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Reset & Clear Output
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‎lab-10_3_1_visdom-example.ipynb

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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"WARNING:root:Setting up a new session...\n"
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]
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}
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],
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import visdom\n",
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"vis = visdom.Visdom()"
@@ -54,22 +46,11 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": null,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'window_371a70736cec9c'"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"outputs": [],
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"source": [
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"vis.text(\"Hello, world!\",env=\"main\")"
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]
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},
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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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"outputs": [
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"data": {
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"text/plain": [
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"'window_371a707d7964e2'"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"a=torch.randn(3,200,200)\n",
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"vis.image(a)"
@@ -111,22 +81,11 @@
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": null,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'window_371a708d402528'"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"outputs": [],
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"source": [
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"vis.images(torch.Tensor(3,3,28,28))"
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]
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},
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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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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Files already downloaded and verified\n"
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]
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}
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],
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"MNIST = dsets.MNIST(root=\"./MNIST_data\",train = True,transform=torchvision.transforms.ToTensor(), download=True)\n",
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"cifar10 = dsets.CIFAR10(root=\"./cifar10\",train = True, transform=torchvision.transforms.ToTensor(),download=True)"
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"torch.Size([3, 32, 32])\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"'window_371a70a62d1308'"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"data = cifar10.__getitem__(0)\n",
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"print(data[0].shape)\n",
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},
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": null,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"torch.Size([1, 28, 28])\n"
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]
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},
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"data": {
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"text/plain": [
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"'window_371a70af889fe0'"
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]
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},
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"execution_count": 9,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"outputs": [],
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"source": [
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"data = MNIST.__getitem__(0)\n",
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"print(data[0].shape)\n",
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},
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"cell_type": "code",
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"execution_count": 10,
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"source": [
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},
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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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"scrolled": true
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"torch.Size([32, 1, 28, 28])\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"for num, value in enumerate(data_loader):\n",
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" value = value[0]\n",
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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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"outputs": [
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{
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"data": {
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"text/plain": [
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"''"
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]
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},
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"execution_count": 21,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"vis.close(env=\"main\")"
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]
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},
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"cell_type": "code",
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"execution_count": 15,
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"source": [
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"cell_type": "code",
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"execution_count": 17,
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"source": [
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},
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"cell_type": "code",
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"metadata": {
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"scrolled": true
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"outputs": [
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"data": {
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"text/plain": [
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"'window_371a70f95f8dee'"
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"execution_count": 18,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"outputs": [],
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"source": [
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"Y_append = torch.randn(1)\n",
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"X_append = torch.Tensor([6])\n",
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},
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"torch.Size([10])\n",
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"torch.Size([10, 1])\n",
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"torch.Size([10, 2])\n"
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]
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}
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],
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"num = torch.Tensor(list(range(0,10)))\n",
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"num = num.view(-1,1)\n",
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},
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},
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},
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{
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"cell_type": "code",
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"execution_count": 27,
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"metadata": {},
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"outputs": [
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"data": {
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"text/plain": [
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"''"
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"vis.close(env=\"main\")"
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]

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