





'''simple docstring'''






from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments






def      __A						(							):
  lowerCAmelCase     :    Any						=   HfArgumentParser(A_	)
  lowerCAmelCase     :    Dict						=   parser.parse_args_into_dataclasses()[0]
  lowerCAmelCase     :    Any						=   TensorFlowBenchmark(args=A_	)
  try:
    lowerCAmelCase     :    List[Any]						=   parser.parse_args_into_dataclasses()[0]
  except ValueError as e:
    lowerCAmelCase     :    str						=   "Arg --no_{0} is no longer used, please use --no-{0} instead."
    lowerCAmelCase     :    Tuple						=   " ".join(str(A_	).split(" "	)[:-1]	)
    lowerCAmelCase     :    List[str]						=   ""
    lowerCAmelCase     :    List[str]						=   eval(str(A_	).split(" "	)[-1]	)
    lowerCAmelCase     :    Dict						=   []
    for arg in depreciated_args:
      # arg[2:] removes '--'
      if arg[2:] in TensorFlowBenchmark.deprecated_args:
        # arg[5:] removes '--no_'
        full_error_msg += arg_error_msg.format(arg[5:]	)
      else:
        wrong_args.append(A_	)
    if len(A_	) > 0:
      lowerCAmelCase     :    List[Any]						=   full_error_msg + begin_error_msg + str(A_	)
    raise ValueError(A_	)
  benchmark.run()


if __name__ == "__main__":
     main()










'''simple docstring'''






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 OwlViTImageProcessor, OwlViTProcessor
@require_vision
class 		lowerCamelCase  (      unittest.TestCase       ):



	def   _lowerCamelCase    (   self	):
			lowerCAmelCase     :    Tuple						=   tempfile.mkdtemp()

			# fmt: off
			lowerCAmelCase     :    List[Any]						=   ["", "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						=   dict(zip(a_		,      range(len(a_	)	)	)	)
			lowerCAmelCase     :    List[str]						=   ["#version: 0.2", "l o", "lo w</w>", "e r</w>", ""]
			lowerCAmelCase     :    List[Any]						=   {"unk_token": "<unk>"}

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

			lowerCAmelCase     :    Dict						=   {
			    "do_resize": True,
			    "size": 20,
			    "do_center_crop": True,
			    "crop_size": 18,
			    "do_normalize": True,
			    "image_mean": [0.48145466, 0.4578275, 0.40821073],
			    "image_std": [0.26862954, 0.26130258, 0.27577711],
			}
			lowerCAmelCase     :    int						=   os.path.join(self.tmpdirname		,      a_	)
			with open(self.image_processor_file		,      "w"		,      encoding="utf-8"	) as fp:
					json.dump(a_		,      a_	)



	def   _lowerCamelCase    (   self		,      **a_	):
			return CLIPTokenizer.from_pretrained(self.tmpdirname		,      pad_token="!"		,      **a_	)



	def   _lowerCamelCase    (   self		,      **a_	):
			return CLIPTokenizerFast.from_pretrained(self.tmpdirname		,      pad_token="!"		,      **a_	)



	def   _lowerCamelCase    (   self		,      **a_	):
			return OwlViTImageProcessor.from_pretrained(self.tmpdirname		,      **a_	)



	def   _lowerCamelCase    (   self	):
			shutil.rmtree(self.tmpdirname	)



	def   _lowerCamelCase    (   self	):
			lowerCAmelCase     :    str						=   [np.random.randint(255		,      size=(3, 30, 400)		,      dtype=np.uinta	)]

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

			return image_inputs



	def   _lowerCamelCase    (   self	):
			lowerCAmelCase     :    Optional[Any]						=   self.get_tokenizer()
			lowerCAmelCase     :    Union[str, Any]						=   self.get_rust_tokenizer()
			lowerCAmelCase     :    Optional[int]						=   self.get_image_processor()

			lowerCAmelCase     :    Optional[int]						=   OwlViTProcessor(tokenizer=a_		,      image_processor=a_	)
			processor_slow.save_pretrained(self.tmpdirname	)
			lowerCAmelCase     :    Optional[Any]						=   OwlViTProcessor.from_pretrained(self.tmpdirname		,      use_fast=a_	)

			lowerCAmelCase     :    int						=   OwlViTProcessor(tokenizer=a_		,      image_processor=a_	)
			processor_fast.save_pretrained(self.tmpdirname	)
			lowerCAmelCase     :    List[Any]						=   OwlViTProcessor.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		,      a_	)
			self.assertIsInstance(processor_fast.tokenizer		,      a_	)

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



	def   _lowerCamelCase    (   self	):
			lowerCAmelCase     :    Dict						=   OwlViTProcessor(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     :    Dict						=   self.get_image_processor(do_normalize=a_	)

			lowerCAmelCase     :    Optional[int]						=   OwlViTProcessor.from_pretrained(
			    self.tmpdirname		,      bos_token="(BOS)"		,      eos_token="(EOS)"		,      do_normalize=a_	)

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

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



	def   _lowerCamelCase    (   self	):
			lowerCAmelCase     :    Tuple						=   self.get_image_processor()
			lowerCAmelCase     :    Optional[int]						=   self.get_tokenizer()

			lowerCAmelCase     :    str						=   OwlViTProcessor(tokenizer=a_		,      image_processor=a_	)

			lowerCAmelCase     :    Optional[int]						=   self.prepare_image_inputs()

			lowerCAmelCase     :    List[str]						=   image_processor(a_		,      return_tensors="np"	)
			lowerCAmelCase     :    Any						=   processor(images=a_		,      return_tensors="np"	)

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



	def   _lowerCamelCase    (   self	):
			lowerCAmelCase     :    Dict						=   self.get_image_processor()
			lowerCAmelCase     :    List[str]						=   self.get_tokenizer()

			lowerCAmelCase     :    int						=   OwlViTProcessor(tokenizer=a_		,      image_processor=a_	)

			lowerCAmelCase     :    Tuple						=   "lower newer"

			lowerCAmelCase     :    int						=   processor(text=a_		,      return_tensors="np"	)

			lowerCAmelCase     :    Tuple						=   tokenizer(a_		,      return_tensors="np"	)

			for key in encoded_tok.keys():
					self.assertListEqual(encoded_tok[key][0].tolist()		,      encoded_processor[key][0].tolist()	)



	def   _lowerCamelCase    (   self	):
			lowerCAmelCase     :    str						=   self.get_image_processor()
			lowerCAmelCase     :    int						=   self.get_tokenizer()

			lowerCAmelCase     :    List[str]						=   OwlViTProcessor(tokenizer=a_		,      image_processor=a_	)

			lowerCAmelCase     :    Dict						=   "lower newer"
			lowerCAmelCase     :    Tuple						=   self.prepare_image_inputs()

			lowerCAmelCase     :    Any						=   processor(text=a_		,      images=a_	)

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

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



	def   _lowerCamelCase    (   self	):
			lowerCAmelCase     :    List[str]						=   "google/owlvit-base-patch32"
			lowerCAmelCase     :    List[Any]						=   OwlViTProcessor.from_pretrained(a_	)

			lowerCAmelCase     :    Dict						=   ["cat", "nasa badge"]
			lowerCAmelCase     :    Optional[int]						=   processor(text=a_	)

			lowerCAmelCase     :    Optional[int]						=   16
			self.assertListEqual(list(inputs.keys()	)		,      ["input_ids", "attention_mask"]	)
			self.assertEqual(inputs["input_ids"].shape		,      (2, seq_length)	)

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



	def   _lowerCamelCase    (   self	):
			lowerCAmelCase     :    Optional[int]						=   "google/owlvit-base-patch32"
			lowerCAmelCase     :    Tuple						=   OwlViTProcessor.from_pretrained(a_	)

			lowerCAmelCase     :    List[Any]						=   [["cat", "nasa badge"], ["person"]]
			lowerCAmelCase     :    int						=   processor(text=a_	)

			lowerCAmelCase     :    List[Any]						=   16
			lowerCAmelCase     :    Union[str, Any]						=   len(a_	)
			lowerCAmelCase     :    str						=   max([len(a_	) for texts in input_texts]	)

			self.assertListEqual(list(inputs.keys()	)		,      ["input_ids", "attention_mask"]	)
			self.assertEqual(inputs["input_ids"].shape		,      (batch_size * num_max_text_queries, seq_length)	)

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



	def   _lowerCamelCase    (   self	):
			lowerCAmelCase     :    Optional[int]						=   "google/owlvit-base-patch32"
			lowerCAmelCase     :    Union[str, Any]						=   OwlViTProcessor.from_pretrained(a_	)

			lowerCAmelCase     :    List[Any]						=   ["cat", "nasa badge"]
			lowerCAmelCase     :    Any						=   processor(text=a_	)

			lowerCAmelCase     :    Optional[Any]						=   16
			lowerCAmelCase     :    Optional[Any]						=   inputs["input_ids"]
			lowerCAmelCase     :    str						=   [
			    [49_406, 2_368, 49_407, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
			    [49_406, 6_841, 11_301, 49_407, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
			]

			self.assertListEqual(list(inputs.keys()	)		,      ["input_ids", "attention_mask"]	)
			self.assertEqual(inputs["input_ids"].shape		,      (2, seq_length)	)
			self.assertListEqual(list(input_ids[0]	)		,      predicted_ids[0]	)
			self.assertListEqual(list(input_ids[1]	)		,      predicted_ids[1]	)



	def   _lowerCamelCase    (   self	):
			lowerCAmelCase     :    Optional[Any]						=   self.get_image_processor()
			lowerCAmelCase     :    Optional[Any]						=   self.get_tokenizer()

			lowerCAmelCase     :    Dict						=   OwlViTProcessor(tokenizer=a_		,      image_processor=a_	)

			lowerCAmelCase     :    str						=   self.prepare_image_inputs()
			lowerCAmelCase     :    Tuple						=   self.prepare_image_inputs()

			lowerCAmelCase     :    List[Any]						=   processor(images=a_		,      query_images=a_	)

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

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





	def   _lowerCamelCase    (   self	):
			lowerCAmelCase     :    Tuple						=   self.get_image_processor()
			lowerCAmelCase     :    int						=   self.get_tokenizer()

			lowerCAmelCase     :    str						=   OwlViTProcessor(tokenizer=a_		,      image_processor=a_	)

			lowerCAmelCase     :    Union[str, Any]						=   [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

			lowerCAmelCase     :    List[Any]						=   processor.batch_decode(a_	)
			lowerCAmelCase     :    Union[str, Any]						=   tokenizer.batch_decode(a_	)

			self.assertListEqual(a_		,      a_	)



