



import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
						from PIL import Image

						from transformers import CLIPSegProcessor, ViTImageProcessor



@require_vision
class   UpperCAmelCase_    (       unittest.TestCase):







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							int    =    tempfile.mkdtemp()

														# fmt: off
														_lowerCAmelCase     :							int    =    ['''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     :							Tuple    =    dict(zip(__lowercase,			range(len(__lowercase))))
														_lowerCAmelCase     :							List[Any]    =    ['''#version: 0.2''', '''l o''', '''lo w</w>''', '''e r</w>''', '''''']
														_lowerCAmelCase     :							Optional[Any]    =    {'''unk_token''': '''<unk>'''}

														_lowerCAmelCase     :							List[str]    =    os.path.join(self.tmpdirname,			VOCAB_FILES_NAMES["vocab_file"])
														_lowerCAmelCase     :							List[Any]    =    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(__lowercase) + "\n")
														with open(self.merges_file,			"w",			encoding="utf-8") as fp:
																					fp.write("\n".join(__lowercase))

														_lowerCAmelCase     :							List[str]    =    {
														    '''do_resize''': True,
														    '''size''': 20,
														    '''do_center_crop''': True,
														    '''crop_size''': 18,
														    '''do_normalize''': True,
														    '''image_mean''': [0.48_145_466, 0.4_578_275, 0.40_821_073],
														    '''image_std''': [0.26_862_954, 0.26_130_258, 0.27_577_711],
														}
														_lowerCAmelCase     :							Any    =    os.path.join(self.tmpdirname,			__lowercase)
														with open(self.image_processor_file,			"w",			encoding="utf-8") as fp:
																					json.dump(__lowercase,			__lowercase)







							def    snake_case__      (   self,			**__a):

														'''simple docstring'''

														return CLIPTokenizer.from_pretrained(self.tmpdirname,			**__lowercase)







							def    snake_case__      (   self,			**__a):

														'''simple docstring'''

														return CLIPTokenizerFast.from_pretrained(self.tmpdirname,			**__lowercase)







							def    snake_case__      (   self,			**__a):

														'''simple docstring'''

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







							def    snake_case__      (   self):

														'''simple docstring'''

														shutil.rmtree(self.tmpdirname)







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							Dict    =    [np.random.randint(255,			size=(3, 30, 400),			dtype=np.uinta)]

														_lowerCAmelCase     :							int    =    [Image.fromarray(np.moveaxis(__lowercase,			0,			-1)) for x in image_inputs]

														return image_inputs







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							Dict    =    self.get_tokenizer()
														_lowerCAmelCase     :							str    =    self.get_rust_tokenizer()
														_lowerCAmelCase     :							Optional[Any]    =    self.get_image_processor()

														_lowerCAmelCase     :							List[Any]    =    CLIPSegProcessor(tokenizer=__lowercase,			image_processor=__lowercase)
														processor_slow.save_pretrained(self.tmpdirname)
														_lowerCAmelCase     :							Optional[int]    =    CLIPSegProcessor.from_pretrained(self.tmpdirname,			use_fast=__lowercase)

														_lowerCAmelCase     :							Union[str, Any]    =    CLIPSegProcessor(tokenizer=__lowercase,			image_processor=__lowercase)
														processor_fast.save_pretrained(self.tmpdirname)
														_lowerCAmelCase     :							Dict    =    CLIPSegProcessor.from_pretrained(self.tmpdirname)

														self.assertEqual(processor_slow.tokenizer.get_vocab(),			tokenizer_slow.get_vocab())
														self.assertEqual(processor_fast.tokenizer.get_vocab(),			tokenizer_fast.get_vocab())
														self.assertEqual(tokenizer_slow.get_vocab(),			tokenizer_fast.get_vocab())
														self.assertIsInstance(processor_slow.tokenizer,			__lowercase)
														self.assertIsInstance(processor_fast.tokenizer,			__lowercase)

														self.assertEqual(processor_slow.image_processor.to_json_string(),			image_processor.to_json_string())
														self.assertEqual(processor_fast.image_processor.to_json_string(),			image_processor.to_json_string())
														self.assertIsInstance(processor_slow.image_processor,			__lowercase)
														self.assertIsInstance(processor_fast.image_processor,			__lowercase)







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							Dict    =    CLIPSegProcessor(tokenizer=self.get_tokenizer(),			image_processor=self.get_image_processor())
														processor.save_pretrained(self.tmpdirname)

														_lowerCAmelCase     :							int    =    self.get_tokenizer(bos_token="(BOS)",			eos_token="(EOS)")
														_lowerCAmelCase     :							List[Any]    =    self.get_image_processor(do_normalize=__lowercase,			padding_value=1.0)

														_lowerCAmelCase     :							Optional[Any]    =    CLIPSegProcessor.from_pretrained(
														    self.tmpdirname,			bos_token="(BOS)",			eos_token="(EOS)",			do_normalize=__lowercase,			padding_value=1.0)

														self.assertEqual(processor.tokenizer.get_vocab(),			tokenizer_add_kwargs.get_vocab())
														self.assertIsInstance(processor.tokenizer,			__lowercase)

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







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							Optional[int]    =    self.get_image_processor()
														_lowerCAmelCase     :							Optional[Any]    =    self.get_tokenizer()

														_lowerCAmelCase     :							Dict    =    CLIPSegProcessor(tokenizer=__lowercase,			image_processor=__lowercase)

														_lowerCAmelCase     :							Dict    =    self.prepare_image_inputs()

														_lowerCAmelCase     :							Union[str, Any]    =    image_processor(__lowercase,			return_tensors="np")
														_lowerCAmelCase     :							str    =    processor(images=__lowercase,			return_tensors="np")

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







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							Tuple    =    self.get_image_processor()
														_lowerCAmelCase     :							Dict    =    self.get_tokenizer()

														_lowerCAmelCase     :							str    =    CLIPSegProcessor(tokenizer=__lowercase,			image_processor=__lowercase)

														_lowerCAmelCase     :							Tuple    =    '''lower newer'''

														_lowerCAmelCase     :							str    =    processor(text=__lowercase)

														_lowerCAmelCase     :							Optional[Any]    =    tokenizer(__lowercase)

														for key in encoded_tok.keys():
																					self.assertListEqual(encoded_tok[key],			encoded_processor[key])







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							str    =    self.get_image_processor()
														_lowerCAmelCase     :							Tuple    =    self.get_tokenizer()

														_lowerCAmelCase     :							Optional[Any]    =    CLIPSegProcessor(tokenizer=__lowercase,			image_processor=__lowercase)

														_lowerCAmelCase     :							Optional[int]    =    '''lower newer'''
														_lowerCAmelCase     :							str    =    self.prepare_image_inputs()

														_lowerCAmelCase     :							Any    =    processor(text=__lowercase,			images=__lowercase)

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

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







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							str    =    self.get_image_processor()
														_lowerCAmelCase     :							Tuple    =    self.get_tokenizer()

														_lowerCAmelCase     :							List[Any]    =    CLIPSegProcessor(tokenizer=__lowercase,			image_processor=__lowercase)

														_lowerCAmelCase     :							Optional[Any]    =    self.prepare_image_inputs()
														_lowerCAmelCase     :							Optional[Any]    =    self.prepare_image_inputs()

														_lowerCAmelCase     :							List[Any]    =    processor(images=__lowercase,			visual_prompt=__lowercase)

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

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







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							Optional[Any]    =    self.get_image_processor()
														_lowerCAmelCase     :							List[str]    =    self.get_tokenizer()

														_lowerCAmelCase     :							Optional[Any]    =    CLIPSegProcessor(tokenizer=__lowercase,			image_processor=__lowercase)

														_lowerCAmelCase     :							int    =    [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

														_lowerCAmelCase     :							Optional[Any]    =    processor.batch_decode(__lowercase)
														_lowerCAmelCase     :							Any    =    tokenizer.batch_decode(__lowercase)

														self.assertListEqual(__lowercase,			__lowercase)

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowercase							 =					logging.get_logger(__name__)

__lowercase							 =					{'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}


class 	lowerCamelCase_     (   UpperCAmelCase_ ):






    '''simple docstring'''






    a__	:						str						=      """ctrl"""
    a__	:						Dict						=      ["""past_key_values"""]
    a__	:						Tuple						=      {
        """max_position_embeddings""": """n_positions""",
        """hidden_size""": """n_embd""",
        """num_attention_heads""": """n_head""",
        """num_hidden_layers""": """n_layer""",
    }







    def __init__(	self , __lowercase=246_534 , __lowercase=256 , __lowercase=1_280 , __lowercase=8_192 , __lowercase=48 , __lowercase=16 , __lowercase=0.1 , __lowercase=0.1 , __lowercase=1E-6 , __lowercase=0.02 , __lowercase=True , **__lowercase , )       ->	List[Any]:
        __UpperCamelCase     :List[str]			  =		vocab_size
        __UpperCamelCase     :Optional[Any]			  =		n_positions
        __UpperCamelCase     :Dict			  =		n_embd
        __UpperCamelCase     :Dict			  =		n_layer
        __UpperCamelCase     :List[Any]			  =		n_head
        __UpperCamelCase     :int			  =		dff
        __UpperCamelCase     :Union[str, Any]			  =		resid_pdrop
        __UpperCamelCase     :Optional[int]			  =		embd_pdrop
        __UpperCamelCase     :List[Any]			  =		layer_norm_epsilon
        __UpperCamelCase     :Dict			  =		initializer_range

        __UpperCamelCase     :Any			  =		use_cache

        super().__init__(**__lowercase)





