





import hashlib
import unittest
from typing import Dict

import numpy as np

from transformers import (
    MODEL_FOR_MASK_GENERATION_MAPPING,
    TF_MODEL_FOR_MASK_GENERATION_MAPPING,
    is_vision_available,
    pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_tf,
    require_torch,
    require_vision,
    slow,
)


if is_vision_available():
  from PIL import Image
else:





  class  lowerCAmelCase							:







    @staticmethod
    def   UpperCAmelCase					(      *_lowercase  :Any   ,							**_lowercase  :Dict ):






       '''simple docstring'''





       pass


def _A       (   __magic_name__	):
   lowercase__			       =  hashlib.mda(image.tobytes()	)
   return m.hexdigest()[:10]


def _A       (   __magic_name__	):
   lowercase__			       =  np.array(__magic_name__	)
   lowercase__			       =  npimg.shape
   return {"hash": hashimage(__magic_name__	), "shape": shape}







@is_pipeline_test
@require_vision
@require_torch
class  lowerCAmelCase							(       unittest.TestCase ):
  __lowerCamelCase		=      dict(
      (list(MODEL_FOR_MASK_GENERATION_MAPPING.items() ) if MODEL_FOR_MASK_GENERATION_MAPPING else []) )
  __lowerCamelCase		=      dict(
      (list(TF_MODEL_FOR_MASK_GENERATION_MAPPING.items() ) if TF_MODEL_FOR_MASK_GENERATION_MAPPING else []) )







  def   UpperCAmelCase					(      self  :Tuple   ,							_lowercase  :List[Any]   ,							_lowercase  :Any   ,							_lowercase  :Optional[Any] ):






     '''simple docstring'''





     lowercase__			       =  MaskGenerationPipeline(model=_lowercase   ,							image_processor=_lowercase )
     return image_segmenter, [
         "./tests/fixtures/tests_samples/COCO/000000039769.png",
         "./tests/fixtures/tests_samples/COCO/000000039769.png",
     ]







  def   UpperCAmelCase					(      self  :Dict   ,							_lowercase  :Union[str, Any]   ,							_lowercase  :str ):






     '''simple docstring'''





     pass







  @require_tf
  @unittest.skip("Image segmentation not implemented in TF" )
  def   UpperCAmelCase					(      self  :Optional[int] ):






     '''simple docstring'''





     pass







  @slow
  @require_torch
  def   UpperCAmelCase					(      self  :Tuple ):






     '''simple docstring'''





     lowercase__			       =  pipeline("mask-generation"   ,							model="facebook/sam-vit-huge" )

     lowercase__			       =  image_segmenter("http://images.cocodataset.org/val2017/000000039769.jpg"   ,							points_per_batch=2_56 )

     # Shortening by hashing
     lowercase__			       =  []
     for i, o in enumerate(outputs["masks"] ):
        new_outupt += [{"mask": mask_to_test_readable(_lowercase ), "scores": outputs["scores"][i]}]

     # fmt: off
     self.assertEqual(
         nested_simplify(_lowercase   ,							decimals=4 )   ,							[
             {"mask": {"hash": "115ad19f5f", "shape": (4_80, 6_40)}, "scores": 1.0444},
             {"mask": {"hash": "6affa964c6", "shape": (4_80, 6_40)}, "scores": 1.021},
             {"mask": {"hash": "dfe28a0388", "shape": (4_80, 6_40)}, "scores": 1.0167},
             {"mask": {"hash": "c0a5f4a318", "shape": (4_80, 6_40)}, "scores": 1.0132},
             {"mask": {"hash": "fe8065c197", "shape": (4_80, 6_40)}, "scores": 1.0053},
             {"mask": {"hash": "e2d0b7a0b7", "shape": (4_80, 6_40)}, "scores": 0.9967},
             {"mask": {"hash": "453c7844bd", "shape": (4_80, 6_40)}, "scores": 0.993},
             {"mask": {"hash": "3d44f2926d", "shape": (4_80, 6_40)}, "scores": 0.9909},
             {"mask": {"hash": "64033ddc3f", "shape": (4_80, 6_40)}, "scores": 0.9879},
             {"mask": {"hash": "801064ff79", "shape": (4_80, 6_40)}, "scores": 0.9834},
             {"mask": {"hash": "6172f276ef", "shape": (4_80, 6_40)}, "scores": 0.9716},
             {"mask": {"hash": "b49e60e084", "shape": (4_80, 6_40)}, "scores": 0.9612},
             {"mask": {"hash": "a811e775fd", "shape": (4_80, 6_40)}, "scores": 0.9599},
             {"mask": {"hash": "a6a8ebcf4b", "shape": (4_80, 6_40)}, "scores": 0.9552},
             {"mask": {"hash": "9d8257e080", "shape": (4_80, 6_40)}, "scores": 0.9532},
             {"mask": {"hash": "32de6454a8", "shape": (4_80, 6_40)}, "scores": 0.9516},
             {"mask": {"hash": "af3d4af2c8", "shape": (4_80, 6_40)}, "scores": 0.9499},
             {"mask": {"hash": "3c6db475fb", "shape": (4_80, 6_40)}, "scores": 0.9483},
             {"mask": {"hash": "c290813fb9", "shape": (4_80, 6_40)}, "scores": 0.9464},
             {"mask": {"hash": "b6f0b8f606", "shape": (4_80, 6_40)}, "scores": 0.943},
             {"mask": {"hash": "92ce16bfdf", "shape": (4_80, 6_40)}, "scores": 0.943},
             {"mask": {"hash": "c749b25868", "shape": (4_80, 6_40)}, "scores": 0.9408},
             {"mask": {"hash": "efb6cab859", "shape": (4_80, 6_40)}, "scores": 0.9335},
             {"mask": {"hash": "1ff2eafb30", "shape": (4_80, 6_40)}, "scores": 0.9326},
             {"mask": {"hash": "788b798e24", "shape": (4_80, 6_40)}, "scores": 0.9262},
             {"mask": {"hash": "abea804f0e", "shape": (4_80, 6_40)}, "scores": 0.8999},
             {"mask": {"hash": "7b9e8ddb73", "shape": (4_80, 6_40)}, "scores": 0.8986},
             {"mask": {"hash": "cd24047c8a", "shape": (4_80, 6_40)}, "scores": 0.8984},
             {"mask": {"hash": "6943e6bcbd", "shape": (4_80, 6_40)}, "scores": 0.8873},
             {"mask": {"hash": "b5f47c9191", "shape": (4_80, 6_40)}, "scores": 0.8871}
         ]   ,							)
     # fmt: on







  @require_torch
  @slow
  def   UpperCAmelCase					(      self  :int ):






     '''simple docstring'''





     lowercase__			       =  "facebook/sam-vit-huge"
     lowercase__			       =  pipeline("mask-generation"   ,							model=_lowercase )

     lowercase__			       =  image_segmenter(
         "http://images.cocodataset.org/val2017/000000039769.jpg"   ,							pred_iou_thresh=1   ,							points_per_batch=2_56 )

     # Shortening by hashing
     lowercase__			       =  []
     for i, o in enumerate(outputs["masks"] ):
        new_outupt += [{"mask": mask_to_test_readable(_lowercase ), "scores": outputs["scores"][i]}]

     self.assertEqual(
         nested_simplify(_lowercase   ,							decimals=4 )   ,							[
             {"mask": {"hash": "115ad19f5f", "shape": (4_80, 6_40)}, "scores": 1.0444},
             {"mask": {"hash": "6affa964c6", "shape": (4_80, 6_40)}, "scores": 1.0210},
             {"mask": {"hash": "dfe28a0388", "shape": (4_80, 6_40)}, "scores": 1.0167},
             {"mask": {"hash": "c0a5f4a318", "shape": (4_80, 6_40)}, "scores": 1.0132},
             {"mask": {"hash": "fe8065c197", "shape": (4_80, 6_40)}, "scores": 1.0053},
         ]   ,							)













import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_torch_available, is_vision_available


if is_torch_available():
  import torch


if is_vision_available():
  from PIL import Image

  from transformers import MgpstrProcessor, ViTImageProcessor





@require_torch
@require_vision
class  lowerCAmelCase							(       unittest.TestCase ):
  __lowerCamelCase		=      ViTImageProcessor if is_vision_available() else None







  @property
  def   UpperCAmelCase					(      self  :Union[str, Any] ):






     '''simple docstring'''





     return self.image_processor_tester.prepare_image_processor_dict()







  def   UpperCAmelCase					(      self  :Optional[int] ):






     '''simple docstring'''





     lowercase__			       =  (3, 32, 1_28)
     lowercase__			       =  tempfile.mkdtemp()

     # fmt: off
     lowercase__			       =  ["[GO]", "[s]", "0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z"]
     # fmt: on
     lowercase__			       =  dict(zip(_lowercase   ,							range(len(_lowercase ) ) ) )

     lowercase__			       =  os.path.join(self.tmpdirname   ,							VOCAB_FILES_NAMES["vocab_file"] )
     with open(self.vocab_file   ,							"w"   ,							encoding="utf-8" ) as fp:
        fp.write(json.dumps(_lowercase ) + "\n" )

     lowercase__			       =  {
         "do_normalize": False,
         "do_resize": True,
         "image_processor_type": "ViTImageProcessor",
         "resample": 3,
         "size": {"height": 32, "width": 1_28},
     }
     lowercase__			       =  os.path.join(self.tmpdirname   ,							_lowercase )
     with open(self.image_processor_file   ,							"w"   ,							encoding="utf-8" ) as fp:
        json.dump(_lowercase   ,							_lowercase )







  def   UpperCAmelCase					(      self  :Optional[Any]   ,							**_lowercase  :str ):






     '''simple docstring'''





     return MgpstrTokenizer.from_pretrained(self.tmpdirname   ,							**_lowercase )







  def   UpperCAmelCase					(      self  :List[Any]   ,							**_lowercase  :List[str] ):






     '''simple docstring'''





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







  def   UpperCAmelCase					(      self  :List[Any] ):






     '''simple docstring'''





     shutil.rmtree(self.tmpdirname )







  def   UpperCAmelCase					(      self  :str ):






     '''simple docstring'''





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

     lowercase__			       =  Image.fromarray(np.moveaxis(_lowercase   ,							0   ,							-1 ) )

     return image_input







  def   UpperCAmelCase					(      self  :List[Any] ):






     '''simple docstring'''





     lowercase__			       =  self.get_tokenizer()
     lowercase__			       =  self.get_image_processor()

     lowercase__			       =  MgpstrProcessor(tokenizer=_lowercase   ,							image_processor=_lowercase )
     processor.save_pretrained(self.tmpdirname )
     lowercase__			       =  MgpstrProcessor.from_pretrained(self.tmpdirname   ,							use_fast=_lowercase )

     self.assertEqual(processor.char_tokenizer.get_vocab()   ,							tokenizer.get_vocab() )
     self.assertIsInstance(processor.char_tokenizer   ,							_lowercase )

     self.assertEqual(processor.image_processor.to_json_string()   ,							image_processor.to_json_string() )
     self.assertIsInstance(processor.image_processor   ,							_lowercase )







  def   UpperCAmelCase					(      self  :Optional[Any] ):






     '''simple docstring'''





     lowercase__			       =  self.get_tokenizer()
     lowercase__			       =  self.get_image_processor()

     lowercase__			       =  MgpstrProcessor(tokenizer=_lowercase   ,							image_processor=_lowercase )
     processor.save_pretrained(self.tmpdirname )

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

     lowercase__			       =  MgpstrProcessor.from_pretrained(
         self.tmpdirname   ,							bos_token="(BOS)"   ,							eos_token="(EOS)"   ,							do_normalize=_lowercase   ,							padding_value=1.0 )

     self.assertEqual(processor.char_tokenizer.get_vocab()   ,							tokenizer_add_kwargs.get_vocab() )
     self.assertIsInstance(processor.char_tokenizer   ,							_lowercase )

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







  def   UpperCAmelCase					(      self  :List[Any] ):






     '''simple docstring'''





     lowercase__			       =  self.get_image_processor()
     lowercase__			       =  self.get_tokenizer()

     lowercase__			       =  MgpstrProcessor(tokenizer=_lowercase   ,							image_processor=_lowercase )

     lowercase__			       =  self.prepare_image_inputs()

     lowercase__			       =  image_processor(_lowercase   ,							return_tensors="np" )
     lowercase__			       =  processor(images=_lowercase   ,							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   UpperCAmelCase					(      self  :Optional[Any] ):






     '''simple docstring'''





     lowercase__			       =  self.get_image_processor()
     lowercase__			       =  self.get_tokenizer()

     lowercase__			       =  MgpstrProcessor(tokenizer=_lowercase   ,							image_processor=_lowercase )

     lowercase__			       =  "test"

     lowercase__			       =  processor(text=_lowercase )

     lowercase__			       =  tokenizer(_lowercase )
     for key in encoded_tok.keys():
        self.assertListEqual(encoded_tok[key]   ,							encoded_processor[key] )







  def   UpperCAmelCase					(      self  :Optional[int] ):






     '''simple docstring'''





     lowercase__			       =  self.get_image_processor()
     lowercase__			       =  self.get_tokenizer()

     lowercase__			       =  MgpstrProcessor(tokenizer=_lowercase   ,							image_processor=_lowercase )

     lowercase__			       =  "test"
     lowercase__			       =  self.prepare_image_inputs()

     lowercase__			       =  processor(text=_lowercase   ,							images=_lowercase )

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

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







  def   UpperCAmelCase					(      self  :Tuple ):






     '''simple docstring'''





     lowercase__			       =  self.get_image_processor()
     lowercase__			       =  self.get_tokenizer()

     lowercase__			       =  MgpstrProcessor(tokenizer=_lowercase   ,							image_processor=_lowercase )

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

     lowercase__			       =  processor.char_decode(_lowercase )
     lowercase__			       =  tokenizer.batch_decode(_lowercase )
     lowercase__			       =  [seq.replace(" "   ,							"" ) for seq in decoded_tok]

     self.assertListEqual(_lowercase   ,							_lowercase )







  def   UpperCAmelCase					(      self  :str ):






     '''simple docstring'''





     lowercase__			       =  self.get_image_processor()
     lowercase__			       =  self.get_tokenizer()

     lowercase__			       =  MgpstrProcessor(tokenizer=_lowercase   ,							image_processor=_lowercase )

     lowercase__			       =  None
     lowercase__			       =  self.prepare_image_inputs()

     lowercase__			       =  processor(text=_lowercase   ,							images=_lowercase )

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







  def   UpperCAmelCase					(      self  :List[str] ):






     '''simple docstring'''





     lowercase__			       =  self.get_image_processor()
     lowercase__			       =  self.get_tokenizer()

     lowercase__			       =  MgpstrProcessor(tokenizer=_lowercase   ,							image_processor=_lowercase )

     lowercase__			       =  torch.randn(1   ,							27   ,							38 )
     lowercase__			       =  torch.randn(1   ,							27   ,							5_02_57 )
     lowercase__			       =  torch.randn(1   ,							27   ,							3_05_22 )

     lowercase__			       =  processor.batch_decode([char_input, bpe_input, wp_input] )

     self.assertListEqual(list(results.keys() )   ,							["generated_text", "scores", "char_preds", "bpe_preds", "wp_preds"] )






