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Author SHA1 Message Date
Nikhila Ravi
f0dc65110a Shader API more consistent naming 
Summary:
Renamed shaders to be prefixed with Hard/Soft depending on if they use a probabalistic blending (Soft) or use the closest face (Hard).

There is some code duplication but I thought it would be cleaner to have separate shaders for each task rather than:
- inheritance (which we discussed previously that we want to avoid)
- boolean (hard/soft) or a string (hard/soft) - new blending functions other than the ones provided would need if statements in the current shaders which might get messy.

Also added a `flat_shading` function and a `FlatShader` - I could make this into a tutorial as it was really easy to add a new shader and it might be a nice showcase.

NOTE: There are a few more places where the naming will need to change (e.g the tutorials) but I wanted to reach a consensus on this before changing it everywhere.

Reviewed By: jcjohnson

Differential Revision: D19761036

fbshipit-source-id: f972f6530c7f66dc5550b0284c191abc4a7f6fc4
 2020-02-19 23:16:50 -08:00
Georgia Gkioxari
60f3c4e7d2 cpp support for packed to padded 
Summary:
Cpu implementation for packed to padded and added gradients
```
Benchmark                                     Avg Time(μs)      Peak Time(μs) Iterations
--------------------------------------------------------------------------------
PACKED_TO_PADDED_2_100_300_1_cpu                    138             221           3625
PACKED_TO_PADDED_2_100_300_1_cuda:0                 184             261           2716
PACKED_TO_PADDED_2_100_300_16_cpu                   555             726            901
PACKED_TO_PADDED_2_100_300_16_cuda:0                179             260           2794
PACKED_TO_PADDED_2_100_3000_1_cpu                   396             519           1262
PACKED_TO_PADDED_2_100_3000_1_cuda:0                181             274           2764
PACKED_TO_PADDED_2_100_3000_16_cpu                 4517            5003            111
PACKED_TO_PADDED_2_100_3000_16_cuda:0               224             397           2235
PACKED_TO_PADDED_2_1000_300_1_cpu                   138             212           3616
PACKED_TO_PADDED_2_1000_300_1_cuda:0                180             282           2775
PACKED_TO_PADDED_2_1000_300_16_cpu                  565             711            885
PACKED_TO_PADDED_2_1000_300_16_cuda:0               179             264           2797
PACKED_TO_PADDED_2_1000_3000_1_cpu                  389             494           1287
PACKED_TO_PADDED_2_1000_3000_1_cuda:0               180             271           2777
PACKED_TO_PADDED_2_1000_3000_16_cpu                4522            5170            111
PACKED_TO_PADDED_2_1000_3000_16_cuda:0              216             286           2313
PACKED_TO_PADDED_10_100_300_1_cpu                   251             345           1995
PACKED_TO_PADDED_10_100_300_1_cuda:0                178             262           2806
PACKED_TO_PADDED_10_100_300_16_cpu                 2354            2750            213
PACKED_TO_PADDED_10_100_300_16_cuda:0               178             291           2814
PACKED_TO_PADDED_10_100_3000_1_cpu                 1519            1786            330
PACKED_TO_PADDED_10_100_3000_1_cuda:0               179             237           2791
PACKED_TO_PADDED_10_100_3000_16_cpu               24705           25879             21
PACKED_TO_PADDED_10_100_3000_16_cuda:0              228             316           2191
PACKED_TO_PADDED_10_1000_300_1_cpu                  261             432           1919
PACKED_TO_PADDED_10_1000_300_1_cuda:0               181             261           2756
PACKED_TO_PADDED_10_1000_300_16_cpu                2349            2770            213
PACKED_TO_PADDED_10_1000_300_16_cuda:0              180             256           2782
PACKED_TO_PADDED_10_1000_3000_1_cpu                1613            1929            310
PACKED_TO_PADDED_10_1000_3000_1_cuda:0              183             253           2739
PACKED_TO_PADDED_10_1000_3000_16_cpu              22041           23653             23
PACKED_TO_PADDED_10_1000_3000_16_cuda:0             220             343           2270
PACKED_TO_PADDED_32_100_300_1_cpu                   555             750            901
PACKED_TO_PADDED_32_100_300_1_cuda:0                188             282           2661
PACKED_TO_PADDED_32_100_300_16_cpu                 7550            8131             67
PACKED_TO_PADDED_32_100_300_16_cuda:0               181             272           2770
PACKED_TO_PADDED_32_100_3000_1_cpu                 4574            6327            110
PACKED_TO_PADDED_32_100_3000_1_cuda:0               173             254           2884
PACKED_TO_PADDED_32_100_3000_16_cpu               70366           72563              8
PACKED_TO_PADDED_32_100_3000_16_cuda:0              349             654           1433
PACKED_TO_PADDED_32_1000_300_1_cpu                  612             728            818
PACKED_TO_PADDED_32_1000_300_1_cuda:0               189             295           2647
PACKED_TO_PADDED_32_1000_300_16_cpu                7699            8254             65
PACKED_TO_PADDED_32_1000_300_16_cuda:0              189             311           2646
PACKED_TO_PADDED_32_1000_3000_1_cpu                5105            5261             98
PACKED_TO_PADDED_32_1000_3000_1_cuda:0              191             260           2625
PACKED_TO_PADDED_32_1000_3000_16_cpu              87073           92708              6
PACKED_TO_PADDED_32_1000_3000_16_cuda:0             344             425           1455
--------------------------------------------------------------------------------

Benchmark                                           Avg Time(μs)      Peak Time(μs) Iterations
--------------------------------------------------------------------------------
PACKED_TO_PADDED_TORCH_2_100_300_1_cpu                    492             627           1016
PACKED_TO_PADDED_TORCH_2_100_300_1_cuda:0                 768             975            652
PACKED_TO_PADDED_TORCH_2_100_300_16_cpu                   659             804            760
PACKED_TO_PADDED_TORCH_2_100_300_16_cuda:0                781             918            641
PACKED_TO_PADDED_TORCH_2_100_3000_1_cpu                   624             734            802
PACKED_TO_PADDED_TORCH_2_100_3000_1_cuda:0                778             929            643
PACKED_TO_PADDED_TORCH_2_100_3000_16_cpu                 2609            2850            192
PACKED_TO_PADDED_TORCH_2_100_3000_16_cuda:0               758             901            660
PACKED_TO_PADDED_TORCH_2_1000_300_1_cpu                   467             612           1072
PACKED_TO_PADDED_TORCH_2_1000_300_1_cuda:0                772             905            648
PACKED_TO_PADDED_TORCH_2_1000_300_16_cpu                  689             839            726
PACKED_TO_PADDED_TORCH_2_1000_300_16_cuda:0               789            1143            635
PACKED_TO_PADDED_TORCH_2_1000_3000_1_cpu                  629             735            795
PACKED_TO_PADDED_TORCH_2_1000_3000_1_cuda:0               812             916            616
PACKED_TO_PADDED_TORCH_2_1000_3000_16_cpu                2716            3117            185
PACKED_TO_PADDED_TORCH_2_1000_3000_16_cuda:0              844            1288            593
PACKED_TO_PADDED_TORCH_10_100_300_1_cpu                  2387            2557            210
PACKED_TO_PADDED_TORCH_10_100_300_1_cuda:0               4112            4993            122
PACKED_TO_PADDED_TORCH_10_100_300_16_cpu                 3385            4254            148
PACKED_TO_PADDED_TORCH_10_100_300_16_cuda:0              3959            4902            127
PACKED_TO_PADDED_TORCH_10_100_3000_1_cpu                 2918            3105            172
PACKED_TO_PADDED_TORCH_10_100_3000_1_cuda:0              4054            4450            124
PACKED_TO_PADDED_TORCH_10_100_3000_16_cpu               12748           13623             40
PACKED_TO_PADDED_TORCH_10_100_3000_16_cuda:0             4023            4395            125
PACKED_TO_PADDED_TORCH_10_1000_300_1_cpu                 2258            2492            222
PACKED_TO_PADDED_TORCH_10_1000_300_1_cuda:0              3997            4312            126
PACKED_TO_PADDED_TORCH_10_1000_300_16_cpu                3404            3597            147
PACKED_TO_PADDED_TORCH_10_1000_300_16_cuda:0             3877            4227            129
PACKED_TO_PADDED_TORCH_10_1000_3000_1_cpu                2789            3054            180
PACKED_TO_PADDED_TORCH_10_1000_3000_1_cuda:0             3821            4402            131
PACKED_TO_PADDED_TORCH_10_1000_3000_16_cpu              11967           12963             42
PACKED_TO_PADDED_TORCH_10_1000_3000_16_cuda:0            3729            4290            135
PACKED_TO_PADDED_TORCH_32_100_300_1_cpu                  6933            8152             73
PACKED_TO_PADDED_TORCH_32_100_300_1_cuda:0              11856           12287             43
PACKED_TO_PADDED_TORCH_32_100_300_16_cpu                 9895           11205             51
PACKED_TO_PADDED_TORCH_32_100_300_16_cuda:0             12354           13596             41
PACKED_TO_PADDED_TORCH_32_100_3000_1_cpu                 9516           10128             53
PACKED_TO_PADDED_TORCH_32_100_3000_1_cuda:0             12917           13597             39
PACKED_TO_PADDED_TORCH_32_100_3000_16_cpu               41209           43783             13
PACKED_TO_PADDED_TORCH_32_100_3000_16_cuda:0            12210           13288             41
PACKED_TO_PADDED_TORCH_32_1000_300_1_cpu                 7179            7689             70
PACKED_TO_PADDED_TORCH_32_1000_300_1_cuda:0             11896           12381             43
PACKED_TO_PADDED_TORCH_32_1000_300_16_cpu               10127           15494             50
PACKED_TO_PADDED_TORCH_32_1000_300_16_cuda:0            12034           12817             42
PACKED_TO_PADDED_TORCH_32_1000_3000_1_cpu                8743           10251             58
PACKED_TO_PADDED_TORCH_32_1000_3000_1_cuda:0            12023           12908             42
PACKED_TO_PADDED_TORCH_32_1000_3000_16_cpu              39071           41777             13
PACKED_TO_PADDED_TORCH_32_1000_3000_16_cuda:0           11999           13690             42
--------------------------------------------------------------------------------
```

Reviewed By: bottler, nikhilaravi, jcjohnson

Differential Revision: D19870575

fbshipit-source-id: 23a2477b73373c411899633386c87ab034c3702a
 2020-02-19 10:48:54 -08:00
Nikhila Ravi
8301163d24 transforms 3d convention fix 
Summary: Fixed the rotation matrices generated by the RotateAxisAngle class and updated the tests. Added documentation for Transforms3d to clarify the conventions.

Reviewed By: gkioxari

Differential Revision: D19912903

fbshipit-source-id: c64926ce4e1381b145811557c32b73663d6d92d1
 2020-02-19 10:32:44 -08:00
Jeremy Reizenstein
bdc2bb578c MACOSX_DEPLOYMENT_TARGET=10.14 
Summary:
pybind now seems to need C++17 on a mac, so advise people to use it. (Also delete an unused variable to silence a warning I got on a mac build.)

Reported in github issue #68.

Reviewed By: nikhilaravi

Differential Revision: D19970512

fbshipit-source-id: f9be20c8ed425bd6ba8d009a7d62dad658dccdb1
 2020-02-19 08:43:50 -08:00
Chr1k0
234658901a Update obj_io.py: Make PyTorch3D work with ShapeNetCore.v2 (#49) 
Summary:
Making PyTorch3D work with ShapeNetCore.v2 models from http://shapenet.cs.stanford.edu/shapenet/obj-zip/ShapeNetCore.v2/
The face identifier of the ShapeNetCore.v2 models is followed by two not one blank - example:
"f  1/1/1 2/2/2 3/3/3" instead of
"f 1/1/1 2/2/2 3/3/3"
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/49

Differential Revision: D19951828

Pulled By: gkioxari

fbshipit-source-id: 5695df0fca2059e75eeb73edf4cfe9d9f008e841
 2020-02-18 11:11:58 -08:00
Junior Rojas
3ba4398095 Fix typo (#54) 
Summary: Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/54

Differential Revision: D19951851

Pulled By: gkioxari

fbshipit-source-id: cf41d5806c761639d1efa42a633404b248486c30
 2020-02-18 10:15:16 -08:00
Nikhila Ravi
97acf16de2 lint fixes 
Summary: Ran `dev/linter.sh`.

Reviewed By: bottler

Differential Revision: D19761062

fbshipit-source-id: 1a49abe4a5f2bc7641b2b46e254aa77e6a48aa7d
 2020-02-13 20:50:48 -08:00
Georgia Gkioxari
29cd181a83 CPU implem for face areas normals 
Summary:
Added cpu implementation for face areas normals. Moved test and bm to separate functions.

```
Benchmark                                   Avg Time(μs)      Peak Time(μs) Iterations
--------------------------------------------------------------------------------
FACE_AREAS_NORMALS_2_100_300_False                196             268           2550
FACE_AREAS_NORMALS_2_100_300_True                 106             179           4733
FACE_AREAS_NORMALS_2_100_3000_False              1447            1630            346
FACE_AREAS_NORMALS_2_100_3000_True                107             178           4674
FACE_AREAS_NORMALS_2_1000_300_False               201             309           2486
FACE_AREAS_NORMALS_2_1000_300_True                107             186           4673
FACE_AREAS_NORMALS_2_1000_3000_False             1451            1636            345
FACE_AREAS_NORMALS_2_1000_3000_True               107             186           4655
FACE_AREAS_NORMALS_10_100_300_False               767             918            653
FACE_AREAS_NORMALS_10_100_300_True                106             167           4712
FACE_AREAS_NORMALS_10_100_3000_False             7036            7754             72
FACE_AREAS_NORMALS_10_100_3000_True               113             164           4445
FACE_AREAS_NORMALS_10_1000_300_False              748             947            669
FACE_AREAS_NORMALS_10_1000_300_True               108             169           4638
FACE_AREAS_NORMALS_10_1000_3000_False            7069            7783             71
FACE_AREAS_NORMALS_10_1000_3000_True              108             172           4646
FACE_AREAS_NORMALS_32_100_300_False              2286            2496            219
FACE_AREAS_NORMALS_32_100_300_True                108             180           4631
FACE_AREAS_NORMALS_32_100_3000_False            23184           24369             22
FACE_AREAS_NORMALS_32_100_3000_True               159             213           3147
FACE_AREAS_NORMALS_32_1000_300_False             2414            2645            208
FACE_AREAS_NORMALS_32_1000_300_True               112             197           4480
FACE_AREAS_NORMALS_32_1000_3000_False           21687           22964             24
FACE_AREAS_NORMALS_32_1000_3000_True              141             211           3540
--------------------------------------------------------------------------------

Benchmark                                         Avg Time(μs)      Peak Time(μs) Iterations
--------------------------------------------------------------------------------
FACE_AREAS_NORMALS_TORCH_2_100_300_False               5465            5782             92
FACE_AREAS_NORMALS_TORCH_2_100_300_True                1198            1351            418
FACE_AREAS_NORMALS_TORCH_2_100_3000_False             48228           48869             11
FACE_AREAS_NORMALS_TORCH_2_100_3000_True               1186            1304            422
FACE_AREAS_NORMALS_TORCH_2_1000_300_False              5556            6097             90
FACE_AREAS_NORMALS_TORCH_2_1000_300_True               1200            1328            417
FACE_AREAS_NORMALS_TORCH_2_1000_3000_False            48683           50016             11
FACE_AREAS_NORMALS_TORCH_2_1000_3000_True              1185            1306            422
FACE_AREAS_NORMALS_TORCH_10_100_300_False             24215           25097             21
FACE_AREAS_NORMALS_TORCH_10_100_300_True               1150            1314            435
FACE_AREAS_NORMALS_TORCH_10_100_3000_False           232605          234952              3
FACE_AREAS_NORMALS_TORCH_10_100_3000_True              1193            1314            420
FACE_AREAS_NORMALS_TORCH_10_1000_300_False            24912           25343             21
FACE_AREAS_NORMALS_TORCH_10_1000_300_True              1216            1330            412
FACE_AREAS_NORMALS_TORCH_10_1000_3000_False          239907          241253              3
FACE_AREAS_NORMALS_TORCH_10_1000_3000_True             1226            1333            408
FACE_AREAS_NORMALS_TORCH_32_100_300_False             73991           75776              7
FACE_AREAS_NORMALS_TORCH_32_100_300_True               1193            1339            420
FACE_AREAS_NORMALS_TORCH_32_100_3000_False           728932          728932              1
FACE_AREAS_NORMALS_TORCH_32_100_3000_True              1186            1359            422
FACE_AREAS_NORMALS_TORCH_32_1000_300_False            76385           79129              7
FACE_AREAS_NORMALS_TORCH_32_1000_300_True              1165            1310            430
FACE_AREAS_NORMALS_TORCH_32_1000_3000_False          753276          753276              1
FACE_AREAS_NORMALS_TORCH_32_1000_3000_True             1205            1340            415
--------------------------------------------------------------------------------
```

Reviewed By: bottler, jcjohnson

Differential Revision: D19864385

fbshipit-source-id: 3a87ae41a8e3ab5560febcb94961798f2e09dfb8
 2020-02-13 11:42:48 -08:00
Jeremy Reizenstein
8fe65d5f56 Single function to load meshes from OBJs. join_meshes. 
Summary:
Create the textures and the Meshes object from OBJ files in a single call.

There is functionality in OBJ files (like normals) which is ignored by this function.

Reviewed By: gkioxari

Differential Revision: D19691699

fbshipit-source-id: e26442ed80ff231b65b17d6c54c9d41e22b4e4a3
 2020-02-13 03:38:07 -08:00
Jeremy Reizenstein
23bb27956a remove print statements 
Reviewed By: gkioxari

Differential Revision: D19834684

fbshipit-source-id: 553dbf84d1062149b4915d313fc0f96eb047798c
 2020-02-11 15:16:15 -08:00
Nikhila Ravi
09992a388f Update tutorials for Google Colab 
Summary:
Update all colab notebooks to:
- Install pytorch3d using pip install from github.
- Retrieve data using `wget`. I set the wget commands to save the files in the same directory structure as in the PyTorch3d repo so that the rest of the tutorial would work for running locally or on Colab.

This should resolve the issues on GitHub with running the colab notebooks.

Reviewed By: gkioxari

Differential Revision: D19827450

fbshipit-source-id: d7b338597ddfd9a84c24592d4dccd274cae11d05
 2020-02-10 19:08:01 -08:00
uzkt
3b1a0741b6 fix small typo in deform_source_mesh_to_target_mesh.ipynb (#34) 
Summary:
fixed target object data folder path './data/doplhin'-> './data/dolphin'
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/34

Differential Revision: D19815377

Pulled By: nikhilaravi

fbshipit-source-id: ff17f6aef8d835b11d7803e912a311c7118b03fa
 2020-02-10 09:14:09 -08:00
Nikhila Ravi
dcb094800f ignore cuda for cpu only installation 
Summary:
Added if `WITH_CUDA` checks for points/mesh rasterization. If installing on cpu only then this causes `Undefined symbol` errors when trying to import pytorch3d.

We had these checks for all the other cuda files but not the rasterization files.

Thanks ppwwyyxx for the tip!

Reviewed By: ppwwyyxx, gkioxari

Differential Revision: D19801495

fbshipit-source-id: 20e7adccfdb33ac731c00a89414b2beaf0a35529
 2020-02-08 09:14:47 -08:00
Yannick Soom
ca588a59d7 small typo in deform_source_mesh_to_target_mesh.ipynb (#24) 
Summary:
fixed small typo in deform_source_mesh_to_target_mesh.ipynb
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/24

Differential Revision: D19801629

Pulled By: nikhilaravi

fbshipit-source-id: 59459f701e0a4c02e749a1b594ca77935fd037d1
 2020-02-07 17:15:08 -08:00
Ignacio López-Francos
a2c68b15d5 fix small typo in README.md (#21) 
Summary:
the dot at the pip command was outside of the inline code formatting. I just moved the back tick after the dot.
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/21

Differential Revision: D19791603

Pulled By: nikhilaravi

fbshipit-source-id: 6b0bedd2a788aef0d9678f9c1c25354ada76a3f4
 2020-02-07 09:56:59 -08:00
frederikzt
b778668132 Added single quote to the markdown block (#23) 
Summary:
The missing single quote makes you unable to directly cope the line if code into Colab
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/23

Differential Revision: D19791643

Pulled By: nikhilaravi

fbshipit-source-id: 2aa043ad4163eb7146c7b8b00bd8846ae61d8009
 2020-02-07 09:49:43 -08:00
Jeremy Reizenstein
533887a188 remove dataclass for python 3.6 compatibility. 
Summary: Make RasterizationSettings be a NamedTuple instead of a dataclass. This makes the mesh renderer work with python 3.6.

Reviewed By: nikhilaravi

Differential Revision: D19769924

fbshipit-source-id: db839f3506dda7d3344fb8a101fa75bdf139ce39
 2020-02-06 16:17:42 -08:00
Nikhila Ravi
3c9f06581a update website css on mobile 
Summary: Updated media queries for website on mobile.

Reviewed By: gkioxari

Differential Revision: D19745526

fbshipit-source-id: a8dc25fcc04726056231d2e1ebeb581251be9324
 2020-02-05 10:55:52 -08:00
Nikhila Ravi
10ec66dadb website updates 
Summary:
A few minor updates to the website.
- fix the color gradient on the homepage
- fix unicode escape for the copyright symbol

Reviewed By: gkioxari

Differential Revision: D19744165

fbshipit-source-id: 31068bd0b408fe7b298e1f69d9998d64498e9d8c
 2020-02-05 09:50:52 -08:00
Nikhila Ravi
15d3a4557e Setup website with docusaurus (#11) 
Summary:
Set up landing page, docs page, and html versions of the ipython notebook tutorials.
Pull Request resolved: https://github.com/fairinternal/pytorch3d/pull/11

Reviewed By: gkioxari

Differential Revision: D19730380

Pulled By: nikhilaravi

fbshipit-source-id: 5df8d3f2ac2f8dce4d51f5d14fc336508c2fd0ea
 2020-02-04 17:27:16 -08:00
Justin Johnson
e290f87ca9 Add CPU implementation for nearest neighbor 
Summary:
Adds a CPU implementation for `pytorch3d.ops.nn_points_idx`.

Also renames the associated C++ and CUDA functions to use `AllCaps` names used in other C++ / CUDA code.

Reviewed By: gkioxari

Differential Revision: D19670491

fbshipit-source-id: 1b6409404025bf05e6a93f5d847e35afc9062f05
 2020-02-03 10:06:10 -08:00
Haoqi Fan
25c2f34096 update install.md 
Reviewed By: bottler, wanyenlo

Differential Revision: D19658045

fbshipit-source-id: a623a81c1ed1fa4054ea55bf06a2926e297b7966
 2020-01-31 14:31:00 -08:00
Georgia Gkioxari
659ad34389 load texture flag 
Summary: Add flag for loading textures

Reviewed By: nikhilaravi

Differential Revision: D19664437

fbshipit-source-id: 3cc4e6179df9b7e24efff9e7da3b164253f1d775
 2020-01-31 13:37:35 -08:00
Jeremy Reizenstein
244b7eb80e allow packaging tools to override CUDA settings 
Summary: This makes sure circle ci builds work with cuda even on machines with no gpu.

Reviewed By: gkioxari

Differential Revision: D19543957

fbshipit-source-id: 9cbfcd4fca22ebe89434ffa71c25d75dd18d2eb6
 2020-01-27 06:19:53 -08:00
Yun Chen
674ee44ca8 fix conda install cmd in INSTALL.md 
Summary: Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/8

Differential Revision: D19556466

Pulled By: nikhilaravi

fbshipit-source-id: 26aa361882b688e7cd159e0d7d8cfad37d0049c1
 2020-01-24 07:25:40 -08:00
Yun Chen
d46e7fa1a6 fix link to tutorials in readme 
Summary: Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/7

Differential Revision: D19556384

Pulled By: nikhilaravi

fbshipit-source-id: 4bd93a3bff92cbba78600bda703a19fd1c663109
 2020-01-24 07:19:21 -08:00
Nikhila Ravi
fd9df7423d update requirements.txt for readthedocs (#6) 
Summary:
We need to install pytorch3d in RTD. Update requirements.txt accordingly.
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/6

Reviewed By: gkioxari

Differential Revision: D19549348

Pulled By: nikhilaravi

fbshipit-source-id: d8d6efe0af9c0d4c7cc6f7662d392f5b3bc16a8c
 2020-01-23 17:31:05 -08:00
Nikhila Ravi
1af6af9bc1 add docs/requirements.txt for readthedocs.io 
Summary: Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/5

Reviewed By: gkioxari

Differential Revision: D19548185

Pulled By: nikhilaravi

fbshipit-source-id: edc825d483a29f1a3311d46b4f349a6bc330c085
 2020-01-23 16:40:15 -08:00
Nikhila Ravi
349a499f33 update conf.py for readthedocs 
Summary: Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/4

Differential Revision: D19546949

Pulled By: nikhilaravi

fbshipit-source-id: ce30785322a60c408fd6aa2f1cd3eb5d07015c7b
 2020-01-23 15:55:32 -08:00
facebook-github-bot
dbf06b504b Initial commit 
fbshipit-source-id: ad58e416e3ceeca85fae0583308968d04e78fe0d
v0.1.0 		2020-01-23 11:53:46 -08:00