
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


__magic_name__            =  get_tests_dir('''fixtures/test_sentencepiece.model''')


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

__magic_name__            =  50_003
__magic_name__            =  50_002




@require_sentencepiece
@require_tokenizers
class 					_SCREAMING_SNAKE_CASE  (      __lowerCAmelCase       ,					unittest.TestCase ):
						_A						:		Union[str, Any]    	=     PLBartTokenizer
						_A						:		Optional[Any]    	=     None
						_A						:		int    	=     False
						def A_			(			self ):
										super().setUp()

										# We have a SentencePiece fixture for testing
										snake_case__						=				PLBartTokenizer(lowerCAmelCase_		,	language_codes="base"		,	keep_accents=lowerCAmelCase_ )
										tokenizer.save_pretrained(self.tmpdirname )
						def A_			(			self ):
										snake_case__						=				PLBartTokenizer(lowerCAmelCase_		,	language_codes="base"		,	keep_accents=lowerCAmelCase_ )

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

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

										snake_case__						=				tokenizer.tokenize("I was born in 92000, and this is falsé." )
										self.assertListEqual(
										    lowerCAmelCase_		,	[
										        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",
										        ".",
										    ]		,	)
										snake_case__						=				tokenizer.convert_tokens_to_ids(lowerCAmelCase_ )
										self.assertListEqual(
										    lowerCAmelCase_		,	[
										        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]
										    ]		,	)

										snake_case__						=				tokenizer.convert_ids_to_tokens(lowerCAmelCase_ )
										self.assertListEqual(
										    lowerCAmelCase_		,	[
										        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>",
										        ".",
										    ]		,	)

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

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

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



						def A_			(			self ):
										snake_case__						=				PLBartTokenizer(lowerCAmelCase_		,	language_codes="multi"		,	keep_accents=lowerCAmelCase_ )

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

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

										snake_case__						=				tokenizer.tokenize("I was born in 92000, and this is falsé." )
										self.assertListEqual(
										    lowerCAmelCase_		,	[
										        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",
										        ".",
										    ]		,	)
										snake_case__						=				tokenizer.convert_tokens_to_ids(lowerCAmelCase_ )
										self.assertListEqual(
										    lowerCAmelCase_		,	[
										        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]
										    ]		,	)

										snake_case__						=				tokenizer.convert_ids_to_tokens(lowerCAmelCase_ )
										self.assertListEqual(
										    lowerCAmelCase_		,	[
										        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>",
										        ".",
										    ]		,	)
										snake_case__						=				tokenizer.vocab_size
										snake_case__						=				[tokenizer.convert_ids_to_tokens(lowerCAmelCase_ ) for x in range(end - 7		,	lowerCAmelCase_ )]

										self.assertListEqual(
										    lowerCAmelCase_		,	["__java__", "__python__", "__en_XX__", "__javascript__", "__php__", "__ruby__", "__go__"] )
										snake_case__						=				"java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"
										snake_case__						=				tokenizer(lowerCAmelCase_ ).input_ids
										self.assertEqual(
										    tokenizer.decode(lowerCAmelCase_		,	skip_special_tokens=lowerCAmelCase_		,	clean_up_tokenization_spaces=lowerCAmelCase_ )		,	lowerCAmelCase_		,	)





@require_torch
@require_sentencepiece
@require_tokenizers
class 					_SCREAMING_SNAKE_CASE  (      unittest.TestCase ):
						_A						:		Any    	=     '''uclanlp/plbart-python-en_XX'''
						_A						:		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])''',
						]
						_A						:		Dict    	=     [
						    '''Returns the maximum value of a b c.''',
						    '''Sums the values of a b c.''',
						]
						_A						:		List[str]    	=     [
						    1_34,
						    54_52,
						    3_34_60,
						    3_34_41,
						    3_34_63,
						    3_34_65,
						    3_34_63,
						    3_34_49,
						    9_88,
						    20,
						    3_34_56,
						    19,
						    3_34_56,
						    7_71,
						    39,
						    42_58,
						    8_89,
						    33_18,
						    3_34_41,
						    3_34_63,
						    3_34_65,
						    3_34_63,
						    3_34_49,
						    24_71,
						    2,
						    PYTHON_CODE,
						]
						@classmethod
						def A_			(			cls ):
										snake_case__						=				PLBartTokenizer.from_pretrained(
										    cls.checkpoint_name		,	language_codes="base"		,	src_lang="python"		,	tgt_lang="en_XX" )
										snake_case__						=				1
										return cls
						def A_			(			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 A_			(			self ):
										snake_case__						=				self.tokenizer.batch_encode_plus(self.src_text ).input_ids[0]
										self.assertListEqual(self.expected_src_tokens		,	lowerCAmelCase_ )
						def A_			(			self ):
										self.assertIn(lowerCAmelCase_		,	self.tokenizer.all_special_ids )
										snake_case__						=				[EN_CODE, 90_37, 3_34_42, 57, 7_52, 1_53, 14, 56, 18, 9, 2]
										snake_case__						=				self.tokenizer.decode(lowerCAmelCase_		,	skip_special_tokens=lowerCAmelCase_ )
										snake_case__						=				self.tokenizer.decode(generated_ids[1:]		,	skip_special_tokens=lowerCAmelCase_ )
										self.assertEqual(lowerCAmelCase_		,	lowerCAmelCase_ )
										self.assertNotIn(self.tokenizer.eos_token		,	lowerCAmelCase_ )
						def A_			(			self ):
										snake_case__						=				["def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])" * 20]
										self.assertIsInstance(src_text[0]		,	lowerCAmelCase_ )
										snake_case__						=				10
										snake_case__						=				self.tokenizer(lowerCAmelCase_		,	max_length=lowerCAmelCase_		,	truncation=lowerCAmelCase_ ).input_ids[0]
										self.assertEqual(ids[-2]		,	2 )
										self.assertEqual(ids[-1]		,	lowerCAmelCase_ )
										self.assertEqual(len(lowerCAmelCase_ )		,	lowerCAmelCase_ )
						def A_			(			self ):
										self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "__java__"] )		,	[5_00_04, 5_00_01] )
						def A_			(			self ):
										snake_case__						=				tempfile.mkdtemp()
										snake_case__						=				self.tokenizer.fairseq_tokens_to_ids
										self.tokenizer.save_pretrained(lowerCAmelCase_ )
										snake_case__						=				PLBartTokenizer.from_pretrained(lowerCAmelCase_ )
										self.assertDictEqual(new_tok.fairseq_tokens_to_ids		,	lowerCAmelCase_ )
						@require_torch
						def A_			(			self ):
										snake_case__						=				self.tokenizer(self.src_text		,	text_target=self.tgt_text		,	padding=lowerCAmelCase_		,	return_tensors="pt" )
										snake_case__						=				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]		,	lowerCAmelCase_ )
										self.assertEqual(batch.decoder_input_ids[1][-1]		,	2 )
										self.assertEqual(batch.labels[1][-2:].tolist()		,	[2, EN_CODE] )
						@require_torch
						def A_			(			self ):
										snake_case__						=				self.tokenizer(
										    self.src_text		,	text_target=self.tgt_text		,	padding=lowerCAmelCase_		,	truncation=lowerCAmelCase_		,	max_length=len(self.expected_src_tokens )		,	return_tensors="pt"		,	)
										snake_case__						=				shift_tokens_right(batch["labels"]		,	self.tokenizer.pad_token_id )

										self.assertIsInstance(lowerCAmelCase_		,	lowerCAmelCase_ )

										self.assertEqual((2, 26)		,	batch.input_ids.shape )
										self.assertEqual((2, 26)		,	batch.attention_mask.shape )
										snake_case__						=				batch.input_ids.tolist()[0]
										self.assertListEqual(self.expected_src_tokens		,	lowerCAmelCase_ )
										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 A_			(			self ):
										snake_case__						=				self.tokenizer(self.src_text		,	padding=lowerCAmelCase_		,	truncation=lowerCAmelCase_		,	max_length=3		,	return_tensors="pt" )
										snake_case__						=				self.tokenizer(
										    text_target=self.tgt_text		,	padding=lowerCAmelCase_		,	truncation=lowerCAmelCase_		,	max_length=10		,	return_tensors="pt" )
										snake_case__						=				targets["input_ids"]
										snake_case__						=				shift_tokens_right(lowerCAmelCase_		,	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 A_			(			self ):
										snake_case__						=				self.tokenizer._build_translation_inputs(
										    "A test"		,	return_tensors="pt"		,	src_lang="en_XX"		,	tgt_lang="java" )

										self.assertEqual(
										    nested_simplify(lowerCAmelCase_ )		,	{
										        # 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,
										    }		,	)





from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame





def 	SCREAMING_SNAKE_CASE__    (      __lowerCAmelCase = "laptop"							):
    snake_case__						=				F"""https://www.amazon.in/laptop/s?k={product}"""
    snake_case__						=				{
        "User-Agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36\n        (KHTML, like Gecko)Chrome/44.0.2403.157 Safari/537.36",
        "Accept-Language": "en-US, en;q=0.5",
    }
    snake_case__						=				BeautifulSoup(requests.get(__lowerCAmelCase    ,		headers=__lowerCAmelCase							).text							)
    # Initialize a Pandas dataframe with the column titles
    snake_case__						=				DataFrame(
        columns=[
            "Product Title",
            "Product Link",
            "Current Price of the product",
            "Product Rating",
            "MRP of the product",
            "Discount",
        ]							)
    # Loop through each entry and store them in the dataframe
    for item, _ in zip_longest(
        soup.find_all(
            "div"    ,		attrs={"class": "s-result-item", "data-component-type": "s-search-result"}    ,		)    ,		soup.find_all("div"    ,		attrs={"class": "a-row a-size-base a-color-base"}							)    ,		):
        try:
            snake_case__						=				item.ha.text
            snake_case__						=				"https://www.amazon.in/" + item.ha.a["href"]
            snake_case__						=				item.find("span"    ,		attrs={"class": "a-offscreen"}							).text
            try:
                snake_case__						=				item.find("span"    ,		attrs={"class": "a-icon-alt"}							).text
            except AttributeError:
                snake_case__						=				"Not available"
            try:
                snake_case__						=				(
                    "₹"
                    + item.find(
                        "span"    ,		attrs={"class": "a-price a-text-price"}							).text.split("₹"							)[1]
                )
            except AttributeError:
                snake_case__						=				""
            try:
                snake_case__						=				float(
                    (
                        (
                            float(product_mrp.strip("₹"							).replace(","    ,		""							)							)
                            - float(product_price.strip("₹"							).replace(","    ,		""							)							)
                        )
                        / float(product_mrp.strip("₹"							).replace(","    ,		""							)							)
                    )
                    * 100							)
            except ValueError:
                snake_case__						=				float("nan"							)
        except AttributeError:
            pass
        snake_case__						=				[
            product_title,
            product_link,
            product_price,
            product_rating,
            product_mrp,
            discount,
        ]
    snake_case__						=				" "
    snake_case__						=				" "
    data_frame.index += 1
    return data_frame


if __name__ == "__main__":
     __magic_name__            =  '''headphones'''
     get_amazon_product_data(product).to_csv(F'''Amazon Product Data for {product}.csv''')



