


"""simple docstring"""







import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def  a__      (    SCREAMING_SNAKE_CASE   :   Any    ,				SCREAMING_SNAKE_CASE   :   str=7    ):


  '''simple docstring'''







  lowerCAmelCase					:					int								=							None
  if token is not None:
    lowerCAmelCase					:					str								=							{"Accept": "application/vnd.github+json", "Authorization": f"""Bearer {token}"""}

  # The id of a workflow (not of a workflow run)
  lowerCAmelCase					:					List[str]								=							"636036"

  lowerCAmelCase					:					List[Any]								=							f"""https://api.github.com/repos/huggingface/transformers/actions/workflows/{workflow_id}/runs"""
  # On `main` branch + event being `schedule` + not returning PRs + only `num_runs` results
  url += f"""?branch=main&event=schedule&exclude_pull_requests=true&per_page={num_runs}"""

  lowerCAmelCase					:					Optional[int]								=							requests.get(SCREAMING_SNAKE_CASE    ,				headers=SCREAMING_SNAKE_CASE    ).json()

  return result["workflow_runs"]
def  a__      (    SCREAMING_SNAKE_CASE   :   Dict    ):


  '''simple docstring'''







  lowerCAmelCase					:					Any								=							get_daily_ci_runs(SCREAMING_SNAKE_CASE    )
  lowerCAmelCase					:					List[str]								=							None
  for workflow_run in workflow_runs:
    if workflow_run["status"] == "completed":
      lowerCAmelCase					:					List[Any]								=							workflow_run["id"]
      break

  return workflow_run_id
def  a__      (    SCREAMING_SNAKE_CASE   :   Tuple    ,				SCREAMING_SNAKE_CASE   :   Tuple    ,				SCREAMING_SNAKE_CASE   :   str    ):


  '''simple docstring'''







  lowerCAmelCase					:					Optional[Any]								=							get_last_daily_ci_runs(SCREAMING_SNAKE_CASE    )
  if workflow_run_id is not None:
    lowerCAmelCase					:					List[str]								=							get_artifacts_links(worflow_run_id=SCREAMING_SNAKE_CASE    ,				token=SCREAMING_SNAKE_CASE    )
    for artifact_name in artifact_names:
      if artifact_name in artifacts_links:
        lowerCAmelCase					:					Optional[int]								=							artifacts_links[artifact_name]
        download_artifact(
            artifact_name=SCREAMING_SNAKE_CASE    ,				artifact_url=SCREAMING_SNAKE_CASE    ,				output_dir=SCREAMING_SNAKE_CASE    ,				token=SCREAMING_SNAKE_CASE    )





def  a__      (    SCREAMING_SNAKE_CASE   :   Union[str, Any]    ,				SCREAMING_SNAKE_CASE   :   Dict    ,				SCREAMING_SNAKE_CASE   :   Optional[int]    ):


  '''simple docstring'''







  get_last_daily_ci_artifacts(SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    )

  lowerCAmelCase					:					List[Any]								=							{}
  for artifact_name in artifact_names:
    lowerCAmelCase					:					Optional[Any]								=							os.path.join(SCREAMING_SNAKE_CASE    ,				f"""{artifact_name}.zip"""    )
    if os.path.isfile(SCREAMING_SNAKE_CASE    ):
      lowerCAmelCase					:					List[str]								=							{}
      with zipfile.ZipFile(SCREAMING_SNAKE_CASE    ) as z:
        for filename in z.namelist():
          if not os.path.isdir(SCREAMING_SNAKE_CASE    ):
            # read the file
            with z.open(SCREAMING_SNAKE_CASE    ) as f:
              lowerCAmelCase					:					Any								=							f.read().decode("UTF-8"    )

  return results









"""simple docstring"""







# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional

import numpy as np
import pyarrow as pa

from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter


if TYPE_CHECKING:
     import jax
     import jaxlib

lowerCAmelCase__				    =       get_logger()

lowerCAmelCase__				    =       None


class 				SCREAMING_SNAKE_CASE__    (		TensorFormatter[Mapping, "jax.Array", Mapping]    ):
       """simple docstring"""


       def __init__(						self		,					snake_case__=None		,					snake_case__=None		,					**snake_case__						):






         """simple docstring"""





         super().__init__(features=snake_case__						)
         import jax
         from jaxlib.xla_client import Device

         if isinstance(snake_case__		,					snake_case__						):
           raise ValueError(
               f"""Expected {device} to be a `str` not {type(snake_case__						)}, as `jaxlib.xla_extension.Device` """
               "is not serializable neither with `pickle` nor with `dill`. Instead you can surround "
               "the device with `str()` to get its string identifier that will be internally mapped "
               "to the actual `jaxlib.xla_extension.Device`."						)
         lowerCAmelCase					:					List[str]								=							device if isinstance(snake_case__		,					snake_case__						) else str(jax.devices()[0]						)
         # using global variable since `jaxlib.xla_extension.Device` is not serializable neither
         # with `pickle` nor with `dill`, so we need to use a global variable instead
         global DEVICE_MAPPING
         if DEVICE_MAPPING is None:
           lowerCAmelCase					:					Optional[Any]								=							self._map_devices_to_str()
         if self.device not in list(DEVICE_MAPPING.keys()						):
           logger.warning(
               f"""Device with string identifier {self.device} not listed among the available """
               f"""devices: {list(DEVICE_MAPPING.keys()						)}, so falling back to the default """
               f"""device: {str(jax.devices()[0]						)}."""						)
           lowerCAmelCase					:					Dict								=							str(jax.devices()[0]						)
         lowerCAmelCase					:					Union[str, Any]								=							jnp_array_kwargs

       @staticmethod
       def 	lowercase__							(						):






         """simple docstring"""





         import jax

         return {str(snake_case__						): device for device in jax.devices()}

       def 	lowercase__							(						self		,					snake_case__						):






         """simple docstring"""





         import jax
         import jax.numpy as jnp

         if isinstance(snake_case__		,					snake_case__						) and column:
           if all(
               isinstance(snake_case__		,					jax.Array						) and x.shape == column[0].shape and x.dtype == column[0].dtype for x in column						):
             return jnp.stack(snake_case__		,					axis=0						)
         return column

       def 	lowercase__							(						self		,					snake_case__						):






         """simple docstring"""





         import jax
         import jax.numpy as jnp

         if isinstance(snake_case__		,					(str, bytes, type(snake_case__						))						):
           return value
         elif isinstance(snake_case__		,					(np.character, np.ndarray)						) and np.issubdtype(value.dtype		,					np.character						):
           return value.tolist()

         lowerCAmelCase					:					Tuple								=							{}

         if isinstance(snake_case__		,					(np.number, np.ndarray)						) and np.issubdtype(value.dtype		,					np.integer						):
           # the default int precision depends on the jax config
           # see https://jax.readthedocs.io/en/latest/notebooks/Common_Gotchas_in_JAX.html#double-64bit-precision
           if jax.config.jax_enable_xaa:
             lowerCAmelCase					:					List[Any]								=							{"dtype": jnp.intaa}
           else:
             lowerCAmelCase					:					Optional[Any]								=							{"dtype": jnp.intaa}
         elif isinstance(snake_case__		,					(np.number, np.ndarray)						) and np.issubdtype(value.dtype		,					np.floating						):
           lowerCAmelCase					:					int								=							{"dtype": jnp.floataa}
         elif config.PIL_AVAILABLE and "PIL" in sys.modules:
           import PIL.Image

           if isinstance(snake_case__		,					PIL.Image.Image						):
             lowerCAmelCase					:					Dict								=							np.asarray(snake_case__						)

        # using global variable since `jaxlib.xla_extension.Device` is not serializable neither
        # with `pickle` nor with `dill`, so we need to use a global variable instead
         global DEVICE_MAPPING
         if DEVICE_MAPPING is None:
           lowerCAmelCase					:					str								=							self._map_devices_to_str()

         with jax.default_device(DEVICE_MAPPING[self.device]						):
           # calling jnp.array on a np.ndarray does copy the data
           # see https://github.com/google/jax/issues/4486
           return jnp.array(snake_case__		,					**{**default_dtype, **self.jnp_array_kwargs}						)

       def 	lowercase__							(						self		,					snake_case__						):






         """simple docstring"""





         import jax

         # support for torch, tf, jax etc.
         if config.TORCH_AVAILABLE and "torch" in sys.modules:
           import torch

           if isinstance(snake_case__		,					torch.Tensor						):
             return self._tensorize(data_struct.detach().cpu().numpy()[()]						)
         if hasattr(snake_case__		,					"__array__"						) and not isinstance(snake_case__		,					jax.Array						):
           lowerCAmelCase					:					Dict								=							data_struct.__array__()
         # support for nested types like struct of list of struct
         if isinstance(snake_case__		,					np.ndarray						):
           if data_struct.dtype == object:  # jax arrays cannot be instantied from an array of objects
             return self._consolidate([self.recursive_tensorize(snake_case__						) for substruct in data_struct]						)
         elif isinstance(snake_case__		,					(list, tuple)						):
           return self._consolidate([self.recursive_tensorize(snake_case__						) for substruct in data_struct]						)
         return self._tensorize(snake_case__						)

       def 	lowercase__							(						self		,					snake_case__						):






         """simple docstring"""





         return map_nested(self._recursive_tensorize		,					snake_case__		,					map_list=snake_case__						)

       def 	lowercase__							(						self		,					snake_case__						):






         """simple docstring"""





         lowerCAmelCase					:					List[Any]								=							self.numpy_arrow_extractor().extract_row(snake_case__						)
         lowerCAmelCase					:					Tuple								=							self.python_features_decoder.decode_row(snake_case__						)
         return self.recursive_tensorize(snake_case__						)

       def 	lowercase__							(						self		,					snake_case__						):






         """simple docstring"""





         lowerCAmelCase					:					Optional[int]								=							self.numpy_arrow_extractor().extract_column(snake_case__						)
         lowerCAmelCase					:					Dict								=							self.python_features_decoder.decode_column(snake_case__		,					pa_table.column_names[0]						)
         lowerCAmelCase					:					Optional[Any]								=							self.recursive_tensorize(snake_case__						)
         lowerCAmelCase					:					Dict								=							self._consolidate(snake_case__						)
         return column







       def 	lowercase__							(						self		,					snake_case__						):






         """simple docstring"""





         lowerCAmelCase					:					Optional[Any]								=							self.numpy_arrow_extractor().extract_batch(snake_case__						)
         lowerCAmelCase					:					str								=							self.python_features_decoder.decode_batch(snake_case__						)
         lowerCAmelCase					:					Tuple								=							self.recursive_tensorize(snake_case__						)
         for column_name in batch:
           lowerCAmelCase					:					Optional[int]								=							self._consolidate(batch[column_name]						)
         return batch





