


"""simple docstring"""


import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


A     :   List[Any]			    =			get_tests_dir("fixtures/test_sentencepiece.model")


if is_torch_available():
	from transformers.models.plbart.modeling_plbart import shift_tokens_right

A     :   Union[str, Any]			    =			5_0_0_0_3
A     :   Any			    =			5_0_0_0_2
@require_sentencepiece
@require_tokenizers
class   _UpperCamelCase  (   lowerCAmelCase__       ,unittest.TestCase		):
							'''simple docstring'''







							__UpperCAmelCase						:    str				      =PLBartTokenizer
							__UpperCAmelCase						:    Optional[Any]				      =None
							__UpperCAmelCase						:    Optional[Any]				      =False

							def 			snake_case				(     self	):
										super().setUp()

										# We have a SentencePiece fixture for testing
										__lowerCAmelCase				    =			PLBartTokenizer(__a    ,   language_codes="base"    ,   keep_accents=__a	)
										tokenizer.save_pretrained(self.tmpdirname	)

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			PLBartTokenizer(__a    ,   language_codes="base"    ,   keep_accents=__a	)

										__lowerCAmelCase				    =			tokenizer.tokenize("This is a test"	)
										self.assertListEqual(__a    ,   ["▁This", "▁is", "▁a", "▁t", "est"]	)

										self.assertListEqual(
										    tokenizer.convert_tokens_to_ids(__a	)    ,   [value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]    ,   )

										__lowerCAmelCase				    =			tokenizer.tokenize("I was born in 92000, and this is falsé."	)
										self.assertListEqual(
										    __a    ,   [
										        SPIECE_UNDERLINE + "I",
										        SPIECE_UNDERLINE + "was",
										        SPIECE_UNDERLINE + "b",
										        "or",
										        "n",
										        SPIECE_UNDERLINE + "in",
										        SPIECE_UNDERLINE + "",
										        "9",
										        "2",
										        "0",
										        "0",
										        "0",
										        ",",
										        SPIECE_UNDERLINE + "and",
										        SPIECE_UNDERLINE + "this",
										        SPIECE_UNDERLINE + "is",
										        SPIECE_UNDERLINE + "f",
										        "al",
										        "s",
										        "é",
										        ".",
										    ]    ,   )
										__lowerCAmelCase				    =			tokenizer.convert_tokens_to_ids(__a	)
										self.assertListEqual(
										    __a    ,   [
										        value + tokenizer.fairseq_offset
										        for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
										    ]    ,   )

										__lowerCAmelCase				    =			tokenizer.convert_ids_to_tokens(__a	)
										self.assertListEqual(
										    __a    ,   [
										        SPIECE_UNDERLINE + "I",
										        SPIECE_UNDERLINE + "was",
										        SPIECE_UNDERLINE + "b",
										        "or",
										        "n",
										        SPIECE_UNDERLINE + "in",
										        SPIECE_UNDERLINE + "",
										        "<unk>",
										        "2",
										        "0",
										        "0",
										        "0",
										        ",",
										        SPIECE_UNDERLINE + "and",
										        SPIECE_UNDERLINE + "this",
										        SPIECE_UNDERLINE + "is",
										        SPIECE_UNDERLINE + "f",
										        "al",
										        "s",
										        "<unk>",
										        ".",
										    ]    ,   )

										__lowerCAmelCase				    =			tokenizer.vocab_size
										__lowerCAmelCase				    =			[tokenizer.convert_ids_to_tokens(__a	) for x in range(end - 4    ,   __a	)]

										self.assertListEqual(__a    ,   ["__java__", "__python__", "__en_XX__", "<mask>"]	)

										__lowerCAmelCase				    =			"java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"
										__lowerCAmelCase				    =			tokenizer(__a	).input_ids
										self.assertEqual(
										    tokenizer.decode(__a    ,   skip_special_tokens=__a    ,   clean_up_tokenization_spaces=__a	)    ,   __a    ,   )



							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			PLBartTokenizer(__a    ,   language_codes="multi"    ,   keep_accents=__a	)

										__lowerCAmelCase				    =			tokenizer.tokenize("This is a test"	)
										self.assertListEqual(__a    ,   ["▁This", "▁is", "▁a", "▁t", "est"]	)

										self.assertListEqual(
										    tokenizer.convert_tokens_to_ids(__a	)    ,   [value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]    ,   )

										__lowerCAmelCase				    =			tokenizer.tokenize("I was born in 92000, and this is falsé."	)
										self.assertListEqual(
										    __a    ,   [
										        SPIECE_UNDERLINE + "I",
										        SPIECE_UNDERLINE + "was",
										        SPIECE_UNDERLINE + "b",
										        "or",
										        "n",
										        SPIECE_UNDERLINE + "in",
										        SPIECE_UNDERLINE + "",
										        "9",
										        "2",
										        "0",
										        "0",
										        "0",
										        ",",
										        SPIECE_UNDERLINE + "and",
										        SPIECE_UNDERLINE + "this",
										        SPIECE_UNDERLINE + "is",
										        SPIECE_UNDERLINE + "f",
										        "al",
										        "s",
										        "é",
										        ".",
										    ]    ,   )
										__lowerCAmelCase				    =			tokenizer.convert_tokens_to_ids(__a	)
										self.assertListEqual(
										    __a    ,   [
										        value + tokenizer.fairseq_offset
										        for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
										    ]    ,   )

										__lowerCAmelCase				    =			tokenizer.convert_ids_to_tokens(__a	)
										self.assertListEqual(
										    __a    ,   [
										        SPIECE_UNDERLINE + "I",
										        SPIECE_UNDERLINE + "was",
										        SPIECE_UNDERLINE + "b",
										        "or",
										        "n",
										        SPIECE_UNDERLINE + "in",
										        SPIECE_UNDERLINE + "",
										        "<unk>",
										        "2",
										        "0",
										        "0",
										        "0",
										        ",",
										        SPIECE_UNDERLINE + "and",
										        SPIECE_UNDERLINE + "this",
										        SPIECE_UNDERLINE + "is",
										        SPIECE_UNDERLINE + "f",
										        "al",
										        "s",
										        "<unk>",
										        ".",
										    ]    ,   )
										__lowerCAmelCase				    =			tokenizer.vocab_size
										__lowerCAmelCase				    =			[tokenizer.convert_ids_to_tokens(__a	) for x in range(end - 7    ,   __a	)]

										self.assertListEqual(
										    __a    ,   ["__java__", "__python__", "__en_XX__", "__javascript__", "__php__", "__ruby__", "__go__"]	)
										__lowerCAmelCase				    =			"java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"
										__lowerCAmelCase				    =			tokenizer(__a	).input_ids
										self.assertEqual(
										    tokenizer.decode(__a    ,   skip_special_tokens=__a    ,   clean_up_tokenization_spaces=__a	)    ,   __a    ,   )
@require_torch
@require_sentencepiece
@require_tokenizers
class   _UpperCamelCase  (   unittest.TestCase		):
							'''simple docstring'''







							__UpperCAmelCase						:    Dict				      ="""uclanlp/plbart-python-en_XX"""
							__UpperCAmelCase						:    List[str]				      =[
							    """def maximum(a,b,c):NEW_LINE_INDENTreturn max([a,b,c])""",
							    """def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])""",
							]
							__UpperCAmelCase						:    List[Any]				      =[
							    """Returns the maximum value of a b c.""",
							    """Sums the values of a b c.""",
							]
							__UpperCAmelCase						:    Optional[int]				      =[
							    1_3_4,
							    5_4_5_2,
							    3_3_4_6_0,
							    3_3_4_4_1,
							    3_3_4_6_3,
							    3_3_4_6_5,
							    3_3_4_6_3,
							    3_3_4_4_9,
							    9_8_8,
							    2_0,
							    3_3_4_5_6,
							    1_9,
							    3_3_4_5_6,
							    7_7_1,
							    3_9,
							    4_2_5_8,
							    8_8_9,
							    3_3_1_8,
							    3_3_4_4_1,
							    3_3_4_6_3,
							    3_3_4_6_5,
							    3_3_4_6_3,
							    3_3_4_4_9,
							    2_4_7_1,
							    2,
							    PYTHON_CODE,
							]

							@classmethod
							def 			snake_case				(     cls	):
										__lowerCAmelCase				    =			PLBartTokenizer.from_pretrained(
										    cls.checkpoint_name    ,   language_codes="base"    ,   src_lang="python"    ,   tgt_lang="en_XX"	)
										__lowerCAmelCase				    =			1
										return cls

							def 			snake_case				(     self	):
										self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__java__"]    ,   5_00_01	)
										self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__python__"]    ,   5_00_02	)
										self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__en_XX__"]    ,   5_00_03	)

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.tokenizer.batch_encode_plus(self.src_text	).input_ids[0]
										self.assertListEqual(self.expected_src_tokens    ,   __a	)

							def 			snake_case				(     self	):
										self.assertIn(__a    ,   self.tokenizer.all_special_ids	)
										__lowerCAmelCase				    =			[EN_CODE, 90_37, 3_34_42, 57, 7_52, 1_53, 14, 56, 18, 9, 2]
										__lowerCAmelCase				    =			self.tokenizer.decode(__a    ,   skip_special_tokens=__a	)
										__lowerCAmelCase				    =			self.tokenizer.decode(generated_ids[1:]    ,   skip_special_tokens=__a	)
										self.assertEqual(__a    ,   __a	)
										self.assertNotIn(self.tokenizer.eos_token    ,   __a	)

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			["def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])" * 20]
										self.assertIsInstance(src_text[0]    ,   __a	)
										__lowerCAmelCase				    =			10
										__lowerCAmelCase				    =			self.tokenizer(__a    ,   max_length=__a    ,   truncation=__a	).input_ids[0]
										self.assertEqual(ids[-2]    ,   2	)
										self.assertEqual(ids[-1]    ,   __a	)
										self.assertEqual(len(__a	)    ,   __a	)

							def 			snake_case				(     self	):
										self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "__java__"]	)    ,   [5_00_04, 5_00_01]	)

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			tempfile.mkdtemp()
										__lowerCAmelCase				    =			self.tokenizer.fairseq_tokens_to_ids
										self.tokenizer.save_pretrained(__a	)
										__lowerCAmelCase				    =			PLBartTokenizer.from_pretrained(__a	)
										self.assertDictEqual(new_tok.fairseq_tokens_to_ids    ,   __a	)

							@require_torch
							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.tokenizer(self.src_text    ,   text_target=self.tgt_text    ,   padding=__a    ,   return_tensors="pt"	)
										__lowerCAmelCase				    =			shift_tokens_right(batch["labels"]    ,   self.tokenizer.pad_token_id	)

										# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
										self.assertEqual(batch.input_ids[1][-2:].tolist()    ,   [2, PYTHON_CODE]	)
										self.assertEqual(batch.decoder_input_ids[1][0]    ,   __a	)
										self.assertEqual(batch.decoder_input_ids[1][-1]    ,   2	)
										self.assertEqual(batch.labels[1][-2:].tolist()    ,   [2, EN_CODE]	)

							@require_torch
							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.tokenizer(
										    self.src_text    ,   text_target=self.tgt_text    ,   padding=__a    ,   truncation=__a    ,   max_length=len(self.expected_src_tokens	)    ,   return_tensors="pt"    ,   )
										__lowerCAmelCase				    =			shift_tokens_right(batch["labels"]    ,   self.tokenizer.pad_token_id	)

										self.assertIsInstance(__a    ,   __a	)

										self.assertEqual((2, 26)    ,   batch.input_ids.shape	)
										self.assertEqual((2, 26)    ,   batch.attention_mask.shape	)
										__lowerCAmelCase				    =			batch.input_ids.tolist()[0]
										self.assertListEqual(self.expected_src_tokens    ,   __a	)
										self.assertEqual(2    ,   batch.decoder_input_ids[0, -1]	)  # EOS
										# Test that special tokens are reset
										self.assertEqual(self.tokenizer.prefix_tokens    ,   []	)
										self.assertEqual(self.tokenizer.suffix_tokens    ,   [self.tokenizer.eos_token_id, PYTHON_CODE]	)

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.tokenizer(self.src_text    ,   padding=__a    ,   truncation=__a    ,   max_length=3    ,   return_tensors="pt"	)
										__lowerCAmelCase				    =			self.tokenizer(
										    text_target=self.tgt_text    ,   padding=__a    ,   truncation=__a    ,   max_length=10    ,   return_tensors="pt"	)
										__lowerCAmelCase				    =			targets["input_ids"]
										__lowerCAmelCase				    =			shift_tokens_right(__a    ,   self.tokenizer.pad_token_id	)

										self.assertEqual(batch.input_ids.shape[1]    ,   3	)
										self.assertEqual(batch.decoder_input_ids.shape[1]    ,   10	)



							@require_torch
							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.tokenizer._build_translation_inputs(
										    "A test"    ,   return_tensors="pt"    ,   src_lang="en_XX"    ,   tgt_lang="java"	)

										self.assertEqual(
										    nested_simplify(__a	)    ,   {
										        # A, test, EOS, en_XX
										        "input_ids": [[1_50, 2_42, 2, 5_00_03]],
										        "attention_mask": [[1, 1, 1, 1]],
										        # java
										        "forced_bos_token_id": 5_00_01,
										    }    ,   )








"""simple docstring"""


import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image

from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_processing.dithering import burkes as bs
from digital_image_processing.edge_detection import canny
from digital_image_processing.filters import convolve as conv
from digital_image_processing.filters import gaussian_filter as gg
from digital_image_processing.filters import local_binary_pattern as lbp
from digital_image_processing.filters import median_filter as med
from digital_image_processing.filters import sobel_filter as sob
from digital_image_processing.resize import resize as rs

A     :   Union[str, Any]			    =			imread(R"digital_image_processing/image_data/lena_small.jpg")
A     :   Optional[Any]			    =			cvtColor(img, COLOR_BGR2GRAY)


def _lowerCamelCase	(		):

			'''simple docstring'''




			__lowerCAmelCase				    =			cn.convert_to_negative(_UpperCamelCase      )
			# assert negative_img array for at least one True
			assert negative_img.any()


def _lowerCamelCase	(		):

			'''simple docstring'''




			with Image.open("digital_image_processing/image_data/lena_small.jpg"      ) as img:
						# Work around assertion for response
						assert str(cc.change_contrast(_UpperCamelCase    , 110      )      ).startswith(
						    "<PIL.Image.Image image mode=RGB size=100x100 at"      )


def _lowerCamelCase	(		):

			'''simple docstring'''




			__lowerCAmelCase				    =			canny.gen_gaussian_kernel(9    , sigma=1.4      )
			# Assert ambiguous array
			assert resp.all()


def _lowerCamelCase	(		):

			'''simple docstring'''




			__lowerCAmelCase				    =			imread("digital_image_processing/image_data/lena_small.jpg"    , 0      )
			# assert ambiguous array for all == True
			assert canny_img.all()
			__lowerCAmelCase				    =			canny.canny(_UpperCamelCase      )
			# assert canny array for at least one True
			assert canny_array.any()


def _lowerCamelCase	(		):

			'''simple docstring'''




			assert gg.gaussian_filter(_UpperCamelCase    , 5    , sigma=0.9      ).all()


def _lowerCamelCase	(		):

			'''simple docstring'''




			__lowerCAmelCase				    =			array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]      )
			__lowerCAmelCase				    =			conv.img_convolve(_UpperCamelCase    , _UpperCamelCase      ).astype(_UpperCamelCase      )
			assert res.any()


def _lowerCamelCase	(		):

			'''simple docstring'''




			assert med.median_filter(_UpperCamelCase    , 3      ).any()


def _lowerCamelCase	(		):

			'''simple docstring'''




			__lowerCAmelCase    ,	__lowerCAmelCase				    =			sob.sobel_filter(_UpperCamelCase      )
			assert grad.any() and theta.any()


def _lowerCamelCase	(		):

			'''simple docstring'''




			__lowerCAmelCase				    =			sp.make_sepia(_UpperCamelCase    , 20      )
			assert sepia.all()


def _lowerCamelCase	(		_UpperCamelCase = "digital_image_processing/image_data/lena_small.jpg"      ):

			'''simple docstring'''




			__lowerCAmelCase				    =			bs.Burkes(imread(_UpperCamelCase    , 1      )    , 120      )
			burkes.process()
			assert burkes.output_img.any()


def _lowerCamelCase	(		_UpperCamelCase = "digital_image_processing/image_data/lena_small.jpg"    , ):

			'''simple docstring'''




			__lowerCAmelCase				    =			rs.NearestNeighbour(imread(_UpperCamelCase    , 1      )    , 400    , 200      )
			nn.process()
			assert nn.output.any()


def _lowerCamelCase	(		):

			'''simple docstring'''




			__lowerCAmelCase				    =			"digital_image_processing/image_data/lena.jpg"

			# Reading the image and converting it to grayscale.
			__lowerCAmelCase				    =			imread(_UpperCamelCase    , 0      )

			# Test for get_neighbors_pixel function() return not None
			__lowerCAmelCase				    =			0
			__lowerCAmelCase				    =			0
			__lowerCAmelCase				    =			image[x_coordinate][y_coordinate]

			__lowerCAmelCase				    =			lbp.get_neighbors_pixel(
			    _UpperCamelCase    , _UpperCamelCase    , _UpperCamelCase    , _UpperCamelCase      )

			assert neighbors_pixels is not None

			# Test for local_binary_pattern function()
			# Create a numpy array as the same height and width of read image
			__lowerCAmelCase				    =			np.zeros((image.shape[0], image.shape[1])      )

			# Iterating through the image and calculating the local binary pattern value
			# for each pixel.
			for i in range(0    , image.shape[0]      ):
						for j in range(0    , image.shape[1]      ):
									__lowerCAmelCase				    =			lbp.local_binary_value(_UpperCamelCase    , _UpperCamelCase    , _UpperCamelCase      )

			assert lbp_image.any()




