           __snake_case:		List[str]					    =		os.path.join(UpperCamelCase__				,							UpperCamelCase__						)
           __snake_case:		List[str]					    =		zipfile.ZipFile(UpperCamelCase__				,							"""r"""						)
           __snake_case:		Tuple					    =		archive.open("""messages.json"""						).read().decode("""utf-8"""						)
         __snake_case:		Optional[int]					    =		log.split("""\n"""						)[:-1]
         self.assertEqual(self.get_value_from_key(UpperCamelCase__				,							"""curr_step"""				,							UpperCamelCase__						)				,							0						)
         self.assertEqual(self.get_value_from_key(UpperCamelCase__				,							"""total_loss"""						)				,							0.1						)
         self.assertEqual(self.get_value_from_key(UpperCamelCase__				,							"""iteration"""						)				,							1						)
         self.assertEqual(self.get_value_from_key(UpperCamelCase__				,							"""my_text"""						)				,							"""some_value"""						)







class        __snake_case			(				_lowercase     ):





       '''simple docstring'''







       lowerCAmelCase__ 						=	[
           """total_loss""",
           """iteration""",
           """my_text""",
           """learning_rate""",
           """num_iterations""",
           """some_boolean""",
           """some_string""",
       ]

       lowerCAmelCase__ 						=	"""my_custom_tracker"""
       lowerCAmelCase__ 						=	False




       def __init__(    self					:       Any				,							A					:       str						):
         __snake_case:		str					    =		open(f'''{dir}/log.csv'''				,							"""w+"""						)
         __snake_case:		Optional[int]					    =		csv.DictWriter(self.f				,							fieldnames=self._col_names						)
         self.writer.writeheader()




       @property
       def 				UpperCAmelCase__					(    self					:       Any						):
         return self.writer




       def 				UpperCAmelCase__					(    self					:       List[str]				,							A					:       dict						):
         logger.info("""Call init"""						)
         self.writer.writerow(UpperCamelCase__						)




       def 				UpperCAmelCase__					(    self					:       Any				,							A					:       dict				,							A					:       Optional[int]						):
         logger.info("""Call log"""						)
         self.writer.writerow(UpperCamelCase__						)






       def 				UpperCAmelCase__					(    self					:       int						):
         self.f.close()







class        __snake_case			(				unittest.TestCase     ):





       '''simple docstring'''







       def 				UpperCAmelCase__					(    self					:       List[Any]						):
         with tempfile.TemporaryDirectory() as d:
           __snake_case:		List[str]					    =		MyCustomTracker(UpperCamelCase__						)
           __snake_case:		Dict					    =		Accelerator(log_with=UpperCamelCase__						)
           __snake_case:		Optional[int]					    =		{"""num_iterations""": 12, """learning_rate""": 1E-2, """some_boolean""": False, """some_string""": """some_value"""}
           accelerator.init_trackers("""Some name"""				,							UpperCamelCase__						)
           accelerator.end_training()
           with open(f'''{d}/log.csv'''				,							"""r"""						) as f:
             __snake_case:		str					    =		csv.DictReader(UpperCamelCase__						)
             __snake_case:		Dict					    =		next(UpperCamelCase__						)
             __snake_case:		Any					    =		{
                 """total_loss""": """""",
                 """iteration""": """""",
                 """my_text""": """""",
                 """learning_rate""": """0.01""",
                 """num_iterations""": """12""",
                 """some_boolean""": """False""",
                 """some_string""": """some_value""",
             }
             self.assertDictEqual(UpperCamelCase__				,							UpperCamelCase__						)






       def 				UpperCAmelCase__					(    self					:       Tuple						):
         with tempfile.TemporaryDirectory() as d:
           __snake_case:		Tuple					    =		MyCustomTracker(UpperCamelCase__						)
           __snake_case:		Union[str, Any]					    =		Accelerator(log_with=UpperCamelCase__						)
           accelerator.init_trackers("""Some name"""						)
           __snake_case:		str					    =		{"""total_loss""": 0.1, """iteration""": 1, """my_text""": """some_value"""}
           accelerator.log(UpperCamelCase__				,							step=0						)
           accelerator.end_training()
           with open(f'''{d}/log.csv'''				,							"""r"""						) as f:
             __snake_case:		Tuple					    =		csv.DictReader(UpperCamelCase__						)
             __snake_case:		Union[str, Any]					    =		next(UpperCamelCase__						)
             __snake_case:		Union[str, Any]					    =		{
                 """total_loss""": """0.1""",
                 """iteration""": """1""",
                 """my_text""": """some_value""",
                 """learning_rate""": """""",
                 """num_iterations""": """""",
                 """some_boolean""": """""",
                 """some_string""": """""",
             }
             self.assertDictEqual(UpperCamelCase__				,							UpperCamelCase__						)














'''simple docstring'''







import unittest
from pathlib import Path

from transformers import is_vision_available, load_tool
from transformers.testing_utils import get_tests_dir

from .test_tools_common import ToolTesterMixin


if is_vision_available():
			from PIL import Image

class _lowercase      (							unittest.TestCase							, _lowercase						):




							def 						lowerCamelCase_							(				self:							Tuple	):
														lowerCamelCase__   :      Optional[Any]			    =			load_tool("""image-captioning"""	)
														self.tool.setup()
														lowerCamelCase__   :      Optional[Any]			    =			load_tool("""image-captioning"""     ,				remote=UpperCamelCase__	)




							def 						lowerCamelCase_							(				self:							int	):
														lowerCamelCase__   :      List[Any]			    =			Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""	)	) / """000000039769.png"""	)
														lowerCamelCase__   :      Optional[Any]			    =			self.tool(UpperCamelCase__	)
														self.assertEqual(UpperCamelCase__     ,				"""two cats sleeping on a couch"""	)




							def 						lowerCamelCase_							(				self:							Union[str, Any]	):
														lowerCamelCase__   :      Tuple			    =			Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""	)	) / """000000039769.png"""	)
														lowerCamelCase__   :      Dict			    =			self.remote_tool(UpperCamelCase__	)
														self.assertEqual(UpperCamelCase__     ,				"""two cats sleeping on a couch"""	)




							def 						lowerCamelCase_							(				self:							str	):
														lowerCamelCase__   :      Optional[int]			    =			Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""	)	) / """000000039769.png"""	)
														lowerCamelCase__   :      str			    =			self.tool(image=UpperCamelCase__	)
														self.assertEqual(UpperCamelCase__     ,				"""two cats sleeping on a couch"""	)




							def 						lowerCamelCase_							(				self:							Union[str, Any]	):
														lowerCamelCase__   :      Optional[int]			    =			Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""	)	) / """000000039769.png"""	)
														lowerCamelCase__   :      Optional[int]			    =			self.remote_tool(image=UpperCamelCase__	)
														self.assertEqual(UpperCamelCase__     ,				"""two cats sleeping on a couch"""	)

