
import mpmath  # for roots of unity
import numpy as np





class 	_lowerCAmelCase					:




				def __init__(					self				,				_UpperCamelCase=None				,				_UpperCamelCase=None     )				->      Optional[int]:
							# Input as list
							lowerCAmelCase_						=	list(poly_a or [0]     )[:]
							lowerCAmelCase_						=	list(poly_b or [0]     )[:]

							# Remove leading zero coefficients
							while self.polyA[-1] == 0:
										self.polyA.pop()
							lowerCAmelCase_						=	len(self.polyA     )

							while self.polyB[-1] == 0:
										self.polyB.pop()
							lowerCAmelCase_						=	len(self.polyB     )

							# Add 0 to make lengths equal a power of 2
							lowerCAmelCase_						=	int(
							    2 ** np.ceil(np.loga(len(self.polyA     ) + len(self.polyB     ) - 1     )     )     )

							while len(self.polyA     ) < self.c_max_length:
										self.polyA.append(0     )
							while len(self.polyB     ) < self.c_max_length:
										self.polyB.append(0     )
							# A complex root used for the fourier transform
							lowerCAmelCase_						=	complex(mpmath.root(x=1				,				n=self.c_max_length				,				k=1     )     )

							# The product
							lowerCAmelCase_						=	self.__multiply()




				def      __a						(					self				,				_UpperCamelCase     )				->      Optional[int]:
							lowerCAmelCase_						=	[[x] for x in self.polyA] if which == "A" else [[x] for x in self.polyB]
							# Corner case
							if len(_UpperCamelCase     ) <= 1:
										return dft[0]
							#
							lowerCAmelCase_						=	self.c_max_length // 2
							while next_ncol > 0:
										lowerCAmelCase_						=	[[] for i in range(_UpperCamelCase     )]
										lowerCAmelCase_						=	self.root**next_ncol

										# First half of next step
										lowerCAmelCase_						=	1
										for j in range(self.c_max_length // (next_ncol * 2)     ):
													for i in range(_UpperCamelCase     ):
																new_dft[i].append(dft[i][j] + current_root * dft[i + next_ncol][j]     )
													current_root *= root
										# Second half of next step
										lowerCAmelCase_						=	1
										for j in range(self.c_max_length // (next_ncol * 2)     ):
													for i in range(_UpperCamelCase     ):
																new_dft[i].append(dft[i][j] - current_root * dft[i + next_ncol][j]     )
													current_root *= root
										# Update
										lowerCAmelCase_						=	new_dft
										lowerCAmelCase_						=	next_ncol // 2
							return dft[0]




				def      __a						(					self     )				->      Any:
							lowerCAmelCase_						=	self.__dft("A"     )
							lowerCAmelCase_						=	self.__dft("B"     )
							lowerCAmelCase_						=	[[dft_a[i] * dft_b[i] for i in range(self.c_max_length     )]]
							del dft_a
							del dft_b

							# Corner Case
							if len(inverce_c[0]     ) <= 1:
										return inverce_c[0]
							# Inverse DFT
							lowerCAmelCase_						=	2
							while next_ncol <= self.c_max_length:
										lowerCAmelCase_						=	[[] for i in range(_UpperCamelCase     )]
										lowerCAmelCase_						=	self.root ** (next_ncol // 2)
										lowerCAmelCase_						=	1
										# First half of next step
										for j in range(self.c_max_length // next_ncol     ):
													for i in range(next_ncol // 2     ):
																# Even positions
																new_inverse_c[i].append(
																    (
																        inverce_c[i][j]
																        + inverce_c[i][j + self.c_max_length // next_ncol]
																    )
																    / 2     )
																# Odd positions
																new_inverse_c[i + next_ncol // 2].append(
																    (
																        inverce_c[i][j]
																        - inverce_c[i][j + self.c_max_length // next_ncol]
																    )
																    / (2 * current_root)     )
													current_root *= root
										# Update
										lowerCAmelCase_						=	new_inverse_c
										next_ncol *= 2
							# Unpack
							lowerCAmelCase_						=	[round(x[0].real				,				8     ) + round(x[0].imag				,				8     ) * 1j for x in inverce_c]

							# Remove leading 0's
							while inverce_c[-1] == 0:
										inverce_c.pop()
							return inverce_c




				def __str__(					self     )				->      str:
							lowerCAmelCase_						=	"A = " + " + ".join(
							    f"""{coef}*x^{i}""" for coef, i in enumerate(self.polyA[: self.len_A]     )     )
							lowerCAmelCase_						=	"B = " + " + ".join(
							    f"""{coef}*x^{i}""" for coef, i in enumerate(self.polyB[: self.len_B]     )     )
							lowerCAmelCase_						=	"A*B = " + " + ".join(
							    f"""{coef}*x^{i}""" for coef, i in enumerate(self.product     )     )

							return f"""{a}\n{b}\n{c}"""


# Unit tests
if __name__ == "__main__":
			import doctest

			doctest.testmod()





import json
import os
import unittest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class 	_lowerCAmelCase					(	__a					,      unittest.TestCase       ):
				_lowercase					=CLIPTokenizer
				_lowercase					=CLIPTokenizerFast
				_lowercase					=True
				_lowercase					={}
				_lowercase					=False




				def      __a						(					self     )				->      Dict:
							super().setUp()

							# fmt: off
							lowerCAmelCase_						=	["l", "o", "w", "e", "r", "s", "t", "i", "d", "n", "lo", "l</w>", "w</w>", "r</w>", "t</w>", "low</w>", "er</w>", "lowest</w>", "newer</w>", "wider", "<unk>", "<|startoftext|>", "<|endoftext|>"]
							# fmt: on
							lowerCAmelCase_						=	dict(zip(_UpperCamelCase				,				range(len(_UpperCamelCase     )     )     )     )
							lowerCAmelCase_						=	["#version: 0.2", "l o", "lo w</w>", "e r</w>"]
							lowerCAmelCase_						=	{"unk_token": "<unk>"}

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




				def      __a						(					self				,				**_UpperCamelCase     )				->      Any:
							kwargs.update(self.special_tokens_map     )
							return CLIPTokenizer.from_pretrained(self.tmpdirname				,				**_UpperCamelCase     )




				def      __a						(					self				,				**_UpperCamelCase     )				->      int:
							kwargs.update(self.special_tokens_map     )
							return CLIPTokenizerFast.from_pretrained(self.tmpdirname				,				**_UpperCamelCase     )




				def      __a						(					self				,				_UpperCamelCase     )				->      List[str]:
							lowerCAmelCase_						=	"lower newer"
							lowerCAmelCase_						=	"lower newer"
							return input_text, output_text




				def      __a						(					self     )				->      List[Any]:
							lowerCAmelCase_						=	CLIPTokenizer(self.vocab_file				,				self.merges_file				,				**self.special_tokens_map     )
							lowerCAmelCase_						=	"lower newer"
							lowerCAmelCase_						=	["lo", "w", "er</w>", "n", "e", "w", "er</w>"]
							lowerCAmelCase_						=	tokenizer.tokenize(_UpperCamelCase     )
							self.assertListEqual(_UpperCamelCase				,				_UpperCamelCase     )

							lowerCAmelCase_						=	tokens + [tokenizer.unk_token]
							lowerCAmelCase_						=	[10, 2, 16, 9, 3, 2, 16, 20]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCamelCase     )				,				_UpperCamelCase     )




				@require_ftfy
				def      __a						(					self     )				->      Union[str, Any]:
							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
										with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""     ):
													lowerCAmelCase_						=	self.tokenizer_class.from_pretrained(_UpperCamelCase				,				**_UpperCamelCase     )
													lowerCAmelCase_						=	self.rust_tokenizer_class.from_pretrained(_UpperCamelCase				,				**_UpperCamelCase     )

													lowerCAmelCase_						=	"A\n'll 11p223RF☆ho!!to?'d'd''d of a cat to-$''d."
													lowerCAmelCase_						=	tokenizer_s.tokenize(_UpperCamelCase     )
													lowerCAmelCase_						=	tokenizer_r.tokenize(_UpperCamelCase     )

													self.assertListEqual(_UpperCamelCase				,				_UpperCamelCase     )

													# Test that the tokenization is identical on an example containing a character (Latin Small Letter A
													# with Tilde) encoded in 2 different ways
													lowerCAmelCase_						=	"xa\u0303y" + " " + "x\xe3y"
													lowerCAmelCase_						=	tokenizer_s.tokenize(_UpperCamelCase     )
													lowerCAmelCase_						=	tokenizer_r.tokenize(_UpperCamelCase     )

													self.assertListEqual(_UpperCamelCase				,				_UpperCamelCase     )

													# Test that the tokenization is identical on unicode of space type
													lowerCAmelCase_						=	[
													    "\u0009",  # (horizontal tab, '\t')
													    "\u000B",  # (vertical tab)
													    "\u000C",  # (form feed)
													    "\u0020",  # (space, ' ')
													    "\u200E",  # (left-to-right mark):w
													    "\u200F",  # (right-to-left mark)
													]
													for unicode_seq in spaces_unicodes:
																lowerCAmelCase_						=	tokenizer_s.tokenize(_UpperCamelCase     )
																lowerCAmelCase_						=	tokenizer_r.tokenize(_UpperCamelCase     )

																self.assertListEqual(_UpperCamelCase				,				_UpperCamelCase     )

													# Test that the tokenization is identical on unicode of line break type
													lowerCAmelCase_						=	[
													    "\u000A",  # (line feed, '\n')
													    "\r\n",  # (carriage return and line feed, '\r\n')
													    "\u000D",  # (carriage return, '\r')
													    "\r",  # (carriage return, '\r')
													    "\u000D",  # (carriage return, '\r')
													    "\u2028",  # (line separator)
													    "\u2029",  # (paragraph separator)
													    # "\u0085", # (next line)
													]

													# The tokenization is not identical for the character "\u0085" (next line). The slow version using ftfy transforms
													# it into the Horizontal Ellipsis character "…" ("\u2026") while the fast version transforms it into a
													# space (and thus into an empty list).

													for unicode_seq in line_break_unicodes:
																lowerCAmelCase_						=	tokenizer_s.tokenize(_UpperCamelCase     )
																lowerCAmelCase_						=	tokenizer_r.tokenize(_UpperCamelCase     )

																self.assertListEqual(_UpperCamelCase				,				_UpperCamelCase     )




				def      __a						(					self     )				->      str:
							# Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space`
							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
										with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""     ):
													lowerCAmelCase_						=	"hello"  # `hello` is a token in the vocabulary of `pretrained_name`
													lowerCAmelCase_						=	f"""{text_of_1_token} {text_of_1_token}"""

													lowerCAmelCase_						=	self.rust_tokenizer_class.from_pretrained(
													    _UpperCamelCase				,				use_fast=_UpperCamelCase				,				)
													lowerCAmelCase_						=	tokenizer_r(_UpperCamelCase				,				return_offsets_mapping=_UpperCamelCase				,				add_special_tokens=_UpperCamelCase     )
													self.assertEqual(encoding.offset_mapping[0]				,				(0, len(_UpperCamelCase     ))     )
													self.assertEqual(
													    encoding.offset_mapping[1]				,				(len(_UpperCamelCase     ) + 1, len(_UpperCamelCase     ) + 1 + len(_UpperCamelCase     ))				,				)

													lowerCAmelCase_						=	f""" {text}"""

													lowerCAmelCase_						=	self.rust_tokenizer_class.from_pretrained(
													    _UpperCamelCase				,				use_fast=_UpperCamelCase				,				)
													lowerCAmelCase_						=	tokenizer_r(_UpperCamelCase				,				return_offsets_mapping=_UpperCamelCase				,				add_special_tokens=_UpperCamelCase     )
													self.assertEqual(encoding.offset_mapping[0]				,				(1, 1 + len(_UpperCamelCase     ))     )
													self.assertEqual(
													    encoding.offset_mapping[1]				,				(1 + len(_UpperCamelCase     ) + 1, 1 + len(_UpperCamelCase     ) + 1 + len(_UpperCamelCase     ))				,				)




				def      __a						(					self     )				->      Optional[Any]:
							# Test related to the breaking change introduced in transformers v4.17.0
							# We need to check that an error in raised when the user try to load a previous version of the tokenizer.
							with self.assertRaises(_UpperCamelCase     ) as context:
										self.rust_tokenizer_class.from_pretrained("robot-test/old-clip-tokenizer"     )

							self.assertTrue(
							    context.exception.args[0].startswith(
							        "The `backend_tokenizer` provided does not match the expected format."     )     )




				@require_ftfy
				def      __a						(					self     )				->      str:
							super().test_tokenization_python_rust_equals()




				def      __a						(					self     )				->      Any:
							# CLIP always lower cases letters
							pass



