PyTorch Lab - 11 - Pytorch CUDA Semantics

demo11-TensorflowDynamicComputationGraphs.ipynb

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   "source": [
    "import numpy as np\n",
    "\n",
    "import tensorflow as tf"
   ]
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   "cell_type": "code",
   "execution_count": 2,
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   "source": [
    "tf.enable_eager_execution()"
   ]
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    "tf.executing_eagerly() "
   ]
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Only variable and constants are compatible with eager execution "
   ]
  },
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   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "W = tf.Variable(6, name = 'var_W')\n",
    "\n",
    "x = tf.constant([10, 10], name = 'x')\n",
    "\n",
    "b = tf.Variable(3, name = 'constant_b')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Variable 'var_W:0' shape=() dtype=int32, numpy=6>"
      ]
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     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
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    "W"
   ]
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   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: id=64, shape=(2,), dtype=int32, numpy=array([10, 10], dtype=int32)>"
      ]
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     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
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    "x"
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   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
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    {
     "data": {
      "text/plain": [
       "<tf.Variable 'constant_b:0' shape=() dtype=int32, numpy=3>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = W * x + b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: id=80, shape=(2,), dtype=int32, numpy=array([63, 63], dtype=int32)>"
      ]
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     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "y"
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   "cell_type": "code",
   "execution_count": 24,
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     "text": [
      "tf.Tensor([63 63], shape=(2,), dtype=int32)\n"
     ]
    }
   ],
   "source": [
    "print(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tf.Tensor([60 60], shape=(2,), dtype=int32)\n"
     ]
    }
   ],
   "source": [
    "print(W*x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://www.tensorflow.org/guide/eager#work_with_graphs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<tf.Tensor: id=108, shape=(), dtype=int32, numpy=60>,\n",
       "       <tf.Tensor: id=111, shape=(), dtype=int32, numpy=60>], dtype=object)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np_result = np.multiply(W, x)\n",
    "\n",
    "np_result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "W.numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([63, 63], dtype=int32)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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