





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

from tabulate import DataRow, TableFormat, tabulate


UpperCamelCase__           =			TableFormat(
    lineabove=None,
    linebelowheader=None,
    linebetweenrows=None,
    linebelow=None,
    headerrow=DataRow("", "|", "|"),
    datarow=DataRow("", "|", "|"),
    padding=1,
    with_header_hide=None,
)


UpperCamelCase__           =			[]
UpperCamelCase__           =			[]

UpperCamelCase__           =			{"type": "section", "text": {"type": "plain_text", "text": "No failed tests! 🤗", "emoji": True}}

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

UpperCamelCase__           =			0
for log in Path().glob("*.log"):
					UpperCamelCase__           =			0
					with open(log, "r") as f:
										for line in f:
															UpperCamelCase__           =			json.loads(line)
															if line.get("nodeid", "") != "":
																				UpperCamelCase__           =			line["nodeid"]
																				if line.get("duration", None) is not None:
																									UpperCamelCase__           =			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])
					UpperCamelCase__           =			[]
					log.unlink()

UpperCamelCase__           =			""
UpperCamelCase__           =			[]
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"
															UpperCamelCase__           =			[]
															UpperCamelCase__           =			{}
															for test in failed_tests:
																				UpperCamelCase__           =			test[0].split("::")
																				UpperCamelCase__           =			data[0].split("/")[-1]
																				if data[0] not in filesafailed:
																									UpperCamelCase__           =			[data[1:]]
																				else:
																									filesafailed[data[0]] += [data[1:]]
																				failed_table.append(data)

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

															UpperCamelCase__           =			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_000:
										UpperCamelCase__           =			"Too many failed tests, please see the full report in the Action results."
										UpperCamelCase__           =			len(err) + 10
										UpperCamelCase__           =			message[: 3_000 - offset] + f"""\n...\n```\n{err}"""
					print(f"""### {message}""")
else:
					UpperCamelCase__           =			"No failed tests! 🤗"
					print(f"""## {message}""")
					payload.append(no_error_payload)

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

					UpperCamelCase__           =			WebClient(token=os.environ["SLACK_API_TOKEN"])
					if message != "No failed tests! 🤗":
										UpperCamelCase__           =			{
										    "type": "section",
										    "text": {
										        "type": "mrkdwn",
										        "text": message,
										    },
										}
										payload.append(md_report)
										UpperCamelCase__           =			{
										    "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)
										UpperCamelCase__           =			{
										    "type": "context",
										    "elements": [
										        {
										            "type": "plain_text",
										            "text": f"""Nightly {os.environ.get('TEST_TYPE')} test results for {date.today()}""",
										        }
										    ],
										}
										payload.append(date_report)
					UpperCamelCase__           =			client.chat_postMessage(channel="#accelerate-ci-daily", text=message, blocks=payload)
					UpperCamelCase__           =			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
															UpperCamelCase__           =			""
															for i, row in enumerate(test_failures):
																				if row[0] != test_class:
																									UpperCamelCase__           =			row[0]
																				else:
																									UpperCamelCase__           =			""

															UpperCamelCase__           =			{
															    "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],
															)











from typing import Tuple, Union

from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig


if is_timm_available():
					import timm


if is_torch_available():
					from torch import Tensor

class 							__SCREAMING_SNAKE_CASE       (  _a ,		_a							):
							snake_case  :   int      =							"""pixel_values"""
							snake_case  :   List[Any]      =							False
							snake_case  :   str      =							TimmBackboneConfig






							def __init__(    self	,			__lowerCAmelCase	,			**__lowerCAmelCase	):
														requires_backends(self	,			"""timm"""	)
														super().__init__(__lowerCAmelCase	)
														UpperCamelCase__					  =      config

														if config.backbone is None:
																					raise ValueError("""backbone is not set in the config. Please set it to a timm model name."""	)

														if config.backbone not in timm.list_models():
																					raise ValueError(f"""backbone {config.backbone} is not supported by timm."""	)

														if hasattr(__lowerCAmelCase	,			"""out_features"""	) and config.out_features is not None:
																					raise ValueError("""out_features is not supported by TimmBackbone. Please use out_indices instead."""	)

														UpperCamelCase__					  =      getattr(__lowerCAmelCase	,			"""use_pretrained_backbone"""	,			__lowerCAmelCase	)
														if pretrained is None:
																					raise ValueError("""use_pretrained_backbone is not set in the config. Please set it to True or False."""	)

														# We just take the final layer by default. This matches the default for the transformers models.
														UpperCamelCase__					  =      config.out_indices if getattr(__lowerCAmelCase	,			"""out_indices"""	,			__lowerCAmelCase	) is not None else (-1,)

														UpperCamelCase__					  =      timm.create_model(
														    config.backbone	,			pretrained=__lowerCAmelCase	,			features_only=config.features_only	,			in_chans=config.num_channels	,			out_indices=__lowerCAmelCase	,			**__lowerCAmelCase	,			)
														# These are used to control the output of the model when called. If output_hidden_states is True, then
														# return_layers is modified to include all layers.
														UpperCamelCase__					  =      self._backbone.return_layers
														UpperCamelCase__					  =      {layer["""module"""]: str(__lowerCAmelCase	) for i, layer in enumerate(self._backbone.feature_info.info	)}
														super()._init_backbone(__lowerCAmelCase	)






							@classmethod
							def 					_lowerCamelCase		(    cls	,			__lowerCAmelCase	,			*__lowerCAmelCase	,			**__lowerCAmelCase	):
														requires_backends(cls	,			["""vision""", """timm"""]	)
														from ...models.timm_backbone import TimmBackboneConfig

														UpperCamelCase__					  =      kwargs.pop("""config"""	,			TimmBackboneConfig()	)

														UpperCamelCase__					  =      kwargs.pop("""use_timm_backbone"""	,			__lowerCAmelCase	)
														if not use_timm:
																					raise ValueError("""use_timm_backbone must be True for timm backbones"""	)

														UpperCamelCase__					  =      kwargs.pop("""num_channels"""	,			config.num_channels	)
														UpperCamelCase__					  =      kwargs.pop("""features_only"""	,			config.features_only	)
														UpperCamelCase__					  =      kwargs.pop("""use_pretrained_backbone"""	,			config.use_pretrained_backbone	)
														UpperCamelCase__					  =      kwargs.pop("""out_indices"""	,			config.out_indices	)
														UpperCamelCase__					  =      TimmBackboneConfig(
														    backbone=__lowerCAmelCase	,			num_channels=__lowerCAmelCase	,			features_only=__lowerCAmelCase	,			use_pretrained_backbone=__lowerCAmelCase	,			out_indices=__lowerCAmelCase	,			)
														return super()._from_config(__lowerCAmelCase	,			**__lowerCAmelCase	)






							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	):
														pass







							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	,			__lowerCAmelCase=None	,			__lowerCAmelCase=None	,			__lowerCAmelCase=None	,			**__lowerCAmelCase	):
														UpperCamelCase__					  =      return_dict if return_dict is not None else self.config.use_return_dict
														UpperCamelCase__					  =      (
														    output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
														)
														UpperCamelCase__					  =      output_attentions if output_attentions is not None else self.config.output_attentions

														if output_attentions:
																					raise ValueError("""Cannot output attentions for timm backbones at the moment"""	)

														if output_hidden_states:
																					# We modify the return layers to include all the stages of the backbone
																					UpperCamelCase__					  =      self._all_layers
																					UpperCamelCase__					  =      self._backbone(__lowerCAmelCase	,			**__lowerCAmelCase	)
																					UpperCamelCase__					  =      self._return_layers
																					UpperCamelCase__					  =      tuple(hidden_states[i] for i in self.out_indices	)
														else:
																					UpperCamelCase__					  =      self._backbone(__lowerCAmelCase	,			**__lowerCAmelCase	)
																					UpperCamelCase__					  =      None

														UpperCamelCase__					  =      tuple(__lowerCAmelCase	)
														UpperCamelCase__					  =      tuple(__lowerCAmelCase	) if hidden_states is not None else None

														if not return_dict:
																					UpperCamelCase__					  =      (feature_maps,)
																					if output_hidden_states:
																												UpperCamelCase__					  =      output + (hidden_states,)
																					return output

														return BackboneOutput(feature_maps=__lowerCAmelCase	,			hidden_states=__lowerCAmelCase	,			attentions=__lowerCAmelCase	)




