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Merged
merged 2 commits into from
Feb 28, 2023
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Style updates - cleaned up outputs #949

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33fdf4e
Style updates - cleaned up outputs
ovalle15 Feb 28, 2023
b99babd
Added comment about min data rows for current demo
ovalle15 Feb 28, 2023
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98 changes: 49 additions & 49 deletions examples/basics/custom_embeddings.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -50,11 +50,26 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 1,
"metadata": {
"id": "wRIdzkYf7T18"
"id": "wRIdzkYf7T18",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "13ee42f0-4206-493f-f402-ac7c84916e5e"
},
"outputs": [],
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m189.2/189.2 KB\u001b[0m \u001b[31m3.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.8/7.8 MB\u001b[0m \u001b[31m52.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Building wheel for pygeotile (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
]
}
],
"source": [
"# labelbox\n",
"!pip3 install -q labelbox[data]\n",
Expand All @@ -75,13 +90,13 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 2,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "9k82ueIu8Dy1",
"outputId": "cc728790-fc62-4d8d-a3e7-94739ffec809"
"outputId": "5323157e-872b-4bf2-a65c-0fa9662cdbe8"
},
"outputs": [
{
Expand All @@ -90,7 +105,9 @@
"text": [
" Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
" Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
" Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n"
" Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m62.8/62.8 KB\u001b[0m \u001b[31m2.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25h Building wheel for advlib (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n"
]
}
],
Expand Down Expand Up @@ -136,13 +153,14 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 32,
"metadata": {
"id": "tOIyo5pC7PTz"
},
"outputs": [],
"source": [
"# get images from a Labelbox dataset\n",
"# Our systems start to process data after 1000 embeddings of each type, for this demo make sure your dataset is over 1000 data rows",
"dataset = client.get_dataset(\"<ADD YOUR DATASET ID>\")\n",
"drs = list(dataset.export_data_rows(timeout_seconds=9999))\n",
"data_row_ids = [dr.uid for dr in drs]"
Expand All @@ -161,7 +179,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 33,
"metadata": {
"id": "iJFGf0w7swnW"
},
Expand Down Expand Up @@ -193,37 +211,20 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 35,
"metadata": {
"id": "u0ZgybLK67n0",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "d644f81a-014e-4de9-913a-74211972e9b2"
"outputId": "7e1991a0-8e0a-4e63-e8d8-dfdcf095a625"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Nb of custom embedding vectors in sanity_check_payload: 1000\n",
"sanity_check_payload: "
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"IOPub data rate exceeded.\n",
"The notebook server will temporarily stop sending output\n",
"to the client in order to avoid crashing it.\n",
"To change this limit, set the config variable\n",
"`--NotebookApp.iopub_data_rate_limit`.\n",
"\n",
"Current values:\n",
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
"NotebookApp.rate_limit_window=3.0 (secs)\n",
"\n"
"Nb of custom embedding vectors in sanity_check_payload: 1000\n"
]
}
],
Expand Down Expand Up @@ -251,13 +252,13 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 46,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "YQeCS_U98BD2",
"outputId": "178dc3be-6e89-4df8-ec3d-2fa6dacc0be0"
"outputId": "cdeb0bc7-9ea1-4864-88ff-122f6dab8af4"
},
"outputs": [
{
Expand All @@ -266,9 +267,8 @@
"text": [
"00000000-0000-0000-0000-000000000000 - Image Embedding (CLIP ViT-B/32) - dims: 512 \n",
"00000000-0000-0000-0000-000000000001 - Text embedding (All-MPNet-base-v2) - dims: 768 \n",
"521eadfe-f8e9-4135-9ead-fef8e9713546 - my_custom_embedding_2048_dimensions - dims: 2048 \n",
"a03948c1-151a-4a1a-b948-c1151a6a1a1d - ResNet50_2048_dimensions - dims: 2048 \n",
"baf8856a-e5f7-4781-b885-6ae5f7b78192 - my_custom_embedding - dims: 8 \n"
"45cafc7a-5314-462a-8afc-7a5314062a3b - my_custom_embedding_2048_dimensions - dims: 2048 \n",
"7d3a6118-589d-4b6c-ba61-18589dbb6ccf - ResNet50_2048_dimensions - dims: 2048 \n"
]
}
],
Expand All @@ -279,34 +279,34 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 47,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "spyHzkLP67dI",
"outputId": "21b6fda1-7a38-4bd5-d244-dfc90b8a5090"
"outputId": "8a046562-5eb1-4fb1-8f23-6958f8b58e1f"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Embedding type created id=521eadfe-f8e9-4135-9ead-fef8e9713546\n"
"Embedding type created id=da5d4b0f-e440-4e2e-9d4b-0fe4400e2e8d\n"
]
}
],
"source": [
"# # Create a new custom embedding\n",
"!advtool embeddings create my_custom_embedding_2048_dimensions 2048\n",
"!advtool embeddings create my_custom_embedding_2048_dimensions_v2 2048\n",
"# will return the ID of the newly created embedding, e.g. 0ddc5d5c-0963-41ad-9c5d-5c0963a1ad98"
]
},
{
"cell_type": "code",
"source": [
"# # Delete a custom embedding\n",
"# !advtool embeddings delete 521eadfe-f8e9-4135-9ead-fef8e9713546"
"# !advtool embeddings delete 2e122b85-7def-44fb-922b-857defe4fb8a"
],
"metadata": {
"id": "MafxKyncxyvR"
Expand All @@ -325,13 +325,13 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 49,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "twDd5XNM67Zo",
"outputId": "a7715fe7-3fc3-43d0-8316-bbc45a7dee60"
"outputId": "cb4573de-5417-449b-b560-9f99cfe6eda4"
},
"outputs": [
{
Expand All @@ -345,43 +345,43 @@
}
],
"source": [
"# Upload the payload to Labelbox\n",
"!advtool embeddings import 521eadfe-f8e9-4135-9ead-fef8e9713546 ./payload.ndjson"
"# Upload the payload to Labelbox \n",
"!advtool embeddings import da5d4b0f-e440-4e2e-9d4b-0fe4400e2e8d ./payload.ndjson"
]
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 63,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "wC0eeEPM9aAM",
"outputId": "5889b2f8-1a07-4748-b3bf-efab545f1417"
"outputId": "55932ddf-2dde-48c1-fd90-29532b8cfdf2"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"0\n"
"1000\n"
]
}
],
"source": [
"# count how many data rows have a specific custom embedding\n",
"!advtool embeddings count 521eadfe-f8e9-4135-9ead-fef8e9713546"
"# count how many data rows have a specific custom embedding (This can take a couple of minutes)\n",
"!advtool embeddings count da5d4b0f-e440-4e2e-9d4b-0fe4400e2e8d"
]
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 64,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "5AKDMJfO9Z51",
"outputId": "b3b6e7ca-1e99-4563-d8fe-038375008b69"
"outputId": "207f251f-0350-451e-ffcb-661cafb0529f"
},
"outputs": [
{
Expand Down