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Fix indentation and title capitalization.
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@rxwei
rxwei committed Mar 11, 2019
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150 changes: 75 additions & 75 deletions docs/site/tutorials/custom_differentiation.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -84,7 +84,7 @@
"metadata": {
"id": "j0a8prgZTlEO",
"colab_type": "code",
"outputId": "b32010bb-e291-4ae1-b090-f2c13b3e061c",
"outputId": "f0f65b8a-30ce-46bb-a6c5-efe3e8956e44",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 85
Expand All @@ -109,7 +109,7 @@
"print(\"exp(3) =\", sillyExp(3))\n",
"print(\"𝛁exp(3) =\", gradient(of: sillyExp)(3))"
],
"execution_count": 50,
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
Expand Down Expand Up @@ -141,21 +141,21 @@
"metadata": {
"id": "ctRt6vBO5Wle",
"colab_type": "code",
"outputId": "49580e7d-0bde-4e78-b825-12444bf39767",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 68
},
"outputId": "5ff3cb6b-9a1c-4fcc-f9e2-d7daaea369d0"
}
},
"cell_type": "code",
"source": [
"let x: Float = 2.0\n",
"let y: Float = 3.0\n",
"gradient(at: x, y) { x, y in\n",
" sin(sin(sin(x))) + cos(cos(cos(y))).withoutDerivative()\n",
" sin(sin(sin(x))) + cos(cos(cos(y))).withoutDerivative()\n",
"}"
],
"execution_count": 54,
"execution_count": 3,
"outputs": [
{
"output_type": "execute_result",
Expand All @@ -169,7 +169,7 @@
"metadata": {
"tags": []
},
"execution_count": 54
"execution_count": 3
}
]
},
Expand Down Expand Up @@ -213,7 +213,7 @@
"metadata": {
"id": "eKne7szjD8lr",
"colab_type": "code",
"outputId": "50f14b9e-4dba-4f94-d1d6-fe9b54c115cb",
"outputId": "31bba009-3758-4179-92dc-f080dcba8421",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 68
Expand All @@ -233,7 +233,7 @@
" return a + b\n",
"}"
],
"execution_count": 0,
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
Expand All @@ -253,7 +253,7 @@
"metadata": {
"tags": []
},
"execution_count": 40
"execution_count": 4
}
]
},
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"metadata": {
"id": "fnSeAbs9-hf3",
"colab_type": "code",
"outputId": "55070f9f-4673-4374-cea0-41f878966ddd",
"outputId": "80ea60b8-e17c-47d5-9364-c8768c3e377e",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 527
"height": 547
}
},
"cell_type": "code",
Expand Down Expand Up @@ -319,41 +319,41 @@
" optimizer.update(&classifier.allDifferentiableVariables, along: 𝛁model)\n",
"}"
],
"execution_count": 0,
"execution_count": 5,
"outputs": [
{
"output_type": "stream",
"text": [
"Loss: 0.5\r\n",
"∂L/∂ŷ = [[-0.25], [-0.25], [-0.25], [-0.25]]\r\n",
"∂L/∂layer1 = [[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]\r\n",
"Loss: 0.5\r\n",
"∂L/∂ŷ = [[-0.25], [-0.25], [-0.25], [-0.25]]\r\n",
"∂L/∂layer1 = [[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]\r\n",
"Loss: 0.5\r\n",
"∂L/∂ŷ = [[-0.25], [-0.25], [-0.25], [-0.25]]\r\n",
"∂L/∂layer1 = [[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]\r\n",
"Loss: 0.5\r\n",
"∂L/∂ŷ = [[-0.25], [-0.25], [-0.25], [-0.25]]\r\n",
"∂L/∂layer1 = [[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]\r\n",
"Loss: 0.5\r\n",
"∂L/∂ŷ = [[-0.25], [-0.25], [-0.25], [-0.25]]\r\n",
"∂L/∂layer1 = [[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]\r\n",
"Loss: 0.5\r\n",
"∂L/∂ŷ = [[-0.25], [-0.25], [-0.25], [-0.25]]\r\n",
"∂L/∂layer1 = [[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]\r\n",
"Loss: 0.5\r\n",
"∂L/∂ŷ = [[-0.25], [-0.25], [-0.25], [-0.25]]\n",
"∂L/∂layer1 = [[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]\n",
"Loss: 0.5\n",
"∂L/∂ŷ = [[-0.25], [-0.25], [-0.25], [-0.25]]\n",
"∂L/∂layer1 = [[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]\n",
"Loss: 0.5\n",
"∂L/∂ŷ = [[-0.25], [-0.25], [-0.25], [-0.25]]\n",
"∂L/∂layer1 = [[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]\n",
"Loss: 0.5\n",
"∂L/∂ŷ = [[-0.25], [-0.25], [-0.25], [-0.25]]\n",
"∂L/∂layer1 = [[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]\n"
"Loss: 0.33426732\n",
"∂L/∂ŷ = [[-0.25], [-0.078446716], [-0.12092987], [0.031454742]]\n",
"∂L/∂layer1 = [[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.03357383, -0.027463656, 0.037523113, -0.002631738, -0.030937709, -0.014981618, -0.02623924, -0.026290288, 0.027446445, 0.01046889], [-0.051755875, -0.042336714, 0.057843916, -0.004056967, -0.047692157, -0.023094976, -0.040449213, -0.040527906, 0.042310182, 0.016138362], [0.013462082, 0.0110120885, -0.015045625, 0.0010552468, 0.012405078, 0.006007172, 0.010521135, 0.010541604, -0.011005187, -0.0041977055]]\n",
"Loss: 0.33176333\n",
"∂L/∂ŷ = [[-0.24746439], [-0.07523262], [-0.11674469], [0.03514868]]\n",
"∂L/∂layer1 = [[-0.10602461, -0.08665162, 0.11829134, -0.008301959, -0.09804342, -0.04726032, -0.08280819, -0.082981184, 0.08658129, 0.032860693], [-0.032232955, -0.0263433, 0.035962217, -0.0025239112, -0.029806564, -0.014367796, -0.025174841, -0.025227433, 0.026321916, 0.009990108], [-0.050018553, -0.040879082, 0.05580555, -0.003916562, -0.046253316, -0.022295699, -0.039065886, -0.0391475, 0.0408459, 0.015502479], [0.015059238, 0.01230759, -0.016801547, 0.0011791714, 0.013925628, 0.006712634, 0.011761686, 0.011786258, -0.0122976, -0.0046673785]]\n",
"Loss: 0.3263967\n",
"∂L/∂ŷ = [[-0.24090183], [-0.068522125], [-0.10922298], [0.04169026]]\n",
"∂L/∂layer1 = [[-0.10332261, -0.08436972, 0.115082964, -0.008081798, -0.09583634, -0.046007015, -0.08064418, -0.08082552, 0.08428522, 0.031835504], [-0.029389087, -0.023998126, 0.032734204, -0.002298787, -0.027259693, -0.013086237, -0.022938434, -0.022990014, 0.02397409, 0.009055292], [-0.046845652, -0.038252562, 0.052177705, -0.0036642232, -0.043451436, -0.020859215, -0.036563434, -0.03664565, 0.03821425, 0.014433966], [0.01788092, 0.01460095, -0.019916158, 0.0013986289, 0.016585354, 0.0079619335, 0.013956212, 0.013987594, -0.014586327, -0.005509425]]\n",
"Loss: 0.32171223\n",
"∂L/∂ŷ = [[-0.23473385], [-0.062339008], [-0.102276154], [0.047599167]]\n",
"∂L/∂layer1 = [[-0.10078285, -0.08222727, 0.11207248, -0.007874874, -0.09368697, -0.044829067, -0.078606784, -0.07879931, 0.082127206, 0.030880556], [-0.026765218, -0.021837354, 0.029763442, -0.0020913552, -0.024880743, -0.011905396, -0.02087585, -0.02092698, 0.021810781, 0.008201047], [-0.04391221, -0.035827335, 0.04883123, -0.0034311705, -0.040820457, -0.019532524, -0.03424985, -0.034333736, 0.035783738, 0.013455003], [0.020436676, 0.016673988, -0.02272598, 0.0015968615, 0.018997777, 0.009090407, 0.015939828, 0.015978869, -0.016653698, -0.006261938]]\n",
"Loss: 0.31760892\n",
"∂L/∂ŷ = [[-0.22893232], [-0.056644887], [-0.0958622], [0.0529218]]\n",
"∂L/∂layer1 = [[-0.09839373, -0.080213994, 0.109245166, -0.007680244, -0.0915977, -0.0437211, -0.0766867, -0.076893255, 0.0800974, 0.02998989], [-0.024345629, -0.019847406, 0.02703061, -0.0019003282, -0.022664083, -0.010817943, -0.018974645, -0.019025752, 0.019818557, 0.00742042], [-0.041200995, -0.033588488, 0.045744885, -0.0032159945, -0.038355254, -0.018307598, -0.03211148, -0.03219797, 0.033539664, 0.0125578465], [0.02274547, 0.0185429, -0.025253974, 0.0017754257, 0.021174446, 0.010106915, 0.017727504, 0.01777525, -0.018515948, -0.0069327]]\n",
"Loss: 0.3140006\n",
"∂L/∂ŷ = [[-0.22347087], [-0.051403634], [-0.08994151], [0.057702184]]\n",
"∂L/∂layer1 = [[-0.09614439, -0.07832037, 0.106587306, -0.0074970224, -0.08956989, -0.04267808, -0.07487536, -0.07509866, 0.07818659, 0.029158076], [-0.022115506, -0.018015554, 0.024517624, -0.0017244942, -0.020603213, -0.009816977, -0.017223122, -0.017274486, 0.017984781, 0.0067070536], [-0.038695745, -0.031522017, 0.04289876, -0.0030173666, -0.03604967, -0.017176874, -0.030135486, -0.030225359, 0.03146817, 0.011735407], [0.024825346, 0.020223022, -0.027521798, 0.0019357986, 0.02312775, 0.011019863, 0.019333491, 0.01939115, -0.020188477, -0.0075288774]]\n",
"Loss: 0.3108136\n",
"∂L/∂ŷ = [[-0.21832475], [-0.046581082], [-0.084476836], [0.061981946]]\n",
"∂L/∂layer1 = [[-0.094024695, -0.07653748, 0.10408614, -0.0073243803, -0.08760406, -0.041695286, -0.07316483, -0.07340741, 0.076386094, 0.02838015], [-0.020060813, -0.016329797, 0.022207491, -0.0015627067, -0.018690927, -0.008895975, -0.015610217, -0.015661974, 0.016297497, 0.0060551], [-0.036381166, -0.029614802, 0.04027426, -0.0028340372, -0.033896815, -0.01613324, -0.028309815, -0.028403677, 0.029556224, 0.010981189], [0.026693417, 0.021728832, -0.02954984, 0.0020793765, 0.024870614, 0.011837205, 0.020771343, 0.020840213, -0.021685854, -0.008057066]]\n",
"Loss: 0.30798542\n",
"∂L/∂ŷ = [[-0.2134709], [-0.042145163], [-0.07943327], [0.06580055]]\n",
"∂L/∂layer1 = [[-0.092025176, -0.07485708, 0.10172984, -0.007161543, -0.08570006, -0.040768307, -0.07154774, -0.07181193, 0.07468786, 0.02765159], [-0.018168358, -0.0147788925, 0.020084333, -0.00141389, -0.016919604, -0.00804881, -0.014125537, -0.014177696, 0.014745485, 0.0054592015], [-0.034242887, -0.027854579, 0.03785403, -0.0026648352, -0.031889293, -0.015170028, -0.026623163, -0.02672147, 0.027791614, 0.010289253], [0.028365958, 0.023074042, -0.031357337, 0.0022074832, 0.026416298, 0.012566475, 0.022053968, 0.022135403, -0.023021882, -0.008523362]]\n",
"Loss: 0.30546278\n",
"∂L/∂ŷ = [[-0.20888776], [-0.03806588], [-0.07477814], [0.069194704]]\n",
"∂L/∂layer1 = [[-0.09013698, -0.07327145, 0.099507414, -0.007007787, -0.08385716, -0.039893024, -0.07001727, -0.070305154, 0.07308434, 0.026968256], [-0.016425777, -0.013352349, 0.018133363, -0.0012770379, -0.015281396, -0.007269756, -0.012759335, -0.012811797, 0.013318251, 0.0049144593], [-0.03226745, -0.02622989, 0.035621904, -0.0025086643, -0.030019386, -0.014281, -0.025064949, -0.025168007, 0.026162906, 0.009654161], [0.02985815, 0.024271391, -0.032962132, 0.0023213506, 0.027777938, 0.013214685, 0.023193432, 0.023288796, -0.024209408, -0.008933316]]\n",
"Loss: 0.30320063\n",
"∂L/∂ŷ = [[-0.20455518], [-0.0343152], [-0.07048094], [0.07219905]]\n",
"∂L/∂layer1 = [[-0.08835188, -0.07177346, 0.09740865, -0.0068624374, -0.082074195, -0.039065596, -0.068567075, -0.06888049, 0.07156848, 0.02632637], [-0.014821488, -0.012040373, 0.016340809, -0.0011512097, -0.013768374, -0.0065534576, -0.011502485, -0.011555062, 0.012005987, 0.0044163857], [-0.03044227, -0.024730057, 0.033562843, -0.0023645016, -0.028279249, -0.013460329, -0.023625273, -0.023733262, 0.02465943, 0.0090709375], [0.031184357, 0.025332898, -0.034381, 0.0024221407, 0.028968606, 0.01378845, 0.024201185, 0.024311805, -0.025260549, -0.009292059]]\n"
],
"name": "stdout"
}
Expand Down Expand Up @@ -436,7 +436,7 @@
"metadata": {
"id": "oee8SXital45",
"colab_type": "code",
"outputId": "5e502634-096b-44ab-e1e4-a3b2fc7dd32c",
"outputId": "f4e7bd68-606a-46d6-96f4-c5294d8e302a",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 102
Expand All @@ -461,7 +461,7 @@
"let grad = backprop(1)\n",
"print(\"Gradient = \\(grad)\")"
],
"execution_count": 0,
"execution_count": 7,
"outputs": [
{
"output_type": "stream",
Expand Down Expand Up @@ -666,7 +666,7 @@
"metadata": {
"id": "-x1nYu0uVSPn",
"colab_type": "code",
"outputId": "17c183ef-5ad0-41c6-a939-33dc6f6dae9e",
"outputId": "fcdc6e19-2ffa-49f3-908f-e5823a485f9d",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 527
Expand Down Expand Up @@ -696,41 +696,41 @@
" opt.update(&model.allDifferentiableVariables, along: dL_dθ)\n",
"}"
],
"execution_count": 0,
"execution_count": 12,
"outputs": [
{
"output_type": "stream",
"text": [
"Starting training step 1\r\n",
" Running original computation...\r\n",
" Applying Conv2D<Float> layer...\r\n",
" Loss: 2.7489972\r\n",
" Running backpropagation...\r\n",
" Applying Conv2D<Float> layer...\r\n",
"Starting training step 2\r\n",
" Running original computation...\r\n",
" Applying Conv2D<Float> layer...\r\n",
" Loss: 2.4839666\r\n",
" Running backpropagation...\r\n",
" Applying Conv2D<Float> layer...\r\n",
"Starting training step 3\r\n",
" Running original computation...\r\n",
" Applying Conv2D<Float> layer...\r\n",
" Loss: 2.2441723\r\n",
" Running backpropagation...\r\n",
" Applying Conv2D<Float> layer...\r\n",
"Starting training step 4\r\n",
" Running original computation...\r\n",
" Applying Conv2D<Float> layer...\r\n",
" Loss: 2.0292702\r\n",
" Running backpropagation...\r\n",
" Applying Conv2D<Float> layer...\r\n",
"Starting training step 5\r\n",
" Running original computation...\r\n",
" Applying Conv2D<Float> layer...\r\n",
" Loss: 1.8355687\r\n",
" Running backpropagation...\r\n",
" Applying Conv2D<Float> layer...\r\n"
" Applying Conv2D<Float> layer...\n",
" Loss: 3.6660562\n",
" Running backpropagation...\n",
" Applying Conv2D<Float> layer...\n",
"Starting training step 2\n",
" Running original computation...\n",
" Applying Conv2D<Float> layer...\n",
" Loss: 3.1203392\n",
" Running backpropagation...\n",
" Applying Conv2D<Float> layer...\n",
"Starting training step 3\n",
" Running original computation...\n",
" Applying Conv2D<Float> layer...\n",
" Loss: 2.7324893\n",
" Running backpropagation...\n",
" Applying Conv2D<Float> layer...\n",
"Starting training step 4\n",
" Running original computation...\n",
" Applying Conv2D<Float> layer...\n",
" Loss: 2.4246051\n",
" Running backpropagation...\n",
" Applying Conv2D<Float> layer...\n",
"Starting training step 5\n",
" Running original computation...\n",
" Applying Conv2D<Float> layer...\n",
" Loss: 2.1656146\n",
" Running backpropagation...\n",
" Applying Conv2D<Float> layer...\n"
],
"name": "stdout"
}
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14 changes: 7 additions & 7 deletions docs/site/tutorials/using_raw_tensorflow_operators.ipynb
View file
Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "Using Raw TensorFlow Operators.ipynb",
"name": "Using raw TensorFlow operators.ipynb",
"version": "0.3.2",
"provenance": [],
"collapsed_sections": [],
Expand Down Expand Up @@ -56,7 +56,7 @@
},
"cell_type": "markdown",
"source": [
"# Using Raw TensorFlow Operators\n",
"# Using raw TensorFlow operators\n",
"\n",
"Building on TensorFlow, Swift for TensorFlow takes a fresh approach to API design. APIs are carefully curated from established libraries and combined with new language idioms. This means that not all TensorFlow APIs will be directly available as Swift APIs, and our API curation needs time and dedicated effort to evolve. However, do not worry if your favorite TensorFlow operator is not available in Swift -- the TensorFlow Swift library gives you transparent access to most TensorFlow operators, under the `Raw` namespace.\n"
]
Expand Down Expand Up @@ -91,7 +91,7 @@
},
"cell_type": "markdown",
"source": [
"## Calling Raw Operators\n",
"## Calling raw operators\n",
"\n",
"Simply find the function you need under the `Raw` namespace via code completion."
]
Expand All @@ -110,7 +110,7 @@
"source": [
"Raw.mul(Tensor([2.0, 3.0]), Tensor([5.0, 6.0]))"
],
"execution_count": 8,
"execution_count": 0,
"outputs": [
{
"output_type": "execute_result",
Expand Down Expand Up @@ -164,7 +164,7 @@
"let y: Tensor<Double> = [[8.0, 7.0], [6.0, 5.0]]\n",
"x .* y"
],
"execution_count": 3,
"execution_count": 0,
"outputs": [
{
"output_type": "execute_result",
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" (x .* y).sum()\n",
"}"
],
"execution_count": 17,
"execution_count": 0,
"outputs": [
{
"output_type": "execute_result",
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"print(Raw.matMul(matrix, matrix, transposeA: false, transposeB: true))\n",
"print(Raw.matMul(matrix, matrix, transposeA: false, transposeB: false))"
],
"execution_count": 16,
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
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