14.5-tf-data-cache.ipynb

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   "id": "821be114-acbc-4d87-8ef8-03ca6cb2dbeb",
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   "source": [
    "import tensorflow as tf\n",
    "from time import time"
   ]
  },
  {
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   "execution_count": 107,
   "id": "a17d7aa5-505e-4306-ae47-f39830b3406b",
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   "source": [
    "dataset = tf.data.Dataset.range(10000)\n",
    "dataset = dataset.map(lambda x: sum([x**i for i in range(1000)]))\n",
    "dataset = dataset.cache()"
   ]
  },
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     "execution_count": 108,
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   "source": [
    "# The first time reading through the data will generate the data using\n",
    "# `range` and `map`.\n",
    "tik = time()\n",
    "list(dataset.as_numpy_iterator())\n",
    "tok = time()\n",
    "round(tok-tik,2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "94724841-417a-4490-ae0e-784e18d35c35",
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     "execution_count": 106,
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   "source": [
    "# Subsequent iterations read from the cache.\n",
    "tik = time()\n",
    "list(dataset.as_numpy_iterator())\n",
    "tok = time()\n",
    "round(tok-tik,2)"
   ]
  },
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