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@@ -24,9 +24,9 @@ n_classes = 10 # MNIST total classes (0-9 digits)
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dropout = 0.75 # Dropout, probability to keep units
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# tf Graph input
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-x = tf.placeholder(tf.types.float32, [None, n_input])
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-y = tf.placeholder(tf.types.float32, [None, n_classes])
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-keep_prob = tf.placeholder(tf.types.float32) #dropout (keep probability)
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+x = tf.placeholder(tf.float32, [None, n_input])
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+y = tf.placeholder(tf.float32, [None, n_classes])
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+keep_prob = tf.placeholder(tf.float32) #dropout (keep probability)
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# Create model
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def conv2d(img, w, b):
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