

"""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 CLIPSegProcessor, ViTImageProcessor




@require_vision
class  _lowerCAmelCase  (     unittest.TestCase       ):







 """simple docstring"""







 def  _lowercase			(      self							:      Union[str, Any]     ):
    __lowercase								=						tempfile.mkdtemp()

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

    __lowercase								=						os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["vocab_file"]     )
    __lowercase								=						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__     )     )

    __lowercase								=						{
        "do_resize": True,
        "size": 2_0,
        "do_center_crop": True,
        "crop_size": 1_8,
        "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],
    }
    __lowercase								=						os.path.join(self.tmpdirname, UpperCAmelCase__     )
    with open(self.image_processor_file, "w", encoding="utf-8"     ) as fp:
       json.dump(UpperCAmelCase__, UpperCAmelCase__     )


 def  _lowercase			(      self							:      List[Any], **UpperCAmelCase__							:      List[str]     ):
    return CLIPTokenizer.from_pretrained(self.tmpdirname, **UpperCAmelCase__     )


 def  _lowercase			(      self							:      List[str], **UpperCAmelCase__							:      Tuple     ):
    return CLIPTokenizerFast.from_pretrained(self.tmpdirname, **UpperCAmelCase__     )


 def  _lowercase			(      self							:      Dict, **UpperCAmelCase__							:      List[Any]     ):
    return ViTImageProcessor.from_pretrained(self.tmpdirname, **UpperCAmelCase__     )


 def  _lowercase			(      self							:      Optional[Any]     ):
    shutil.rmtree(self.tmpdirname     )


 def  _lowercase			(      self							:      Tuple     ):
    __lowercase								=						[np.random.randint(2_5_5, size=(3, 3_0, 4_0_0), dtype=np.uinta     )]

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

    return image_inputs


 def  _lowercase			(      self							:      Tuple     ):
    __lowercase								=						self.get_tokenizer()
    __lowercase								=						self.get_rust_tokenizer()
    __lowercase								=						self.get_image_processor()

    __lowercase								=						CLIPSegProcessor(tokenizer=UpperCAmelCase__, image_processor=UpperCAmelCase__     )
    processor_slow.save_pretrained(self.tmpdirname     )
    __lowercase								=						CLIPSegProcessor.from_pretrained(self.tmpdirname, use_fast=UpperCAmelCase__     )

    __lowercase								=						CLIPSegProcessor(tokenizer=UpperCAmelCase__, image_processor=UpperCAmelCase__     )
    processor_fast.save_pretrained(self.tmpdirname     )
    __lowercase								=						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  _lowercase			(      self							:      List[str]     ):
    __lowercase								=						CLIPSegProcessor(tokenizer=self.get_tokenizer(), image_processor=self.get_image_processor()     )
    processor.save_pretrained(self.tmpdirname     )

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

    __lowercase								=						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  _lowercase			(      self							:      Tuple     ):
    __lowercase								=						self.get_image_processor()
    __lowercase								=						self.get_tokenizer()

    __lowercase								=						CLIPSegProcessor(tokenizer=UpperCAmelCase__, image_processor=UpperCAmelCase__     )

    __lowercase								=						self.prepare_image_inputs()

    __lowercase								=						image_processor(UpperCAmelCase__, return_tensors="np"     )
    __lowercase								=						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  _lowercase			(      self							:      int     ):
    __lowercase								=						self.get_image_processor()
    __lowercase								=						self.get_tokenizer()

    __lowercase								=						CLIPSegProcessor(tokenizer=UpperCAmelCase__, image_processor=UpperCAmelCase__     )

    __lowercase								=						"lower newer"

    __lowercase								=						processor(text=UpperCAmelCase__     )

    __lowercase								=						tokenizer(UpperCAmelCase__     )

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


 def  _lowercase			(      self							:      int     ):
    __lowercase								=						self.get_image_processor()
    __lowercase								=						self.get_tokenizer()

    __lowercase								=						CLIPSegProcessor(tokenizer=UpperCAmelCase__, image_processor=UpperCAmelCase__     )

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

    __lowercase								=						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  _lowercase			(      self							:      int     ):
    __lowercase								=						self.get_image_processor()
    __lowercase								=						self.get_tokenizer()

    __lowercase								=						CLIPSegProcessor(tokenizer=UpperCAmelCase__, image_processor=UpperCAmelCase__     )

    __lowercase								=						self.prepare_image_inputs()
    __lowercase								=						self.prepare_image_inputs()

    __lowercase								=						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  _lowercase			(      self							:      Dict     ):
    __lowercase								=						self.get_image_processor()
    __lowercase								=						self.get_tokenizer()

    __lowercase								=						CLIPSegProcessor(tokenizer=UpperCAmelCase__, image_processor=UpperCAmelCase__     )

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

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

    self.assertListEqual(UpperCAmelCase__, UpperCAmelCase__     )







"""simple docstring"""





from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


try:
   if not (is_transformers_available() and is_torch_available()):
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
   from .notes_encoder import SpectrogramNotesEncoder
   from .continous_encoder import SpectrogramContEncoder
   from .pipeline_spectrogram_diffusion import (
       SpectrogramContEncoder,
       SpectrogramDiffusionPipeline,
       TaFilmDecoder,
   )

try:
   if not (is_transformers_available() and is_torch_available() and is_note_seq_available()):
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from ...utils.dummy_transformers_and_torch_and_note_seq_objects import *  # noqa F403
else:
   from .midi_utils import MidiProcessor




