



'''simple docstring'''







import json
import os
import pickle
import subprocess
from hashlib import mda
from pathlib import Path
from tempfile import gettempdir
from textwrap import dedent
from types import CodeType, FunctionType
from unittest import TestCase
from unittest.mock import patch

import pytest
from multiprocess import Pool
from packaging import version

import datasets
from datasets.fingerprint import Hasher, fingerprint_transform
from datasets.table import InMemoryTable

from .utils import (
    require_regex,
    require_spacy,
    require_spacy_model,
    require_tiktoken,
    require_torch,
    require_transformers,
)

class    lowerCamelCase_				:






   '''simple docstring'''

   def __init__(	self  ,    __UpperCamelCase			):
       UpperCamelCase__	     =      foo







   def __call__(	self			):
       return self.foo

class    lowerCamelCase_				(						datasets.Dataset	):






   '''simple docstring'''

   @fingerprint_transform(inplace=__UpperCamelCase			)
   def 						_UpperCamelCase							(	self  ,    __UpperCamelCase  ,    *__UpperCamelCase  ,    **__UpperCamelCase			):
       return DatasetChild(self.data  ,    fingerprint=__UpperCamelCase			)







   @fingerprint_transform(inplace=__UpperCamelCase			)
   def 						_UpperCamelCase							(	self  ,    __UpperCamelCase  ,    *__UpperCamelCase  ,    **__UpperCamelCase			):
       return DatasetChild(self.data  ,    fingerprint=__UpperCamelCase			)

class    lowerCamelCase_				:






   '''simple docstring'''

   def __init__(	self  ,    __UpperCamelCase			):
       UpperCamelCase__	     =      callable


   def __call__(	self  ,    *__UpperCamelCase  ,    **__UpperCamelCase			):
       if self.callable is not None:
           return self.callable(*__UpperCamelCase  ,    **__UpperCamelCase			)







   def __getstate__(	self			):
       raise pickle.PicklingError()

class    lowerCamelCase_				(						lowerCAmelCase_	):






   '''simple docstring'''

   @require_transformers
   @pytest.mark.integration
   def 						_UpperCamelCase							(	self			):
       from transformers import AutoTokenizer

       def encode(__UpperCamelCase			):
           return tokenizer(__UpperCamelCase			)

       # TODO: add hash consistency tests across sessions
       UpperCamelCase__	     =      AutoTokenizer.from_pretrained("bert-base-uncased"			)
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(lambda __UpperCamelCase			: tokenizer(__UpperCamelCase			)			)			).hexdigest()
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       UpperCamelCase__	     =      AutoTokenizer.from_pretrained("bert-base-cased"			)
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(lambda __UpperCamelCase			: tokenizer(__UpperCamelCase			)			)			).hexdigest()
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       UpperCamelCase__	     =      AutoTokenizer.from_pretrained("bert-base-uncased"			)
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(lambda __UpperCamelCase			: tokenizer(__UpperCamelCase			)			)			).hexdigest()
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)
       self.assertNotEqual(__UpperCamelCase  ,    __UpperCamelCase			)
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)
       self.assertNotEqual(__UpperCamelCase  ,    __UpperCamelCase			)
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)
       self.assertNotEqual(__UpperCamelCase  ,    __UpperCamelCase			)


   @require_transformers
   @pytest.mark.integration
   def 						_UpperCamelCase							(	self			):
       from transformers import AutoTokenizer

       UpperCamelCase__	     =      AutoTokenizer.from_pretrained("gpt2"			)
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       tokenizer("Hello world !"			)  # call once to change the tokenizer's cache
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)







   @require_regex
   def 						_UpperCamelCase							(	self			):
       import regex

       UpperCamelCase__	     =      regex.Regex("foo"			)
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       UpperCamelCase__	     =      regex.Regex("bar"			)
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       UpperCamelCase__	     =      regex.Regex("foo"			)
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)
       self.assertNotEqual(__UpperCamelCase  ,    __UpperCamelCase			)

class    lowerCamelCase_				(						lowerCAmelCase_	):






   '''simple docstring'''

   def 						_UpperCamelCase							(	self			):
       def func():
           return foo

       UpperCamelCase__	     =      [0]
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       UpperCamelCase__	     =      [1]
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       UpperCamelCase__	     =      [0]
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)
       self.assertNotEqual(__UpperCamelCase  ,    __UpperCamelCase			)


   def 						_UpperCamelCase							(	self			):
       def func():
           pass

       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()

       def func():
           pass

       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)


   def 						_UpperCamelCase							(	self			):
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(Foo([0]			)			)			).hexdigest()
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(Foo([1]			)			)			).hexdigest()
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(Foo([0]			)			)			).hexdigest()
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)
       self.assertNotEqual(__UpperCamelCase  ,    __UpperCamelCase			)


   def 						_UpperCamelCase							(	self			):
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(Foo([0]			).__call__			)			).hexdigest()
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(Foo([1]			).__call__			)			).hexdigest()
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(Foo([0]			).__call__			)			).hexdigest()
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)
       self.assertNotEqual(__UpperCamelCase  ,    __UpperCamelCase			)


   def 						_UpperCamelCase							(	self			):
       UpperCamelCase__	     =      (
           "co_argcount",
           "co_kwonlyargcount",
           "co_nlocals",
           "co_stacksize",
           "co_flags",
           "co_code",
           "co_consts",
           "co_names",
           "co_varnames",
           "co_filename",
           "co_name",
           "co_firstlineno",
           "co_lnotab",
           "co_freevars",
           "co_cellvars",
       )

       def _create_code_pyaa(*__UpperCamelCase			):
           if hasattr(args[-3]  ,    "encode"			):
               UpperCamelCase__	     =      list(__UpperCamelCase			)
               UpperCamelCase__	     =      args[-3].encode()  # co_lnotab
               UpperCamelCase__	     =      args[-10].encode()  # co_code
           if hasattr(__UpperCamelCase  ,    "co_posonlyargcount"			):
               if len(__UpperCamelCase			) == 16:
                   return CodeType(*__UpperCamelCase			)
               elif len(__UpperCamelCase			) == 15:
                   return CodeType(args[0]  ,    0  ,    *args[1:]			)
               return CodeType(args[0]  ,    0  ,    0  ,    *args[1:]			)
           elif hasattr(__UpperCamelCase  ,    "co_kwonlyargcount"			):
               if len(__UpperCamelCase			) == 16:
                   return CodeType(args[0]  ,    *args[2:]			)
               elif len(__UpperCamelCase			) == 15:
                   return CodeType(*__UpperCamelCase			)
               return CodeType(args[0]  ,    0  ,    *args[1:]			)
           if len(__UpperCamelCase			) == 16:
               return CodeType(args[0]  ,    *args[3:]			)
           elif len(__UpperCamelCase			) == 15:
               return CodeType(args[0]  ,    *args[2:]			)
           return CodeType(*__UpperCamelCase			)

       def create_ipython_func(__UpperCamelCase  ,    __UpperCamelCase			):
           def func():
               return returned_obj

           UpperCamelCase__	     =      func.__code__
           # Use _create_code from dill in order to make it work for different python versions
           if datasets.config.PY_VERSION < version.parse("3.8"			):
               UpperCamelCase__	     =      _create_code_pyaa(
                   *[getattr(__UpperCamelCase  ,    __UpperCamelCase			) if k != "co_filename" else co_filename for k in code_args_pyaa]			)
           else:
               UpperCamelCase__	     =      code.replace(co_filename=__UpperCamelCase			)
           return FunctionType(__UpperCamelCase  ,    func.__globals__  ,    func.__name__  ,    func.__defaults__  ,    func.__closure__			)

       UpperCamelCase__     ,	UpperCamelCase__	     =      "<ipython-input-2-e0383a102aae>", [0]
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(create_ipython_func(__UpperCamelCase  ,    __UpperCamelCase			)			)			).hexdigest()
       UpperCamelCase__     ,	UpperCamelCase__	     =      "<ipython-input-2-e0383a102aae>", [1]
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(create_ipython_func(__UpperCamelCase  ,    __UpperCamelCase			)			)			).hexdigest()
       UpperCamelCase__     ,	UpperCamelCase__	     =      "<ipython-input-5-713f6613acf3>", [0]
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(create_ipython_func(__UpperCamelCase  ,    __UpperCamelCase			)			)			).hexdigest()
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)
       self.assertNotEqual(__UpperCamelCase  ,    __UpperCamelCase			)

       UpperCamelCase__     ,	UpperCamelCase__	     =      os.path.join(gettempdir()  ,    "ipykernel_12345"  ,    "321456789.py"			), [0]
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(create_ipython_func(__UpperCamelCase  ,    __UpperCamelCase			)			)			).hexdigest()
       UpperCamelCase__     ,	UpperCamelCase__	     =      os.path.join(gettempdir()  ,    "ipykernel_12345"  ,    "321456789.py"			), [1]
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(create_ipython_func(__UpperCamelCase  ,    __UpperCamelCase			)			)			).hexdigest()
       UpperCamelCase__     ,	UpperCamelCase__	     =      os.path.join(gettempdir()  ,    "ipykernel_12345"  ,    "654123987.py"			), [0]
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(create_ipython_func(__UpperCamelCase  ,    __UpperCamelCase			)			)			).hexdigest()
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)
       self.assertNotEqual(__UpperCamelCase  ,    __UpperCamelCase			)







   def 						_UpperCamelCase							(	self			):
       UpperCamelCase__     ,	UpperCamelCase__	     =      [0], [1]

       def func():
           return foo, bar

       UpperCamelCase__	     =      "__main__"

       def globalvars_mocka_side_effect(__UpperCamelCase  ,    *__UpperCamelCase  ,    **__UpperCamelCase			):
           return {"foo": foo, "bar": bar}

       def globalvars_mocka_side_effect(__UpperCamelCase  ,    *__UpperCamelCase  ,    **__UpperCamelCase			):
           return {"bar": bar, "foo": foo}

       with patch("dill.detect.globalvars"  ,    side_effect=__UpperCamelCase			) as globalvars_mocka:
           UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
           self.assertGreater(globalvars_mocka.call_count  ,    0			)
       with patch("dill.detect.globalvars"  ,    side_effect=__UpperCamelCase			) as globalvars_mocka:
           UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
           self.assertGreater(globalvars_mocka.call_count  ,    0			)
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)

class    lowerCamelCase_				(						lowerCAmelCase_	):






   '''simple docstring'''

   def 						_UpperCamelCase							(	self			):
       UpperCamelCase__	     =      Hasher.hash("hello"			)
       UpperCamelCase__	     =      Hasher.hash("hello"			)
       UpperCamelCase__	     =      Hasher.hash("there"			)
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)
       self.assertNotEqual(__UpperCamelCase  ,    __UpperCamelCase			)


   def 						_UpperCamelCase							(	self			):
       UpperCamelCase__	     =      Hasher.hash(Foo("hello"			)			)
       UpperCamelCase__	     =      Hasher.hash(Foo("hello"			)			)
       UpperCamelCase__	     =      Hasher.hash(Foo("there"			)			)
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)
       self.assertNotEqual(__UpperCamelCase  ,    __UpperCamelCase			)


   def 						_UpperCamelCase							(	self			):
       UpperCamelCase__	     =      Hasher()
       for x in ["hello", Foo("hello"			)]:
           hasher.update(__UpperCamelCase			)
       UpperCamelCase__	     =      hasher.hexdigest()
       UpperCamelCase__	     =      Hasher()
       for x in ["hello", Foo("hello"			)]:
           hasher.update(__UpperCamelCase			)
       UpperCamelCase__	     =      hasher.hexdigest()
       UpperCamelCase__	     =      Hasher()
       for x in ["there", Foo("there"			)]:
           hasher.update(__UpperCamelCase			)
       UpperCamelCase__	     =      hasher.hexdigest()
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)
       self.assertNotEqual(__UpperCamelCase  ,    __UpperCamelCase			)


   def 						_UpperCamelCase							(	self			):
       with self.assertRaises(pickle.PicklingError			):
           Hasher.hash(UnpicklableCallable(Foo("hello"			)			)			)


   def 						_UpperCamelCase							(	self			):
       UpperCamelCase__	     =      "abc"
       UpperCamelCase__	     =      [string, string]  # two strings have the same ids
       UpperCamelCase__	     =      [string, string]
       UpperCamelCase__	     =      json.loads(f'["{string}", "{string}"]'			)  # two strings have different ids
       self.assertIs(obja[0]  ,    __UpperCamelCase			)
       self.assertIs(obja[0]  ,    obja[1]			)
       self.assertIs(obja[0]  ,    __UpperCamelCase			)
       self.assertIs(obja[0]  ,    obja[1]			)
       self.assertIsNot(obja[0]  ,    __UpperCamelCase			)
       self.assertIsNot(obja[0]  ,    obja[1]			)
       UpperCamelCase__	     =      Hasher.hash(__UpperCamelCase			)
       UpperCamelCase__	     =      Hasher.hash(__UpperCamelCase			)
       UpperCamelCase__	     =      Hasher.hash(__UpperCamelCase			)
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)


   @require_tiktoken
   def 						_UpperCamelCase							(	self			):
       import tiktoken

       UpperCamelCase__	     =      tiktoken.get_encoding("gpt2"			)
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       UpperCamelCase__	     =      tiktoken.get_encoding("r50k_base"			)
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       UpperCamelCase__	     =      tiktoken.get_encoding("gpt2"			)
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)
       self.assertNotEqual(__UpperCamelCase  ,    __UpperCamelCase			)


   @require_torch
   def 						_UpperCamelCase							(	self			):
       import torch

       UpperCamelCase__	     =      torch.tensor([1.0]			)
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       UpperCamelCase__	     =      torch.tensor([2.0]			)
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       UpperCamelCase__	     =      torch.tensor([1.0]			)
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)
       self.assertNotEqual(__UpperCamelCase  ,    __UpperCamelCase			)







   @require_spacy
   @require_spacy_model("en_core_web_sm"			)
   @require_spacy_model("fr_core_news_sm"			)
   @pytest.mark.integration
   def 						_UpperCamelCase							(	self			):
       import spacy

       UpperCamelCase__	     =      spacy.load("en_core_web_sm"			)
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       UpperCamelCase__	     =      spacy.load("fr_core_news_sm"			)
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       UpperCamelCase__	     =      spacy.load("en_core_web_sm"			)
       UpperCamelCase__	     =      mda(datasets.utils.py_utils.dumps(__UpperCamelCase			)			).hexdigest()
       self.assertEqual(__UpperCamelCase  ,    __UpperCamelCase			)
       self.assertNotEqual(__UpperCamelCase  ,    __UpperCamelCase			)





@pytest.mark.integration
def     snake_case__			(lowerCAmelCase_						):
    UpperCamelCase__	     =      tmp_path / "dir1"
    UpperCamelCase__	     =      tmp_path / "dir2"
    dira.mkdir()
    dira.mkdir()
    UpperCamelCase__	     =      "script.py"
    UpperCamelCase__	     =      dedent(
        "\n    from datasets.fingerprint import Hasher\n    def foo():\n        pass\n    print(Hasher.hash(foo))\n    "						)
    UpperCamelCase__	     =      dira / script_filename
    UpperCamelCase__	     =      dira / script_filename
    with script_patha.open("w"						) as f:
        f.write(lowerCAmelCase_						)
    with script_patha.open("w"						) as f:
        f.write(lowerCAmelCase_						)
    UpperCamelCase__	     =      subprocess.check_output(["python", str(lowerCAmelCase_						)]						)
    UpperCamelCase__	     =      subprocess.check_output(["python", str(lowerCAmelCase_						)]						)
    assert fingerprinta == fingerprinta





def     snake_case__			():
    UpperCamelCase__	     =      {"a": [0, 1, 2]}
    UpperCamelCase__	     =      DatasetChild(InMemoryTable.from_pydict(lowerCAmelCase_						)						)
    UpperCamelCase__	     =      dataset.funca()._fingerprint
    assert expected_fingerprint == dataset.funca()._fingerprint
    assert expected_fingerprint != dataset.funca()._fingerprint

    with Pool(2						) as p:
        assert expected_fingerprint == p.apply_async(dataset.funca						).get()._fingerprint
        assert expected_fingerprint != p.apply_async(dataset.funca						).get()._fingerprint





def     snake_case__			():
    UpperCamelCase__	     =      {"a": [0, 1, 2]}

    class    lowerCamelCase_				(						datasets.Dataset	):






       '''simple docstring'''

       @fingerprint_transform(inplace=__UpperCamelCase			)
       def 						_UpperCamelCase							(	self  ,    __UpperCamelCase			):
           return DummyDatasetChild(self.data  ,    fingerprint=__UpperCamelCase			)

    UpperCamelCase__	     =      DummyDatasetChild(InMemoryTable.from_pydict(lowerCAmelCase_						)						).func()

    class    lowerCamelCase_				(						datasets.Dataset	):






       '''simple docstring'''

       @fingerprint_transform(inplace=__UpperCamelCase  ,    version="1.0.0"			)
       def 						_UpperCamelCase							(	self  ,    __UpperCamelCase			):
           return DummyDatasetChild(self.data  ,    fingerprint=__UpperCamelCase			)

    UpperCamelCase__	     =      DummyDatasetChild(InMemoryTable.from_pydict(lowerCAmelCase_						)						).func()

    class    lowerCamelCase_				(						datasets.Dataset	):






       '''simple docstring'''

       @fingerprint_transform(inplace=__UpperCamelCase  ,    version="2.0.0"			)
       def 						_UpperCamelCase							(	self  ,    __UpperCamelCase			):
           return DummyDatasetChild(self.data  ,    fingerprint=__UpperCamelCase			)

    UpperCamelCase__	     =      DummyDatasetChild(InMemoryTable.from_pydict(lowerCAmelCase_						)						).func()

    assert len({fingeprint_no_version, fingeprint_a, fingeprint_a}						) == 3





def     snake_case__			():
    # AttributeError: module 'dill._dill' has no attribute 'stack'
    UpperCamelCase__	     =      Hasher()
    hasher.update(lambda lowerCAmelCase_						: x						)









'''simple docstring'''







import bisect
import copy
from collections import defaultdict

import numpy as np
from torch.utils.data import BatchSampler, Sampler

from utils import logger





def     snake_case__			(lowerCAmelCase_       ,	lowerCAmelCase_						):
    UpperCamelCase__	     =      copy.deepcopy(lowerCAmelCase_						)
    UpperCamelCase__	     =      sorted(lowerCAmelCase_						)
    UpperCamelCase__	     =      [bisect.bisect_right(lowerCAmelCase_       ,	lowerCAmelCase_						) for y in x]
    return quantized





def     snake_case__			(lowerCAmelCase_       ,	lowerCAmelCase_=0						):
    UpperCamelCase__	     =      np.arange(start=3       ,	stop=lowerCAmelCase_       ,	step=4						).tolist() if k > 0 else [10]
    UpperCamelCase__	     =      _quantize(lowerCAmelCase_       ,	lowerCAmelCase_						)
    # count number of elements per group
    UpperCamelCase__	     =      np.unique(lowerCAmelCase_       ,	return_counts=lowerCAmelCase_						)[1]
    UpperCamelCase__	     =      [0] + bins + [np.inf]
    logger.info("Using {} as bins for aspect lengths quantization".format(lowerCAmelCase_						)						)
    logger.info("Count of instances per bin: {}".format(lowerCAmelCase_						)						)
    return groups





class    lowerCamelCase_				(						lowerCAmelCase_	):






   '''simple docstring'''

   def __init__(	self  ,    __UpperCamelCase  ,    __UpperCamelCase  ,    __UpperCamelCase			):
       if not isinstance(__UpperCamelCase  ,    __UpperCamelCase			):
           raise ValueError(
               "sampler should be an instance of torch.utils.data.Sampler, but got sampler={}".format(__UpperCamelCase			)			)
       UpperCamelCase__	     =      sampler
       UpperCamelCase__	     =      group_ids
       UpperCamelCase__	     =      batch_size


   def __iter__(	self			):
       UpperCamelCase__	     =      defaultdict(__UpperCamelCase			)
       UpperCamelCase__	     =      defaultdict(__UpperCamelCase			)

       UpperCamelCase__	     =      0
       for idx in self.sampler:
           UpperCamelCase__	     =      self.group_ids[idx]
           buffer_per_group[group_id].append(__UpperCamelCase			)
           samples_per_group[group_id].append(__UpperCamelCase			)
           if len(buffer_per_group[group_id]			) == self.batch_size:
               yield buffer_per_group[group_id]  # TODO
               num_batches += 1
               del buffer_per_group[group_id]
           assert len(buffer_per_group[group_id]			) < self.batch_size

       # now we have run out of elements that satisfy
       # the group criteria, let's return the remaining
       # elements so that the size of the sampler is
       # deterministic
       UpperCamelCase__	     =      len(self			)
       UpperCamelCase__	     =      expected_num_batches - num_batches
       if num_remaining > 0:
           # for the remaining batches, group the batches by similar lengths
           UpperCamelCase__	     =      []
           for group_id, idxs in sorted(buffer_per_group.items()  ,    key=lambda __UpperCamelCase			: x[0]			):
               batch_idx.extend(__UpperCamelCase			)
               if len(__UpperCamelCase			) >= self.batch_size:
                   yield batch_idx[: self.batch_size]
                   UpperCamelCase__	     =      batch_idx[self.batch_size :]
                   num_remaining -= 1
           if len(__UpperCamelCase			) > 0:
               yield batch_idx
               num_remaining -= 1
       assert num_remaining == 0







   def __len__(	self			):
       return (len(self.sampler			) + self.batch_size - 1) // self.batch_size




