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Hvass-LabsHvass-Labs
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Tiny fix.
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‎14_DeepDream.ipynb

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@@ -41,7 +41,6 @@
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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},
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"outputs": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"collapsed": false
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"metadata": {},
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"outputs": [
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{
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"data": {
@@ -140,9 +137,7 @@
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {
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"collapsed": false
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"metadata": {},
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"outputs": [
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{
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"data": {
@@ -181,9 +176,7 @@
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {
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"collapsed": false
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"metadata": {},
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"outputs": [],
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"source": [
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"import inception5h"
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {
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"collapsed": false
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
@@ -263,7 +254,6 @@
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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},
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"outputs": [
@@ -671,7 +661,8 @@
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" # Calculate the value of the gradient.\n",
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" # This tells us how to change the image so as to\n",
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" # maximize the mean of the given layer-tensor.\n",
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" grad = tiled_gradient(gradient=gradient, image=img)\n",
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" grad = tiled_gradient(gradient=gradient, image=img,\n",
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" tile_size=tile_size)\n",
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" \n",
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" # Blur the gradient with different amounts and add\n",
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" # them together. The blur amount is also increased\n",
@@ -839,9 +830,7 @@
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{
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"cell_type": "code",
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"execution_count": 21,
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"metadata": {
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"collapsed": false
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"metadata": {},
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"outputs": [
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"data": {
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"cell_type": "code",
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"execution_count": 22,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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},
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"outputs": [
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{
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"cell_type": "code",
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"execution_count": 23,
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"metadata": {
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"collapsed": false
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"cell_type": "code",
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"execution_count": 25,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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"outputs": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"layer_tensor = model.layer_tensors[6]\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"layer_tensor = model.layer_tensors[7][:,:,:,0:3]\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"layer_tensor = model.layer_tensors[11][:,:,:,0]\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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"metadata": {},
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"outputs": [],
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"source": [
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"image = load_image(filename='images/giger.jpg')\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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"metadata": {},
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"outputs": [],
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"source": [
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"layer_tensor = model.layer_tensors[3]\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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"metadata": {},
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"outputs": [],
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"source": [
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"layer_tensor = model.layer_tensors[5]\n",
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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"outputs": [],
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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"metadata": {},
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"outputs": [],
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"source": [
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"layer_tensor = model.layer_tensors[6]\n",
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"metadata": {
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"anaconda-cloud": {},
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"kernelspec": {
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"display_name": "Python [default]",
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.5.2"
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"version": "3.6.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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"nbformat_minor": 1
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}

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