import gc
import unittest

from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax


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

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






    '''simple docstring'''




    def      _a    (    self ):
       # clean up the VRAM after each test
       super().tearDown()
       gc.collect()




    def      _a    (    self ):
       lowerCAmelCase_  ,	lowerCAmelCase_:							Tuple       =	FlaxControlNetModel.from_pretrained(
           "lllyasviel/sd-controlnet-canny"       ,						from_pt=lowerCamelCase__       ,						dtype=jnp.bfloataa )
       lowerCAmelCase_  ,	lowerCAmelCase_:							Optional[int]       =	FlaxStableDiffusionControlNetPipeline.from_pretrained(
           "runwayml/stable-diffusion-v1-5"       ,						controlnet=lowerCamelCase__       ,						from_pt=lowerCamelCase__       ,						dtype=jnp.bfloataa )
       lowerCAmelCase_:							Any       =	controlnet_params

       lowerCAmelCase_:							Any       =	"bird"
       lowerCAmelCase_:							Optional[int]       =	jax.device_count()
       lowerCAmelCase_:							Optional[int]       =	pipe.prepare_text_inputs([prompts] * num_samples )

       lowerCAmelCase_:							Dict       =	load_image(
           "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd_controlnet/bird_canny.png" )
       lowerCAmelCase_:							List[Any]       =	pipe.prepare_image_inputs([canny_image] * num_samples )

       lowerCAmelCase_:							Any       =	jax.random.PRNGKey(0 )
       lowerCAmelCase_:							List[str]       =	jax.random.split(lowerCamelCase__       ,						jax.device_count() )

       lowerCAmelCase_:							Optional[Any]       =	replicate(lowerCamelCase__ )
       lowerCAmelCase_:							Optional[Any]       =	shard(lowerCamelCase__ )
       lowerCAmelCase_:							int       =	shard(lowerCamelCase__ )

       lowerCAmelCase_:							Optional[Any]       =	pipe(
           prompt_ids=lowerCamelCase__       ,						image=lowerCamelCase__       ,						params=lowerCamelCase__       ,						prng_seed=lowerCamelCase__       ,						num_inference_steps=50       ,						jit=lowerCamelCase__       ,						).images
       assert images.shape == (jax.device_count(), 1, 768, 512, 3)

       lowerCAmelCase_:							Dict       =	images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:] )
       lowerCAmelCase_:							List[Any]       =	images[0, 253:256, 253:256, -1]

       lowerCAmelCase_:							List[str]       =	jnp.asarray(jax.device_get(image_slice.flatten() ) )
       lowerCAmelCase_:							Tuple       =	jnp.array(
           [0.1_6_7_9_6_9, 0.1_1_6_6_9_9, 0.0_8_1_5_4_3, 0.1_5_4_2_9_7, 0.1_3_2_8_1_2, 0.1_0_8_8_8_7, 0.1_6_9_9_2_2, 0.1_6_9_9_2_2, 0.2_0_5_0_7_8] )
       print(F'''output_slice: {output_slice}''' )
       assert jnp.abs(output_slice - expected_slice ).max() < 1E-2




    def      _a    (    self ):
       lowerCAmelCase_  ,	lowerCAmelCase_:							Optional[Any]       =	FlaxControlNetModel.from_pretrained(
           "lllyasviel/sd-controlnet-openpose"       ,						from_pt=lowerCamelCase__       ,						dtype=jnp.bfloataa )
       lowerCAmelCase_  ,	lowerCAmelCase_:							Any       =	FlaxStableDiffusionControlNetPipeline.from_pretrained(
           "runwayml/stable-diffusion-v1-5"       ,						controlnet=lowerCamelCase__       ,						from_pt=lowerCamelCase__       ,						dtype=jnp.bfloataa )
       lowerCAmelCase_:							Dict       =	controlnet_params

       lowerCAmelCase_:							Any       =	"Chef in the kitchen"
       lowerCAmelCase_:							Optional[Any]       =	jax.device_count()
       lowerCAmelCase_:							Dict       =	pipe.prepare_text_inputs([prompts] * num_samples )

       lowerCAmelCase_:							List[str]       =	load_image(
           "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd_controlnet/pose.png" )
       lowerCAmelCase_:							int       =	pipe.prepare_image_inputs([pose_image] * num_samples )

       lowerCAmelCase_:							str       =	jax.random.PRNGKey(0 )
       lowerCAmelCase_:							Optional[int]       =	jax.random.split(lowerCamelCase__       ,						jax.device_count() )

       lowerCAmelCase_:							List[str]       =	replicate(lowerCamelCase__ )
       lowerCAmelCase_:							Optional[Any]       =	shard(lowerCamelCase__ )
       lowerCAmelCase_:							Dict       =	shard(lowerCamelCase__ )

       lowerCAmelCase_:							List[str]       =	pipe(
           prompt_ids=lowerCamelCase__       ,						image=lowerCamelCase__       ,						params=lowerCamelCase__       ,						prng_seed=lowerCamelCase__       ,						num_inference_steps=50       ,						jit=lowerCamelCase__       ,						).images
       assert images.shape == (jax.device_count(), 1, 768, 512, 3)

       lowerCAmelCase_:							List[Any]       =	images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:] )
       lowerCAmelCase_:							List[Any]       =	images[0, 253:256, 253:256, -1]

       lowerCAmelCase_:							int       =	jnp.asarray(jax.device_get(image_slice.flatten() ) )
       lowerCAmelCase_:							Tuple       =	jnp.array(
           [[0.2_7_1_4_8_4, 0.2_6_1_7_1_9, 0.2_7_5_3_9_1, 0.2_7_7_3_4_4, 0.2_7_9_2_9_7, 0.2_9_1_0_1_6, 0.2_9_4_9_2_2, 0.3_0_2_7_3_4, 0.3_0_2_7_3_4]] )
       print(F'''output_slice: {output_slice}''' )
       assert jnp.abs(output_slice - expected_slice ).max() < 1E-2
import contextlib
import os
import sqlitea

import pytest

from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def 		snake_case__	(		lowercase							,				lowercase					):
   assert isinstance(lowercase							,				lowercase					)
   assert dataset.num_rows == 4
   assert dataset.num_columns == 3
   assert dataset.column_names == ["col_1", "col_2", "col_3"]
   for feature, expected_dtype in expected_features.items():
      assert dataset.features[feature].dtype == expected_dtype
@require_sqlalchemy
@pytest.mark.parametrize("keep_in_memory"							,				[False, True]					)
def 		snake_case__	(		lowercase							,				lowercase							,				lowercase							,				lowercase					):
   lowerCAmelCase_:							Any       =	tmp_path / "cache"
   lowerCAmelCase_:							int       =	{"col_1": "string", "col_2": "int64", "col_3": "float64"}
   with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
      lowerCAmelCase_:							Optional[int]       =	SqlDatasetReader(
          "dataset"							,				"sqlite:///" + sqlite_path							,				cache_dir=lowercase							,				keep_in_memory=lowercase					).read()
   _check_sql_dataset(lowercase							,				lowercase					)
@require_sqlalchemy
@pytest.mark.parametrize(
    "features"							,				[
        None,
        {"col_1": "string", "col_2": "int64", "col_3": "float64"},
        {"col_1": "string", "col_2": "string", "col_3": "string"},
        {"col_1": "int32", "col_2": "int32", "col_3": "int32"},
        {"col_1": "float32", "col_2": "float32", "col_3": "float32"},
    ]							,				)
def 		snake_case__	(		lowercase							,				lowercase							,				lowercase							,				lowercase					):
   lowerCAmelCase_:							List[str]       =	tmp_path / "cache"
   lowerCAmelCase_:							int       =	{"col_1": "string", "col_2": "int64", "col_3": "float64"}
   lowerCAmelCase_:							List[str]       =	features.copy() if features else default_expected_features
   lowerCAmelCase_:							Any       =	(
       Features({feature: Value(lowercase					) for feature, dtype in features.items()}					) if features is not None else None
   )
   lowerCAmelCase_:							int       =	SqlDatasetReader("dataset"							,				"sqlite:///" + sqlite_path							,				features=lowercase							,				cache_dir=lowercase					).read()
   _check_sql_dataset(lowercase							,				lowercase					)
def 		snake_case__	(		lowercase					):
   with contextlib.closing(sqlitea.connect(lowercase					)					) as con:
      lowerCAmelCase_:							Any       =	con.cursor()
      cur.execute("SELECT * FROM dataset"					)
      for row in cur:
         yield row
@require_sqlalchemy
def 		snake_case__	(		lowercase							,				lowercase							,				lowercase					):
   lowerCAmelCase_:							Optional[int]       =	tmp_path / "cache"
   lowerCAmelCase_:							Optional[Any]       =	os.path.join(lowercase							,				"tmp.sql"					)
   lowerCAmelCase_:							str       =	SqlDatasetReader("dataset"							,				"sqlite:///" + sqlite_path							,				cache_dir=lowercase					).read()
   SqlDatasetWriter(lowercase							,				"dataset"							,				"sqlite:///" + output_sqlite_path							,				num_proc=1					).write()

   lowerCAmelCase_:							Union[str, Any]       =	iter_sql_file(lowercase					)
   lowerCAmelCase_:							str       =	iter_sql_file(lowercase					)

   for rowa, rowa in zip(lowercase							,				lowercase					):
      assert rowa == rowa
@require_sqlalchemy
def 		snake_case__	(		lowercase							,				lowercase							,				lowercase					):
   lowerCAmelCase_:							str       =	tmp_path / "cache"
   lowerCAmelCase_:							Optional[int]       =	os.path.join(lowercase							,				"tmp.sql"					)
   lowerCAmelCase_:							Optional[Any]       =	SqlDatasetReader("dataset"							,				"sqlite:///" + sqlite_path							,				cache_dir=lowercase					).read()
   SqlDatasetWriter(lowercase							,				"dataset"							,				"sqlite:///" + output_sqlite_path							,				num_proc=2					).write()

   lowerCAmelCase_:							Optional[Any]       =	iter_sql_file(lowercase					)
   lowerCAmelCase_:							Optional[int]       =	iter_sql_file(lowercase					)

   for rowa, rowa in zip(lowercase							,				lowercase					):
      assert rowa == rowa







@require_sqlalchemy
def 		snake_case__	(		lowercase							,				lowercase							,				lowercase					):
   lowerCAmelCase_:							Union[str, Any]       =	tmp_path / "cache"
   lowerCAmelCase_:							int       =	os.path.join(lowercase							,				"tmp.sql"					)
   lowerCAmelCase_:							Any       =	SqlDatasetReader("dataset"							,				"sqlite:///" + sqlite_path							,				cache_dir=lowercase					).read()
   with pytest.raises(lowercase					):
      SqlDatasetWriter(lowercase							,				"dataset"							,				"sqlite:///" + output_sqlite_path							,				num_proc=0					).write()