


'''simple docstring'''







import json
import os
from datetime import date
from pathlib import Path

from tabulate import DataRow, TableFormat, tabulate


a__  :					List[Any]        =       TableFormat(
    lineabove=None,
    linebelowheader=None,
    linebetweenrows=None,
    linebelow=None,
    headerrow=DataRow('', '|', '|'),
    datarow=DataRow('', '|', '|'),
    padding=1,
    with_header_hide=None,
)


a__  :					Optional[int]        =       []
a__  :					List[str]        =       []

a__  :					Optional[Any]        =       {"""type""": """section""", """text""": {"""type""": """plain_text""", """text""": """No failed tests! 🤗""", """emoji""": True}}

a__  :					List[str]        =       [
    {
        """type""": """header""",
        """text""": {
            """type""": """plain_text""",
            """text""": F"""🤗 Accelerate nightly {os.environ.get('TEST_TYPE', '')} test results""",
            """emoji""": True,
        },
    }
]

a__  :					str        =       0
for log in Path().glob('*.log'):
  a__  :					Dict        =       0
  with open(log, 'r') as f:
    for line in f:
      a__  :					Optional[int]        =       json.loads(line)
      if line.get('nodeid', '') != "":
        a__  :					Dict        =       line["""nodeid"""]
        if line.get('duration', None) is not None:
          a__  :					Optional[int]        =       F"""{line['duration']:.4f}"""
          if line.get('outcome', '') == "failed":
            section_num_failed += 1
            failed.append([test, duration, log.name.split('_')[0]])
            total_num_failed += 1
  group_info.append([str(log), section_num_failed, failed])
  a__  :					Union[str, Any]        =       []
  log.unlink()

a__  :					List[Any]        =       """"""
a__  :					Any        =       []
if total_num_failed > 0:
  for name, num_failed, failed_tests in group_info:
    if num_failed > 0:
      if num_failed == 1:
        message += F"*{name[1:]}: {num_failed} failed test*\n"
      else:
        message += F"*{name[1:]}: {num_failed} failed tests*\n"
      a__  :					Union[str, Any]        =       []
      a__  :					Dict        =       {}
      for test in failed_tests:
        a__  :					Dict        =       test[0].split('::')
        a__  :					Optional[Any]        =       data[0].split('/')[-1]
        if data[0] not in filesafailed:
          a__  :					List[Any]        =       [data[1:]]
        else:
          filesafailed[data[0]] += [data[1:]]
        failed_table.append(data)

      a__  :					Optional[Any]        =       [test[0] for test in failed_table]
      a__  :					Any        =       list(set(files))
      # Count number of instances in failed_tests
      a__  :					Optional[int]        =       []
      for file in individual_files:
        table.append([file, len(filesafailed[file])])

      a__  :					Optional[Any]        =       tabulate(
          table,
          headers=['Test Location', 'Num Failed'],
          tablefmt=hf_table_format,
          stralign='right',
      )
      message += F"\n```\n{failed_table}\n```"
      all_filesafailed.append(filesafailed)
  if len(message) > 3_0_0_0:
    a__  :					int        =       """Too many failed tests, please see the full report in the Action results."""
    a__  :					Dict        =       len(err) + 1_0
    a__  :					List[str]        =       message[: 3_0_0_0 - offset] + F"""\n...\n```\n{err}"""
  print(F"""### {message}""")
else:
  a__  :					str        =       """No failed tests! 🤗"""
  print(F"""## {message}""")
  payload.append(no_error_payload)

if os.environ.get('TEST_TYPE', '') != "":
  from slack_sdk import WebClient

  a__  :					List[Any]        =       WebClient(token=os.environ['SLACK_API_TOKEN'])
  if message != "No failed tests! 🤗":
    a__  :					List[str]        =       {
        """type""": """section""",
        """text""": {
            """type""": """mrkdwn""",
            """text""": message,
        },
    }
    payload.append(md_report)
    a__  :					Tuple        =       {
        """type""": """section""",
        """text""": {
            """type""": """mrkdwn""",
            """text""": """*For more details:*""",
        },
        """accessory""": {
            """type""": """button""",
            """text""": {
                """type""": """plain_text""",
                """text""": """Check Action results""",
                """emoji""": True,
            },
            """url""": F"""https://github.com/{os.environ['GITHUB_REPOSITORY']}/actions/runs/{os.environ['GITHUB_RUN_ID']}""",
        },
    }
    payload.append(action_button)
    a__  :					int        =       {
        """type""": """context""",
        """elements""": [
            {
                """type""": """plain_text""",
                """text""": F"""Nightly {os.environ.get('TEST_TYPE')} test results for {date.today()}""",
            }
        ],
    }
    payload.append(date_report)
  a__  :					Union[str, Any]        =       client.chat_postMessage(channel='#accelerate-ci-daily', text=message, blocks=payload)
  a__  :					Dict        =       response.data["""ts"""]
  for failed_file in all_filesafailed:
    for test_location, test_failures in failed_file.items():
      # Keep only the first instance of the test name
      a__  :					Optional[Any]        =       """"""
      for i, row in enumerate(test_failures):
        if row[0] != test_class:
          a__  :					Dict        =       row[0]
        else:
          a__  :					int        =       """"""

      a__  :					Dict        =       {
          """type""": """section""",
          """text""": {
              """type""": """mrkdwn""",
              """text""": F"""Test location: {test_location}\n```\n{tabulate(test_failures, headers=['Class', 'Test'], tablefmt=hf_table_format, stralign='right')}\n```""",
          },
      }

      client.chat_postMessage(
          channel='#accelerate-ci-daily',
          thread_ts=ts,
          blocks=[payload],
      )






"""simple docstring"""






import numpy as np
import torch
from imwatermark import WatermarkEncoder


# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
__lowerCAmelCase    :       Union[str, Any]					     =0B1011_0011_1110_1100_1001_0000_0111_1011_1011_0001_1001_1110
# bin(x)[2:] gives bits of x as str, use int to convert them to 0/1
__lowerCAmelCase    :       Optional[int]					     =[int(bit) for bit in bin(WATERMARK_MESSAGE)[2:]]





class  _A						:

      def __init__(						self						):







            """simple docstring"""



            lowercase														=	WATERMARK_BITS
            lowercase														=	WatermarkEncoder()

            self.encoder.set_watermark("""bits"""		,       self.watermark						)







      def 				A__       (						self		,       __lowerCAmelCase						):







            """simple docstring"""



            if images.shape[-1] < 256:
                  return images

            lowercase														=	(255 * (images / 2 + 0.5)).cpu().permute(0		,       2		,       3		,       1						).float().numpy()

            lowercase														=	[self.encoder.encode(__lowerCAmelCase		,       """dwtDct"""						) for image in images]

            lowercase														=	torch.from_numpy(np.array(__lowerCAmelCase						)						).permute(0		,       3		,       1		,       2						)

            lowercase														=	torch.clamp(2 * (images / 255 - 0.5)		,       min=-1.0		,       max=1.0						)
            return images



