





import os
import tempfile
import unittest

import numpy as np

from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow


if is_flax_available():
  import jax
  import jax.numpy as jnp
  from flax.jax_utils import replicate
  from flax.training.common_utils import shard

  from diffusers import FlaxDDIMScheduler, FlaxDiffusionPipeline, FlaxStableDiffusionPipeline





@require_flax
class  lowerCAmelCase							(       unittest.TestCase ):







  def   UpperCAmelCase					(      self  :int ):






     '''simple docstring'''





     with tempfile.TemporaryDirectory() as tmpdirname:
        # pipeline has Flax weights
        lowercase__			       =  FlaxDiffusionPipeline.from_pretrained(
            "hf-internal-testing/tiny-stable-diffusion-pipe"   ,							safety_checker=_lowercase   ,							cache_dir=_lowercase )

        lowercase__			       =  [t[-1] for t in os.walk(os.path.join(_lowercase   ,							os.listdir(_lowercase )[0]   ,							"snapshots" ) )]
        lowercase__			       =  [item for sublist in all_root_files for item in sublist]

        # None of the downloaded files should be a PyTorch file even if we have some here:
        # https://huggingface.co/hf-internal-testing/tiny-stable-diffusion-pipe/blob/main/unet/diffusion_pytorch_model.bin
        assert not any(f.endswith(".bin" ) for f in files )





@slow
@require_flax
class  lowerCAmelCase							(       unittest.TestCase ):







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






     '''simple docstring'''





     lowercase__       ,							lowercase__			       =  FlaxStableDiffusionPipeline.from_pretrained(
         "hf-internal-testing/tiny-stable-diffusion-pipe"   ,							safety_checker=_lowercase )

     lowercase__			       =  (
         "A cinematic film still of Morgan Freeman starring as Jimi Hendrix, portrait, 40mm lens, shallow depth of"
         " field, close up, split lighting, cinematic"
     )

     lowercase__			       =  jax.random.PRNGKey(0 )
     lowercase__			       =  4

     lowercase__			       =  jax.device_count()
     lowercase__			       =  num_samples * [prompt]
     lowercase__			       =  pipeline.prepare_inputs(_lowercase )

     # shard inputs and rng
     lowercase__			       =  replicate(_lowercase )
     lowercase__			       =  jax.random.split(_lowercase   ,							_lowercase )
     lowercase__			       =  shard(_lowercase )

     lowercase__			       =  pipeline(_lowercase   ,							_lowercase   ,							_lowercase   ,							_lowercase   ,							jit=_lowercase ).images

     assert images.shape == (num_samples, 1, 64, 64, 3)
     if jax.device_count() == 8:
        assert np.abs(np.abs(images[0, 0, :2, :2, -2:]   ,							dtype=np.floataa ).sum() - 4.1514745 ) < 1e-3
        assert np.abs(np.abs(_lowercase   ,							dtype=np.floataa ).sum() - 49947.875 ) < 5e-1

     lowercase__			       =  pipeline.numpy_to_pil(np.asarray(images.reshape((num_samples,) + images.shape[-3:] ) ) )
     assert len(_lowercase ) == num_samples







  def   UpperCAmelCase					(      self  :Any ):






     '''simple docstring'''





     lowercase__       ,							lowercase__			       =  FlaxStableDiffusionPipeline.from_pretrained(
         "CompVis/stable-diffusion-v1-4"   ,							revision="flax"   ,							safety_checker=_lowercase )

     lowercase__			       =  (
         "A cinematic film still of Morgan Freeman starring as Jimi Hendrix, portrait, 40mm lens, shallow depth of"
         " field, close up, split lighting, cinematic"
     )

     lowercase__			       =  jax.random.PRNGKey(0 )
     lowercase__			       =  50

     lowercase__			       =  jax.device_count()
     lowercase__			       =  num_samples * [prompt]
     lowercase__			       =  pipeline.prepare_inputs(_lowercase )

     # shard inputs and rng
     lowercase__			       =  replicate(_lowercase )
     lowercase__			       =  jax.random.split(_lowercase   ,							_lowercase )
     lowercase__			       =  shard(_lowercase )

     lowercase__			       =  pipeline(_lowercase   ,							_lowercase   ,							_lowercase   ,							_lowercase   ,							jit=_lowercase ).images

     assert images.shape == (num_samples, 1, 5_12, 5_12, 3)
     if jax.device_count() == 8:
        assert np.abs((np.abs(images[0, 0, :2, :2, -2:]   ,							dtype=np.floataa ).sum() - 0.05652401) ) < 1e-3
        assert np.abs((np.abs(_lowercase   ,							dtype=np.floataa ).sum() - 2383808.2) ) < 5e-1







  def   UpperCAmelCase					(      self  :Optional[int] ):






     '''simple docstring'''





     lowercase__       ,							lowercase__			       =  FlaxStableDiffusionPipeline.from_pretrained(
         "CompVis/stable-diffusion-v1-4"   ,							revision="bf16"   ,							dtype=jnp.bfloataa   ,							safety_checker=_lowercase )

     lowercase__			       =  (
         "A cinematic film still of Morgan Freeman starring as Jimi Hendrix, portrait, 40mm lens, shallow depth of"
         " field, close up, split lighting, cinematic"
     )

     lowercase__			       =  jax.random.PRNGKey(0 )
     lowercase__			       =  50

     lowercase__			       =  jax.device_count()
     lowercase__			       =  num_samples * [prompt]
     lowercase__			       =  pipeline.prepare_inputs(_lowercase )

     # shard inputs and rng
     lowercase__			       =  replicate(_lowercase )
     lowercase__			       =  jax.random.split(_lowercase   ,							_lowercase )
     lowercase__			       =  shard(_lowercase )

     lowercase__			       =  pipeline(_lowercase   ,							_lowercase   ,							_lowercase   ,							_lowercase   ,							jit=_lowercase ).images

     assert images.shape == (num_samples, 1, 5_12, 5_12, 3)
     if jax.device_count() == 8:
        assert np.abs((np.abs(images[0, 0, :2, :2, -2:]   ,							dtype=np.floataa ).sum() - 0.04003906) ) < 1e-3
        assert np.abs((np.abs(_lowercase   ,							dtype=np.floataa ).sum() - 2373516.75) ) < 5e-1







  def   UpperCAmelCase					(      self  :str ):






     '''simple docstring'''





     lowercase__       ,							lowercase__			       =  FlaxStableDiffusionPipeline.from_pretrained(
         "CompVis/stable-diffusion-v1-4"   ,							revision="bf16"   ,							dtype=jnp.bfloataa )

     lowercase__			       =  (
         "A cinematic film still of Morgan Freeman starring as Jimi Hendrix, portrait, 40mm lens, shallow depth of"
         " field, close up, split lighting, cinematic"
     )

     lowercase__			       =  jax.random.PRNGKey(0 )
     lowercase__			       =  50

     lowercase__			       =  jax.device_count()
     lowercase__			       =  num_samples * [prompt]
     lowercase__			       =  pipeline.prepare_inputs(_lowercase )

     # shard inputs and rng
     lowercase__			       =  replicate(_lowercase )
     lowercase__			       =  jax.random.split(_lowercase   ,							_lowercase )
     lowercase__			       =  shard(_lowercase )

     lowercase__			       =  pipeline(_lowercase   ,							_lowercase   ,							_lowercase   ,							_lowercase   ,							jit=_lowercase ).images

     assert images.shape == (num_samples, 1, 5_12, 5_12, 3)
     if jax.device_count() == 8:
        assert np.abs((np.abs(images[0, 0, :2, :2, -2:]   ,							dtype=np.floataa ).sum() - 0.04003906) ) < 1e-3
        assert np.abs((np.abs(_lowercase   ,							dtype=np.floataa ).sum() - 2373516.75) ) < 5e-1







  def   UpperCAmelCase					(      self  :Tuple ):






     '''simple docstring'''





     lowercase__			       =  FlaxDDIMScheduler(
         beta_start=0.00085   ,							beta_end=0.012   ,							beta_schedule="scaled_linear"   ,							set_alpha_to_one=_lowercase   ,							steps_offset=1   ,							)

     lowercase__       ,							lowercase__			       =  FlaxStableDiffusionPipeline.from_pretrained(
         "CompVis/stable-diffusion-v1-4"   ,							revision="bf16"   ,							dtype=jnp.bfloataa   ,							scheduler=_lowercase   ,							safety_checker=_lowercase   ,							)
     lowercase__			       =  scheduler.create_state()

     lowercase__			       =  scheduler_state

     lowercase__			       =  (
         "A cinematic film still of Morgan Freeman starring as Jimi Hendrix, portrait, 40mm lens, shallow depth of"
         " field, close up, split lighting, cinematic"
     )

     lowercase__			       =  jax.random.PRNGKey(0 )
     lowercase__			       =  50

     lowercase__			       =  jax.device_count()
     lowercase__			       =  num_samples * [prompt]
     lowercase__			       =  pipeline.prepare_inputs(_lowercase )

     # shard inputs and rng
     lowercase__			       =  replicate(_lowercase )
     lowercase__			       =  jax.random.split(_lowercase   ,							_lowercase )
     lowercase__			       =  shard(_lowercase )

     lowercase__			       =  pipeline(_lowercase   ,							_lowercase   ,							_lowercase   ,							_lowercase   ,							jit=_lowercase ).images

     assert images.shape == (num_samples, 1, 5_12, 5_12, 3)
     if jax.device_count() == 8:
        assert np.abs((np.abs(images[0, 0, :2, :2, -2:]   ,							dtype=np.floataa ).sum() - 0.045043945) ) < 1e-3
        assert np.abs((np.abs(_lowercase   ,							dtype=np.floataa ).sum() - 2347693.5) ) < 5e-1







  def   UpperCAmelCase					(      self  :List[str] ):






     '''simple docstring'''





     lowercase__			       =  (
         "A cinematic film still of Morgan Freeman starring as Jimi Hendrix, portrait, 40mm lens, shallow depth of"
         " field, close up, split lighting, cinematic"
     )

     lowercase__			       =  jax.device_count()
     lowercase__			       =  num_samples * [prompt]
     lowercase__			       =  jax.random.split(jax.random.PRNGKey(0 )   ,							_lowercase )

     lowercase__       ,							lowercase__			       =  FlaxStableDiffusionPipeline.from_pretrained(
         "CompVis/stable-diffusion-v1-4"   ,							revision="bf16"   ,							dtype=jnp.bfloataa   ,							safety_checker=_lowercase   ,							)

     lowercase__			       =  replicate(_lowercase )
     lowercase__			       =  pipeline.prepare_inputs(_lowercase )
     lowercase__			       =  shard(_lowercase )
     lowercase__			       =  pipeline(_lowercase   ,							_lowercase   ,							_lowercase   ,							jit=_lowercase ).images
     assert images.shape == (num_samples, 1, 5_12, 5_12, 3)
     lowercase__			       =  images[2, 0, 2_56, 10:17, 1]

     # With memory efficient attention
     lowercase__       ,							lowercase__			       =  FlaxStableDiffusionPipeline.from_pretrained(
         "CompVis/stable-diffusion-v1-4"   ,							revision="bf16"   ,							dtype=jnp.bfloataa   ,							safety_checker=_lowercase   ,							use_memory_efficient_attention=_lowercase   ,							)

     lowercase__			       =  replicate(_lowercase )
     lowercase__			       =  pipeline.prepare_inputs(_lowercase )
     lowercase__			       =  shard(_lowercase )
     lowercase__			       =  pipeline(_lowercase   ,							_lowercase   ,							_lowercase   ,							jit=_lowercase ).images
     assert images_eff.shape == (num_samples, 1, 5_12, 5_12, 3)
     lowercase__			       =  images[2, 0, 2_56, 10:17, 1]

     # I checked the results visually and they are very similar. However, I saw that the max diff is `1` and the `sum`
     # over the 8 images is exactly `256`, which is very suspicious. Testing a random slice for now.
     assert abs(slice_eff - slice ).max() < 1e-2













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"] )






