


'''simple docstring'''






import unittest

import numpy as np

from transformers import is_flax_available
from transformers.testing_utils import require_flax

from ..test_modeling_flax_common import ids_tensor


if is_flax_available():
							import jax
							import jax.numpy as jnp

							from transformers.generation import (
							    FlaxForcedBOSTokenLogitsProcessor,
							    FlaxForcedEOSTokenLogitsProcessor,
							    FlaxLogitsProcessorList,
							    FlaxMinLengthLogitsProcessor,
							    FlaxTemperatureLogitsWarper,
							    FlaxTopKLogitsWarper,
							    FlaxTopPLogitsWarper,
							)




@require_flax
class 	a__       (							unittest.TestCase						):





							'''simple docstring'''






							def 						__SCREAMING_SNAKE_CASE							(	self      ,					lowerCamelCase_      ,					lowerCamelCase_     ) ->							Dict:
														lowerCAmelCase__      =			jnp.ones((batch_size, length)     ) / length
														return scores







							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							Any:
														lowerCAmelCase__      =			None
														lowerCAmelCase__      =			20

														lowerCAmelCase__      =			self._get_uniform_logits(batch_size=2      ,					length=lowerCamelCase__     )

														# tweak scores to not be uniform anymore
														lowerCAmelCase__      =			scores.at[1, 5].set((1 / length) + 0.1     )  # peak, 1st batch
														lowerCAmelCase__      =			scores.at[1, 10].set((1 / length) - 0.4     )  # valley, 1st batch

														# compute softmax
														lowerCAmelCase__      =			jax.nn.softmax(lowerCamelCase__      ,					axis=-1     )

														lowerCAmelCase__      =			FlaxTemperatureLogitsWarper(temperature=0.5     )
														lowerCAmelCase__      =			FlaxTemperatureLogitsWarper(temperature=1.3     )

														lowerCAmelCase__      =			jax.nn.softmax(temp_dist_warper_sharper(lowerCamelCase__      ,					scores.copy()      ,					cur_len=lowerCamelCase__     )      ,					axis=-1     )
														lowerCAmelCase__      =			jax.nn.softmax(temp_dist_warper_smoother(lowerCamelCase__      ,					scores.copy()      ,					cur_len=lowerCamelCase__     )      ,					axis=-1     )

														# uniform distribution stays uniform
														self.assertTrue(jnp.allclose(probs[0, :]      ,					warped_prob_sharp[0, :]      ,					atol=1e-3     )     )
														self.assertTrue(jnp.allclose(probs[0, :]      ,					warped_prob_smooth[0, :]      ,					atol=1e-3     )     )

														# sharp peaks get higher, valleys get lower
														self.assertLess(probs[1, :].max()      ,					warped_prob_sharp[1, :].max()     )
														self.assertGreater(probs[1, :].min()      ,					warped_prob_sharp[1, :].min()     )

														# smooth peaks get lower, valleys get higher
														self.assertGreater(probs[1, :].max()      ,					warped_prob_smooth[1, :].max()     )
														self.assertLess(probs[1, :].min()      ,					warped_prob_smooth[1, :].min()     )







							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							Union[str, Any]:
														lowerCAmelCase__      =			None
														lowerCAmelCase__      =			10
														lowerCAmelCase__      =			2

														# create ramp distribution
														lowerCAmelCase__      =			np.broadcast_to(np.arange(lowerCamelCase__     )[None, :]      ,					(batch_size, vocab_size)     ).copy()
														lowerCAmelCase__      =			ramp_logits[1:, : vocab_size // 2] + vocab_size

														lowerCAmelCase__      =			FlaxTopKLogitsWarper(3     )

														lowerCAmelCase__      =			top_k_warp(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )

														# check that correct tokens are filtered
														self.assertListEqual(jnp.isinf(scores[0]     ).tolist()      ,					7 * [True] + 3 * [False]     )
														self.assertListEqual(jnp.isinf(scores[1]     ).tolist()      ,					2 * [True] + 3 * [False] + 5 * [True]     )

														# check special case
														lowerCAmelCase__      =			5
														lowerCAmelCase__      =			FlaxTopKLogitsWarper(top_k=1      ,					filter_value=0.0      ,					min_tokens_to_keep=3     )

														lowerCAmelCase__      =			np.broadcast_to(np.arange(lowerCamelCase__     )[None, :]      ,					(batch_size, length)     ).copy()
														lowerCAmelCase__      =			top_k_warp_safety_check(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )

														# min_tokens overwrites k: 3 tokens are kept => 2 tokens are nullified
														self.assertListEqual((scores == 0.0).sum(axis=-1     ).tolist()      ,					[2, 2]     )







							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							List[str]:
														lowerCAmelCase__      =			None
														lowerCAmelCase__      =			10
														lowerCAmelCase__      =			2

														# create distribution and take log (inverse to Softmax as taken in TopPLogitsWarper)
														lowerCAmelCase__      =			np.log(np.array([[0.3, 0.1, 0.1, 0.5], [0.15, 0.3, 0.3, 0.25]]     )     )

														lowerCAmelCase__      =			FlaxTopPLogitsWarper(0.8     )
														lowerCAmelCase__      =			np.exp(top_p_warp(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )     )

														# dist should be filtered to keep min num values so that sum is >= top_p
														# exp (-inf) => 0
														lowerCAmelCase__      =			np.array([[0.3, 0.0, 0.0, 0.5], [0.0, 0.3, 0.3, 0.25]]     )
														self.assertTrue(np.allclose(lowerCamelCase__      ,					lowerCamelCase__      ,					atol=1e-3     )     )

														# check edge cases with negative and extreme logits
														lowerCAmelCase__      =			np.broadcast_to(np.arange(lowerCamelCase__     )[None, :]      ,					(batch_size, vocab_size)     ).copy() - (
														    vocab_size // 2
														)

														# make ramp_logits more extreme
														lowerCAmelCase__      =			ramp_logits[1] * 1_00.0

														# make sure at least 2 tokens are kept
														lowerCAmelCase__      =			FlaxTopPLogitsWarper(0.9      ,					min_tokens_to_keep=2      ,					filter_value=0.0     )
														lowerCAmelCase__      =			top_p_warp(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )

														# first batch should keep three tokens, second batch would keep only 1, but due to `min_tokens_to_keep=2` keeps 2.
														self.assertListEqual((filtered_dist != 0.0).sum(axis=-1     ).tolist()      ,					[3, 2]     )







							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							List[Any]:
														lowerCAmelCase__      =			20
														lowerCAmelCase__      =			4
														lowerCAmelCase__      =			0

														lowerCAmelCase__      =			FlaxMinLengthLogitsProcessor(min_length=10      ,					eos_token_id=lowerCamelCase__     )

														# check that min length is applied at length 5
														lowerCAmelCase__      =			ids_tensor((batch_size, 20)      ,					vocab_size=20     )
														lowerCAmelCase__      =			5
														lowerCAmelCase__      =			self._get_uniform_logits(lowerCamelCase__      ,					lowerCamelCase__     )
														lowerCAmelCase__      =			min_dist_processor(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )
														self.assertListEqual(scores_before_min_length[:, eos_token_id].tolist()      ,					4 * [-float('''inf'''     )]     )

														# check that min length is not applied anymore at length 15
														lowerCAmelCase__      =			self._get_uniform_logits(lowerCamelCase__      ,					lowerCamelCase__     )
														lowerCAmelCase__      =			15
														lowerCAmelCase__      =			min_dist_processor(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )
														self.assertFalse(jnp.isinf(lowerCamelCase__     ).any()     )







							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							Any:
														lowerCAmelCase__      =			20
														lowerCAmelCase__      =			4
														lowerCAmelCase__      =			0

														lowerCAmelCase__      =			FlaxForcedBOSTokenLogitsProcessor(bos_token_id=lowerCamelCase__     )

														# check that all scores are -inf except the bos_token_id score
														lowerCAmelCase__      =			ids_tensor((batch_size, 1)      ,					vocab_size=20     )
														lowerCAmelCase__      =			1
														lowerCAmelCase__      =			self._get_uniform_logits(lowerCamelCase__      ,					lowerCamelCase__     )
														lowerCAmelCase__      =			logits_processor(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )
														self.assertTrue(jnp.isneginf(scores[:, bos_token_id + 1 :]     ).all()     )
														self.assertListEqual(scores[:, bos_token_id].tolist()      ,					4 * [0]     )  # score for bos_token_id shold be zero

														# check that bos_token_id is not forced if current length is greater than 1
														lowerCAmelCase__      =			3
														lowerCAmelCase__      =			self._get_uniform_logits(lowerCamelCase__      ,					lowerCamelCase__     )
														lowerCAmelCase__      =			logits_processor(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )
														self.assertFalse(jnp.isinf(lowerCamelCase__     ).any()     )







							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							Union[str, Any]:
														lowerCAmelCase__      =			20
														lowerCAmelCase__      =			4
														lowerCAmelCase__      =			0
														lowerCAmelCase__      =			5

														lowerCAmelCase__      =			FlaxForcedEOSTokenLogitsProcessor(max_length=lowerCamelCase__      ,					eos_token_id=lowerCamelCase__     )

														# check that all scores are -inf except the eos_token_id when max_length is reached
														lowerCAmelCase__      =			ids_tensor((batch_size, 4)      ,					vocab_size=20     )
														lowerCAmelCase__      =			4
														lowerCAmelCase__      =			self._get_uniform_logits(lowerCamelCase__      ,					lowerCamelCase__     )
														lowerCAmelCase__      =			logits_processor(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )
														self.assertTrue(jnp.isneginf(scores[:, eos_token_id + 1 :]     ).all()     )
														self.assertListEqual(scores[:, eos_token_id].tolist()      ,					4 * [0]     )  # score for eos_token_id should be zero

														# check that eos_token_id is not forced if max_length is not reached
														lowerCAmelCase__      =			3
														lowerCAmelCase__      =			self._get_uniform_logits(lowerCamelCase__      ,					lowerCamelCase__     )
														lowerCAmelCase__      =			logits_processor(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )
														self.assertFalse(jnp.isinf(lowerCamelCase__     ).any()     )







							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							Dict:
														lowerCAmelCase__      =			4
														lowerCAmelCase__      =			10
														lowerCAmelCase__      =			15
														lowerCAmelCase__      =			2
														lowerCAmelCase__      =			1
														lowerCAmelCase__      =			15

														# dummy input_ids and scores
														lowerCAmelCase__      =			ids_tensor((batch_size, sequence_length)      ,					lowerCamelCase__     )
														lowerCAmelCase__      =			input_ids.copy()

														lowerCAmelCase__      =			self._get_uniform_logits(lowerCamelCase__      ,					lowerCamelCase__     )
														lowerCAmelCase__      =			scores.copy()

														# instantiate all dist processors
														lowerCAmelCase__      =			FlaxTemperatureLogitsWarper(temperature=0.5     )
														lowerCAmelCase__      =			FlaxTopKLogitsWarper(3     )
														lowerCAmelCase__      =			FlaxTopPLogitsWarper(0.8     )

														# instantiate all logits processors
														lowerCAmelCase__      =			FlaxMinLengthLogitsProcessor(min_length=10      ,					eos_token_id=lowerCamelCase__     )
														lowerCAmelCase__      =			FlaxForcedBOSTokenLogitsProcessor(bos_token_id=lowerCamelCase__     )
														lowerCAmelCase__      =			FlaxForcedEOSTokenLogitsProcessor(max_length=lowerCamelCase__      ,					eos_token_id=lowerCamelCase__     )

														lowerCAmelCase__      =			10

														# no processor list
														lowerCAmelCase__      =			temp_dist_warp(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )
														lowerCAmelCase__      =			top_k_warp(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )
														lowerCAmelCase__      =			top_p_warp(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )
														lowerCAmelCase__      =			min_dist_proc(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )
														lowerCAmelCase__      =			bos_dist_proc(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )
														lowerCAmelCase__      =			eos_dist_proc(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )

														# with processor list
														lowerCAmelCase__      =			FlaxLogitsProcessorList(
														    [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc]     )
														lowerCAmelCase__      =			processor(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )

														# scores should be equal
														self.assertTrue(jnp.allclose(lowerCamelCase__      ,					lowerCamelCase__      ,					atol=1e-3     )     )

														# input_ids should never be changed
														self.assertListEqual(input_ids.tolist()      ,					input_ids_comp.tolist()     )







							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							List[str]:
														lowerCAmelCase__      =			4
														lowerCAmelCase__      =			10
														lowerCAmelCase__      =			15
														lowerCAmelCase__      =			2
														lowerCAmelCase__      =			1
														lowerCAmelCase__      =			15

														# dummy input_ids and scores
														lowerCAmelCase__      =			ids_tensor((batch_size, sequence_length)      ,					lowerCamelCase__     )
														lowerCAmelCase__      =			input_ids.copy()

														lowerCAmelCase__      =			self._get_uniform_logits(lowerCamelCase__      ,					lowerCamelCase__     )
														lowerCAmelCase__      =			scores.copy()

														# instantiate all dist processors
														lowerCAmelCase__      =			FlaxTemperatureLogitsWarper(temperature=0.5     )
														lowerCAmelCase__      =			FlaxTopKLogitsWarper(3     )
														lowerCAmelCase__      =			FlaxTopPLogitsWarper(0.8     )

														# instantiate all logits processors
														lowerCAmelCase__      =			FlaxMinLengthLogitsProcessor(min_length=10      ,					eos_token_id=lowerCamelCase__     )
														lowerCAmelCase__      =			FlaxForcedBOSTokenLogitsProcessor(bos_token_id=lowerCamelCase__     )
														lowerCAmelCase__      =			FlaxForcedEOSTokenLogitsProcessor(max_length=lowerCamelCase__      ,					eos_token_id=lowerCamelCase__     )

														lowerCAmelCase__      =			10

														# no processor list
														def run_no_processor_list(lowerCamelCase_      ,					lowerCamelCase_      ,					lowerCamelCase_     ):
																					lowerCAmelCase__      =			temp_dist_warp(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )
																					lowerCAmelCase__      =			top_k_warp(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )
																					lowerCAmelCase__      =			top_p_warp(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )
																					lowerCAmelCase__      =			min_dist_proc(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )
																					lowerCAmelCase__      =			bos_dist_proc(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )
																					lowerCAmelCase__      =			eos_dist_proc(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )
																					return scores

														# with processor list
														def run_processor_list(lowerCamelCase_      ,					lowerCamelCase_      ,					lowerCamelCase_     ):
																					lowerCAmelCase__      =			FlaxLogitsProcessorList(
																					    [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc]     )
																					lowerCAmelCase__      =			processor(lowerCamelCase__      ,					lowerCamelCase__      ,					cur_len=lowerCamelCase__     )
																					return scores

														lowerCAmelCase__      =			jax.jit(lowerCamelCase__     )
														lowerCAmelCase__      =			jax.jit(lowerCamelCase__     )

														lowerCAmelCase__      =			jitted_run_no_processor_list(lowerCamelCase__      ,					lowerCamelCase__      ,					lowerCamelCase__     )
														lowerCAmelCase__      =			jitted_run_processor_list(lowerCamelCase__      ,					lowerCamelCase__      ,					lowerCamelCase__     )

														# scores should be equal
														self.assertTrue(jnp.allclose(lowerCamelCase__      ,					lowerCamelCase__      ,					atol=1e-3     )     )

														# input_ids should never be changed
														self.assertListEqual(input_ids.tolist()      ,					input_ids_comp.tolist()     )



'''simple docstring'''






import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device


__UpperCAmelCase					       =							False




class 	a__       (							unittest.TestCase						):





							'''simple docstring'''






							pass




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





							'''simple docstring'''






							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							str:
														lowerCAmelCase__      =			VersatileDiffusionImageVariationPipeline.from_pretrained('''shi-labs/versatile-diffusion'''     )
														pipe.to(lowerCamelCase_     )
														pipe.set_progress_bar_config(disable=lowerCamelCase_     )

														lowerCAmelCase__      =			load_image(
														    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'''     )
														lowerCAmelCase__      =			torch.manual_seed(0     )
														lowerCAmelCase__      =			pipe(
														    image=lowerCamelCase_      ,					generator=lowerCamelCase_      ,					guidance_scale=7.5      ,					num_inference_steps=50      ,					output_type='''numpy'''      ,					).images

														lowerCAmelCase__      =			image[0, 2_53:2_56, 2_53:2_56, -1]

														assert image.shape == (1, 5_12, 5_12, 3)
														lowerCAmelCase__      =			np.array([0.0_441, 0.0_469, 0.0_507, 0.0_575, 0.0_632, 0.0_650, 0.0_865, 0.0_909, 0.0_945]     )

														assert np.abs(image_slice.flatten() - expected_slice     ).max() < 1e-2