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mitdeeplearning/lab1.py

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@@ -80,6 +80,7 @@ def test_batch_func_next_step(func, args):
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return True
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def test_custom_dense_layer_output(y):
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# define the ground truth value
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true_y = np.array([[0.27064407 0.1826951 0.50374055]],dtype='float32')
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assert tf.shape(y).numpy().tolist() == list(true_y.shape), "[FAIL] output is of incorrect shape. expected {} but got {}".format(true_y.shape, y.numpy().shape)
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np.testing.assert_almost_equal(y.numpy(), true_y, decimal=7, err_msg="[FAIL] output is of incorrect value. expected {} but got {}".format(true_y, y.numpy()), verbose=True)

setup.py

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@@ -22,13 +22,13 @@ def get_dist(pkgname):
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setup(
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name = 'mitdeeplearning', # How you named your package folder (MyLib)
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packages = ['mitdeeplearning'], # Chose the same as "name"
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version = '0.4.3', # Start with a small number and increase it with every change you make
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version = '0.5.4', # Start with a small number and increase it with every change you make
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license='MIT', # Chose a license from here: https://help.github.com/articles/licensing-a-repository
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description = 'Official software labs for MIT Introduction to Deep Learning (http://introtodeeplearning.com)', # Give a short description about your library
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author = 'Alexander Amini', # Type in your name
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author_email = '[email protected]', # Type in your E-Mail
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url = 'http://introtodeeplearning.com', # Provide either the link to your github or to your website
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download_url = 'https://github.com/aamini/introtodeeplearning/archive/v0.4.3.tar.gz', # I explain this later on
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download_url = 'https://github.com/aamini/introtodeeplearning/archive/v0.5.4.tar.gz', # I explain this later on
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keywords = ['deep learning', 'neural networks', 'tensorflow', 'introduction'], # Keywords that define your package best
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install_requires=install_deps,
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classifiers=[

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