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   "cell_type": "markdown",
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   "source": [
    "## Math\n",
    "- https://www.tensorflow.org/api_docs/python/math_ops/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 0. Loading TF and Fixtures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "sess = tf.InteractiveSession()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def namestr(obj, namespace):\n",
    "    return [name for name in namespace if namespace[name] is obj][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "======Fixture=======\n",
      "Tensor Matrix - m1\n",
      "Shape: (1, 2)\n",
      "[[ 1.  2.]]\n",
      "\n",
      "Tensor Matrix - m2\n",
      "Shape: (2, 1)\n",
      "[[ 3.]\n",
      " [ 4.]]\n",
      "\n",
      "Tensor Matrix - m3\n",
      "Shape: (1, 2, 3)\n",
      "[[[ 1.  2.  3.]\n",
      "  [ 4.  5.  6.]]]\n",
      "\n",
      "Tensor Matrix - m4\n",
      "Shape: (2, 2, 3)\n",
      "[[[  1.   2.   3.]\n",
      "  [  4.   5.   6.]]\n",
      "\n",
      " [[  7.   8.   9.]\n",
      "  [ 10.  11.  12.]]]\n",
      "\n",
      "Tensor Matrix - m5\n",
      "Shape: (1, 2, 2)\n",
      "[[[ 1.  2.]\n",
      "  [ 3.  4.]]]\n",
      "\n",
      "Tensor Matrix - m6\n",
      "Shape: (1, 3)\n",
      "[[ 3.  4.  5.]]\n",
      "\n",
      "====================\n"
     ]
    }
   ],
   "source": [
    "m1 = tf.constant(value = [[1., 2.]])\n",
    "m2 = tf.constant(value = [[3.],[4.]])\n",
    "m3 = tf.constant(value = [[[1., 2., 3.], [4., 5., 6.]]])\n",
    "m4 = tf.constant(value = [[[1., 2., 3.], [4., 5., 6.]], [[7., 8., 9.] ,[10., 11., 12.]]])\n",
    "m5 = tf.constant(value = [[[1., 2.], [3., 4.]]])\n",
    "m6 = tf.constant(value = [[3., 4., 5.]])\n",
    "\n",
    "def printFixture(isShapeOut, tensorMatrixList):\n",
    "    print \"======Fixture=======\"\n",
    "    \n",
    "    for m in tensorMatrixList:\n",
    "        print \"Tensor Matrix - \" + namestr(m, globals())\n",
    "        if (isShapeOut):\n",
    "            print \"Shape:\", m.get_shape()\n",
    "        print m.eval()\n",
    "        print\n",
    "        \n",
    "    print \"====================\"\n",
    "\n",
    "printFixture(True, (m1, m2, m3, m4, m5, m6))    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Arithmetic Operators"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### - tf.add(x, y, name=None)\n",
    "- https://www.tensorflow.org/versions/master/api_docs/python/math_ops/arithmetic_operators#add"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "======Fixture=======\n",
      "Tensor Matrix - m1\n",
      "Shape: (1, 2)\n",
      "[[ 1.  2.]]\n",
      "\n",
      "Tensor Matrix - m2\n",
      "Shape: (2, 1)\n",
      "[[ 3.]\n",
      " [ 4.]]\n",
      "\n",
      "====================\n",
      "[[ 4.  5.]\n",
      " [ 5.  6.]]\n",
      "[[ 4.  5.]\n",
      " [ 5.  6.]]\n"
     ]
    }
   ],
   "source": [
    "printFixture(True, (m1, m2))\n",
    "r1 = tf.add(m1, m2)\n",
    "print r1.eval()\n",
    "r2 = m1 + m2\n",
    "print r2.eval()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### - tf.multiply(x, y, name=None)\n",
    "- https://www.tensorflow.org/api_docs/python/tf/multiply"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "======Fixture=======\n",
      "Tensor Matrix - m1\n",
      "Shape: (1, 2)\n",
      "[[ 1.  2.]]\n",
      "\n",
      "Tensor Matrix - m2\n",
      "Shape: (2, 1)\n",
      "[[ 3.]\n",
      " [ 4.]]\n",
      "\n",
      "====================\n",
      "[[ 3.  6.]\n",
      " [ 4.  8.]]\n",
      "[[ 3.  6.]\n",
      " [ 4.  8.]]\n",
      "[[ 3.  6.]\n",
      " [ 4.  8.]]\n"
     ]
    }
   ],
   "source": [
    "printFixture(True, (m1, m2))\n",
    "r1 = tf.multiply(m1, m2)\n",
    "print r1.eval()\n",
    "r2 = tf.multiply(m1, m2)\n",
    "print r2.eval()\n",
    "r3 = m1 * m2\n",
    "print r3.eval()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Matrix Math Functions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### - tf.matmul(a, b, transpose_a=False, transpose_b=False, adjoint_a=False, adjoint_b=False, a_is_sparse=False, b_is_sparse=False, name=None)\n",
    "- https://www.tensorflow.org/api_docs/python/tf/matmul"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "======Fixture=======\n",
      "Tensor Matrix - m1\n",
      "Shape: (1, 2)\n",
      "[[ 1.  2.]]\n",
      "\n",
      "Tensor Matrix - m2\n",
      "Shape: (2, 1)\n",
      "[[ 3.]\n",
      " [ 4.]]\n",
      "\n",
      "====================\n",
      "[[ 11.]]\n",
      "[[ 3.  6.]\n",
      " [ 4.  8.]]\n"
     ]
    }
   ],
   "source": [
    "printFixture(True, (m1, m2))\n",
    "r1 = tf.matmul(a = m1, b = m2)   #(1, 2) x (2, 1)\n",
    "print r1.eval()\n",
    "r2 = tf.matmul(a = m2, b = m1)   #(2, 1) x (1, 2)\n",
    "print r2.eval()"
   ]
  }
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