






import unittest

from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


_a    :   Optional[Any]        =			get_tests_dir("""fixtures/spiece.model""")







@require_sentencepiece
@require_tokenizers
class 	_UpperCAmelCase  (  __UpperCAmelCase				,							unittest.TestCase		):




      """simple docstring"""



      A          =    DebertaVaTokenizer
      A          =    DebertaVaTokenizerFast
      A          =    True
      A          =    True
      def 			snake_case_      (   self		):



          '''simple docstring'''
          super().setUp()

          # We have a SentencePiece fixture for testing
          lowerCAmelCase__   :Optional[int]      							=				DebertaVaTokenizer(lowerCAmelCase_    ,	unk_token="<unk>"		)
          tokenizer.save_pretrained(self.tmpdirname		)
      def 			snake_case_      (   self    ,	_lowerCAmelCase		):



          '''simple docstring'''
          lowerCAmelCase__   :List[str]      							=				"this is a test"
          lowerCAmelCase__   :str      							=				"this is a test"
          return input_text, output_text
      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :Optional[int]      							=				"<pad>"
          lowerCAmelCase__   :int      							=				0

          self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCAmelCase_		)    ,	lowerCAmelCase_		)
          self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCAmelCase_		)    ,	lowerCAmelCase_		)
      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :Any      							=				list(self.get_tokenizer().get_vocab().keys()		)
          self.assertEqual(vocab_keys[0]    ,	"<pad>"		)
          self.assertEqual(vocab_keys[1]    ,	"<unk>"		)
          self.assertEqual(vocab_keys[-1]    ,	"[PAD]"		)
          self.assertEqual(len(lowerCAmelCase_		)    ,	30_001		)
      def 			snake_case_      (   self		):



          '''simple docstring'''
          self.assertEqual(self.get_tokenizer().vocab_size    ,	30_000		)
      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :List[Any]      							=				" \tHeLLo!how  \n Are yoU?  "
          lowerCAmelCase__   :Tuple      							=				["▁hello", "!", "how", "▁are", "▁you", "?"]
          # fmt: on

          lowerCAmelCase__   :Dict      							=				DebertaVaTokenizer(lowerCAmelCase_    ,	do_lower_case=lowerCAmelCase_		)
          lowerCAmelCase__   :Any      							=				tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)		)

          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)

          lowerCAmelCase__   :int      							=				DebertaVaTokenizerFast(lowerCAmelCase_    ,	do_lower_case=lowerCAmelCase_		)
          lowerCAmelCase__   :str      							=				rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)		)

          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)
      @unittest.skip("There is an inconsistency between slow and fast tokenizer due to a bug in the fast one."		)
      def 			snake_case_      (   self		):



          '''simple docstring'''
          pass
      @unittest.skip("There is an inconsistency between slow and fast tokenizer due to a bug in the fast one."		)
      def 			snake_case_      (   self		):



          '''simple docstring'''
          pass
      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :Optional[int]      							=				"I was born in 92000, and this is falsé."
          lowerCAmelCase__   :Tuple      							=				["▁", "<unk>", "▁was", "▁born", "▁in", "▁9", "2000", "▁", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "▁", ".", ]
          # fmt: on

          lowerCAmelCase__   :Any      							=				DebertaVaTokenizer(lowerCAmelCase_    ,	split_by_punct=lowerCAmelCase_		)
          lowerCAmelCase__   :Union[str, Any]      							=				tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)		)

          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)

          lowerCAmelCase__   :List[str]      							=				DebertaVaTokenizerFast(lowerCAmelCase_    ,	split_by_punct=lowerCAmelCase_		)
          lowerCAmelCase__   :int      							=				rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)		)

          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)
      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :int      							=				"I was born in 92000, and this is falsé."
          lowerCAmelCase__   :List[str]      							=				["▁i", "▁was", "▁born", "▁in", "▁9", "2000", "▁", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "▁", ".", ]
          # fmt: on

          lowerCAmelCase__   :str      							=				DebertaVaTokenizer(lowerCAmelCase_    ,	do_lower_case=lowerCAmelCase_    ,	split_by_punct=lowerCAmelCase_		)
          lowerCAmelCase__   :List[str]      							=				tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)		)
          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)

          lowerCAmelCase__   :int      							=				DebertaVaTokenizerFast(lowerCAmelCase_    ,	do_lower_case=lowerCAmelCase_    ,	split_by_punct=lowerCAmelCase_		)
          lowerCAmelCase__   :Any      							=				rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)		)
          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)
      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :List[str]      							=				"I was born in 92000, and this is falsé."
          lowerCAmelCase__   :str      							=				["▁i", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", ".", ]
          # fmt: on

          lowerCAmelCase__   :Union[str, Any]      							=				DebertaVaTokenizer(lowerCAmelCase_    ,	do_lower_case=lowerCAmelCase_    ,	split_by_punct=lowerCAmelCase_		)
          lowerCAmelCase__   :int      							=				tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)		)

          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)

          lowerCAmelCase__   :Optional[Any]      							=				DebertaVaTokenizerFast(lowerCAmelCase_    ,	do_lower_case=lowerCAmelCase_    ,	split_by_punct=lowerCAmelCase_		)
          lowerCAmelCase__   :List[Any]      							=				rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)		)

          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)
      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :Optional[Any]      							=				"I was born in 92000, and this is falsé."
          lowerCAmelCase__   :List[str]      							=				["▁", "<unk>", "▁was", "▁born", "▁in", "▁9", "2000", "▁", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "▁", ".", ]
          # fmt: on

          lowerCAmelCase__   :Optional[Any]      							=				DebertaVaTokenizer(lowerCAmelCase_    ,	do_lower_case=lowerCAmelCase_    ,	split_by_punct=lowerCAmelCase_		)
          lowerCAmelCase__   :Any      							=				tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)		)

          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)

          lowerCAmelCase__   :str      							=				DebertaVaTokenizerFast(lowerCAmelCase_    ,	do_lower_case=lowerCAmelCase_    ,	split_by_punct=lowerCAmelCase_		)
          lowerCAmelCase__   :Optional[Any]      							=				rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)		)

          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)
      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :List[str]      							=				" \tHeLLo!how  \n Are yoU?  "
          lowerCAmelCase__   :Dict      							=				["▁", "<unk>", "e", "<unk>", "o", "!", "how", "▁", "<unk>", "re", "▁yo", "<unk>", "?"]
          # fmt: on

          lowerCAmelCase__   :Any      							=				DebertaVaTokenizer(lowerCAmelCase_    ,	do_lower_case=lowerCAmelCase_    ,	split_by_punct=lowerCAmelCase_		)
          lowerCAmelCase__   :List[str]      							=				tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)		)

          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)

          lowerCAmelCase__   :Any      							=				DebertaVaTokenizerFast(lowerCAmelCase_    ,	do_lower_case=lowerCAmelCase_    ,	split_by_punct=lowerCAmelCase_		)
          lowerCAmelCase__   :List[Any]      							=				rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)		)

          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)
      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :Dict      							=				self.get_tokenizer()
          lowerCAmelCase__   :Optional[int]      							=				self.get_rust_tokenizer()

          lowerCAmelCase__   :List[Any]      							=				"I was born in 92000, and this is falsé."

          lowerCAmelCase__   :Dict      							=				tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)		)
          lowerCAmelCase__   :List[Any]      							=				rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)		)
          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)

          lowerCAmelCase__   :str      							=				tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)
          lowerCAmelCase__   :int      							=				rust_tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)
          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)

          lowerCAmelCase__   :Tuple      							=				self.get_rust_tokenizer()
          lowerCAmelCase__   :Optional[Any]      							=				tokenizer.encode(lowerCAmelCase_		)
          lowerCAmelCase__   :List[Any]      							=				rust_tokenizer.encode(lowerCAmelCase_		)
          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)
      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :List[Any]      							=				"This is a test"
          lowerCAmelCase__   :Optional[Any]      							=				[13, 1, 4_398, 25, 21, 1_289]
          lowerCAmelCase__   :List[str]      							=				["▁", "T", "his", "▁is", "▁a", "▁test"]
          lowerCAmelCase__   :Tuple      							=				["▁", "<unk>", "his", "▁is", "▁a", "▁test"]

          lowerCAmelCase__   :int      							=				DebertaVaTokenizer(lowerCAmelCase_    ,	keep_accents=lowerCAmelCase_		)
          lowerCAmelCase__   :Any      							=				DebertaVaTokenizerFast(lowerCAmelCase_    ,	keep_accents=lowerCAmelCase_		)

          lowerCAmelCase__   :List[Any]      							=				tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)
          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)
          lowerCAmelCase__   :Any      							=				tokenizer.tokenize(lowerCAmelCase_		)
          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)
          lowerCAmelCase__   :Optional[int]      							=				tokenizer.convert_ids_to_tokens(lowerCAmelCase_		)
          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)

          lowerCAmelCase__   :Optional[Any]      							=				rust_tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)
          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)
          lowerCAmelCase__   :Optional[int]      							=				rust_tokenizer.tokenize(lowerCAmelCase_		)
          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)
          lowerCAmelCase__   :List[Any]      							=				rust_tokenizer.convert_ids_to_tokens(lowerCAmelCase_		)
          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)

          # fmt: off
          lowerCAmelCase__   :List[Any]      							=				"I was born in 92000, and this is falsé."
          lowerCAmelCase__   :Tuple      							=				[13, 1, 23, 386, 19, 561, 3_050, 15, 17, 48, 25, 8_256, 18, 1, 9]
          lowerCAmelCase__   :List[Any]      							=				["▁", "I", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "é", ".", ]
          lowerCAmelCase__   :int      							=				["▁", "<unk>", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", ".", ]
          # fmt: on

          lowerCAmelCase__   :Optional[Any]      							=				tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)
          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)
          lowerCAmelCase__   :List[Any]      							=				tokenizer.tokenize(lowerCAmelCase_		)
          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)
          lowerCAmelCase__   :Dict      							=				tokenizer.convert_ids_to_tokens(lowerCAmelCase_		)
          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)

          lowerCAmelCase__   :int      							=				rust_tokenizer.encode(lowerCAmelCase_    ,	add_special_tokens=lowerCAmelCase_		)
          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)
          lowerCAmelCase__   :Tuple      							=				rust_tokenizer.tokenize(lowerCAmelCase_		)
          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)
          lowerCAmelCase__   :List[str]      							=				rust_tokenizer.convert_ids_to_tokens(lowerCAmelCase_		)
          self.assertListEqual(lowerCAmelCase_    ,	lowerCAmelCase_		)
      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :Tuple      							=				DebertaVaTokenizer(lowerCAmelCase_		)

          lowerCAmelCase__   :Optional[int]      							=				tokenizer.encode("sequence builders"		)
          lowerCAmelCase__   :Dict      							=				tokenizer.encode("multi-sequence build"		)

          lowerCAmelCase__   :Optional[int]      							=				tokenizer.build_inputs_with_special_tokens(lowerCAmelCase_		)
          lowerCAmelCase__   :Optional[Any]      							=				tokenizer.build_inputs_with_special_tokens(lowerCAmelCase_    ,	lowerCAmelCase_		)

          self.assertEqual([tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]    ,	lowerCAmelCase_		)
          self.assertEqual(
              [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [tokenizer.sep_token_id]    ,	lowerCAmelCase_    ,	)



      @slow
      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :Dict      							=				{"input_ids": [[1, 39_867, 36, 19_390, 486, 27, 35_052, 81_436, 18, 60_685, 1_225, 7, 35_052, 81_436, 18, 9_367, 16_899, 18, 15_937, 53, 594, 773, 18, 16_287, 30_465, 36, 15_937, 6, 41_139, 38, 36_979, 60_763, 191, 6, 34_132, 99, 6, 50_538, 390, 43_230, 6, 34_132, 2_779, 20_850, 14, 699, 1_072, 1_194, 36, 382, 10_901, 53, 7, 699, 1_072, 2_084, 36, 20_422, 630, 53, 19, 105, 3_049, 1_896, 1_053, 16_899, 1_506, 11, 37_978, 4_243, 7, 1_237, 31_869, 200, 16_566, 654, 6, 35_052, 81_436, 7, 55_630, 13_593, 4, 2], [1, 26, 15_011, 13, 667, 8, 1_053, 18, 23_611, 1_237, 72_356, 12_820, 34, 104_134, 1_209, 35, 13_313, 6_627, 21, 202, 347, 7, 164, 2_399, 11, 46, 4_485, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 5, 1_232, 2_864, 15_785, 14_951, 105, 5, 8_581, 1_250, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "token_type_ids": [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
          # fmt: on

          self.tokenizer_integration_test_util(
              expected_encoding=lowerCAmelCase_    ,	model_name="microsoft/deberta-v2-xlarge"    ,	revision="ad6e42c1532ddf3a15c39246b63f5559d558b670"    ,	)











import gc
import random
import unittest

import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel

from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import floats_tensor, load_image, load_numpy, slow
from diffusers.utils.testing_utils import require_torch_gpu, torch_device

from ..test_pipelines_common import PipelineTesterMixin, assert_mean_pixel_difference







class 	_UpperCAmelCase  (  _A				,							unittest.TestCase		):




      """simple docstring"""



      A          =    ShapEImgaImgPipeline
      A          =    ['''image''']
      A          =    ['''image''']
      A          =    [
          '''num_images_per_prompt''',
          '''num_inference_steps''',
          '''generator''',
          '''latents''',
          '''guidance_scale''',
          '''frame_size''',
          '''output_type''',
          '''return_dict''',
      ]
      A          =    False
      @property
      def 			snake_case_      (   self		):



          '''simple docstring'''
          return 32
      @property
      def 			snake_case_      (   self		):



          '''simple docstring'''
          return 32
      @property
      def 			snake_case_      (   self		):



          '''simple docstring'''
          return self.time_input_dim * 4
      @property
      def 			snake_case_      (   self		):



          '''simple docstring'''
          return 8
      @property
      def 			snake_case_      (   self		):



          '''simple docstring'''
          torch.manual_seed(0		)
          lowerCAmelCase__   :Any      							=				CLIPVisionConfig(
              hidden_size=self.text_embedder_hidden_size    ,	image_size=64    ,	projection_dim=self.text_embedder_hidden_size    ,	intermediate_size=37    ,	num_attention_heads=4    ,	num_channels=3    ,	num_hidden_layers=5    ,	patch_size=1    ,	)

          lowerCAmelCase__   :int      							=				CLIPVisionModel(_lowerCAmelCase		)
          return model
      @property
      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :List[str]      							=				CLIPImageProcessor(
              crop_size=224    ,	do_center_crop=_lowerCAmelCase    ,	do_normalize=_lowerCAmelCase    ,	do_resize=_lowerCAmelCase    ,	image_mean=[0.4814_5466, 0.457_8275, 0.4082_1073]    ,	image_std=[0.2686_2954, 0.2613_0258, 0.2757_7711]    ,	resample=3    ,	size=224    ,	)

          return image_processor
      @property
      def 			snake_case_      (   self		):



          '''simple docstring'''
          torch.manual_seed(0		)

          lowerCAmelCase__   :Any      							=				{
              "num_attention_heads": 2,
              "attention_head_dim": 16,
              "embedding_dim": self.time_input_dim,
              "num_embeddings": 32,
              "embedding_proj_dim": self.text_embedder_hidden_size,
              "time_embed_dim": self.time_embed_dim,
              "num_layers": 1,
              "clip_embed_dim": self.time_input_dim * 2,
              "additional_embeddings": 0,
              "time_embed_act_fn": "gelu",
              "norm_in_type": "layer",
              "embedding_proj_norm_type": "layer",
              "encoder_hid_proj_type": None,
              "added_emb_type": None,
          }

          lowerCAmelCase__   :int      							=				PriorTransformer(**_lowerCAmelCase		)
          return model
      @property
      def 			snake_case_      (   self		):



          '''simple docstring'''
          torch.manual_seed(0		)

          lowerCAmelCase__   :List[Any]      							=				{
              "param_shapes": (
                  (self.renderer_dim, 93),
                  (self.renderer_dim, 8),
                  (self.renderer_dim, 8),
                  (self.renderer_dim, 8),
              ),
              "d_latent": self.time_input_dim,
              "d_hidden": self.renderer_dim,
              "n_output": 12,
              "background": (
                  0.1,
                  0.1,
                  0.1,
              ),
          }
          lowerCAmelCase__   :str      							=				ShapERenderer(**_lowerCAmelCase		)
          return model
      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :Any      							=				self.dummy_prior
          lowerCAmelCase__   :str      							=				self.dummy_image_encoder
          lowerCAmelCase__   :Optional[Any]      							=				self.dummy_image_processor
          lowerCAmelCase__   :Union[str, Any]      							=				self.dummy_renderer

          lowerCAmelCase__   :str      							=				HeunDiscreteScheduler(
              beta_schedule="exp"    ,	num_train_timesteps=1_024    ,	prediction_type="sample"    ,	use_karras_sigmas=_lowerCAmelCase    ,	clip_sample=_lowerCAmelCase    ,	clip_sample_range=1.0    ,	)
          lowerCAmelCase__   :Any      							=				{
              "prior": prior,
              "image_encoder": image_encoder,
              "image_processor": image_processor,
              "renderer": renderer,
              "scheduler": scheduler,
          }

          return components
      def 			snake_case_      (   self    ,	_lowerCAmelCase    ,	_lowerCAmelCase=0		):



          '''simple docstring'''
          lowerCAmelCase__   :List[Any]      							=				floats_tensor((1, 3, 64, 64)    ,	rng=random.Random(_lowerCAmelCase		)		).to(_lowerCAmelCase		)

          if str(_lowerCAmelCase		).startswith("mps"		):
              lowerCAmelCase__   :Dict      							=				torch.manual_seed(_lowerCAmelCase		)
          else:
              lowerCAmelCase__   :str      							=				torch.Generator(device=_lowerCAmelCase		).manual_seed(_lowerCAmelCase		)
          lowerCAmelCase__   :Tuple      							=				{
              "image": input_image,
              "generator": generator,
              "num_inference_steps": 1,
              "frame_size": 32,
              "output_type": "np",
          }
          return inputs
      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :Optional[int]      							=				"cpu"

          lowerCAmelCase__   :Union[str, Any]      							=				self.get_dummy_components()

          lowerCAmelCase__   :Union[str, Any]      							=				self.pipeline_class(**_lowerCAmelCase		)
          lowerCAmelCase__   :Optional[int]      							=				pipe.to(_lowerCAmelCase		)

          pipe.set_progress_bar_config(disable=_lowerCAmelCase		)

          lowerCAmelCase__   :int      							=				pipe(**self.get_dummy_inputs(_lowerCAmelCase		)		)
          lowerCAmelCase__   :List[Any]      							=				output.images[0]
          lowerCAmelCase__   :List[Any]      							=				image[0, -3:, -3:, -1]

          assert image.shape == (20, 32, 32, 3)

          lowerCAmelCase__   :str      							=				np.array(
              [
                  0.0003_9216,
                  0.0003_9216,
                  0.0003_9216,
                  0.0003_9216,
                  0.0003_9216,
                  0.0003_9216,
                  0.0003_9216,
                  0.0003_9216,
                  0.0003_9216,
              ]		)

          assert np.abs(image_slice.flatten() - expected_slice		).max() < 1e-2
      def 			snake_case_      (   self		):



          '''simple docstring'''
          # NOTE: Larger batch sizes cause this test to timeout, only test on smaller batches
          self._test_inference_batch_consistent(batch_sizes=[1, 2]		)
      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :Any      							=				torch_device == "cpu"
          lowerCAmelCase__   :Tuple      							=				True
          self._test_inference_batch_single_identical(
              batch_size=2    ,	test_max_difference=_lowerCAmelCase    ,	relax_max_difference=_lowerCAmelCase    ,	)



      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :List[str]      							=				self.get_dummy_components()
          lowerCAmelCase__   :Tuple      							=				self.pipeline_class(**_lowerCAmelCase		)
          lowerCAmelCase__   :Optional[Any]      							=				pipe.to(_lowerCAmelCase		)
          pipe.set_progress_bar_config(disable=_lowerCAmelCase		)

          lowerCAmelCase__   :Tuple      							=				1
          lowerCAmelCase__   :List[Any]      							=				2

          lowerCAmelCase__   :List[str]      							=				self.get_dummy_inputs(_lowerCAmelCase		)

          for key in inputs.keys():
              if key in self.batch_params:
                  lowerCAmelCase__   :Any      							=				batch_size * [inputs[key]]

          lowerCAmelCase__   :Optional[Any]      							=				pipe(**_lowerCAmelCase    ,	num_images_per_prompt=_lowerCAmelCase		)[0]

          assert images.shape[0] == batch_size * num_images_per_prompt







@slow
@require_torch_gpu
class 	_UpperCAmelCase  (  unittest.TestCase		):




      """simple docstring"""



      def 			snake_case_      (   self		):



          '''simple docstring'''
          # clean up the VRAM after each test
          super().tearDown()
          gc.collect()
          torch.cuda.empty_cache()



      def 			snake_case_      (   self		):



          '''simple docstring'''
          lowerCAmelCase__   :Optional[Any]      							=				load_image(
              "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main" "/shap_e/corgi.png"		)
          lowerCAmelCase__   :int      							=				load_numpy(
              "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
              "/shap_e/test_shap_e_img2img_out.npy"		)
          lowerCAmelCase__   :Optional[int]      							=				ShapEImgaImgPipeline.from_pretrained("openai/shap-e-img2img"		)
          lowerCAmelCase__   :Tuple      							=				pipe.to(_lowerCAmelCase		)
          pipe.set_progress_bar_config(disable=_lowerCAmelCase		)

          lowerCAmelCase__   :Any      							=				torch.Generator(device=_lowerCAmelCase		).manual_seed(0		)

          lowerCAmelCase__   :List[Any]      							=				pipe(
              _lowerCAmelCase    ,	generator=_lowerCAmelCase    ,	guidance_scale=3.0    ,	num_inference_steps=64    ,	frame_size=64    ,	output_type="np"    ,	).images[0]

          assert images.shape == (20, 64, 64, 3)

          assert_mean_pixel_difference(_lowerCAmelCase    ,	_lowerCAmelCase		)



