





import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import FEATURE_EXTRACTOR_NAME, is_vision_available


if is_vision_available():
				from PIL import Image

				from transformers import ChineseCLIPImageProcessor, ChineseCLIPProcessor







@require_vision
class   _UpperCamelCase  (       unittest.TestCase  ):







					'''simple docstring'''

					def        SCREAMING_SNAKE_CASE							(						self    :  List[Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     tempfile.mkdtemp()

						UpperCAmelCase_								=     [
						    """[UNK]""",
						    """[CLS]""",
						    """[SEP]""",
						    """[PAD]""",
						    """[MASK]""",
						    """的""",
						    """价""",
						    """格""",
						    """是""",
						    """15""",
						    """便""",
						    """alex""",
						    """##andra""",
						    """，""",
						    """。""",
						    """-""",
						    """t""",
						    """shirt""",
						]
						UpperCAmelCase_								=     os.path.join(self.tmpdirname ,					VOCAB_FILES_NAMES["""vocab_file"""]		)
						with open(self.vocab_file ,					"""w""" ,					encoding="""utf-8"""		) as vocab_writer:
							vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]		)		)

						UpperCAmelCase_								=     {
						    """do_resize""": True,
						    """size""": {"""height""": 2_24, """width""": 2_24},
						    """do_center_crop""": True,
						    """crop_size""": {"""height""": 18, """width""": 18},
						    """do_normalize""": True,
						    """image_mean""": [0.48145466, 0.4578275, 0.40821073],
						    """image_std""": [0.26862954, 0.26130258, 0.27577711],
						    """do_convert_rgb""": True,
						}
						UpperCAmelCase_								=     os.path.join(self.tmpdirname ,					__lowercase		)
						with open(self.image_processor_file ,					"""w""" ,					encoding="""utf-8"""		) as fp:
							json.dump(__lowercase ,					__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  List[Any] ,					**__lowercase    :  Optional[Any]		):






						'''simple docstring'''







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





					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[Any] ,					**__lowercase    :  Optional[Any]		):






						'''simple docstring'''







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





					def        SCREAMING_SNAKE_CASE							(						self    :  int ,					**__lowercase    :  int		):






						'''simple docstring'''







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





					def        SCREAMING_SNAKE_CASE							(						self    :  Any		):






						'''simple docstring'''







						shutil.rmtree(self.tmpdirname		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[int]		):






						'''simple docstring'''







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

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

						return image_inputs





					def        SCREAMING_SNAKE_CASE							(						self    :  List[Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.get_tokenizer()
						UpperCAmelCase_								=     self.get_rust_tokenizer()
						UpperCAmelCase_								=     self.get_image_processor()

						UpperCAmelCase_								=     ChineseCLIPProcessor(tokenizer=__lowercase ,					image_processor=__lowercase		)
						processor_slow.save_pretrained(self.tmpdirname		)
						UpperCAmelCase_								=     ChineseCLIPProcessor.from_pretrained(self.tmpdirname ,					use_fast=__lowercase		)

						UpperCAmelCase_								=     ChineseCLIPProcessor(tokenizer=__lowercase ,					image_processor=__lowercase		)
						processor_fast.save_pretrained(self.tmpdirname		)
						UpperCAmelCase_								=     ChineseCLIPProcessor.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        SCREAMING_SNAKE_CASE							(						self    :  int		):






						'''simple docstring'''







						UpperCAmelCase_								=     ChineseCLIPProcessor(tokenizer=self.get_tokenizer() ,					image_processor=self.get_image_processor()		)
						processor.save_pretrained(self.tmpdirname		)

						UpperCAmelCase_								=     self.get_tokenizer(cls_token="""(CLS)""" ,					sep_token="""(SEP)"""		)
						UpperCAmelCase_								=     self.get_image_processor(do_normalize=__lowercase		)

						UpperCAmelCase_								=     ChineseCLIPProcessor.from_pretrained(
						    self.tmpdirname ,					cls_token="""(CLS)""" ,					sep_token="""(SEP)""" ,					do_normalize=__lowercase		)

						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        SCREAMING_SNAKE_CASE							(						self    :  Tuple		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.get_image_processor()
						UpperCAmelCase_								=     self.get_tokenizer()

						UpperCAmelCase_								=     ChineseCLIPProcessor(tokenizer=__lowercase ,					image_processor=__lowercase		)

						UpperCAmelCase_								=     self.prepare_image_inputs()

						UpperCAmelCase_								=     image_processor(__lowercase ,					return_tensors="""np"""		)
						UpperCAmelCase_								=     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        SCREAMING_SNAKE_CASE							(						self    :  Optional[Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.get_image_processor()
						UpperCAmelCase_								=     self.get_tokenizer()

						UpperCAmelCase_								=     ChineseCLIPProcessor(tokenizer=__lowercase ,					image_processor=__lowercase		)

						UpperCAmelCase_								=     """Alexandra，T-shirt的价格是15便士。"""

						UpperCAmelCase_								=     processor(text=__lowercase		)

						UpperCAmelCase_								=     tokenizer(__lowercase		)

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





					def        SCREAMING_SNAKE_CASE							(						self    :  str		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.get_image_processor()
						UpperCAmelCase_								=     self.get_tokenizer()

						UpperCAmelCase_								=     ChineseCLIPProcessor(tokenizer=__lowercase ,					image_processor=__lowercase		)

						UpperCAmelCase_								=     """Alexandra，T-shirt的价格是15便士。"""
						UpperCAmelCase_								=     self.prepare_image_inputs()

						UpperCAmelCase_								=     processor(text=__lowercase ,					images=__lowercase		)

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

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





					def        SCREAMING_SNAKE_CASE							(						self    :  List[Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.get_image_processor()
						UpperCAmelCase_								=     self.get_tokenizer()

						UpperCAmelCase_								=     ChineseCLIPProcessor(tokenizer=__lowercase ,					image_processor=__lowercase		)

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

						UpperCAmelCase_								=     processor.batch_decode(__lowercase		)
						UpperCAmelCase_								=     tokenizer.batch_decode(__lowercase		)

						self.assertListEqual(__lowercase ,					__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  List[Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.get_image_processor()
						UpperCAmelCase_								=     self.get_tokenizer()

						UpperCAmelCase_								=     ChineseCLIPProcessor(tokenizer=__lowercase ,					image_processor=__lowercase		)

						UpperCAmelCase_								=     """Alexandra，T-shirt的价格是15便士。"""
						UpperCAmelCase_								=     self.prepare_image_inputs()

						UpperCAmelCase_								=     processor(text=__lowercase ,					images=__lowercase		)

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









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


UpperCamelCase__   : Any					  = logging.get_logger(__name__)

UpperCamelCase__   : int					  = {
    """CarlCochet/trajectory-transformer-halfcheetah-medium-v2""": (
        """https://huggingface.co/CarlCochet/trajectory-transformer-halfcheetah-medium-v2/resolve/main/config.json"""
    ),
    # See all TrajectoryTransformer models at https://huggingface.co/models?filter=trajectory_transformer
}







class   _UpperCamelCase  (       A_  ):







					'''simple docstring'''

					lowerCamelCase     :     Tuple			    =       'trajectory_transformer'
					lowerCamelCase     :     Optional[Any]			    =       ['past_key_values']
					lowerCamelCase     :     Tuple			    =       {
					    'hidden_size': 'n_embd',
					    'num_attention_heads': 'n_head',
					    'num_hidden_layers': 'n_layer',
					}





					def __init__(						self    :  Union[str, Any] ,					__lowercase    :  Optional[Any]=1_00 ,					__lowercase    :  int=5 ,					__lowercase    :  str=1 ,					__lowercase    :  Union[str, Any]=1 ,					__lowercase    :  Optional[Any]=2_49 ,					__lowercase    :  Tuple=6 ,					__lowercase    :  Tuple=17 ,					__lowercase    :  List[str]=25 ,					__lowercase    :  Tuple=4 ,					__lowercase    :  Dict=4 ,					__lowercase    :  int=1_28 ,					__lowercase    :  List[str]=0.1 ,					__lowercase    :  Optional[Any]=0.1 ,					__lowercase    :  Union[str, Any]=0.1 ,					__lowercase    :  Tuple=0.0006 ,					__lowercase    :  Optional[int]=5_12 ,					__lowercase    :  Any=0.02 ,					__lowercase    :  Tuple=1e-12 ,					__lowercase    :  Optional[Any]=1 ,					__lowercase    :  Dict=True ,					__lowercase    :  Optional[Any]=1 ,					__lowercase    :  str=5_02_56 ,					__lowercase    :  Any=5_02_56 ,					**__lowercase    :  str ,					):






						'''simple docstring'''







						UpperCAmelCase_								=     vocab_size
						UpperCAmelCase_								=     action_weight
						UpperCAmelCase_								=     reward_weight
						UpperCAmelCase_								=     value_weight
						UpperCAmelCase_								=     max_position_embeddings
						UpperCAmelCase_								=     block_size
						UpperCAmelCase_								=     action_dim
						UpperCAmelCase_								=     observation_dim
						UpperCAmelCase_								=     transition_dim
						UpperCAmelCase_								=     learning_rate
						UpperCAmelCase_								=     n_layer
						UpperCAmelCase_								=     n_head
						UpperCAmelCase_								=     n_embd
						UpperCAmelCase_								=     embd_pdrop
						UpperCAmelCase_								=     attn_pdrop
						UpperCAmelCase_								=     resid_pdrop
						UpperCAmelCase_								=     initializer_range
						UpperCAmelCase_								=     layer_norm_eps
						UpperCAmelCase_								=     kaiming_initializer_range
						UpperCAmelCase_								=     use_cache
						super().__init__(pad_token_id=__lowercase ,					bos_token_id=__lowercase ,					eos_token_id=__lowercase ,					**__lowercase		)


