Installation problem on windows 10

[Areshey]

============================= test session starts =============================
platform win32 -- Python 3.9.10, pytest-7.0.1, pluggy-1.0.0
rootdir: C:\Users\pc1\Documents\myProject\pythonCode\AI\aima-python-master, configfile: pytest.ini
plugins: cov-3.0.0
collected 419 items

tests\test_agents.py ................ [ 3%]
tests\test_agents4e.py ................ [ 7%]
tests\test_csp.py ......................................... [ 17%]
tests\test_deep_learning4e.py ...F [ 18%]
tests\test_games.py ... [ 19%]
tests\test_games4e.py .... [ 20%]
tests\test_knowledge.py ........... [ 22%]
tests\test_learning.py ............... [ 26%]
tests\test_learning4e.py ............. [ 29%]
tests\test_logic.py ...................................... [ 38%]
tests\test_logic4e.py .................................... [ 47%]
tests\test_mdp.py ...... [ 48%]
tests\test_mdp4e.py ...... [ 49%]
tests\test_nlp.py .................... [ 54%]
tests\test_nlp4e.py ............ [ 57%]
tests\test_perception4e.py .......F. [ 59%]
tests\test_planning.py ..................................... [ 68%]
tests\test_probabilistic_learning.py . [ 68%]
tests\test_probability.py ........................ [ 74%]
tests\test_probability4e.py ...................... [ 79%]
tests\test_reinforcement_learning.py .... [ 80%]
tests\test_reinforcement_learning4e.py .... [ 81%]
tests\test_search.py .......................... [ 87%]
tests\test_text.py ............... [ 91%]
tests\test_utils.py .................................... [100%]

================================== FAILURES ===================================
______________________________ test_autoencoder _______________________________

def test_autoencoder():
    iris = DataSet(name='iris')
    classes = ['setosa', 'versicolor', 'virginica']
    iris.classes_to_numbers(classes)
    inputs = np.asarray(iris.examples)

  al = AutoencoderLearner(inputs, 100)

tests\test_deep_learning4e.py:74:

---

inputs = array([[5.1, 3.5, 1.4, 0.2, 0. ],
[4.9, 3. , 1.4, 0.2, 0. ],
[4.7, 3.2, 1.3, 0.2, 0. ],
[4.6, 3.1... 5. , 1.9, 2. ],
[6.5, 3. , 5.2, 2. , 2. ],
[6.2, 3.4, 5.4, 2.3, 2. ],
[5.9, 3. , 5.1, 1.8, 2. ]])
encoding_size = 100, epochs = 200, verbose = False

def AutoencoderLearner(inputs, encoding_size, epochs=200, verbose=False):
    """
    Simple example of linear auto encoder learning producing the input itself.
    :param inputs: a batch of input data in np.ndarray type
    :param encoding_size: int, the size of encoding layer
    :param epochs: number of epochs
    :param verbose: verbosity mode
    :return: a keras model
    """

    # init data
    input_size = len(inputs[0])

    # init model
    model = Sequential()
    model.add(Dense(encoding_size, input_dim=input_size, activation='relu', kernel_initializer='random_uniform',
                    bias_initializer='ones'))
    model.add(Dense(input_size, activation='relu', kernel_initializer='random_uniform', bias_initializer='ones'))

    # update model with sgd

  sgd = optimizers.SGD(lr=0.01)

E AttributeError: module 'keras.optimizers' has no attribute 'SGD'

deep_learning4e.py:578: AttributeError
_____________________________ test_simple_convnet _____________________________

def test_simple_convnet():

  train, val, test = load_MINST(1000, 100, 10)

tests\test_perception4e.py:65:

---

train_size = 1000, val_size = 100, test_size = 10

def load_MINST(train_size, val_size, test_size):
    """Load MINST dataset from keras"""
    (x_train, y_train), (x_test, y_test) = mnist.load_data()
    total_size = len(x_train)
    if train_size + val_size > total_size:
        train_size = total_size - val_size
    x_train = x_train.reshape(x_train.shape[0], 1, 28, 28)
    x_test = x_test.reshape(x_test.shape[0], 1, 28, 28)
    x_train = x_train.astype('float32')
    x_train /= 255
    test_x = x_test.astype('float32')
    test_x /= 255

  y_train = keras.utils.to_categorical(y_train, 10)

E AttributeError: module 'keras.utils' has no attribute 'to_categorical'

perception4e.py:312: AttributeError
=========================== short test summary info ===========================
FAILED tests/test_deep_learning4e.py::test_autoencoder - AttributeError: modu...
FAILED tests/test_perception4e.py::test_simple_convnet - AttributeError: modu...
================== 2 failed, 417 passed in 89.51s (0:01:29) ===================