




"""simple docstring"""






import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile

import pyarrow as pa
import pyarrow.parquet as pq
import pytest

import datasets
import datasets.config







@pytest.fixture(scope='session'						)
def 	_snake_case     (							):
				_lowerCamelCase	:     Dict       =       10
				_lowerCamelCase	:     List[Any]       =       datasets.Features(
				    {
				        'tokens': datasets.Sequence(datasets.Value('string'						)						),
				        'labels': datasets.Sequence(datasets.ClassLabel(names=['negative', 'positive']						)						),
				        'answers': datasets.Sequence(
				            {
				                'text': datasets.Value('string'						),
				                'answer_start': datasets.Value('int32'						),
				            }						),
				        'id': datasets.Value('int64'						),
				    }						)
				_lowerCamelCase	:     Union[str, Any]       =       datasets.Dataset.from_dict(
				    {
				        'tokens': [['foo'] * 5] * n,
				        'labels': [[1] * 5] * n,
				        'answers': [{'answer_start': [97], 'text': ['1976']}] * 10,
				        'id': list(range(a_						)						),
				    }				,       features=a_				,       )
				return dataset







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__						):
				_lowerCamelCase	:     Tuple       =       str(tmp_path_factory.mktemp('data'						) / 'file.arrow'						)
				dataset.map(cache_file_name=a_						)
				return filename


# FILE_CONTENT + files


lowercase__			=		"""\\n    Text data.\n    Second line of data."""







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     List[Any]       =       tmp_path_factory.mktemp('data'						) / """file.txt"""
				_lowerCamelCase	:     str       =       FILE_CONTENT
				with open(a_				,       'w'						) as f:
								f.write(a_						)
				return filename







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				import bza

				_lowerCamelCase	:     Union[str, Any]       =       tmp_path_factory.mktemp('data'						) / """file.txt.bz2"""
				_lowerCamelCase	:     str       =       bytes(a_				,       'utf-8'						)
				with bza.open(a_				,       'wb'						) as f:
								f.write(a_						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				import gzip

				_lowerCamelCase	:     Dict       =       str(tmp_path_factory.mktemp('data'						) / 'file.txt.gz'						)
				_lowerCamelCase	:     Union[str, Any]       =       bytes(a_				,       'utf-8'						)
				with gzip.open(a_				,       'wb'						) as f:
								f.write(a_						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):

				if datasets.config.LZ4_AVAILABLE:
								import lza.frame

								_lowerCamelCase	:     Tuple       =       tmp_path_factory.mktemp('data'						) / """file.txt.lz4"""
								_lowerCamelCase	:     Any       =       bytes(a_				,       'utf-8'						)
								with lza.frame.open(a_				,       'wb'						) as f:
												f.write(a_						)
								return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__						):

				if datasets.config.PY7ZR_AVAILABLE:
								import pyazr

								_lowerCamelCase	:     Tuple       =       tmp_path_factory.mktemp('data'						) / """file.txt.7z"""
								with pyazr.SevenZipFile(a_				,       'w'						) as archive:
												archive.write(a_				,       arcname=os.path.basename(a_						)						)
								return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__						):
				import tarfile

				_lowerCamelCase	:     int       =       tmp_path_factory.mktemp('data'						) / """file.txt.tar"""
				with tarfile.TarFile(a_				,       'w'						) as f:
								f.add(a_				,       arcname=os.path.basename(a_						)						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				import lzma

				_lowerCamelCase	:     int       =       tmp_path_factory.mktemp('data'						) / """file.txt.xz"""
				_lowerCamelCase	:     Optional[int]       =       bytes(a_				,       'utf-8'						)
				with lzma.open(a_				,       'wb'						) as f:
								f.write(a_						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__						):
				import zipfile

				_lowerCamelCase	:     Any       =       tmp_path_factory.mktemp('data'						) / """file.txt.zip"""
				with zipfile.ZipFile(a_				,       'w'						) as f:
								f.write(a_				,       arcname=os.path.basename(a_						)						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):

				if datasets.config.ZSTANDARD_AVAILABLE:
								import zstandard as zstd

								_lowerCamelCase	:     str       =       tmp_path_factory.mktemp('data'						) / """file.txt.zst"""
								_lowerCamelCase	:     List[Any]       =       bytes(a_				,       'utf-8'						)
								with zstd.open(a_				,       'wb'						) as f:
												f.write(a_						)
								return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     int       =       tmp_path_factory.mktemp('data'						) / """file.xml"""
				_lowerCamelCase	:     List[str]       =       textwrap.dedent(
				    '\\n    <?xml version=\"1.0\" encoding=\"UTF-8\" ?>\n    <tmx version=\"1.4\">\n      <header segtype=\"sentence\" srclang=\"ca\" />\n      <body>\n        <tu>\n          <tuv xml:lang=\"ca\"><seg>Contingut 1</seg></tuv>\n          <tuv xml:lang=\"en\"><seg>Content 1</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang=\"ca\"><seg>Contingut 2</seg></tuv>\n          <tuv xml:lang=\"en\"><seg>Content 2</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang=\"ca\"><seg>Contingut 3</seg></tuv>\n          <tuv xml:lang=\"en\"><seg>Content 3</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang=\"ca\"><seg>Contingut 4</seg></tuv>\n          <tuv xml:lang=\"en\"><seg>Content 4</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang=\"ca\"><seg>Contingut 5</seg></tuv>\n          <tuv xml:lang=\"en\"><seg>Content 5</seg></tuv>\n        </tu>\n      </body>\n    </tmx>'						)
				with open(a_				,       'w'						) as f:
								f.write(a_						)
				return filename


lowercase__			=		[
    {"""col_1""": """0""", """col_2""": 0, """col_3""": 0.0},
    {"""col_1""": """1""", """col_2""": 1, """col_3""": 1.0},
    {"""col_1""": """2""", """col_2""": 2, """col_3""": 2.0},
    {"""col_1""": """3""", """col_2""": 3, """col_3""": 3.0},
]
lowercase__			=		[
    {"""col_1""": """4""", """col_2""": 4, """col_3""": 4.0},
    {"""col_1""": """5""", """col_2""": 5, """col_3""": 5.0},
]
lowercase__			=		{
    """col_1""": ["""0""", """1""", """2""", """3"""],
    """col_2""": [0, 1, 2, 3],
    """col_3""": [0.0, 1.0, 2.0, 3.0],
}

lowercase__			=		[
    {"""col_3""": 0.0, """col_1""": """0""", """col_2""": 0},
    {"""col_3""": 1.0, """col_1""": """1""", """col_2""": 1},
]

lowercase__			=		[
    {"""col_1""": """s0""", """col_2""": 0, """col_3""": 0.0},
    {"""col_1""": """s1""", """col_2""": 1, """col_3""": 1.0},
    {"""col_1""": """s2""", """col_2""": 2, """col_3""": 2.0},
    {"""col_1""": """s3""", """col_2""": 3, """col_3""": 3.0},
]







@pytest.fixture(scope='session'						)
def 	_snake_case     (							):
				return DATA_DICT_OF_LISTS







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     int       =       datasets.Dataset.from_dict(a_						)
				_lowerCamelCase	:     int       =       str(tmp_path_factory.mktemp('data'						) / 'dataset.arrow'						)
				dataset.map(cache_file_name=a_						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     int       =       str(tmp_path_factory.mktemp('data'						) / 'dataset.sqlite'						)
				with contextlib.closing(sqlitea.connect(a_						)						) as con:
								_lowerCamelCase	:     int       =       con.cursor()
								cur.execute('CREATE TABLE dataset(col_1 text, col_2 int, col_3 real)'						)
								for item in DATA:
												cur.execute('INSERT INTO dataset(col_1, col_2, col_3) VALUES (?, ?, ?)'				,       tuple(item.values()						)						)
								con.commit()
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     Optional[Any]       =       str(tmp_path_factory.mktemp('data'						) / 'dataset.csv'						)
				with open(a_				,       'w'				,       newline=''						) as f:
								_lowerCamelCase	:     List[Any]       =       csv.DictWriter(a_				,       fieldnames=['col_1', 'col_2', 'col_3']						)
								writer.writeheader()
								for item in DATA:
												writer.writerow(a_						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     int       =       str(tmp_path_factory.mktemp('data'						) / 'dataset2.csv'						)
				with open(a_				,       'w'				,       newline=''						) as f:
								_lowerCamelCase	:     Optional[int]       =       csv.DictWriter(a_				,       fieldnames=['col_1', 'col_2', 'col_3']						)
								writer.writeheader()
								for item in DATA:
												writer.writerow(a_						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__						):
				import bza

				_lowerCamelCase	:     Optional[Any]       =       tmp_path_factory.mktemp('data'						) / """dataset.csv.bz2"""
				with open(a_				,       'rb'						) as f:
								_lowerCamelCase	:     Tuple       =       f.read()
				# data = bytes(FILE_CONTENT, "utf-8")
				with bza.open(a_				,       'wb'						) as f:
								f.write(a_						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__				,       lowercase__						):
				_lowerCamelCase	:     Union[str, Any]       =       tmp_path_factory.mktemp('data'						) / """dataset.csv.zip"""
				with zipfile.ZipFile(a_				,       'w'						) as f:
								f.write(a_				,       arcname=os.path.basename(a_						)						)
								f.write(a_				,       arcname=os.path.basename(a_						)						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__				,       lowercase__						):
				_lowerCamelCase	:     Tuple       =       tmp_path_factory.mktemp('data'						) / """dataset.csv.zip"""
				with zipfile.ZipFile(a_				,       'w'						) as f:
								f.write(a_				,       arcname=os.path.basename(csv_path.replace('.csv'				,       '.CSV'						)						)						)
								f.write(a_				,       arcname=os.path.basename(csva_path.replace('.csv'				,       '.CSV'						)						)						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__				,       lowercase__						):
				_lowerCamelCase	:     Tuple       =       tmp_path_factory.mktemp('data'						) / """dataset_with_dir.csv.zip"""
				with zipfile.ZipFile(a_				,       'w'						) as f:
								f.write(a_				,       arcname=os.path.join('main_dir'				,       os.path.basename(a_						)						)						)
								f.write(a_				,       arcname=os.path.join('main_dir'				,       os.path.basename(a_						)						)						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     List[str]       =       str(tmp_path_factory.mktemp('data'						) / 'dataset.parquet'						)
				_lowerCamelCase	:     Dict       =       pa.schema(
				    {
				        'col_1': pa.string(),
				        'col_2': pa.intaa(),
				        'col_3': pa.floataa(),
				    }						)
				with open(a_				,       'wb'						) as f:
								_lowerCamelCase	:     str       =       pq.ParquetWriter(a_				,       schema=a_						)
								_lowerCamelCase	:     List[str]       =       pa.Table.from_pydict({k: [DATA[i][k] for i in range(len(a_						)						)] for k in DATA[0]}				,       schema=a_						)
								writer.write_table(a_						)
								writer.close()
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     Tuple       =       str(tmp_path_factory.mktemp('data'						) / 'dataset.json'						)
				_lowerCamelCase	:     Optional[Any]       =       {"""data""": DATA}
				with open(a_				,       'w'						) as f:
								json.dump(a_				,       a_						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     Optional[int]       =       str(tmp_path_factory.mktemp('data'						) / 'dataset.json'						)
				_lowerCamelCase	:     int       =       {"""data""": DATA_DICT_OF_LISTS}
				with open(a_				,       'w'						) as f:
								json.dump(a_				,       a_						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     Optional[Any]       =       str(tmp_path_factory.mktemp('data'						) / 'dataset.jsonl'						)
				with open(a_				,       'w'						) as f:
								for item in DATA:
												f.write(json.dumps(a_						) + '\n'						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     Tuple       =       str(tmp_path_factory.mktemp('data'						) / 'dataset2.jsonl'						)
				with open(a_				,       'w'						) as f:
								for item in DATA:
												f.write(json.dumps(a_						) + '\n'						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     Any       =       str(tmp_path_factory.mktemp('data'						) / 'dataset_312.jsonl'						)
				with open(a_				,       'w'						) as f:
								for item in DATA_312:
												f.write(json.dumps(a_						) + '\n'						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     List[Any]       =       str(tmp_path_factory.mktemp('data'						) / 'dataset-str.jsonl'						)
				with open(a_				,       'w'						) as f:
								for item in DATA_STR:
												f.write(json.dumps(a_						) + '\n'						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__						):
				import gzip

				_lowerCamelCase	:     str       =       str(tmp_path_factory.mktemp('data'						) / 'dataset.txt.gz'						)
				with open(a_				,       'rb'						) as orig_file:
								with gzip.open(a_				,       'wb'						) as zipped_file:
												zipped_file.writelines(a_						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__						):
				import gzip

				_lowerCamelCase	:     List[Any]       =       str(tmp_path_factory.mktemp('data'						) / 'dataset.jsonl.gz'						)
				with open(a_				,       'rb'						) as orig_file:
								with gzip.open(a_				,       'wb'						) as zipped_file:
												zipped_file.writelines(a_						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__				,       lowercase__						):
				_lowerCamelCase	:     Optional[int]       =       tmp_path_factory.mktemp('data'						) / """dataset.jsonl.zip"""
				with zipfile.ZipFile(a_				,       'w'						) as f:
								f.write(a_				,       arcname=os.path.basename(a_						)						)
								f.write(a_				,       arcname=os.path.basename(a_						)						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__				,       lowercase__				,       lowercase__						):
				_lowerCamelCase	:     Any       =       tmp_path_factory.mktemp('data'						) / """dataset_nested.jsonl.zip"""
				with zipfile.ZipFile(a_				,       'w'						) as f:
								f.write(a_				,       arcname=os.path.join('nested'				,       os.path.basename(a_						)						)						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__				,       lowercase__						):
				_lowerCamelCase	:     Tuple       =       tmp_path_factory.mktemp('data'						) / """dataset_with_dir.jsonl.zip"""
				with zipfile.ZipFile(a_				,       'w'						) as f:
								f.write(a_				,       arcname=os.path.join('main_dir'				,       os.path.basename(a_						)						)						)
								f.write(a_				,       arcname=os.path.join('main_dir'				,       os.path.basename(a_						)						)						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__				,       lowercase__						):
				_lowerCamelCase	:     Dict       =       tmp_path_factory.mktemp('data'						) / """dataset.jsonl.tar"""
				with tarfile.TarFile(a_				,       'w'						) as f:
								f.add(a_				,       arcname=os.path.basename(a_						)						)
								f.add(a_				,       arcname=os.path.basename(a_						)						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__				,       lowercase__				,       lowercase__						):
				_lowerCamelCase	:     Tuple       =       tmp_path_factory.mktemp('data'						) / """dataset_nested.jsonl.tar"""
				with tarfile.TarFile(a_				,       'w'						) as f:
								f.add(a_				,       arcname=os.path.join('nested'				,       os.path.basename(a_						)						)						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     Union[str, Any]       =       ["""0""", """1""", """2""", """3"""]
				_lowerCamelCase	:     Any       =       str(tmp_path_factory.mktemp('data'						) / 'dataset.txt'						)
				with open(a_				,       'w'						) as f:
								for item in data:
												f.write(item + '\n'						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     Dict       =       ["""0""", """1""", """2""", """3"""]
				_lowerCamelCase	:     Tuple       =       str(tmp_path_factory.mktemp('data'						) / 'dataset2.txt'						)
				with open(a_				,       'w'						) as f:
								for item in data:
												f.write(item + '\n'						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     str       =       ["""0""", """1""", """2""", """3"""]
				_lowerCamelCase	:     List[str]       =       tmp_path_factory.mktemp('data'						) / """dataset.abc"""
				with open(a_				,       'w'						) as f:
								for item in data:
												f.write(item + '\n'						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__				,       lowercase__						):
				_lowerCamelCase	:     int       =       tmp_path_factory.mktemp('data'						) / """dataset.text.zip"""
				with zipfile.ZipFile(a_				,       'w'						) as f:
								f.write(a_				,       arcname=os.path.basename(a_						)						)
								f.write(a_				,       arcname=os.path.basename(a_						)						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__				,       lowercase__						):
				_lowerCamelCase	:     List[str]       =       tmp_path_factory.mktemp('data'						) / """dataset_with_dir.text.zip"""
				with zipfile.ZipFile(a_				,       'w'						) as f:
								f.write(a_				,       arcname=os.path.join('main_dir'				,       os.path.basename(a_						)						)						)
								f.write(a_				,       arcname=os.path.join('main_dir'				,       os.path.basename(a_						)						)						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__				,       lowercase__						):
				_lowerCamelCase	:     Optional[Any]       =       tmp_path_factory.mktemp('data'						) / """dataset.ext.zip"""
				with zipfile.ZipFile(a_				,       'w'						) as f:
								f.write(a_				,       arcname=os.path.basename('unsupported.ext'						)						)
								f.write(a_				,       arcname=os.path.basename('unsupported_2.ext'						)						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     Dict       =       """\n""".join(['First', 'Second\u2029with Unicode new line', 'Third']						)
				_lowerCamelCase	:     Tuple       =       str(tmp_path_factory.mktemp('data'						) / 'dataset_with_unicode_new_lines.txt'						)
				with open(a_				,       'w'				,       encoding='utf-8'						) as f:
								f.write(a_						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							):
				return os.path.join('tests'				,       'features'				,       'data'				,       'test_image_rgb.jpg'						)







@pytest.fixture(scope='session'						)
def 	_snake_case     (							):
				return os.path.join('tests'				,       'features'				,       'data'				,       'test_audio_44100.wav'						)







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__				,       lowercase__						):
				_lowerCamelCase	:     Dict       =       tmp_path_factory.mktemp('data'						) / """dataset.img.zip"""
				with zipfile.ZipFile(a_				,       'w'						) as f:
								f.write(a_				,       arcname=os.path.basename(a_						)						)
								f.write(a_				,       arcname=os.path.basename(a_						).replace('.jpg'				,       '2.jpg'						)						)
				return path







@pytest.fixture(scope='session'						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     Any       =       tmp_path_factory.mktemp('data_dir'						)

				(data_dir / "subdir").mkdir()
				with open(data_dir / 'subdir' / 'train.txt'				,       'w'						) as f:
								f.write('foo\n' * 10						)
				with open(data_dir / 'subdir' / 'test.txt'				,       'w'						) as f:
								f.write('bar\n' * 10						)
				# hidden file
				with open(data_dir / 'subdir' / '.test.txt'				,       'w'						) as f:
								f.write('bar\n' * 10						)

				# hidden directory
				(data_dir / ".subdir").mkdir()
				with open(data_dir / '.subdir' / 'train.txt'				,       'w'						) as f:
								f.write('foo\n' * 10						)
				with open(data_dir / '.subdir' / 'test.txt'				,       'w'						) as f:
								f.write('bar\n' * 10						)

				return data_dir







'''simple docstring'''

import numpy as np

# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models

if __name__ == "__main__":
      # Initialising the CNN
      # (Sequential- Building the model layer by layer)
      UpperCamelCase      					=models.Sequential()

      # Step 1 - Convolution
      # Here 64,64 is the length & breadth of dataset images and 3 is for the RGB channel
      # (3,3) is the kernel size (filter matrix)
      classifier.add(
          layers.ConvaD(32, (3, 3), input_shape=(64, 64, 3), activation="relu")
      )

      # Step 2 - Pooling
      classifier.add(layers.MaxPoolingaD(pool_size=(2, 2)))

      # Adding a second convolutional layer
      classifier.add(layers.ConvaD(32, (3, 3), activation="relu"))
      classifier.add(layers.MaxPoolingaD(pool_size=(2, 2)))

      # Step 3 - Flattening
      classifier.add(layers.Flatten())

      # Step 4 - Full connection
      classifier.add(layers.Dense(units=128, activation="relu"))
      classifier.add(layers.Dense(units=1, activation="sigmoid"))

      # Compiling the CNN
      classifier.compile(
          optimizer="adam", loss="binary_crossentropy", metrics=["accuracy"]
      )

      # Part 2 - Fitting the CNN to the images

      # Load Trained model weights

      # from keras.models import load_model
      # regressor=load_model('cnn.h5')

      UpperCamelCase      					=tf.keras.preprocessing.image.ImageDataGenerator(
          rescale=1.0 / 255, shear_range=0.2, zoom_range=0.2, horizontal_flip=True
      )

      UpperCamelCase      					=tf.keras.preprocessing.image.ImageDataGenerator(rescale=1.0 / 255)

      UpperCamelCase      					=train_datagen.flow_from_directory(
          "dataset/training_set", target_size=(64, 64), batch_size=32, class_mode="binary"
      )

      UpperCamelCase      					=test_datagen.flow_from_directory(
          "dataset/test_set", target_size=(64, 64), batch_size=32, class_mode="binary"
      )

      classifier.fit_generator(
          training_set, steps_per_epoch=5, epochs=30, validation_data=test_set
      )

      classifier.save("cnn.h5")

      # Part 3 - Making new predictions

      UpperCamelCase      					=tf.keras.preprocessing.image.load_img(
          "dataset/single_prediction/image.png", target_size=(64, 64)
      )
      UpperCamelCase      					=tf.keras.preprocessing.image.img_to_array(test_image)
      UpperCamelCase      					=np.expand_dims(test_image, axis=0)
      UpperCamelCase      					=classifier.predict(test_image)
      # training_set.class_indices
      if result[0][0] == 0:
            UpperCamelCase      					="Normal"
      if result[0][0] == 1:
            UpperCamelCase      					="Abnormality detected"






