






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      lowercase__     (			unittest.TestCase	):

	def 		UpperCAmelCase  (							self       )->					List[Any]:







							'''simple docstring'''





							lowerCAmelCase__       =						tempfile.mkdtemp()

							# 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       )       )

							lowerCAmelCase__       =						{
							    "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__       =						os.path.join(self.tmpdirname		,    __UpperCAmelCase       )
							with open(self.image_processor_file		,    "w"		,    encoding="utf-8"       ) as fp:
													json.dump(__UpperCAmelCase		,    __UpperCAmelCase       )

	def 		UpperCAmelCase  (							self		,    **__UpperCAmelCase       )->					Optional[Any]:







							'''simple docstring'''





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

	def 		UpperCAmelCase  (							self		,    **__UpperCAmelCase       )->					List[Any]:







							'''simple docstring'''





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

	def 		UpperCAmelCase  (							self		,    **__UpperCAmelCase       )->					List[str]:







							'''simple docstring'''





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

	def 		UpperCAmelCase  (							self       )->					List[Any]:







							'''simple docstring'''





							shutil.rmtree(self.tmpdirname       )

	def 		UpperCAmelCase  (							self       )->					Optional[Any]:







							'''simple docstring'''





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

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

							return image_inputs

	def 		UpperCAmelCase  (							self       )->					List[Any]:







							'''simple docstring'''





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

							lowerCAmelCase__       =						CLIPSegProcessor(tokenizer=__UpperCAmelCase		,    image_processor=__UpperCAmelCase       )
							processor_slow.save_pretrained(self.tmpdirname       )
							lowerCAmelCase__       =						CLIPSegProcessor.from_pretrained(self.tmpdirname		,    use_fast=__UpperCAmelCase       )

							lowerCAmelCase__       =						CLIPSegProcessor(tokenizer=__UpperCAmelCase		,    image_processor=__UpperCAmelCase       )
							processor_fast.save_pretrained(self.tmpdirname       )
							lowerCAmelCase__       =						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		,    __UpperCAmelCase       )
							self.assertIsInstance(processor_fast.tokenizer		,    __UpperCAmelCase       )

							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		,    __UpperCAmelCase       )
							self.assertIsInstance(processor_fast.image_processor		,    __UpperCAmelCase       )

	def 		UpperCAmelCase  (							self       )->					Union[str, Any]:







							'''simple docstring'''





							lowerCAmelCase__       =						CLIPSegProcessor(tokenizer=self.get_tokenizer()		,    image_processor=self.get_image_processor()       )
							processor.save_pretrained(self.tmpdirname       )

							lowerCAmelCase__       =						self.get_tokenizer(bos_token="(BOS)"		,    eos_token="(EOS)"       )
							lowerCAmelCase__       =						self.get_image_processor(do_normalize=__UpperCAmelCase		,    padding_value=1.0       )

							lowerCAmelCase__       =						CLIPSegProcessor.from_pretrained(
							    self.tmpdirname		,    bos_token="(BOS)"		,    eos_token="(EOS)"		,    do_normalize=__UpperCAmelCase		,    padding_value=1.0       )

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

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

	def 		UpperCAmelCase  (							self       )->					Optional[Any]:







							'''simple docstring'''





							lowerCAmelCase__       =						self.get_image_processor()
							lowerCAmelCase__       =						self.get_tokenizer()

							lowerCAmelCase__       =						CLIPSegProcessor(tokenizer=__UpperCAmelCase		,    image_processor=__UpperCAmelCase       )

							lowerCAmelCase__       =						self.prepare_image_inputs()

							lowerCAmelCase__       =						image_processor(__UpperCAmelCase		,    return_tensors="np"       )
							lowerCAmelCase__       =						processor(images=__UpperCAmelCase		,    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 		UpperCAmelCase  (							self       )->					str:







							'''simple docstring'''





							lowerCAmelCase__       =						self.get_image_processor()
							lowerCAmelCase__       =						self.get_tokenizer()

							lowerCAmelCase__       =						CLIPSegProcessor(tokenizer=__UpperCAmelCase		,    image_processor=__UpperCAmelCase       )

							lowerCAmelCase__       =						"lower newer"

							lowerCAmelCase__       =						processor(text=__UpperCAmelCase       )

							lowerCAmelCase__       =						tokenizer(__UpperCAmelCase       )

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

	def 		UpperCAmelCase  (							self       )->					str:







							'''simple docstring'''





							lowerCAmelCase__       =						self.get_image_processor()
							lowerCAmelCase__       =						self.get_tokenizer()

							lowerCAmelCase__       =						CLIPSegProcessor(tokenizer=__UpperCAmelCase		,    image_processor=__UpperCAmelCase       )

							lowerCAmelCase__       =						"lower newer"
							lowerCAmelCase__       =						self.prepare_image_inputs()

							lowerCAmelCase__       =						processor(text=__UpperCAmelCase		,    images=__UpperCAmelCase       )

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

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

	def 		UpperCAmelCase  (							self       )->					Optional[Any]:







							'''simple docstring'''





							lowerCAmelCase__       =						self.get_image_processor()
							lowerCAmelCase__       =						self.get_tokenizer()

							lowerCAmelCase__       =						CLIPSegProcessor(tokenizer=__UpperCAmelCase		,    image_processor=__UpperCAmelCase       )

							lowerCAmelCase__       =						self.prepare_image_inputs()
							lowerCAmelCase__       =						self.prepare_image_inputs()

							lowerCAmelCase__       =						processor(images=__UpperCAmelCase		,    visual_prompt=__UpperCAmelCase       )

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

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


	def 		UpperCAmelCase  (							self       )->					List[Any]:







							'''simple docstring'''





							lowerCAmelCase__       =						self.get_image_processor()
							lowerCAmelCase__       =						self.get_tokenizer()

							lowerCAmelCase__       =						CLIPSegProcessor(tokenizer=__UpperCAmelCase		,    image_processor=__UpperCAmelCase       )

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

							lowerCAmelCase__       =						processor.batch_decode(__UpperCAmelCase       )
							lowerCAmelCase__       =						tokenizer.batch_decode(__UpperCAmelCase       )

							self.assertListEqual(__UpperCAmelCase		,    __UpperCAmelCase       )














import json
import logging
import os
import sys
from time import time
from unittest.mock import patch

from transformers.testing_utils import TestCasePlus, require_torch_tpu


logging.basicConfig(level=logging.DEBUG)

a_							=    logging.getLogger()


def        _a  (     UpperCamelCase_					:				Union[str, Any]   ) ->   Dict:
						"""simple docstring"""







						lowerCAmelCase__       =						{}
						lowerCAmelCase__       =						os.path.join(UpperCamelCase_    ,   "all_results.json"   )
						if os.path.exists(UpperCamelCase_   ):
												with open(UpperCamelCase_    ,   "r"   ) as f:
																		lowerCAmelCase__       =						json.load(UpperCamelCase_   )
						else:
												raise ValueError(F"can't find {path}"   )
						return results


a_							=    logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)





@require_torch_tpu
class      lowercase__     (			_UpperCAmelCase	):

	def 		UpperCAmelCase  (							self       )->					Optional[Any]:







							'''simple docstring'''





							import xla_spawn

							lowerCAmelCase__       =						self.get_auto_remove_tmp_dir()
							lowerCAmelCase__       =						F"\n            ./examples/pytorch/text-classification/run_glue.py\n            --num_cores=8\n            ./examples/pytorch/text-classification/run_glue.py\n            --model_name_or_path distilbert-base-uncased\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv\n            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv\n            --do_train\n            --do_eval\n            --debug tpu_metrics_debug\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --learning_rate=1e-4\n            --max_steps=10\n            --warmup_steps=2\n            --seed=42\n            --max_seq_length=128\n            ".split()

							with patch.object(__UpperCAmelCase		,    "argv"		,    __UpperCAmelCase       ):
													lowerCAmelCase__       =						time()
													xla_spawn.main()
													lowerCAmelCase__       =						time()

													lowerCAmelCase__       =						get_results(__UpperCAmelCase       )
													self.assertGreaterEqual(result["eval_accuracy"]		,    0.75       )

													# Assert that the script takes less than 500 seconds to make sure it doesn't hang.
													self.assertLess(end - start		,    500       )


	def 		UpperCAmelCase  (							self       )->					Dict:







							'''simple docstring'''





							import xla_spawn

							lowerCAmelCase__       =						"\n            ./tests/test_trainer_tpu.py\n            --num_cores=8\n            ./tests/test_trainer_tpu.py\n            ".split()
							with patch.object(__UpperCAmelCase		,    "argv"		,    __UpperCAmelCase       ):
													xla_spawn.main()






