





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 					__snake_case	(  unittest.TestCase    ):


    '''simple docstring'''







    def  lowercase_					(       self   ,				A_   ,				A_     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			jnp.ones((batch_size, length)     ) / length
        return scores



    def  lowercase_					(       self     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			None
        SCREAMING_SNAKE_CASE__											=			20

        SCREAMING_SNAKE_CASE__											=			self._get_uniform_logits(batch_size=2   ,				length=A_     )

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

        # compute softmax
        SCREAMING_SNAKE_CASE__											=			jax.nn.softmax(A_   ,				axis=-1     )

        SCREAMING_SNAKE_CASE__											=			FlaxTemperatureLogitsWarper(temperature=0.5     )
        SCREAMING_SNAKE_CASE__											=			FlaxTemperatureLogitsWarper(temperature=1.3     )

        SCREAMING_SNAKE_CASE__											=			jax.nn.softmax(temp_dist_warper_sharper(A_   ,				scores.copy()   ,				cur_len=A_     )   ,				axis=-1     )
        SCREAMING_SNAKE_CASE__											=			jax.nn.softmax(temp_dist_warper_smoother(A_   ,				scores.copy()   ,				cur_len=A_     )   ,				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  lowercase_					(       self     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			None
        SCREAMING_SNAKE_CASE__											=			10
        SCREAMING_SNAKE_CASE__											=			2

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

        SCREAMING_SNAKE_CASE__											=			FlaxTopKLogitsWarper(3     )

        SCREAMING_SNAKE_CASE__											=			top_k_warp(A_   ,				A_   ,				cur_len=A_     )

        # 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
        SCREAMING_SNAKE_CASE__											=			5
        SCREAMING_SNAKE_CASE__											=			FlaxTopKLogitsWarper(top_k=1   ,				filter_value=0.0   ,				min_tokens_to_keep=3     )

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

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



    def  lowercase_					(       self     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			None
        SCREAMING_SNAKE_CASE__											=			10
        SCREAMING_SNAKE_CASE__											=			2

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

        SCREAMING_SNAKE_CASE__											=			FlaxTopPLogitsWarper(0.8     )
        SCREAMING_SNAKE_CASE__											=			np.exp(top_p_warp(A_   ,				A_   ,				cur_len=A_     )     )

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

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

        # make ramp_logits more extreme
        SCREAMING_SNAKE_CASE__											=			ramp_logits[1] * 100.0

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

        # 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  lowercase_					(       self     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			20
        SCREAMING_SNAKE_CASE__											=			4
        SCREAMING_SNAKE_CASE__											=			0

        SCREAMING_SNAKE_CASE__											=			FlaxMinLengthLogitsProcessor(min_length=10   ,				eos_token_id=A_     )

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

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



    def  lowercase_					(       self     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			20
        SCREAMING_SNAKE_CASE__											=			4
        SCREAMING_SNAKE_CASE__											=			0

        SCREAMING_SNAKE_CASE__											=			FlaxForcedBOSTokenLogitsProcessor(bos_token_id=A_     )

        # check that all scores are -inf except the bos_token_id score
        SCREAMING_SNAKE_CASE__											=			ids_tensor((batch_size, 1)   ,				vocab_size=20     )
        SCREAMING_SNAKE_CASE__											=			1
        SCREAMING_SNAKE_CASE__											=			self._get_uniform_logits(A_   ,				A_     )
        SCREAMING_SNAKE_CASE__											=			logits_processor(A_   ,				A_   ,				cur_len=A_     )
        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
        SCREAMING_SNAKE_CASE__											=			3
        SCREAMING_SNAKE_CASE__											=			self._get_uniform_logits(A_   ,				A_     )
        SCREAMING_SNAKE_CASE__											=			logits_processor(A_   ,				A_   ,				cur_len=A_     )
        self.assertFalse(jnp.isinf(A_     ).any()     )



    def  lowercase_					(       self     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			20
        SCREAMING_SNAKE_CASE__											=			4
        SCREAMING_SNAKE_CASE__											=			0
        SCREAMING_SNAKE_CASE__											=			5

        SCREAMING_SNAKE_CASE__											=			FlaxForcedEOSTokenLogitsProcessor(max_length=A_   ,				eos_token_id=A_     )

        # check that all scores are -inf except the eos_token_id when max_length is reached
        SCREAMING_SNAKE_CASE__											=			ids_tensor((batch_size, 4)   ,				vocab_size=20     )
        SCREAMING_SNAKE_CASE__											=			4
        SCREAMING_SNAKE_CASE__											=			self._get_uniform_logits(A_   ,				A_     )
        SCREAMING_SNAKE_CASE__											=			logits_processor(A_   ,				A_   ,				cur_len=A_     )
        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
        SCREAMING_SNAKE_CASE__											=			3
        SCREAMING_SNAKE_CASE__											=			self._get_uniform_logits(A_   ,				A_     )
        SCREAMING_SNAKE_CASE__											=			logits_processor(A_   ,				A_   ,				cur_len=A_     )
        self.assertFalse(jnp.isinf(A_     ).any()     )



    def  lowercase_					(       self     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			4
        SCREAMING_SNAKE_CASE__											=			10
        SCREAMING_SNAKE_CASE__											=			15
        SCREAMING_SNAKE_CASE__											=			2
        SCREAMING_SNAKE_CASE__											=			1
        SCREAMING_SNAKE_CASE__											=			15

        # dummy input_ids and scores
        SCREAMING_SNAKE_CASE__											=			ids_tensor((batch_size, sequence_length)   ,				A_     )
        SCREAMING_SNAKE_CASE__											=			input_ids.copy()

        SCREAMING_SNAKE_CASE__											=			self._get_uniform_logits(A_   ,				A_     )
        SCREAMING_SNAKE_CASE__											=			scores.copy()

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

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

        SCREAMING_SNAKE_CASE__											=			10

        # no processor list
        SCREAMING_SNAKE_CASE__											=			temp_dist_warp(A_   ,				A_   ,				cur_len=A_     )
        SCREAMING_SNAKE_CASE__											=			top_k_warp(A_   ,				A_   ,				cur_len=A_     )
        SCREAMING_SNAKE_CASE__											=			top_p_warp(A_   ,				A_   ,				cur_len=A_     )
        SCREAMING_SNAKE_CASE__											=			min_dist_proc(A_   ,				A_   ,				cur_len=A_     )
        SCREAMING_SNAKE_CASE__											=			bos_dist_proc(A_   ,				A_   ,				cur_len=A_     )
        SCREAMING_SNAKE_CASE__											=			eos_dist_proc(A_   ,				A_   ,				cur_len=A_     )

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

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

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




    def  lowercase_					(       self     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			4
        SCREAMING_SNAKE_CASE__											=			10
        SCREAMING_SNAKE_CASE__											=			15
        SCREAMING_SNAKE_CASE__											=			2
        SCREAMING_SNAKE_CASE__											=			1
        SCREAMING_SNAKE_CASE__											=			15

        # dummy input_ids and scores
        SCREAMING_SNAKE_CASE__											=			ids_tensor((batch_size, sequence_length)   ,				A_     )
        SCREAMING_SNAKE_CASE__											=			input_ids.copy()

        SCREAMING_SNAKE_CASE__											=			self._get_uniform_logits(A_   ,				A_     )
        SCREAMING_SNAKE_CASE__											=			scores.copy()

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

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

        SCREAMING_SNAKE_CASE__											=			10

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

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

        SCREAMING_SNAKE_CASE__											=			jax.jit(A_     )
        SCREAMING_SNAKE_CASE__											=			jax.jit(A_     )

        SCREAMING_SNAKE_CASE__											=			jitted_run_no_processor_list(A_   ,				A_   ,				A_     )
        SCREAMING_SNAKE_CASE__											=			jitted_run_processor_list(A_   ,				A_   ,				A_     )

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

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





"""simple docstring"""







import importlib
import shutil
import threading
import warnings
from typing import List

import fsspec
import fsspec.asyn

from . import compression
from .hffilesystem import HfFileSystem


A		=						importlib.util.find_spec('s3fs') is not None

if _has_safs:
			from .safilesystem import SaFileSystem  # noqa: F401

A		=						[
    compression.BzaFileSystem,
    compression.GzipFileSystem,
    compression.LzaFileSystem,
    compression.XzFileSystem,
    compression.ZstdFileSystem,
]

# Register custom filesystems
for fs_class in COMPRESSION_FILESYSTEMS + [HfFileSystem]:
			if fs_class.protocol in fsspec.registry and fsspec.registry[fs_class.protocol] is not fs_class:
						warnings.warn(F'''A filesystem protocol was already set for {fs_class.protocol} and will be overwritten.''')
			fsspec.register_implementation(fs_class.protocol, fs_class, clobber=True)

def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							str ):
						"""simple docstring"""






						if "://" in dataset_path:
												snake_case   :			List[str]						    = dataset_path.split("://" )[1]
						return dataset_path

def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							fsspec.AbstractFileSystem ):
						"""simple docstring"""






						if fs is not None and fs.protocol != "file":
												return True
						else:
												return False

def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							fsspec.AbstractFileSystem     ,		lowerCamelCase_:							str     ,		lowerCamelCase_:							str ):
						"""simple docstring"""






						snake_case   :			int						    = not is_remote_filesystem(lowerCamelCase_ )
						if is_local:
												# LocalFileSystem.mv does copy + rm, it is more efficient to simply move a local directory
												shutil.move(fs._strip_protocol(lowerCamelCase_ )     ,		fs._strip_protocol(lowerCamelCase_ ) )
						else:
												fs.mv(lowerCamelCase_     ,		lowerCamelCase_     ,		recursive=lowerCamelCase_ )

def  __SCREAMING_SNAKE_CASE		(			):
						"""simple docstring"""






						if hasattr(fsspec.asyn     ,		"reset_lock" ):
												# for future fsspec>2022.05.0
												fsspec.asyn.reset_lock()
						else:
												snake_case   :			Union[str, Any]						    = None
												snake_case   :			Optional[int]						    = None
												snake_case   :			List[str]						    = threading.Lock()



