





import numpy as np

import datasets


_snake_case           =			'\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\nIt was introduced by Prof. P. C. Mahalanobis in 1936\nand has been used in various statistical applications ever since\n[source: https://www.machinelearningplus.com/statistics/mahalanobis-distance/]\n'

_snake_case           =			'\\n@article{de2000mahalanobis,\n  title={The mahalanobis distance},\n  author={De Maesschalck, Roy and Jouan-Rimbaud, Delphine and Massart, D{\'e}sir{\'e} L},\n  journal={Chemometrics and intelligent laboratory systems},\n  volume={50},\n  number={1},\n  pages={1--18},\n  year={2000},\n  publisher={Elsevier}\n}\n'

_snake_case           =			'\nArgs:\n    X: List of datapoints to be compared with the `reference_distribution`.\n    reference_distribution: List of datapoints from the reference distribution we want to compare to.\nReturns:\n    mahalanobis: The Mahalonobis distance for each datapoint in `X`.\nExamples:\n\n    >>> mahalanobis_metric = datasets.load_metric("mahalanobis")\n    >>> results = mahalanobis_metric.compute(reference_distribution=[[0, 1], [1, 0]], X=[[0, 1]])\n    >>> print(results)\n    {\'mahalanobis\': array([0.5])}\n'





@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION							,							_KWARGS_DESCRIPTION )
class  lowerCAmelCase							(       datasets.Metric ):







  def   UpperCAmelCase					(      self  :int ):






     '''simple docstring'''





     return datasets.MetricInfo(
         description=_DESCRIPTION   ,							citation=_CITATION   ,							inputs_description=_KWARGS_DESCRIPTION   ,							features=datasets.Features(
             {
                 "X": datasets.Sequence(datasets.Value("float"   ,							id="sequence" )   ,							id="X" ),
             } )   ,							)







  def   UpperCAmelCase					(      self  :str   ,							_lowercase  :List[Any]   ,							_lowercase  :Any ):






     '''simple docstring'''





     lowercase__			       =  np.array(lowercase_ )
     lowercase__			       =  np.array(lowercase_ )

     # Assert that arrays are 2D
     if len(X.shape ) != 2:
        raise ValueError("Expected `X` to be a 2D vector" )
     if len(reference_distribution.shape ) != 2:
        raise ValueError("Expected `reference_distribution` to be a 2D vector" )
     if reference_distribution.shape[0] < 2:
        raise ValueError(
            "Expected `reference_distribution` to be a 2D vector with more than one element in the first dimension" )

     # Get mahalanobis distance for each prediction
     lowercase__			       =  X - np.mean(lowercase_ )
     lowercase__			       =  np.cov(reference_distribution.T )
     try:
        lowercase__			       =  np.linalg.inv(lowercase_ )
     except np.linalg.LinAlgError:
        lowercase__			       =  np.linalg.pinv(lowercase_ )
     lowercase__			       =  np.dot(lowercase_   ,							lowercase_ )
     lowercase__			       =  np.dot(lowercase_   ,							X_minus_mu.T ).diagonal()

     return {"mahalanobis": mahal_dist}













import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_torch_available, is_vision_available


if is_torch_available():
  import torch


if is_vision_available():
  from PIL import Image

  from transformers import MgpstrProcessor, ViTImageProcessor





@require_torch
@require_vision
class  lowerCAmelCase							(       unittest.TestCase ):
  __lowerCamelCase		=      ViTImageProcessor if is_vision_available() else None







  @property
  def   UpperCAmelCase					(      self  :Union[str, Any] ):






     '''simple docstring'''





     return self.image_processor_tester.prepare_image_processor_dict()







  def   UpperCAmelCase					(      self  :Optional[int] ):






     '''simple docstring'''





     lowercase__			       =  (3, 32, 1_28)
     lowercase__			       =  tempfile.mkdtemp()

     # fmt: off
     lowercase__			       =  ["[GO]", "[s]", "0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z"]
     # fmt: on
     lowercase__			       =  dict(zip(_lowercase   ,							range(len(_lowercase ) ) ) )

     lowercase__			       =  os.path.join(self.tmpdirname   ,							VOCAB_FILES_NAMES["vocab_file"] )
     with open(self.vocab_file   ,							"w"   ,							encoding="utf-8" ) as fp:
        fp.write(json.dumps(_lowercase ) + "\n" )

     lowercase__			       =  {
         "do_normalize": False,
         "do_resize": True,
         "image_processor_type": "ViTImageProcessor",
         "resample": 3,
         "size": {"height": 32, "width": 1_28},
     }
     lowercase__			       =  os.path.join(self.tmpdirname   ,							_lowercase )
     with open(self.image_processor_file   ,							"w"   ,							encoding="utf-8" ) as fp:
        json.dump(_lowercase   ,							_lowercase )







  def   UpperCAmelCase					(      self  :Optional[Any]   ,							**_lowercase  :str ):






     '''simple docstring'''





     return MgpstrTokenizer.from_pretrained(self.tmpdirname   ,							**_lowercase )







  def   UpperCAmelCase					(      self  :List[Any]   ,							**_lowercase  :List[str] ):






     '''simple docstring'''





     return ViTImageProcessor.from_pretrained(self.tmpdirname   ,							**_lowercase )







  def   UpperCAmelCase					(      self  :List[Any] ):






     '''simple docstring'''





     shutil.rmtree(self.tmpdirname )







  def   UpperCAmelCase					(      self  :str ):






     '''simple docstring'''





     lowercase__			       =  np.random.randint(2_55   ,							size=(3, 30, 4_00)   ,							dtype=np.uinta )

     lowercase__			       =  Image.fromarray(np.moveaxis(_lowercase   ,							0   ,							-1 ) )

     return image_input







  def   UpperCAmelCase					(      self  :List[Any] ):






     '''simple docstring'''





     lowercase__			       =  self.get_tokenizer()
     lowercase__			       =  self.get_image_processor()

     lowercase__			       =  MgpstrProcessor(tokenizer=_lowercase   ,							image_processor=_lowercase )
     processor.save_pretrained(self.tmpdirname )
     lowercase__			       =  MgpstrProcessor.from_pretrained(self.tmpdirname   ,							use_fast=_lowercase )

     self.assertEqual(processor.char_tokenizer.get_vocab()   ,							tokenizer.get_vocab() )
     self.assertIsInstance(processor.char_tokenizer   ,							_lowercase )

     self.assertEqual(processor.image_processor.to_json_string()   ,							image_processor.to_json_string() )
     self.assertIsInstance(processor.image_processor   ,							_lowercase )







  def   UpperCAmelCase					(      self  :Optional[Any] ):






     '''simple docstring'''





     lowercase__			       =  self.get_tokenizer()
     lowercase__			       =  self.get_image_processor()

     lowercase__			       =  MgpstrProcessor(tokenizer=_lowercase   ,							image_processor=_lowercase )
     processor.save_pretrained(self.tmpdirname )

     lowercase__			       =  self.get_tokenizer(bos_token="(BOS)"   ,							eos_token="(EOS)" )
     lowercase__			       =  self.get_image_processor(do_normalize=_lowercase   ,							padding_value=1.0 )

     lowercase__			       =  MgpstrProcessor.from_pretrained(
         self.tmpdirname   ,							bos_token="(BOS)"   ,							eos_token="(EOS)"   ,							do_normalize=_lowercase   ,							padding_value=1.0 )

     self.assertEqual(processor.char_tokenizer.get_vocab()   ,							tokenizer_add_kwargs.get_vocab() )
     self.assertIsInstance(processor.char_tokenizer   ,							_lowercase )

     self.assertEqual(processor.image_processor.to_json_string()   ,							image_processor_add_kwargs.to_json_string() )
     self.assertIsInstance(processor.image_processor   ,							_lowercase )







  def   UpperCAmelCase					(      self  :List[Any] ):






     '''simple docstring'''





     lowercase__			       =  self.get_image_processor()
     lowercase__			       =  self.get_tokenizer()

     lowercase__			       =  MgpstrProcessor(tokenizer=_lowercase   ,							image_processor=_lowercase )

     lowercase__			       =  self.prepare_image_inputs()

     lowercase__			       =  image_processor(_lowercase   ,							return_tensors="np" )
     lowercase__			       =  processor(images=_lowercase   ,							return_tensors="np" )

     for key in input_image_proc.keys():
        self.assertAlmostEqual(input_image_proc[key].sum()   ,							input_processor[key].sum()   ,							delta=1e-2 )







  def   UpperCAmelCase					(      self  :Optional[Any] ):






     '''simple docstring'''





     lowercase__			       =  self.get_image_processor()
     lowercase__			       =  self.get_tokenizer()

     lowercase__			       =  MgpstrProcessor(tokenizer=_lowercase   ,							image_processor=_lowercase )

     lowercase__			       =  "test"

     lowercase__			       =  processor(text=_lowercase )

     lowercase__			       =  tokenizer(_lowercase )
     for key in encoded_tok.keys():
        self.assertListEqual(encoded_tok[key]   ,							encoded_processor[key] )







  def   UpperCAmelCase					(      self  :Optional[int] ):






     '''simple docstring'''





     lowercase__			       =  self.get_image_processor()
     lowercase__			       =  self.get_tokenizer()

     lowercase__			       =  MgpstrProcessor(tokenizer=_lowercase   ,							image_processor=_lowercase )

     lowercase__			       =  "test"
     lowercase__			       =  self.prepare_image_inputs()

     lowercase__			       =  processor(text=_lowercase   ,							images=_lowercase )

     self.assertListEqual(list(inputs.keys() )   ,							["pixel_values", "labels"] )

     # test if it raises when no input is passed
     with pytest.raises(_lowercase ):
        processor()







  def   UpperCAmelCase					(      self  :Tuple ):






     '''simple docstring'''





     lowercase__			       =  self.get_image_processor()
     lowercase__			       =  self.get_tokenizer()

     lowercase__			       =  MgpstrProcessor(tokenizer=_lowercase   ,							image_processor=_lowercase )

     lowercase__			       =  [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9], [3, 4, 3, 1, 1, 8, 9]]

     lowercase__			       =  processor.char_decode(_lowercase )
     lowercase__			       =  tokenizer.batch_decode(_lowercase )
     lowercase__			       =  [seq.replace(" "   ,							"" ) for seq in decoded_tok]

     self.assertListEqual(_lowercase   ,							_lowercase )







  def   UpperCAmelCase					(      self  :str ):






     '''simple docstring'''





     lowercase__			       =  self.get_image_processor()
     lowercase__			       =  self.get_tokenizer()

     lowercase__			       =  MgpstrProcessor(tokenizer=_lowercase   ,							image_processor=_lowercase )

     lowercase__			       =  None
     lowercase__			       =  self.prepare_image_inputs()

     lowercase__			       =  processor(text=_lowercase   ,							images=_lowercase )

     self.assertListEqual(list(inputs.keys() )   ,							processor.model_input_names )







  def   UpperCAmelCase					(      self  :List[str] ):






     '''simple docstring'''





     lowercase__			       =  self.get_image_processor()
     lowercase__			       =  self.get_tokenizer()

     lowercase__			       =  MgpstrProcessor(tokenizer=_lowercase   ,							image_processor=_lowercase )

     lowercase__			       =  torch.randn(1   ,							27   ,							38 )
     lowercase__			       =  torch.randn(1   ,							27   ,							5_02_57 )
     lowercase__			       =  torch.randn(1   ,							27   ,							3_05_22 )

     lowercase__			       =  processor.batch_decode([char_input, bpe_input, wp_input] )

     self.assertListEqual(list(results.keys() )   ,							["generated_text", "scores", "char_preds", "bpe_preds", "wp_preds"] )






