


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				:  Tuple      					=		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				:  Union[str, Any]      					=		tf.keras.preprocessing.image.ImageDataGenerator(
           rescale=1.0 / 255, shear_range=0.2, zoom_range=0.2, horizontal_flip=True
       )

       __UpperCamelCase				:  Union[str, Any]      					=		tf.keras.preprocessing.image.ImageDataGenerator(rescale=1.0 / 255)

       __UpperCamelCase				:  Dict      					=		train_datagen.flow_from_directory(
           'dataset/training_set', target_size=(64, 64), batch_size=32, class_mode='binary'
       )

       __UpperCamelCase				:  int      					=		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				:  Any      					=		tf.keras.preprocessing.image.load_img(
           'dataset/single_prediction/image.png', target_size=(64, 64)
       )
       __UpperCamelCase				:  Tuple      					=		tf.keras.preprocessing.image.img_to_array(test_image)
       __UpperCamelCase				:  Tuple      					=		np.expand_dims(test_image, axis=0)
       __UpperCamelCase				:  Dict      					=		classifier.predict(test_image)
       # training_set.class_indices
       if result[0][0] == 0:
              __UpperCamelCase				:  Union[str, Any]      					=		'Normal'
       if result[0][0] == 1:
              __UpperCamelCase				:  Any      					=		'Abnormality detected'



# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py

import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def      snake_case_						( __lowercase			,       __lowercase			,       __lowercase			,       __lowercase       ):
   UpperCAmelCase_							:      int						=   multiprocessing.Manager()
   UpperCAmelCase_							:      Union[str, Any]						=   manager.list()

   UpperCAmelCase_							:      int						=   multiprocessing.Process(target=__lowercase			,       args=(check_program, result, timeout)       )
   p.start()
   p.join(timeout=timeout + 1       )
   if p.is_alive():
      p.kill()

   if not result:
      result.append('''timed out'''       )

   return {
       "task_id": task_id,
       "passed": result[0] == "passed",
       "result": result[0],
       "completion_id": completion_id,
   }
def      snake_case_						( __lowercase			,       __lowercase			,       __lowercase       ):
   with create_tempdir():
      # These system calls are needed when cleaning up tempdir.
      import os
      import shutil

      UpperCAmelCase_							:      str						=   shutil.rmtree
      UpperCAmelCase_							:      Tuple						=   os.rmdir
      UpperCAmelCase_							:      Dict						=   os.chdir

      # Disable functionalities that can make destructive changes to the test.
      reliability_guard()

      # Run program.
      try:
         UpperCAmelCase_							:      Optional[int]						=   {}
         with swallow_io():
            with time_limit(__lowercase       ):
               exec(__lowercase			,       __lowercase       )
         result.append('''passed'''       )
      except TimeoutException:
         result.append('''timed out'''       )
      except BaseException as e:
         result.append(F'''failed: {e}'''       )

      # Needed for cleaning up.
      UpperCAmelCase_							:      Optional[int]						=   rmtree
      UpperCAmelCase_							:      Optional[Any]						=   rmdir
      UpperCAmelCase_							:      Optional[Any]						=   chdir
@contextlib.contextmanager
def      snake_case_						( __lowercase       ):
   def signal_handler(__lowercase			,       __lowercase       ):
      raise TimeoutException('''Timed out!'''       )

   signal.setitimer(signal.ITIMER_REAL			,       __lowercase       )
   signal.signal(signal.SIGALRM			,       __lowercase       )
   try:
      yield
   finally:
      signal.setitimer(signal.ITIMER_REAL			,       0       )
@contextlib.contextmanager
def      snake_case_						( ):
   UpperCAmelCase_							:      Optional[Any]						=   WriteOnlyStringIO()
   with contextlib.redirect_stdout(__lowercase       ):
      with contextlib.redirect_stderr(__lowercase       ):
         with redirect_stdin(__lowercase       ):
            yield
@contextlib.contextmanager
def      snake_case_						( ):
   with tempfile.TemporaryDirectory() as dirname:
      with chdir(__lowercase       ):
         yield dirname





class  lowerCAmelCase__(    snake_case__						):






    '''simple docstring'''





    pass





class  lowerCAmelCase__(    io.StringIO						):






    '''simple docstring'''





    def 					_lowerCamelCase (	self				:   Dict       ,   *__snake_case				:   List[Any]       ,   **__snake_case				:   int	):





       '''simple docstring'''
       raise OSError





    def 					_lowerCamelCase (	self				:   Dict       ,   *__snake_case				:   int       ,   **__snake_case				:   Any	):





       '''simple docstring'''
       raise OSError





    def 					_lowerCamelCase (	self				:   int       ,   *__snake_case				:   List[str]       ,   **__snake_case				:   Optional[Any]	):





       '''simple docstring'''
       raise OSError





    def 					_lowerCamelCase (	self				:   Union[str, Any]       ,   *__snake_case				:   Optional[Any]       ,   **__snake_case				:   List[Any]	):





       '''simple docstring'''
       return False





class  lowerCAmelCase__(    contextlib._RedirectStream						):  # type: ignore






    '''simple docstring'''





    A_  :     Optional[Any]			= 'stdin'





@contextlib.contextmanager
def      snake_case_						( __lowercase       ):
   if root == ".":
      yield
      return
   UpperCAmelCase_							:      Tuple						=   os.getcwd()
   os.chdir(__lowercase       )
   try:
      yield
   except BaseException as exc:
      raise exc
   finally:
      os.chdir(__lowercase       )


def      snake_case_						( __lowercase=None       ):

   if maximum_memory_bytes is not None:
      import resource

      resource.setrlimit(resource.RLIMIT_AS			,       (maximum_memory_bytes, maximum_memory_bytes)       )
      resource.setrlimit(resource.RLIMIT_DATA			,       (maximum_memory_bytes, maximum_memory_bytes)       )
      if not platform.uname().system == "Darwin":
         resource.setrlimit(resource.RLIMIT_STACK			,       (maximum_memory_bytes, maximum_memory_bytes)       )

   faulthandler.disable()

   import builtins

   UpperCAmelCase_							:      Any						=   None
   UpperCAmelCase_							:      Any						=   None

   import os

   UpperCAmelCase_							:      Union[str, Any]						=   '''1'''

   UpperCAmelCase_							:      List[str]						=   None
   UpperCAmelCase_							:      Dict						=   None
   UpperCAmelCase_							:      Any						=   None
   UpperCAmelCase_							:      Optional[int]						=   None
   UpperCAmelCase_							:      List[str]						=   None
   UpperCAmelCase_							:      List[Any]						=   None
   UpperCAmelCase_							:      Union[str, Any]						=   None
   UpperCAmelCase_							:      str						=   None
   UpperCAmelCase_							:      Dict						=   None
   UpperCAmelCase_							:      int						=   None
   UpperCAmelCase_							:      Dict						=   None
   UpperCAmelCase_							:      List[Any]						=   None
   UpperCAmelCase_							:      List[Any]						=   None
   UpperCAmelCase_							:      Optional[Any]						=   None
   UpperCAmelCase_							:      Optional[Any]						=   None
   UpperCAmelCase_							:      Dict						=   None
   UpperCAmelCase_							:      Optional[Any]						=   None
   UpperCAmelCase_							:      Optional[Any]						=   None
   UpperCAmelCase_							:      Optional[Any]						=   None
   UpperCAmelCase_							:      List[Any]						=   None
   UpperCAmelCase_							:      int						=   None
   UpperCAmelCase_							:      Union[str, Any]						=   None
   UpperCAmelCase_							:      List[Any]						=   None
   UpperCAmelCase_							:      Dict						=   None
   UpperCAmelCase_							:      Union[str, Any]						=   None
   UpperCAmelCase_							:      Dict						=   None
   UpperCAmelCase_							:      Any						=   None

   import shutil

   UpperCAmelCase_							:      Union[str, Any]						=   None
   UpperCAmelCase_							:      Dict						=   None
   UpperCAmelCase_							:      Tuple						=   None

   import subprocess

   UpperCAmelCase_							:      Dict						=   None  # type: ignore

   UpperCAmelCase_							:      Union[str, Any]						=   None

   import sys

   UpperCAmelCase_							:      Optional[Any]						=   None
   UpperCAmelCase_							:      List[Any]						=   None
   UpperCAmelCase_							:      List[Any]						=   None
   UpperCAmelCase_							:      List[str]						=   None
   UpperCAmelCase_							:      Dict						=   None