diff --git a/docs/iou3d.html b/docs/iou3d.html index 17c6b032..ab378300 100644 --- a/docs/iou3d.html +++ b/docs/iou3d.html @@ -107,7 +107,7 @@ The intersection shape is formed by the convex hull from the intersection points

Usage and Code

from pytorch3d.ops import box3d_overlap
 # Assume inputs: boxes1 (M, 8, 3) and boxes2 (N, 8, 3)
-intersection_vol, iou_3d = box3d_overal(boxes1, boxes2)
+intersection_vol, iou_3d = box3d_overlap(boxes1, boxes2)

For more details, read iou_box3d.py.

Note that our implementation is not differentiable as of now. We plan to add gradient support soon.

@@ -122,4 +122,4 @@ intersection_vol, iou_3d = box3d_overal(boxes1, boxes2) year = {2020}, } -
Last updated by Georgia Gkioxari
← CubifyPlotly Visualization →
\ No newline at end of file +
Last updated by Ji Hou
← CubifyPlotly Visualization →
\ No newline at end of file diff --git a/docs/iou3d/index.html b/docs/iou3d/index.html index 17c6b032..ab378300 100644 --- a/docs/iou3d/index.html +++ b/docs/iou3d/index.html @@ -107,7 +107,7 @@ The intersection shape is formed by the convex hull from the intersection points

Usage and Code

from pytorch3d.ops import box3d_overlap
 # Assume inputs: boxes1 (M, 8, 3) and boxes2 (N, 8, 3)
-intersection_vol, iou_3d = box3d_overal(boxes1, boxes2)
+intersection_vol, iou_3d = box3d_overlap(boxes1, boxes2)

For more details, read iou_box3d.py.

Note that our implementation is not differentiable as of now. We plan to add gradient support soon.

@@ -122,4 +122,4 @@ intersection_vol, iou_3d = box3d_overal(boxes1, boxes2) year = {2020}, } -
Last updated by Georgia Gkioxari
← CubifyPlotly Visualization →
\ No newline at end of file +
Last updated by Ji Hou
← CubifyPlotly Visualization →
\ No newline at end of file diff --git a/files/implicitron_config_system.ipynb b/files/implicitron_config_system.ipynb index 365acf19..9d69259e 100644 --- a/files/implicitron_config_system.ipynb +++ b/files/implicitron_config_system.ipynb @@ -1,79 +1,38 @@ { - "metadata": { - "dataExplorerConfig": {}, - "bento_stylesheets": { - "bento/extensions/flow/main.css": true, - "bento/extensions/kernel_selector/main.css": true, - "bento/extensions/kernel_ui/main.css": true, - "bento/extensions/new_kernel/main.css": true, - "bento/extensions/system_usage/main.css": true, - "bento/extensions/theme/main.css": true - }, - "kernelspec": { - "display_name": "pytorch3d", - "language": "python", - "name": "bento_kernel_pytorch3d", - "metadata": { - "kernel_name": "bento_kernel_pytorch3d", - "nightly_builds": true, - "fbpkg_supported": true, - "cinder_runtime": false, - "is_prebuilt": true - } - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3" - }, - "last_server_session_id": "d6b46f14-cee7-44c1-8c51-39a38a4ea4c2", - "last_kernel_id": "90755407-3729-46f4-ab67-ff2cb1daa5cb", - "last_base_url": "https://9177.od.fbinfra.net:443/", - "last_msg_id": "f61034eb-826226915ad9548ffbe495ba_6317", - "captumWidgetMessage": {}, - "outputWidgetContext": {} - }, - "nbformat": 4, - "nbformat_minor": 2, "cells": [ { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "f0af2d90-cb21-4ab4-b4cb-0fd00dbfb77b", - "showInput": true, "customInput": null, - "customOutput": null + "customOutput": null, + "originalKey": "f0af2d90-cb21-4ab4-b4cb-0fd00dbfb77b", + "showInput": true }, + "outputs": [], "source": [ "# Copyright (c) Meta Platforms, Inc. and affiliates. All rights reserved." - ], - "execution_count": null, - "outputs": [] + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { + "customInput": null, "originalKey": "4e15bfa2-5404-40d0-98b6-eb2732c8b72b", - "showInput": false, - "customInput": null + "showInput": false }, "source": [ "# Implicitron's config system" - ], - "attachments": {} + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { + "customInput": null, "originalKey": "287be985-423d-42e0-a2af-1e8c585e723c", - "showInput": false, - "customInput": null + "showInput": false }, "source": [ "Implicitron's components are all based on a unified hierarchical configuration system. \n", @@ -83,17 +42,15 @@ "\n", "The file which defines this system is [here](https://github.com/facebookresearch/pytorch3d/blob/main/pytorch3d/implicitron/tools/config.py) in the PyTorch3D repo.\n", "The Implicitron volumes tutorial contains a simple example of using the config system.\n", - "This tutorial provides detailed hands-on experience in using and modifying Implicitron's configurable components.\n", - "" - ], - "attachments": {} + "This tutorial provides detailed hands-on experience in using and modifying Implicitron's configurable components.\n" + ] }, { "cell_type": "markdown", "metadata": { + "customInput": null, "originalKey": "fde300a2-99cb-4d52-9d5b-4464a2083e0b", - "showInput": false, - "customInput": null + "showInput": false }, "source": [ "## 0. Install and import modules\n", @@ -103,12 +60,14 @@ }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "ad6e94a7-e114-43d3-b038-a5210c7d34c9", - "showInput": true, "customInput": null, - "customOutput": null + "customOutput": null, + "originalKey": "ad6e94a7-e114-43d3-b038-a5210c7d34c9", + "showInput": true }, + "outputs": [], "source": [ "import os\n", "import sys\n", @@ -135,48 +94,48 @@ " !tar xzf 1.10.0.tar.gz\n", " os.environ[\"CUB_HOME\"] = os.getcwd() + \"/cub-1.10.0\"\n", " !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'" - ], - "execution_count": null, - "outputs": [] + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { + "customInput": null, "originalKey": "609896c0-9e2e-4716-b074-b565f0170e32", - "showInput": false, - "customInput": null + "showInput": false }, "source": [ "Ensure omegaconf is installed. If not, run this cell. (It should not be necessary to restart the runtime.)" - ], - "attachments": {} + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "d1c1851e-b9f2-4236-93c3-19aa4d63041c", - "showInput": true, "customInput": null, - "customOutput": null + "customOutput": null, + "originalKey": "d1c1851e-b9f2-4236-93c3-19aa4d63041c", + "showInput": true }, + "outputs": [], "source": [ "!pip install omegaconf" - ], - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "collapsed": false, - "originalKey": "5ac7ef23-b74c-46b2-b8d3-799524d7ba4f", "code_folding": [], - "hidden_ranges": [], - "requestMsgId": "5ac7ef23-b74c-46b2-b8d3-799524d7ba4f", + "collapsed": false, "customOutput": null, "executionStartTime": 1659465468717, - "executionStopTime": 1659465468738 + "executionStopTime": 1659465468738, + "hidden_ranges": [], + "originalKey": "5ac7ef23-b74c-46b2-b8d3-799524d7ba4f", + "requestMsgId": "5ac7ef23-b74c-46b2-b8d3-799524d7ba4f" }, + "outputs": [], "source": [ "from dataclasses import dataclass\n", "from typing import Optional, Tuple\n", @@ -191,16 +150,14 @@ " registry,\n", " run_auto_creation,\n", ")" - ], - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "markdown", "metadata": { + "customInput": null, "originalKey": "a638bf90-eb6b-424d-b53d-eae11954a717", - "showInput": false, - "customInput": null + "showInput": false }, "source": [ "## 1. Introducing dataclasses \n", @@ -210,16 +167,18 @@ }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "71eaad5e-e198-492e-8610-24b0da9dd4ae", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "71eaad5e-e198-492e-8610-24b0da9dd4ae", + "customInput": null, "customOutput": null, "executionStartTime": 1659454972732, - "executionStopTime": 1659454972739 + "executionStopTime": 1659454972739, + "originalKey": "71eaad5e-e198-492e-8610-24b0da9dd4ae", + "requestMsgId": "71eaad5e-e198-492e-8610-24b0da9dd4ae", + "showInput": true }, + "outputs": [], "source": [ "@dataclass\n", "class MyDataclass:\n", @@ -230,230 +189,228 @@ " def __post_init__(self):\n", " print(f\"created with a = {self.a}\")\n", " self.d = 2 * self.b" - ], - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "83202a18-a3d3-44ec-a62d-b3360a302645", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "83202a18-a3d3-44ec-a62d-b3360a302645", + "customInput": null, "customOutput": null, "executionStartTime": 1659454973051, - "executionStopTime": 1659454973077 + "executionStopTime": 1659454973077, + "originalKey": "83202a18-a3d3-44ec-a62d-b3360a302645", + "requestMsgId": "83202a18-a3d3-44ec-a62d-b3360a302645", + "showInput": true }, + "outputs": [], "source": [ "my_dataclass_instance = MyDataclass(a=18)\n", "assert my_dataclass_instance.d == 16" - ], - "execution_count": null, - "outputs": [] + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { + "customInput": null, "originalKey": "b67ccb9f-dc6c-4994-9b99-b5a1bcfebd70", - "showInput": false, - "customInput": null + "showInput": false }, "source": [ "👷 Note that the `dataclass` decorator here is function which modifies the definition of the class itself.\n", "It runs immediately after the definition.\n", "Our config system requires that implicitron library code contains classes whose modified versions need to be aware of user-defined implementations.\n", - "Therefore we need the modification of the class to be delayed. We don't use a decorator.\n", - "" - ], - "attachments": {} + "Therefore we need the modification of the class to be delayed. We don't use a decorator.\n" + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { + "customInput": null, "originalKey": "3e90f664-99df-4387-9c45-a1ad7939ef3a", - "showInput": false, - "customInput": null + "showInput": false }, "source": [ "## 2. Introducing omegaconf and OmegaConf.structured\n", "\n", "The [omegaconf](https://github.com/omry/omegaconf/) library provides a DictConfig class which is like a `dict` with str keys, but with extra features for ease-of-use as a configuration system." - ], - "attachments": {} + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "81c73c9b-27ee-4aab-b55e-fb0dd67fe174", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "81c73c9b-27ee-4aab-b55e-fb0dd67fe174", + "customInput": null, "customOutput": null, "executionStartTime": 1659451341683, - "executionStopTime": 1659451341690 + "executionStopTime": 1659451341690, + "originalKey": "81c73c9b-27ee-4aab-b55e-fb0dd67fe174", + "requestMsgId": "81c73c9b-27ee-4aab-b55e-fb0dd67fe174", + "showInput": true }, + "outputs": [], "source": [ "dc = DictConfig({\"a\": 2, \"b\": True, \"c\": None, \"d\": \"hello\"})\n", "assert dc.a == dc[\"a\"] == 2" - ], - "execution_count": null, - "outputs": [] + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { + "customInput": null, "originalKey": "3b5b76a9-4b76-4784-96ff-2a1212e48e48", - "showInput": false, - "customInput": null + "showInput": false }, "source": [ "OmegaConf has a serialization to and from yaml. The [Hydra](https://hydra.cc/) library relies on this for its configuration files." - ], - "attachments": {} + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "d7a25ec1-caea-46bc-a1da-4b1f040c4b61", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "d7a25ec1-caea-46bc-a1da-4b1f040c4b61", + "customInput": null, "customOutput": null, "executionStartTime": 1659451411835, - "executionStopTime": 1659451411936 + "executionStopTime": 1659451411936, + "originalKey": "d7a25ec1-caea-46bc-a1da-4b1f040c4b61", + "requestMsgId": "d7a25ec1-caea-46bc-a1da-4b1f040c4b61", + "showInput": true }, + "outputs": [], "source": [ "print(OmegaConf.to_yaml(dc))\n", "assert OmegaConf.create(OmegaConf.to_yaml(dc)) == dc" - ], - "execution_count": null, - "outputs": [] + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { + "customInput": null, "originalKey": "777fecdd-8bf6-4fd8-827b-cb8af5477fa8", - "showInput": false, - "customInput": null + "showInput": false }, "source": [ "OmegaConf.structured provides a DictConfig from a dataclass or instance of a dataclass. Unlike a normal DictConfig, it is type-checked and only known keys can be added." - ], - "attachments": {} + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "de36efb4-0b08-4fb8-bb3a-be1b2c0cd162", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "de36efb4-0b08-4fb8-bb3a-be1b2c0cd162", + "customInput": null, "customOutput": null, "executionStartTime": 1659455098879, - "executionStopTime": 1659455098900 + "executionStopTime": 1659455098900, + "originalKey": "de36efb4-0b08-4fb8-bb3a-be1b2c0cd162", + "requestMsgId": "de36efb4-0b08-4fb8-bb3a-be1b2c0cd162", + "showInput": true }, + "outputs": [], "source": [ "structured = OmegaConf.structured(MyDataclass)\n", "assert isinstance(structured, DictConfig)\n", "print(structured)\n", "print()\n", "print(OmegaConf.to_yaml(structured))" - ], - "execution_count": null, - "outputs": [] + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { + "customInput": null, "originalKey": "be4446da-e536-4139-9ba3-37669a5b5e61", - "showInput": false, - "customInput": null + "showInput": false }, "source": [ "`structured` knows it is missing a value for `a`." - ], - "attachments": {} + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { + "customInput": null, "originalKey": "864811e8-1a75-4932-a85e-f681b0541ae9", - "showInput": false, - "customInput": null + "showInput": false }, "source": [ "Such an object has members compatible with the dataclass, so an initialisation can be performed as follows." - ], - "attachments": {} + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "eb88aaa0-c22f-4ffb-813a-ca957b490acb", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "eb88aaa0-c22f-4ffb-813a-ca957b490acb", + "customInput": null, "customOutput": null, "executionStartTime": 1659455580491, - "executionStopTime": 1659455580501 + "executionStopTime": 1659455580501, + "originalKey": "eb88aaa0-c22f-4ffb-813a-ca957b490acb", + "requestMsgId": "eb88aaa0-c22f-4ffb-813a-ca957b490acb", + "showInput": true }, + "outputs": [], "source": [ "structured.a = 21\n", "my_dataclass_instance2 = MyDataclass(**structured)\n", "print(my_dataclass_instance2)" - ], - "execution_count": null, - "outputs": [] + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { + "customInput": null, "originalKey": "2d08c81c-9d18-4de9-8464-0da2d89f94f3", - "showInput": false, - "customInput": null + "showInput": false }, "source": [ "You can also call OmegaConf.structured on an instance." - ], - "attachments": {} + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "5e469bac-32a4-475d-9c09-8b64ba3f2155", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "5e469bac-32a4-475d-9c09-8b64ba3f2155", + "customInput": null, "customOutput": null, "executionStartTime": 1659455594700, - "executionStopTime": 1659455594737 + "executionStopTime": 1659455594737, + "originalKey": "5e469bac-32a4-475d-9c09-8b64ba3f2155", + "requestMsgId": "5e469bac-32a4-475d-9c09-8b64ba3f2155", + "showInput": true }, + "outputs": [], "source": [ "structured_from_instance = OmegaConf.structured(my_dataclass_instance)\n", "my_dataclass_instance3 = MyDataclass(**structured_from_instance)\n", "print(my_dataclass_instance3)" - ], - "execution_count": null, - "outputs": [] + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { - "originalKey": "2ed559e3-8552-465a-938f-30c72a321184", - "showInput": false, - "customInput": null, "collapsed": false, - "requestMsgId": "2ed559e3-8552-465a-938f-30c72a321184", + "customInput": null, "customOutput": null, "executionStartTime": 1659452594203, - "executionStopTime": 1659452594333 + "executionStopTime": 1659452594333, + "originalKey": "2ed559e3-8552-465a-938f-30c72a321184", + "requestMsgId": "2ed559e3-8552-465a-938f-30c72a321184", + "showInput": false }, "source": [ "## 3. Our approach to OmegaConf.structured\n", @@ -461,21 +418,22 @@ "We provide functions which are equivalent to `OmegaConf.structured` but support more features. \n", "To achieve the above using our functions, the following is used.\n", "Note that we indicate configurable classes using a special base class `Configurable`, not a decorator." - ], - "attachments": {} + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "9888afbd-e617-4596-ab7a-fc1073f58656", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "9888afbd-e617-4596-ab7a-fc1073f58656", + "customInput": null, "customOutput": null, "executionStartTime": 1659454053323, - "executionStopTime": 1659454061629 + "executionStopTime": 1659454061629, + "originalKey": "9888afbd-e617-4596-ab7a-fc1073f58656", + "requestMsgId": "9888afbd-e617-4596-ab7a-fc1073f58656", + "showInput": true }, + "outputs": [], "source": [ "class MyConfigurable(Configurable):\n", " a: int\n", @@ -485,105 +443,105 @@ " def __post_init__(self):\n", " print(f\"created with a = {self.a}\")\n", " self.d = 2 * self.b" - ], - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "e43155b4-3da5-4df1-a2f5-da1d0369eec9", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "e43155b4-3da5-4df1-a2f5-da1d0369eec9", + "customInput": null, "customOutput": null, "executionStartTime": 1659454784912, - "executionStopTime": 1659454784928 + "executionStopTime": 1659454784928, + "originalKey": "e43155b4-3da5-4df1-a2f5-da1d0369eec9", + "requestMsgId": "e43155b4-3da5-4df1-a2f5-da1d0369eec9", + "showInput": true }, + "outputs": [], "source": [ - "# expand_args_fields must be called on an object before it is instantiated.\n", - "# A warning is raised if this is missed, but it is possible to not notice the warning.\n", - "# It modifies the class like @dataclass\n", + "# The expand_args_fields function modifies the class like @dataclasses.dataclass.\n", + "# If it has not been called on a Configurable object before it has been instantiated, it will\n", + "# be called automatically.\n", "expand_args_fields(MyConfigurable)\n", "my_configurable_instance = MyConfigurable(a=18)\n", "assert my_configurable_instance.d == 16" - ], - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "96eaae18-dce4-4ee1-b451-1466fea51b9f", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "96eaae18-dce4-4ee1-b451-1466fea51b9f", + "customInput": null, "customOutput": null, "executionStartTime": 1659460669541, - "executionStopTime": 1659460669566 + "executionStopTime": 1659460669566, + "originalKey": "96eaae18-dce4-4ee1-b451-1466fea51b9f", + "requestMsgId": "96eaae18-dce4-4ee1-b451-1466fea51b9f", + "showInput": true }, + "outputs": [], "source": [ - "# get_default_args calls expand_args_fields automatically\n", + "# get_default_args also calls expand_args_fields automatically\n", "our_structured = get_default_args(MyConfigurable)\n", "assert isinstance(our_structured, DictConfig)\n", "print(OmegaConf.to_yaml(our_structured))" - ], - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "359f7925-68de-42cd-bd34-79a099b1c210", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "359f7925-68de-42cd-bd34-79a099b1c210", + "customInput": null, "customOutput": null, "executionStartTime": 1659460454020, - "executionStopTime": 1659460454032 + "executionStopTime": 1659460454032, + "originalKey": "359f7925-68de-42cd-bd34-79a099b1c210", + "requestMsgId": "359f7925-68de-42cd-bd34-79a099b1c210", + "showInput": true }, + "outputs": [], "source": [ "our_structured.a = 21\n", "print(MyConfigurable(**our_structured))" - ], - "execution_count": null, - "outputs": [] + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { - "originalKey": "eac7d385-9365-4098-acf9-4f0a0dbdcb85", - "showInput": false, - "customInput": null, "collapsed": false, - "requestMsgId": "eac7d385-9365-4098-acf9-4f0a0dbdcb85", + "customInput": null, "customOutput": null, "executionStartTime": 1659460599142, - "executionStopTime": 1659460599149 + "executionStopTime": 1659460599149, + "originalKey": "eac7d385-9365-4098-acf9-4f0a0dbdcb85", + "requestMsgId": "eac7d385-9365-4098-acf9-4f0a0dbdcb85", + "showInput": false }, "source": [ "## 4. First enhancement: nested types 🪺\n", "\n", "Our system allows Configurable classes to contain each other. \n", "One thing to remember: add a call to `run_auto_creation` in `__post_init__`." - ], - "attachments": {} + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "9bd70ee5-4ec1-4021-bce5-9638b5088c0a", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "9bd70ee5-4ec1-4021-bce5-9638b5088c0a", + "customInput": null, "customOutput": null, "executionStartTime": 1659465752418, - "executionStopTime": 1659465752976 + "executionStopTime": 1659465752976, + "originalKey": "9bd70ee5-4ec1-4021-bce5-9638b5088c0a", + "requestMsgId": "9bd70ee5-4ec1-4021-bce5-9638b5088c0a", + "showInput": true }, + "outputs": [], "source": [ "class Inner(Configurable):\n", " a: int = 8\n", @@ -598,77 +556,76 @@ "\n", " def __post_init__(self):\n", " run_auto_creation(self)" - ], - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "9f2b9f98-b54b-46cc-9b02-9e902cb279e7", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "9f2b9f98-b54b-46cc-9b02-9e902cb279e7", + "customInput": null, "customOutput": null, "executionStartTime": 1659465762326, - "executionStopTime": 1659465762339 + "executionStopTime": 1659465762339, + "originalKey": "9f2b9f98-b54b-46cc-9b02-9e902cb279e7", + "requestMsgId": "9f2b9f98-b54b-46cc-9b02-9e902cb279e7", + "showInput": true }, + "outputs": [], "source": [ "outer_dc = get_default_args(Outer)\n", "print(OmegaConf.to_yaml(outer_dc))" - ], - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "0254204b-8c7a-4d40-bba6-5132185f63d7", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "0254204b-8c7a-4d40-bba6-5132185f63d7", + "customInput": null, "customOutput": null, "executionStartTime": 1659465772894, - "executionStopTime": 1659465772911 + "executionStopTime": 1659465772911, + "originalKey": "0254204b-8c7a-4d40-bba6-5132185f63d7", + "requestMsgId": "0254204b-8c7a-4d40-bba6-5132185f63d7", + "showInput": true }, + "outputs": [], "source": [ "outer = Outer(**outer_dc)\n", "assert isinstance(outer, Outer)\n", "assert isinstance(outer.inner, Inner)\n", "print(vars(outer))\n", "print(outer.inner)" - ], - "execution_count": null, - "outputs": [] + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { + "customInput": null, "originalKey": "44a78c13-ec92-4a87-808a-c4674b320c22", - "showInput": false, - "customInput": null + "showInput": false }, "source": [ "Note how inner_args is an extra member of outer. `run_auto_creation(self)` is equivalent to\n", "```\n", " self.inner = Inner(**self.inner_args)\n", "```" - ], - "attachments": {} + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { - "originalKey": "af0ec78b-7888-4b0d-9346-63d970d43293", - "showInput": false, - "customInput": null, "collapsed": false, - "requestMsgId": "af0ec78b-7888-4b0d-9346-63d970d43293", + "customInput": null, "customOutput": null, "executionStartTime": 1659461071129, - "executionStopTime": 1659461071137 + "executionStopTime": 1659461071137, + "originalKey": "af0ec78b-7888-4b0d-9346-63d970d43293", + "requestMsgId": "af0ec78b-7888-4b0d-9346-63d970d43293", + "showInput": false }, "source": [ "## 5. Second enhancement: pluggable/replaceable components 🔌\n", @@ -681,21 +638,22 @@ "\n", "A configurable class (i.e. a class which uses our system, i.e. a child of `Configurable` or `ReplaceableBase`) which contains a ReplaceableBase must also \n", "contain a corresponding class_type field of type `str` which indicates which concrete child class to use." - ], - "attachments": {} + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "f2898703-d147-4394-978e-fc7f1f559395", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "f2898703-d147-4394-978e-fc7f1f559395", + "customInput": null, "customOutput": null, "executionStartTime": 1659463453457, - "executionStopTime": 1659463453467 + "executionStopTime": 1659463453467, + "originalKey": "f2898703-d147-4394-978e-fc7f1f559395", + "requestMsgId": "f2898703-d147-4394-978e-fc7f1f559395", + "showInput": true }, + "outputs": [], "source": [ "class InnerBase(ReplaceableBase):\n", " def say_something(self):\n", @@ -717,22 +675,22 @@ "\n", " def say_something(self):\n", " print(\"hello from an Inner2\")" - ], - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "6f171599-51ee-440f-82d7-a59f84d24624", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "6f171599-51ee-440f-82d7-a59f84d24624", + "customInput": null, "customOutput": null, "executionStartTime": 1659463453514, - "executionStopTime": 1659463453592 + "executionStopTime": 1659463453592, + "originalKey": "6f171599-51ee-440f-82d7-a59f84d24624", + "requestMsgId": "6f171599-51ee-440f-82d7-a59f84d24624", + "showInput": true }, + "outputs": [], "source": [ "class Out(Configurable):\n", " inner: InnerBase\n", @@ -744,128 +702,128 @@ "\n", " def talk(self):\n", " self.inner.say_something()" - ], - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "7abaecec-96e6-44df-8c8d-69c36a14b913", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "7abaecec-96e6-44df-8c8d-69c36a14b913", + "customInput": null, "customOutput": null, "executionStartTime": 1659463191360, - "executionStopTime": 1659463191428 + "executionStopTime": 1659463191428, + "originalKey": "7abaecec-96e6-44df-8c8d-69c36a14b913", + "requestMsgId": "7abaecec-96e6-44df-8c8d-69c36a14b913", + "showInput": true }, + "outputs": [], "source": [ "Out_dc = get_default_args(Out)\n", "print(OmegaConf.to_yaml(Out_dc))" - ], - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "c82dc2ca-ba8f-4a44-aed3-43f6b52ec28c", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "c82dc2ca-ba8f-4a44-aed3-43f6b52ec28c", + "customInput": null, "customOutput": null, "executionStartTime": 1659463192717, - "executionStopTime": 1659463192754 + "executionStopTime": 1659463192754, + "originalKey": "c82dc2ca-ba8f-4a44-aed3-43f6b52ec28c", + "requestMsgId": "c82dc2ca-ba8f-4a44-aed3-43f6b52ec28c", + "showInput": true }, + "outputs": [], "source": [ "Out_dc.inner_class_type = \"Inner2\"\n", "out = Out(**Out_dc)\n", "print(out.inner)" - ], - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "aa0e1b04-963a-4724-81b7-5748b598b541", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "aa0e1b04-963a-4724-81b7-5748b598b541", + "customInput": null, "customOutput": null, "executionStartTime": 1659463193751, - "executionStopTime": 1659463193791 + "executionStopTime": 1659463193791, + "originalKey": "aa0e1b04-963a-4724-81b7-5748b598b541", + "requestMsgId": "aa0e1b04-963a-4724-81b7-5748b598b541", + "showInput": true }, + "outputs": [], "source": [ "out.talk()" - ], - "execution_count": null, - "outputs": [] + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { + "customInput": null, "originalKey": "4f78a56c-39cd-4563-a97e-041e5f360f6b", - "showInput": false, - "customInput": null + "showInput": false }, "source": [ "Note in this case there are many `args` members. It is usually fine to ignore them in the code. They are needed for the config." - ], - "attachments": {} + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "ce7069d5-a813-4286-a7cd-6ff40362105a", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "ce7069d5-a813-4286-a7cd-6ff40362105a", + "customInput": null, "customOutput": null, "executionStartTime": 1659462145294, - "executionStopTime": 1659462145307 + "executionStopTime": 1659462145307, + "originalKey": "ce7069d5-a813-4286-a7cd-6ff40362105a", + "requestMsgId": "ce7069d5-a813-4286-a7cd-6ff40362105a", + "showInput": true }, + "outputs": [], "source": [ "print(vars(out))" - ], - "execution_count": null, - "outputs": [] + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { - "originalKey": "c7f051ff-c264-4b89-80dc-36cf179aafaf", - "showInput": false, - "customInput": null, "collapsed": false, - "requestMsgId": "c7f051ff-c264-4b89-80dc-36cf179aafaf", + "customInput": null, "customOutput": null, "executionStartTime": 1659462231114, - "executionStopTime": 1659462231130 + "executionStopTime": 1659462231130, + "originalKey": "c7f051ff-c264-4b89-80dc-36cf179aafaf", + "requestMsgId": "c7f051ff-c264-4b89-80dc-36cf179aafaf", + "showInput": false }, "source": [ "## 6. Example with torch.nn.Module 🔥\n", "Typically in implicitron, we use this system in combination with [`Module`](https://pytorch.org/docs/stable/generated/torch.nn.Module.html)s. \n", "Note in this case it is necessary to call `Module.__init__` explicitly in `__post_init__`." - ], - "attachments": {} + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "42d210d6-09e0-4daf-8ccb-411d30f268f4", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "42d210d6-09e0-4daf-8ccb-411d30f268f4", + "customInput": null, "customOutput": null, "executionStartTime": 1659462645018, - "executionStopTime": 1659462645037 + "executionStopTime": 1659462645037, + "originalKey": "42d210d6-09e0-4daf-8ccb-411d30f268f4", + "requestMsgId": "42d210d6-09e0-4daf-8ccb-411d30f268f4", + "showInput": true }, + "outputs": [], "source": [ "class MyLinear(torch.nn.Module, Configurable):\n", " d_in: int = 2\n", @@ -877,101 +835,100 @@ "\n", " def forward(self, x):\n", " return self.linear.forward(x)" - ], - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "546781fe-5b95-4e48-9cb5-34a634a31313", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "546781fe-5b95-4e48-9cb5-34a634a31313", + "customInput": null, "customOutput": null, "executionStartTime": 1659462692309, - "executionStopTime": 1659462692346 + "executionStopTime": 1659462692346, + "originalKey": "546781fe-5b95-4e48-9cb5-34a634a31313", + "requestMsgId": "546781fe-5b95-4e48-9cb5-34a634a31313", + "showInput": true }, + "outputs": [], "source": [ - "expand_args_fields(MyLinear)\n", "my_linear = MyLinear()\n", "input = torch.zeros(2)\n", "output = my_linear(input)\n", "print(\"output shape:\", output.shape)" - ], - "execution_count": null, - "outputs": [] + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { - "originalKey": "b6cb71e1-1d54-4e89-a422-0a70772c5c03", - "showInput": false, - "customInput": null, "collapsed": false, - "requestMsgId": "b6cb71e1-1d54-4e89-a422-0a70772c5c03", + "customInput": null, "customOutput": null, "executionStartTime": 1659462738302, - "executionStopTime": 1659462738419 + "executionStopTime": 1659462738419, + "originalKey": "b6cb71e1-1d54-4e89-a422-0a70772c5c03", + "requestMsgId": "b6cb71e1-1d54-4e89-a422-0a70772c5c03", + "showInput": false }, "source": [ "`my_linear` has all the usual features of a Module.\n", "E.g. it can be saved and loaded with `torch.save` and `torch.load`.\n", "It has parameters:" - ], - "attachments": {} + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "47e8c53e-2d2c-4b41-8aa3-65aa3ea8a7d3", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "47e8c53e-2d2c-4b41-8aa3-65aa3ea8a7d3", + "customInput": null, "customOutput": null, "executionStartTime": 1659462821485, - "executionStopTime": 1659462821501 + "executionStopTime": 1659462821501, + "originalKey": "47e8c53e-2d2c-4b41-8aa3-65aa3ea8a7d3", + "requestMsgId": "47e8c53e-2d2c-4b41-8aa3-65aa3ea8a7d3", + "showInput": true }, + "outputs": [], "source": [ "for name, value in my_linear.named_parameters():\n", " print(name, value.shape)" - ], - "execution_count": null, - "outputs": [] + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { - "originalKey": "a01f0ea7-55f2-4af9-8e81-45dddf40f13b", - "showInput": false, - "customInput": null, "collapsed": false, - "requestMsgId": "a01f0ea7-55f2-4af9-8e81-45dddf40f13b", + "customInput": null, "customOutput": null, "executionStartTime": 1659463222379, - "executionStopTime": 1659463222409 + "executionStopTime": 1659463222409, + "originalKey": "a01f0ea7-55f2-4af9-8e81-45dddf40f13b", + "requestMsgId": "a01f0ea7-55f2-4af9-8e81-45dddf40f13b", + "showInput": false }, "source": [ "## 7. Example of implementing your own pluggable component \n", "Let's say I am using a library with `Out` like in section **5** but I want to implement my own child of InnerBase. \n", "All I need to do is register its definition, but I need to do this before expand_args_fields is explicitly or implicitly called on Out." - ], - "attachments": {} + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "d9635511-a52b-43d5-8dae-d5c1a3dd9157", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "d9635511-a52b-43d5-8dae-d5c1a3dd9157", + "customInput": null, "customOutput": null, "executionStartTime": 1659463694644, - "executionStopTime": 1659463694653 + "executionStopTime": 1659463694653, + "originalKey": "d9635511-a52b-43d5-8dae-d5c1a3dd9157", + "requestMsgId": "d9635511-a52b-43d5-8dae-d5c1a3dd9157", + "showInput": true }, + "outputs": [], "source": [ "@registry.register\n", "class UserImplementedInner(InnerBase):\n", @@ -979,16 +936,15 @@ "\n", " def say_something(self):\n", " print(\"hello from the user\")" - ], - "execution_count": null, - "outputs": [] + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { + "customInput": null, "originalKey": "f1511aa2-56b8-4ed0-a453-17e2bbfeefe7", - "showInput": false, - "customInput": null + "showInput": false }, "source": [ "At this point, we need to redefine the class Out. \n", @@ -997,21 +953,22 @@ "\n", "If you are running experiments from a script, the thing to remember here is that you must import your own modules, which register your own implementations,\n", "before you *use* the library classes." - ], - "attachments": {} + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "c7bb5a6e-682b-4eb0-a214-e0f5990b9406", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "c7bb5a6e-682b-4eb0-a214-e0f5990b9406", + "customInput": null, "customOutput": null, "executionStartTime": 1659463745967, - "executionStopTime": 1659463745986 + "executionStopTime": 1659463745986, + "originalKey": "c7bb5a6e-682b-4eb0-a214-e0f5990b9406", + "requestMsgId": "c7bb5a6e-682b-4eb0-a214-e0f5990b9406", + "showInput": true }, + "outputs": [], "source": [ "class Out(Configurable):\n", " inner: InnerBase\n", @@ -1023,61 +980,60 @@ "\n", " def talk(self):\n", " self.inner.say_something()" - ], - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "b6ecdc86-4b7b-47c6-9f45-a7e557c94979", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "b6ecdc86-4b7b-47c6-9f45-a7e557c94979", + "customInput": null, "customOutput": null, "executionStartTime": 1659463747398, - "executionStopTime": 1659463747431 + "executionStopTime": 1659463747431, + "originalKey": "b6ecdc86-4b7b-47c6-9f45-a7e557c94979", + "requestMsgId": "b6ecdc86-4b7b-47c6-9f45-a7e557c94979", + "showInput": true }, + "outputs": [], "source": [ - "expand_args_fields(Out)\n", "out2 = Out(inner_class_type=\"UserImplementedInner\")\n", "print(out2.inner)" - ], - "execution_count": null, - "outputs": [] + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { - "originalKey": "c7fe0df3-da13-40b8-9b06-6b1f37f37bb9", - "showInput": false, - "customInput": null, "collapsed": false, - "requestMsgId": "c7fe0df3-da13-40b8-9b06-6b1f37f37bb9", + "customInput": null, "customOutput": null, "executionStartTime": 1659464033633, - "executionStopTime": 1659464033643 + "executionStopTime": 1659464033643, + "originalKey": "c7fe0df3-da13-40b8-9b06-6b1f37f37bb9", + "requestMsgId": "c7fe0df3-da13-40b8-9b06-6b1f37f37bb9", + "showInput": false }, "source": [ "## 8: Example of making a subcomponent pluggable\n", "\n", "Let's look what needs to happen if we have a subcomponent which we make pluggable, to allow users to supply their own." - ], - "attachments": {} + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "e37227b2-6897-4033-8560-9f2040abdeeb", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "e37227b2-6897-4033-8560-9f2040abdeeb", + "customInput": null, "customOutput": null, "executionStartTime": 1659464709922, - "executionStopTime": 1659464709933 + "executionStopTime": 1659464709933, + "originalKey": "e37227b2-6897-4033-8560-9f2040abdeeb", + "requestMsgId": "e37227b2-6897-4033-8560-9f2040abdeeb", + "showInput": true }, + "outputs": [], "source": [ "class SubComponent(Configurable):\n", " x: float = 0.25\n", @@ -1097,55 +1053,54 @@ " for _ in range(self.repeats):\n", " a = self.subcomponent.apply(a)\n", " return a" - ], - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "cab4c121-350e-443f-9a49-bd542a9735a2", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "cab4c121-350e-443f-9a49-bd542a9735a2", + "customInput": null, "customOutput": null, "executionStartTime": 1659464710339, - "executionStopTime": 1659464710459 + "executionStopTime": 1659464710459, + "originalKey": "cab4c121-350e-443f-9a49-bd542a9735a2", + "requestMsgId": "cab4c121-350e-443f-9a49-bd542a9735a2", + "showInput": true }, + "outputs": [], "source": [ - "expand_args_fields(LargeComponent)\n", "large_component = LargeComponent()\n", "assert large_component.apply(3) == 4\n", "print(OmegaConf.to_yaml(LargeComponent))" - ], - "execution_count": null, - "outputs": [] + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { + "customInput": null, "originalKey": "be60323a-badf-46e4-a259-72cae1391028", - "showInput": false, - "customInput": null + "showInput": false }, "source": [ "Made generic:" - ], - "attachments": {} + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "fc0d8cdb-4627-4427-b92a-17ac1c1b37b8", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "fc0d8cdb-4627-4427-b92a-17ac1c1b37b8", + "customInput": null, "customOutput": null, "executionStartTime": 1659464717226, - "executionStopTime": 1659464717261 + "executionStopTime": 1659464717261, + "originalKey": "fc0d8cdb-4627-4427-b92a-17ac1c1b37b8", + "requestMsgId": "fc0d8cdb-4627-4427-b92a-17ac1c1b37b8", + "showInput": true }, + "outputs": [], "source": [ "class SubComponentBase(ReplaceableBase):\n", " def apply(self, a: float) -> float:\n", @@ -1172,42 +1127,40 @@ " for _ in range(self.repeats):\n", " a = self.subcomponent.apply(a)\n", " return a" - ], - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "code", + "execution_count": null, "metadata": { - "originalKey": "bbc3d321-6b49-4356-be75-1a173b1fc3a5", - "showInput": true, - "customInput": null, "collapsed": false, - "requestMsgId": "bbc3d321-6b49-4356-be75-1a173b1fc3a5", + "customInput": null, "customOutput": null, "executionStartTime": 1659464725473, - "executionStopTime": 1659464725587 + "executionStopTime": 1659464725587, + "originalKey": "bbc3d321-6b49-4356-be75-1a173b1fc3a5", + "requestMsgId": "bbc3d321-6b49-4356-be75-1a173b1fc3a5", + "showInput": true }, + "outputs": [], "source": [ - "expand_args_fields(LargeComponent)\n", "large_component = LargeComponent()\n", "assert large_component.apply(3) == 4\n", "print(OmegaConf.to_yaml(LargeComponent))" - ], - "execution_count": null, - "outputs": [] + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { - "originalKey": "5115453a-1d96-4022-97e7-46433e6dcf60", - "showInput": false, - "customInput": null, "collapsed": false, - "requestMsgId": "5115453a-1d96-4022-97e7-46433e6dcf60", + "customInput": null, "customOutput": null, "executionStartTime": 1659464672680, - "executionStopTime": 1659464673231 + "executionStopTime": 1659464673231, + "originalKey": "5115453a-1d96-4022-97e7-46433e6dcf60", + "requestMsgId": "5115453a-1d96-4022-97e7-46433e6dcf60", + "showInput": false }, "source": [ "The following things had to change:\n", @@ -1215,26 +1168,25 @@ "* SubComponent gained a `@registry.register` decoration and had its base class changed to the new one.\n", "* `subcomponent_class_type` was added as a member of the outer class.\n", "* In any saved configuration yaml files, the key `subcomponent_args` had to be changed to `subcomponent_SubComponent_args`." - ], - "attachments": {} + ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": { - "originalKey": "0739269e-5c0e-4551-b06f-f4aab386ba54", - "showInput": false, - "customInput": null, "collapsed": false, - "requestMsgId": "0739269e-5c0e-4551-b06f-f4aab386ba54", + "customInput": null, "customOutput": null, "executionStartTime": 1659462041307, - "executionStopTime": 1659462041637 + "executionStopTime": 1659462041637, + "originalKey": "0739269e-5c0e-4551-b06f-f4aab386ba54", + "requestMsgId": "0739269e-5c0e-4551-b06f-f4aab386ba54", + "showInput": false }, "source": [ "## Appendix: gotchas ⚠️\n", "\n", "* Omitting to define `__post_init__` or not calling `run_auto_creation` in it.\n", - "* Using a configurable class without calling get_default_args or expand_args_fields on it.\n", "* Omitting a type annotation on a field. For example, writing \n", "```\n", " subcomponent_class_type = \"SubComponent\"\n", @@ -1243,10 +1195,50 @@ "```\n", " subcomponent_class_type: str = \"SubComponent\"\n", "```\n", - "\n", - "" - ], - "attachments": {} + "\n" + ] } - ] + ], + "metadata": { + "bento_stylesheets": { + "bento/extensions/flow/main.css": true, + "bento/extensions/kernel_selector/main.css": true, + "bento/extensions/kernel_ui/main.css": true, + "bento/extensions/new_kernel/main.css": true, + "bento/extensions/system_usage/main.css": true, + "bento/extensions/theme/main.css": true + }, + "captumWidgetMessage": {}, + "dataExplorerConfig": {}, + "kernelspec": { + "display_name": "pytorch3d", + "language": "python", + "metadata": { + "cinder_runtime": false, + "fbpkg_supported": true, + "is_prebuilt": true, + "kernel_name": "bento_kernel_pytorch3d", + "nightly_builds": true + }, + "name": "bento_kernel_pytorch3d" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3" + }, + "last_base_url": "https://9177.od.fbinfra.net:443/", + "last_kernel_id": "90755407-3729-46f4-ab67-ff2cb1daa5cb", + "last_msg_id": "f61034eb-826226915ad9548ffbe495ba_6317", + "last_server_session_id": "d6b46f14-cee7-44c1-8c51-39a38a4ea4c2", + "outputWidgetContext": {} + }, + "nbformat": 4, + "nbformat_minor": 2 } diff --git a/files/implicitron_config_system.py b/files/implicitron_config_system.py index 5904e8d5..0f965ad2 100644 --- a/files/implicitron_config_system.py +++ b/files/implicitron_config_system.py @@ -186,9 +186,9 @@ class MyConfigurable(Configurable): # In[ ]: -# expand_args_fields must be called on an object before it is instantiated. -# A warning is raised if this is missed, but it is possible to not notice the warning. -# It modifies the class like @dataclass +# The expand_args_fields function modifies the class like @dataclasses.dataclass. +# If it has not been called on a Configurable object before it has been instantiated, it will +# be called automatically. expand_args_fields(MyConfigurable) my_configurable_instance = MyConfigurable(a=18) assert my_configurable_instance.d == 16 @@ -197,7 +197,7 @@ assert my_configurable_instance.d == 16 # In[ ]: -# get_default_args calls expand_args_fields automatically +# get_default_args also calls expand_args_fields automatically our_structured = get_default_args(MyConfigurable) assert isinstance(our_structured, DictConfig) print(OmegaConf.to_yaml(our_structured)) @@ -357,7 +357,6 @@ class MyLinear(torch.nn.Module, Configurable): # In[ ]: -expand_args_fields(MyLinear) my_linear = MyLinear() input = torch.zeros(2) output = my_linear(input) @@ -415,7 +414,6 @@ class Out(Configurable): # In[ ]: -expand_args_fields(Out) out2 = Out(inner_class_type="UserImplementedInner") print(out2.inner) @@ -450,7 +448,6 @@ class LargeComponent(Configurable): # In[ ]: -expand_args_fields(LargeComponent) large_component = LargeComponent() assert large_component.apply(3) == 4 print(OmegaConf.to_yaml(LargeComponent)) @@ -491,7 +488,6 @@ class LargeComponent(Configurable): # In[ ]: -expand_args_fields(LargeComponent) large_component = LargeComponent() assert large_component.apply(3) == 4 print(OmegaConf.to_yaml(LargeComponent)) @@ -506,7 +502,6 @@ print(OmegaConf.to_yaml(LargeComponent)) # ## Appendix: gotchas ⚠️ # # * Omitting to define `__post_init__` or not calling `run_auto_creation` in it. -# * Using a configurable class without calling get_default_args or expand_args_fields on it. # * Omitting a type annotation on a field. For example, writing # ``` # subcomponent_class_type = "SubComponent" diff --git a/files/implicitron_volumes.ipynb b/files/implicitron_volumes.ipynb index 69a364d4..1af8af1a 100644 --- a/files/implicitron_volumes.ipynb +++ b/files/implicitron_volumes.ipynb @@ -145,10 +145,9 @@ "from pytorch3d.implicitron.dataset.dataset_base import FrameData\n", "from pytorch3d.implicitron.dataset.rendered_mesh_dataset_map_provider import RenderedMeshDatasetMapProvider\n", "from pytorch3d.implicitron.models.generic_model import GenericModel\n", - "from pytorch3d.implicitron.models.implicit_function.base import ImplicitFunctionBase\n", + "from pytorch3d.implicitron.models.implicit_function.base import ImplicitFunctionBase, ImplicitronRayBundle\n", "from pytorch3d.implicitron.models.renderer.base import EvaluationMode\n", - "from pytorch3d.implicitron.tools.config import expand_args_fields, get_default_args, registry, remove_unused_components\n", - "from pytorch3d.renderer import RayBundle\n", + "from pytorch3d.implicitron.tools.config import get_default_args, registry, remove_unused_components\n", "from pytorch3d.renderer.implicit.renderer import VolumeSampler\n", "from pytorch3d.structures import Volumes\n", "from pytorch3d.vis.plotly_vis import plot_batch_individually, plot_scene" @@ -245,17 +244,6 @@ "!wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow_texture.png" ] }, - { - "cell_type": "markdown", - "metadata": { - "customInput": null, - "originalKey": "2a976be8-01bf-4a1c-a6e7-61d5d08c3dbd", - "showInput": false - }, - "source": [ - "If we want to instantiate one of Implicitron's configurable objects, such as `RenderedMeshDatasetMapProvider`, without using the OmegaConf initialisation (get_default_args), we need to call `expand_args_fields` on the class first." - ] - }, { "cell_type": "code", "execution_count": null, @@ -272,7 +260,6 @@ }, "outputs": [], "source": [ - "expand_args_fields(RenderedMeshDatasetMapProvider)\n", "cow_provider = RenderedMeshDatasetMapProvider(\n", " data_file=\"data/cow_mesh/cow.obj\",\n", " use_point_light=False,\n", @@ -405,7 +392,7 @@ "\n", " def forward(\n", " self,\n", - " ray_bundle: RayBundle,\n", + " ray_bundle: ImplicitronRayBundle,\n", " fun_viewpool=None,\n", " global_code=None,\n", " ):\n", @@ -468,7 +455,6 @@ " gm = GenericModel(**cfg)\n", "else:\n", " # constructing GenericModel directly\n", - " expand_args_fields(GenericModel)\n", " gm = GenericModel(\n", " implicit_function_class_type=\"MyVolumes\",\n", " render_image_height=output_resolution,\n", diff --git a/files/implicitron_volumes.py b/files/implicitron_volumes.py index 932b42c4..bce555e1 100644 --- a/files/implicitron_volumes.py +++ b/files/implicitron_volumes.py @@ -73,10 +73,9 @@ from PIL import Image from pytorch3d.implicitron.dataset.dataset_base import FrameData from pytorch3d.implicitron.dataset.rendered_mesh_dataset_map_provider import RenderedMeshDatasetMapProvider from pytorch3d.implicitron.models.generic_model import GenericModel -from pytorch3d.implicitron.models.implicit_function.base import ImplicitFunctionBase +from pytorch3d.implicitron.models.implicit_function.base import ImplicitFunctionBase, ImplicitronRayBundle from pytorch3d.implicitron.models.renderer.base import EvaluationMode -from pytorch3d.implicitron.tools.config import expand_args_fields, get_default_args, registry, remove_unused_components -from pytorch3d.renderer import RayBundle +from pytorch3d.implicitron.tools.config import get_default_args, registry, remove_unused_components from pytorch3d.renderer.implicit.renderer import VolumeSampler from pytorch3d.structures import Volumes from pytorch3d.vis.plotly_vis import plot_batch_individually, plot_scene @@ -112,12 +111,9 @@ get_ipython().system('wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytor get_ipython().system('wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow_texture.png') -# If we want to instantiate one of Implicitron's configurable objects, such as `RenderedMeshDatasetMapProvider`, without using the OmegaConf initialisation (get_default_args), we need to call `expand_args_fields` on the class first. - # In[ ]: -expand_args_fields(RenderedMeshDatasetMapProvider) cow_provider = RenderedMeshDatasetMapProvider( data_file="data/cow_mesh/cow.obj", use_point_light=False, @@ -184,7 +180,7 @@ class MyVolumes(ImplicitFunctionBase, torch.nn.Module): def forward( self, - ray_bundle: RayBundle, + ray_bundle: ImplicitronRayBundle, fun_viewpool=None, global_code=None, ): @@ -225,7 +221,6 @@ if CONSTRUCT_MODEL_FROM_CONFIG: gm = GenericModel(**cfg) else: # constructing GenericModel directly - expand_args_fields(GenericModel) gm = GenericModel( implicit_function_class_type="MyVolumes", render_image_height=output_resolution, diff --git a/files/render_densepose.ipynb b/files/render_densepose.ipynb index 2e668776..68dfe69f 100644 --- a/files/render_densepose.ipynb +++ b/files/render_densepose.ipynb @@ -129,7 +129,7 @@ "## Load the SMPL model\n", "\n", "#### Download the SMPL model\n", - "- Go to http://smpl.is.tue.mpg.de/downloads and sign up.\n", + "- Go to https://smpl.is.tue.mpg.de/download.php and sign up.\n", "- Download SMPL for Python Users and unzip.\n", "- Copy the file male template file **'models/basicModel_m_lbs_10_207_0_v1.0.0.pkl'** to the data/DensePose/ folder.\n", " - rename the file to **'smpl_model.pkl'** or rename the string where it's commented below\n", diff --git a/files/render_densepose.py b/files/render_densepose.py index 8e87ff14..837d6546 100644 --- a/files/render_densepose.py +++ b/files/render_densepose.py @@ -96,7 +96,7 @@ sys.path.append(os.path.abspath('')) # ## Load the SMPL model # # #### Download the SMPL model -# - Go to http://smpl.is.tue.mpg.de/downloads and sign up. +# - Go to https://smpl.is.tue.mpg.de/download.php and sign up. # - Download SMPL for Python Users and unzip. # - Copy the file male template file **'models/basicModel_m_lbs_10_207_0_v1.0.0.pkl'** to the data/DensePose/ folder. # - rename the file to **'smpl_model.pkl'** or rename the string where it's commented below diff --git a/tutorials/implicitron_config_system.html b/tutorials/implicitron_config_system.html index 4f5c2d0c..d0a5d5e4 100644 --- a/tutorials/implicitron_config_system.html +++ b/tutorials/implicitron_config_system.html @@ -384,9 +384,9 @@ Note that we indicate configurable classes using a special base class Conf
In [ ]:
-
# expand_args_fields must be called on an object before it is instantiated.
-# A warning is raised if this is missed, but it is possible to not notice the warning.
-# It modifies the class like @dataclass
+
# The expand_args_fields function modifies the class like @dataclasses.dataclass.
+# If it has not been called on a Configurable object before it has been instantiated, it will
+# be called automatically.
 expand_args_fields(MyConfigurable)
 my_configurable_instance = MyConfigurable(a=18)
 assert my_configurable_instance.d == 16
@@ -400,7 +400,7 @@ Note that we indicate configurable classes using a special base class Conf
 
In [ ]:

 

 

-
# get_default_args calls expand_args_fields automatically
+
# get_default_args also calls expand_args_fields automatically
 our_structured = get_default_args(MyConfigurable)
 assert isinstance(our_structured, DictConfig)
 print(OmegaConf.to_yaml(our_structured))
@@ -642,8 +642,7 @@ Note in this case it is necessary to call Module.__init__ explicitl
 
In [ ]:

 

 

-
expand_args_fields(MyLinear)
-my_linear = MyLinear()
+
my_linear = MyLinear()
 input = torch.zeros(2)
 output = my_linear(input)
 print("output shape:", output.shape)
@@ -736,8 +735,7 @@ before you use the library classes.

 
In [ ]:

 

 

-
expand_args_fields(Out)
-out2 = Out(inner_class_type="UserImplementedInner")
+
out2 = Out(inner_class_type="UserImplementedInner")
 print(out2.inner)
 

 

@@ -785,8 +783,7 @@ before you use the library classes.

 
In [ ]:

 

 

-
expand_args_fields(LargeComponent)
-large_component = LargeComponent()
+
large_component = LargeComponent()
 assert large_component.apply(3) == 4
 print(OmegaConf.to_yaml(LargeComponent))
 

@@ -842,8 +839,7 @@ before you use the library classes.

 
In [ ]:

 

 

-
expand_args_fields(LargeComponent)
-large_component = LargeComponent()
+
large_component = LargeComponent()
 assert large_component.apply(3) == 4
 print(OmegaConf.to_yaml(LargeComponent))
 

@@ -871,7 +867,6 @@ before you use the library classes.

 

 
Appendix: gotchas ⚠️
    
 
  • Omitting to define __post_init__ or not calling run_auto_creation in it.
    • 
-
  • Using a configurable class without calling get_default_args or expand_args_fields on it.
    • 
 
  • Omitting a type annotation on a field. For example, writing 
 
      subcomponent_class_type = "SubComponent"
    
 instead of 
diff --git a/tutorials/implicitron_config_system/index.html b/tutorials/implicitron_config_system/index.html
index 4f5c2d0c..d0a5d5e4 100644
--- a/tutorials/implicitron_config_system/index.html
+++ b/tutorials/implicitron_config_system/index.html
@@ -384,9 +384,9 @@ Note that we indicate configurable classes using a special base class Conf
 
    In [ ]:
    
 
    
 
    
-
    # expand_args_fields must be called on an object before it is instantiated.
-# A warning is raised if this is missed, but it is possible to not notice the warning.
-# It modifies the class like @dataclass
+
    # The expand_args_fields function modifies the class like @dataclasses.dataclass.
+# If it has not been called on a Configurable object before it has been instantiated, it will
+# be called automatically.
 expand_args_fields(MyConfigurable)
 my_configurable_instance = MyConfigurable(a=18)
 assert my_configurable_instance.d == 16
@@ -400,7 +400,7 @@ Note that we indicate configurable classes using a special base class Conf
 
    In [ ]:
    
 
    
 
    
-
    # get_default_args calls expand_args_fields automatically
+
    # get_default_args also calls expand_args_fields automatically
 our_structured = get_default_args(MyConfigurable)
 assert isinstance(our_structured, DictConfig)
 print(OmegaConf.to_yaml(our_structured))
@@ -642,8 +642,7 @@ Note in this case it is necessary to call Module.__init__ explicitl
 
    In [ ]:
    
 
    
 
    
-
    expand_args_fields(MyLinear)
-my_linear = MyLinear()
+
    my_linear = MyLinear()
 input = torch.zeros(2)
 output = my_linear(input)
 print("output shape:", output.shape)
@@ -736,8 +735,7 @@ before you use the library classes.
    
 
    In [ ]:
    
 
    
 
    
-
    expand_args_fields(Out)
-out2 = Out(inner_class_type="UserImplementedInner")
+
    out2 = Out(inner_class_type="UserImplementedInner")
 print(out2.inner)
 
    
 
    
@@ -785,8 +783,7 @@ before you use the library classes.
    
 
    In [ ]:
    
 
    
 
    
-
    expand_args_fields(LargeComponent)
-large_component = LargeComponent()
+
    large_component = LargeComponent()
 assert large_component.apply(3) == 4
 print(OmegaConf.to_yaml(LargeComponent))
 
    
@@ -842,8 +839,7 @@ before you use the library classes.
    
 
    In [ ]:
    
 
    
 
    
-
    expand_args_fields(LargeComponent)
-large_component = LargeComponent()
+
    large_component = LargeComponent()
 assert large_component.apply(3) == 4
 print(OmegaConf.to_yaml(LargeComponent))
 
    
@@ -871,7 +867,6 @@ before you use the library classes.
    
 
    
 
    Appendix: gotchas ⚠️
      
 
    • Omitting to define __post_init__ or not calling run_auto_creation in it.
      • 
-
    • Using a configurable class without calling get_default_args or expand_args_fields on it.
      • 
 
    • Omitting a type annotation on a field. For example, writing 
 
        subcomponent_class_type = "SubComponent"
      
 instead of 
diff --git a/tutorials/implicitron_volumes.html b/tutorials/implicitron_volumes.html
index 04852493..4541a8ea 100644
--- a/tutorials/implicitron_volumes.html
+++ b/tutorials/implicitron_volumes.html
@@ -174,10 +174,9 @@
 from pytorch3d.implicitron.dataset.dataset_base import FrameData
 from pytorch3d.implicitron.dataset.rendered_mesh_dataset_map_provider import RenderedMeshDatasetMapProvider
 from pytorch3d.implicitron.models.generic_model import GenericModel
-from pytorch3d.implicitron.models.implicit_function.base import ImplicitFunctionBase
+from pytorch3d.implicitron.models.implicit_function.base import ImplicitFunctionBase, ImplicitronRayBundle
 from pytorch3d.implicitron.models.renderer.base import EvaluationMode
-from pytorch3d.implicitron.tools.config import expand_args_fields, get_default_args, registry, remove_unused_components
-from pytorch3d.renderer import RayBundle
+from pytorch3d.implicitron.tools.config import get_default_args, registry, remove_unused_components
 from pytorch3d.renderer.implicit.renderer import VolumeSampler
 from pytorch3d.structures import Volumes
 from pytorch3d.vis.plotly_vis import plot_batch_individually, plot_scene
@@ -241,21 +240,12 @@ If running locally, the data is already available at the correct path.
      
 
    
 
    
 
    
-
    
-
    
-
    
-
    
-
    If we want to instantiate one of Implicitron's configurable objects, such as RenderedMeshDatasetMapProvider, without using the OmegaConf initialisation (get_default_args), we need to call expand_args_fields on the class first.
    
-
    
-
    
-
    
 
    
 
    
 
    In [ ]:
    
 
    
 
    
-
    expand_args_fields(RenderedMeshDatasetMapProvider)
-cow_provider = RenderedMeshDatasetMapProvider(
+
    cow_provider = RenderedMeshDatasetMapProvider(
     data_file="data/cow_mesh/cow.obj",
     use_point_light=False,
     resolution=output_resolution,
@@ -344,7 +334,7 @@ We use Python's dataclass annotations for configuring the module.
    
 
     def forward(
         self,
-        ray_bundle: RayBundle,
+        ray_bundle: ImplicitronRayBundle,
         fun_viewpool=None,
         global_code=None,
     ):
@@ -394,7 +384,6 @@ There are two ways to construct it which are equivalent here.
    
     gm = GenericModel(**cfg)
 else:
     # constructing GenericModel directly
-    expand_args_fields(GenericModel)
     gm = GenericModel(
         implicit_function_class_type="MyVolumes",
         render_image_height=output_resolution,
diff --git a/tutorials/implicitron_volumes/index.html b/tutorials/implicitron_volumes/index.html
index 04852493..4541a8ea 100644
--- a/tutorials/implicitron_volumes/index.html
+++ b/tutorials/implicitron_volumes/index.html
@@ -174,10 +174,9 @@
 from pytorch3d.implicitron.dataset.dataset_base import FrameData
 from pytorch3d.implicitron.dataset.rendered_mesh_dataset_map_provider import RenderedMeshDatasetMapProvider
 from pytorch3d.implicitron.models.generic_model import GenericModel
-from pytorch3d.implicitron.models.implicit_function.base import ImplicitFunctionBase
+from pytorch3d.implicitron.models.implicit_function.base import ImplicitFunctionBase, ImplicitronRayBundle
 from pytorch3d.implicitron.models.renderer.base import EvaluationMode
-from pytorch3d.implicitron.tools.config import expand_args_fields, get_default_args, registry, remove_unused_components
-from pytorch3d.renderer import RayBundle
+from pytorch3d.implicitron.tools.config import get_default_args, registry, remove_unused_components
 from pytorch3d.renderer.implicit.renderer import VolumeSampler
 from pytorch3d.structures import Volumes
 from pytorch3d.vis.plotly_vis import plot_batch_individually, plot_scene
@@ -241,21 +240,12 @@ If running locally, the data is already available at the correct path.
    
 
    
 
    
 
    
-
    
-
    
-
    
-
    
-
    If we want to instantiate one of Implicitron's configurable objects, such as RenderedMeshDatasetMapProvider, without using the OmegaConf initialisation (get_default_args), we need to call expand_args_fields on the class first.
    
-
    
-
    
-
    
 
    
 
    
 
    In [ ]:
    
 
    
 
    
-
    expand_args_fields(RenderedMeshDatasetMapProvider)
-cow_provider = RenderedMeshDatasetMapProvider(
+
    cow_provider = RenderedMeshDatasetMapProvider(
     data_file="data/cow_mesh/cow.obj",
     use_point_light=False,
     resolution=output_resolution,
@@ -344,7 +334,7 @@ We use Python's dataclass annotations for configuring the module.
    
 
     def forward(
         self,
-        ray_bundle: RayBundle,
+        ray_bundle: ImplicitronRayBundle,
         fun_viewpool=None,
         global_code=None,
     ):
@@ -394,7 +384,6 @@ There are two ways to construct it which are equivalent here.
    
     gm = GenericModel(**cfg)
 else:
     # constructing GenericModel directly
-    expand_args_fields(GenericModel)
     gm = GenericModel(
         implicit_function_class_type="MyVolumes",
         render_image_height=output_resolution,
diff --git a/tutorials/render_densepose.html b/tutorials/render_densepose.html
index d52b7c81..ecbe75e0 100644
--- a/tutorials/render_densepose.html
+++ b/tutorials/render_densepose.html
@@ -204,7 +204,7 @@ In this tutorial, we provide an example of using DensePose data in PyTorch3D.
    
 
    
 
    Load the SMPL model
    Download the SMPL model
      
-
    • Go to http://smpl.is.tue.mpg.de/downloads and sign up.
      • 
+
    • Go to https://smpl.is.tue.mpg.de/download.php and sign up.
      • 
 
    • Download SMPL for Python Users and unzip.
      • 
 
    • Copy the file male template file 'models/basicModel_m_lbs_10_207_0_v1.0.0.pkl' to the data/DensePose/ folder.
        
 
      • rename the file to 'smpl_model.pkl' or rename the string where it's commented below
        • 
diff --git a/tutorials/render_densepose/index.html b/tutorials/render_densepose/index.html
index d52b7c81..ecbe75e0 100644
--- a/tutorials/render_densepose/index.html
+++ b/tutorials/render_densepose/index.html
@@ -204,7 +204,7 @@ In this tutorial, we provide an example of using DensePose data in PyTorch3D.
        
 
        
 
        Load the SMPL model
        Download the SMPL model