x, name="x")
if isinstance(keep_prob, numbers.Real) and not 0 < keep_prob <= 1:
raise...ops.convert_to_tensor(keep_prob, dtype=x.dtype, name="keep_prob")
keep_prob.get_shape().assert_is_compatible_with...= ops.convert_to_tensor(alpha, dtype=x.dtype, name="alpha")
keep_prob.get_shape().assert_is_compatible_with...(tf.float32, [None, 784])
Y = tf.placeholder(tf.float32, [None, 10])
# dropout (keep_prob) rate 0.7...on training, but should be 1 for testing
keep_prob = tf.placeholder(tf.float32)
# weights & bias for