

'''simple docstring'''






from dataclasses import dataclass, field
from typing import Optional




@dataclass
class     __snake_case		:
					_lowerCAmelCase			     =	field(
					    default='''codeparrot/codeparrot'''    ,   metadata={'''help''': '''Model name or path of model to be trained.'''})
					_lowerCAmelCase			     =	field(
					    default='''./'''    ,   metadata={'''help''': '''Save dir where model repo is cloned and models updates are saved to.'''})
					_lowerCAmelCase			     =	field(
					    default='''codeparrot/codeparrot-clean-train'''    ,   metadata={'''help''': '''Name or path of training dataset.'''})
					_lowerCAmelCase			     =	field(
					    default='''codeparrot/codeparrot-clean-valid'''    ,   metadata={'''help''': '''Name or path of validation dataset.'''})
					_lowerCAmelCase			     =	field(default=2    ,   metadata={'''help''': '''Batch size for training.'''})
					_lowerCAmelCase			     =	field(default=2    ,   metadata={'''help''': '''Batch size for evaluation.'''})
					_lowerCAmelCase			     =	field(default=0.1    ,   metadata={'''help''': '''Value of weight decay.'''})
					_lowerCAmelCase			     =	field(
					    default=10_000    ,   metadata={'''help''': '''Size of buffer used to shuffle streaming dataset.'''})
					_lowerCAmelCase			     =	field(default=2E-4    ,   metadata={'''help''': '''Learning rate fo training.'''})
					_lowerCAmelCase			     =	field(default='''cosine'''    ,   metadata={'''help''': '''Learning rate.'''})
					_lowerCAmelCase			     =	field(
					    default=750    ,   metadata={'''help''': '''Number of warmup steps in the learning rate schedule.'''})
					_lowerCAmelCase			     =	field(
					    default=16    ,   metadata={'''help''': '''Number of gradient accumulation steps.'''})
					_lowerCAmelCase			     =	field(
					    default=__a    ,   metadata={'''help''': '''Use gradient checkpointing to reduce memory footprint.'''})
					_lowerCAmelCase			     =	field(default=50_000    ,   metadata={'''help''': '''Maximum number of training steps.'''})
					_lowerCAmelCase			     =	field(
					    default=-1    ,   metadata={'''help''': '''Maximum number of evaluation steps. If -1 the full dataset is evaluated.'''})
					_lowerCAmelCase			     =	field(default=1_024    ,   metadata={'''help''': '''Sequence lengths used for training.'''})
					_lowerCAmelCase			     =	field(default=1    ,   metadata={'''help''': '''Training seed.'''})
					_lowerCAmelCase			     =	field(
					    default=1_024    ,   metadata={'''help''': '''Interval to save checkpoints. Measured as number of forward passes not training steps.'''}    ,   )
					_lowerCAmelCase			     =	field(
					    default=__a    ,   metadata={'''help''': '''States path if the training should continue from a checkpoint folder.'''})
					_lowerCAmelCase			     =	field(default=__a    ,   metadata={'''help''': '''If True the data is pretokenized.'''})





@dataclass
class     __snake_case		:
					_lowerCAmelCase			     =	field(
					    default='''codeparrot/codeparrot'''    ,   metadata={'''help''': '''Model name or path of model to be evaluated.'''})
					_lowerCAmelCase			     =	field(
					    default='''codeparrot/codeparrot-clean-valid'''    ,   metadata={'''help''': '''Name or path of validation dataset.'''})
					_lowerCAmelCase			     =	field(default=2    ,   metadata={'''help''': '''Batch size used for evaluation.'''})
					_lowerCAmelCase			     =	field(
					    default=-1    ,   metadata={'''help''': '''Maximum number of evaluation steps. If -1 the full dataset is evaluated.'''})
					_lowerCAmelCase			     =	field(default=1_024    ,   metadata={'''help''': '''Length of sequences to be evaluated.'''})
					_lowerCAmelCase			     =	field(default=1    ,   metadata={'''help''': '''Random seed used for evaluation.'''})





@dataclass
class     __snake_case		:
					_lowerCAmelCase			     =	field(
					    default='''codeparrot/codeparrot'''    ,   metadata={'''help''': '''Model name or path of model to be evaluated.'''})
					_lowerCAmelCase			     =	field(default=__a    ,   metadata={'''help''': '''Number of workers used for code evaluation.'''})
					_lowerCAmelCase			     =	field(
					    default=__a    ,   metadata={'''help''': '''The number of human-eval tasks to run. If not included all tasks are evaluated.'''}    ,   )
					_lowerCAmelCase			     =	field(
					    default=__a    ,   metadata={'''help''': '''Sample from the language model\'s output distribution.'''})
					_lowerCAmelCase			     =	field(default=0.2    ,   metadata={'''help''': '''Sampling temperature used for generation.'''})
					_lowerCAmelCase			     =	field(default=256    ,   metadata={'''help''': '''Maximum number of newly generated tokens.'''})
					_lowerCAmelCase			     =	field(default=0    ,   metadata={'''help''': '''Top-k parameter used for generation.'''})
					_lowerCAmelCase			     =	field(default=0.95    ,   metadata={'''help''': '''Top-p parameter used for nucleus sampling.'''})
					_lowerCAmelCase			     =	field(default=10    ,   metadata={'''help''': '''Number of generations to run in parallel.'''})
					_lowerCAmelCase			     =	field(
					    default=200    ,   metadata={'''help''': '''Number of completions to generate for each sample.'''})
					_lowerCAmelCase			     =	field(default=1    ,   metadata={'''help''': '''Random seed used for evaluation.'''})
					_lowerCAmelCase			     =	field(
					    default='''eval_results.json'''    ,   metadata={'''help''': '''Random seed used for evaluation.'''})
					_lowerCAmelCase			     =	field(
					    default='''0'''    ,   metadata={'''help''': '''Allow `code_eval` to execute Python code on machine'''})
					_lowerCAmelCase			     =	field(
					    default=-1    ,   metadata={
					        '''help''': (
					            '''Determine which device to run the `text-generation` Pipeline on. -1 is CPU and any zero or positive'''
					            ''' number corresponds to which GPU device id to run on.'''
					        )
					    }    ,   )





@dataclass
class     __snake_case		:
					_lowerCAmelCase			     =	field(
					    default=__a    ,   metadata={
					        '''help''': '''The number of CPU cores to use for parallel preprocessing. Default uses the maximum available.'''
					    }    ,   )
					_lowerCAmelCase			     =	field(
					    default='''transformersbook/codeparrot'''    ,   metadata={'''help''': '''Folder or name of dataset to process.'''})
					_lowerCAmelCase			     =	field(
					    default='''codeparrot-clean'''    ,   metadata={'''help''': '''Folder to save processed processed dataset.'''})
					_lowerCAmelCase			     =	field(
					    default=100_000    ,   metadata={'''help''': '''Number of files to save per JSON output file.'''})
					_lowerCAmelCase			     =	field(default='''content'''    ,   metadata={'''help''': '''Column containing text data to process.'''})
					_lowerCAmelCase			     =	field(
					    default=1_000    ,   metadata={'''help''': '''Maximum line length in file, otherwise file is filtered.'''})
					_lowerCAmelCase			     =	field(
					    default=100    ,   metadata={'''help''': '''Maximum mean line length in file, otherwise file is filtered.'''})
					_lowerCAmelCase			     =	field(
					    default=0.25    ,   metadata={'''help''': '''Maximum fraction of non-alphanumeric characters, otherwise file is filtered.'''})
					_lowerCAmelCase			     =	field(
					    default=1.5    ,   metadata={'''help''': '''Minimum character token ratio for the file, otherwise file is filtered.'''})
					_lowerCAmelCase			     =	field(
					    default=0.7    ,   metadata={'''help''': '''Probability for filtering config, test and uncommon files.'''})
					_lowerCAmelCase			     =	field(
					    default='''codeparrot/codeparrot'''    ,   metadata={'''help''': '''Name or path to the tokenizer.'''}    ,   )
					_lowerCAmelCase			     =	field(
					    default=__a    ,   metadata={'''help''': '''If True, near-duplicate samples are removed.'''})
					_lowerCAmelCase			     =	field(
					    default=0.85    ,   metadata={'''help''': '''Jaccard threshold for near-duplicate samples.'''})





@dataclass
class     __snake_case		:
					_lowerCAmelCase			     =	field(
					    default='''gpt2'''    ,   metadata={'''help''': '''Base tokenizer to build new tokenizer from.'''})
					_lowerCAmelCase			     =	field(
					    default='''transformersbook/codeparrot-train'''    ,   metadata={'''help''': '''Dataset to train tokenizer on.'''})
					_lowerCAmelCase			     =	field(default='''content'''    ,   metadata={'''help''': '''Column containing text data to process.'''})
					_lowerCAmelCase			     =	field(default=200_000    ,   metadata={'''help''': '''Number of examples to train tokenizer on.'''})
					_lowerCAmelCase			     =	field(
					    default=32_768    ,   metadata={'''help''': '''Number of examples to train the tokenizer on.'''})
					_lowerCAmelCase			     =	field(default='''codeparrot'''    ,   metadata={'''help''': '''Name of new tokenizer.'''})
					_lowerCAmelCase			     =	field(default=__a    ,   metadata={'''help''': '''Push saved tokenizer to the hub.'''})





@dataclass
class     __snake_case		:
					_lowerCAmelCase			     =	field(
					    default='''codeparrot/codeparrot'''    ,   metadata={'''help''': '''Name or path to the tokenizer.'''})
					_lowerCAmelCase			     =	field(
					    default='''codeparrot/codeparrot-clean-train'''    ,   metadata={'''help''': '''Name or path to the dataset to pretokenize.'''})
					_lowerCAmelCase			     =	field(
					    default='''tokenized-codeparrot-train'''    ,   metadata={'''help''': '''Repo name of the pretokenized data.'''})
					_lowerCAmelCase			     =	field(default=__a    ,   metadata={'''help''': '''Number of workers used for code evaluation.'''})





@dataclass
class     __snake_case		:
					_lowerCAmelCase			     =	field(
					    default='''gpt2-large'''    ,   metadata={'''help''': '''Configuration to use for model initialization.'''})
					_lowerCAmelCase			     =	field(
					    default='''codeparrot/codeparrot'''    ,   metadata={'''help''': '''Tokenizer attached to model.'''})
					_lowerCAmelCase			     =	field(default='''codeparrot'''    ,   metadata={'''help''': '''Name of the created model.'''})
					_lowerCAmelCase			     =	field(default=__a    ,   metadata={'''help''': '''Push saved tokenizer to the hub.'''})


'''simple docstring'''






# Imports
import numpy as np




class     __snake_case		:
					def __init__(     self,    A=None,    A=None,    A=None,    A=None,    A=None      ):

									"""simple docstring"""


									self.set_matricies(red=A,    green=A,    blue=A,    red_edge=A,    nir=A      )
					def     UpperCAmelCase_							(     self,    A=None,    A=None,    A=None,    A=None,    A=None      ):

									"""simple docstring"""


									if red is not None:
													lowerCamelCase					:			Optional[int]									= red
									if green is not None:
													lowerCamelCase					:			Optional[int]									= green
									if blue is not None:
													lowerCamelCase					:			List[str]									= blue
									if red_edge is not None:
													lowerCamelCase					:			Tuple									= red_edge
									if nir is not None:
													lowerCamelCase					:			Any									= nir
									return True
					def     UpperCAmelCase_							(     self,    A="",    A=None,    A=None,    A=None,    A=None,    A=None      ):

									"""simple docstring"""


									self.set_matricies(red=A,    green=A,    blue=A,    red_edge=A,    nir=A      )
									lowerCamelCase					:			Optional[int]									= {
									    'ARVI2': self.arvaa,
									    'CCCI': self.ccci,
									    'CVI': self.cvi,
									    'GLI': self.gli,
									    'NDVI': self.ndvi,
									    'BNDVI': self.bndvi,
									    'redEdgeNDVI': self.red_edge_ndvi,
									    'GNDVI': self.gndvi,
									    'GBNDVI': self.gbndvi,
									    'GRNDVI': self.grndvi,
									    'RBNDVI': self.rbndvi,
									    'PNDVI': self.pndvi,
									    'ATSAVI': self.atsavi,
									    'BWDRVI': self.bwdrvi,
									    'CIgreen': self.ci_green,
									    'CIrededge': self.ci_rededge,
									    'CI': self.ci,
									    'CTVI': self.ctvi,
									    'GDVI': self.gdvi,
									    'EVI': self.evi,
									    'GEMI': self.gemi,
									    'GOSAVI': self.gosavi,
									    'GSAVI': self.gsavi,
									    'Hue': self.hue,
									    'IVI': self.ivi,
									    'IPVI': self.ipvi,
									    'I': self.i,
									    'RVI': self.rvi,
									    'MRVI': self.mrvi,
									    'MSAVI': self.m_savi,
									    'NormG': self.norm_g,
									    'NormNIR': self.norm_nir,
									    'NormR': self.norm_r,
									    'NGRDI': self.ngrdi,
									    'RI': self.ri,
									    'S': self.s,
									    'IF': self._if,
									    'DVI': self.dvi,
									    'TVI': self.tvi,
									    'NDRE': self.ndre,
									}

									try:
													return funcs[index]()
									except KeyError:
													print('Index not in the list!'      )
													return False
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return -0.18 + (1.17 * ((self.nir - self.red) / (self.nir + self.red)))
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return ((self.nir - self.redEdge) / (self.nir + self.redEdge)) / (
									    (self.nir - self.red) / (self.nir + self.red)
									)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return self.nir * (self.red / (self.green**2))
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (2 * self.green - self.red - self.blue) / (
									    2 * self.green + self.red + self.blue
									)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (self.nir - self.red) / (self.nir + self.red)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (self.nir - self.blue) / (self.nir + self.blue)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (self.redEdge - self.red) / (self.redEdge + self.red)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (self.nir - self.green) / (self.nir + self.green)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (self.nir - (self.green + self.blue)) / (
									    self.nir + (self.green + self.blue)
									)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (self.nir - (self.green + self.red)) / (
									    self.nir + (self.green + self.red)
									)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (self.nir - (self.blue + self.red)) / (self.nir + (self.blue + self.red))
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (self.nir - (self.green + self.red + self.blue)) / (
									    self.nir + (self.green + self.red + self.blue)
									)
					def     UpperCAmelCase_							(     self,    A=0.08,    A=1.22,    A=0.03      ):

									"""simple docstring"""


									return a * (
									    (self.nir - a * self.red - b)
									    / (a * self.nir + self.red - a * b + x * (1 + a**2))
									)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (0.1 * self.nir - self.blue) / (0.1 * self.nir + self.blue)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (self.nir / self.green) - 1
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (self.nir / self.redEdge) - 1
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (self.red - self.blue) / self.red
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			Union[str, Any]									= self.ndvi()
									return ((ndvi + 0.5) / (abs(ndvi + 0.5      ))) * (abs(ndvi + 0.5      ) ** (1 / 2))
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return self.nir - self.green
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return 2.5 * (
									    (self.nir - self.red) / (self.nir + 6 * self.red - 7.5 * self.blue + 1)
									)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			str									= (2 * (self.nir**2 - self.red**2) + 1.5 * self.nir + 0.5 * self.red) / (
									    self.nir + self.red + 0.5
									)
									return n * (1 - 0.25 * n) - (self.red - 0.125) / (1 - self.red)
					def     UpperCAmelCase_							(     self,    A=0.16      ):

									"""simple docstring"""


									return (self.nir - self.green) / (self.nir + self.green + y)
					def     UpperCAmelCase_							(     self,    A=0.5      ):

									"""simple docstring"""


									return ((self.nir - self.green) / (self.nir + self.green + n)) * (1 + n)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return np.arctan(
									    ((2 * self.red - self.green - self.blue) / 30.5) * (self.green - self.blue)      )
					def     UpperCAmelCase_							(     self,    A=None,    A=None      ):

									"""simple docstring"""


									return (self.nir - b) / (a * self.red)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (self.nir / ((self.nir + self.red) / 2)) * (self.ndvi() + 1)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (self.red + self.green + self.blue) / 30.5
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return self.nir / self.red
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (self.rvi() - 1) / (self.rvi() + 1)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (
									    (2 * self.nir + 1)
									    - ((2 * self.nir + 1) ** 2 - 8 * (self.nir - self.red)) ** (1 / 2)
									) / 2
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return self.green / (self.nir + self.red + self.green)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return self.nir / (self.nir + self.red + self.green)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return self.red / (self.nir + self.red + self.green)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (self.green - self.red) / (self.green + self.red)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (self.red - self.green) / (self.red + self.green)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			Optional[Any]									= np.max([np.max(self.red      ), np.max(self.green      ), np.max(self.blue      )]      )
									lowerCamelCase					:			Tuple									= np.min([np.min(self.red      ), np.min(self.green      ), np.min(self.blue      )]      )
									return (max_value - min_value) / max_value
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (2 * self.red - self.green - self.blue) / (self.green - self.blue)
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return self.nir / self.red
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (self.ndvi() + 0.5) ** (1 / 2)




					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									return (self.nir - self.redEdge) / (self.nir + self.redEdge)
