005 - Softmax.ipynb

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      "[ 0.8360188   0.11314284  0.05083836]\n"
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   "source": [
    "import numpy as np\n",
    "\n",
    "\n",
    "def softmax(x):\n",
    "    \"\"\"Compute softmax values for each sets of scores in x.\"\"\"\n",
    "    return np.exp(x) / np.sum(np.exp(x), axis=0)\n",
    "\n",
    "logits = [3.0, 1.0, 0.2]\n",
    "print(softmax(logits))"
   ]
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   "source": [
    "# TensorFlow softmax"
   ]
  },
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     "text": [
      "[ 0.65900117  0.24243298  0.09856589]\n"
     ]
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   "source": [
    "import tensorflow as tf\n",
    "\n",
    "\n",
    "logit_data = [2.0, 1.0, 0.1]\n",
    "logits = tf.placeholder(tf.float32)\n",
    "\n",
    "softmax = tf.nn.softmax(logits)    \n",
    "\n",
    "with tf.Session() as sess:\n",
    "    output = sess.run(softmax, feed_dict={logits : logit_data })\n",
    "\n",
    "print(output)"
   ]
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