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linter comment strictnesss
Summary: The linter has become stricter about the indenting of comments and docstrings. This was accompanied by a codemod. In a few places we can fix the problem nicer than the codemod has. Reviewed By: gkioxari Differential Revision: D24363880 fbshipit-source-id: 4cff3bbe3d2a834bc92a490469a2b24fa376e6ab
This commit is contained in:
Jeremy Reizenstein
committed by
Facebook GitHub Bot
Facebook GitHub Bot
parent
563d441b00
commit
30e4e891db
@@ -9,177 +9,177 @@ from . import utils as struct_utils
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class Meshes(object):
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"""
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This class provides functions for working with batches of triangulated
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meshes with varying numbers of faces and vertices, and converting between
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representations.
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This class provides functions for working with batches of triangulated
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meshes with varying numbers of faces and vertices, and converting between
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representations.
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Within Meshes, there are three different representations of the faces and
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verts data:
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Within Meshes, there are three different representations of the faces and
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verts data:
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List
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- only used for input as a starting point to convert to other representations.
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Padded
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- has specific batch dimension.
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Packed
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- no batch dimension.
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- has auxillary variables used to index into the padded representation.
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List
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- only used for input as a starting point to convert to other representations.
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Padded
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- has specific batch dimension.
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Packed
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- no batch dimension.
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- has auxillary variables used to index into the padded representation.
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Example:
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Example:
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Input list of verts V_n = [[V_1], [V_2], ... , [V_N]]
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where V_1, ... , V_N are the number of verts in each mesh and N is the
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numer of meshes.
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Input list of verts V_n = [[V_1], [V_2], ... , [V_N]]
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where V_1, ... , V_N are the number of verts in each mesh and N is the
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numer of meshes.
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Input list of faces F_n = [[F_1], [F_2], ... , [F_N]]
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where F_1, ... , F_N are the number of faces in each mesh.
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Input list of faces F_n = [[F_1], [F_2], ... , [F_N]]
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where F_1, ... , F_N are the number of faces in each mesh.
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# SPHINX IGNORE
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List | Padded | Packed
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---------------------------|-------------------------|------------------------
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[[V_1], ... , [V_N]] | size = (N, max(V_n), 3) | size = (sum(V_n), 3)
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| |
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Example for verts: | |
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| |
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V_1 = 3, V_2 = 4, V_3 = 5 | size = (3, 5, 3) | size = (12, 3)
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| |
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List([ | tensor([ | tensor([
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[ | [ | [0.1, 0.3, 0.5],
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[0.1, 0.3, 0.5], | [0.1, 0.3, 0.5], | [0.5, 0.2, 0.1],
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[0.5, 0.2, 0.1], | [0.5, 0.2, 0.1], | [0.6, 0.8, 0.7],
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[0.6, 0.8, 0.7], | [0.6, 0.8, 0.7], | [0.1, 0.3, 0.3],
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], | [0, 0, 0], | [0.6, 0.7, 0.8],
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[ | [0, 0, 0], | [0.2, 0.3, 0.4],
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[0.1, 0.3, 0.3], | ], | [0.1, 0.5, 0.3],
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[0.6, 0.7, 0.8], | [ | [0.7, 0.3, 0.6],
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[0.2, 0.3, 0.4], | [0.1, 0.3, 0.3], | [0.2, 0.4, 0.8],
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[0.1, 0.5, 0.3], | [0.6, 0.7, 0.8], | [0.9, 0.5, 0.2],
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], | [0.2, 0.3, 0.4], | [0.2, 0.3, 0.4],
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[ | [0.1, 0.5, 0.3], | [0.9, 0.3, 0.8],
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[0.7, 0.3, 0.6], | [0, 0, 0], | ])
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[0.2, 0.4, 0.8], | ], |
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[0.9, 0.5, 0.2], | [ |
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[0.2, 0.3, 0.4], | [0.7, 0.3, 0.6], |
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[0.9, 0.3, 0.8], | [0.2, 0.4, 0.8], |
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] | [0.9, 0.5, 0.2], |
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]) | [0.2, 0.3, 0.4], |
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| [0.9, 0.3, 0.8], |
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| ] |
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| ]) |
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Example for faces: | |
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| |
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F_1 = 1, F_2 = 2, F_3 = 7 | size = (3, 7, 3) | size = (10, 3)
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| |
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List([ | tensor([ | tensor([
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[ | [ | [ 0, 1, 2],
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[0, 1, 2], | [0, 1, 2], | [ 3, 4, 5],
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], | [-1, -1, -1], | [ 4, 5, 6],
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[ | [-1, -1, -1] | [ 8, 9, 7],
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[0, 1, 2], | [-1, -1, -1] | [ 7, 8, 10],
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[1, 2, 3], | [-1, -1, -1] | [ 9, 10, 8],
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], | [-1, -1, -1], | [11, 10, 9],
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[ | [-1, -1, -1], | [11, 7, 8],
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[1, 2, 0], | ], | [11, 10, 8],
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[0, 1, 3], | [ | [11, 9, 8],
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[2, 3, 1], | [0, 1, 2], | ])
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[4, 3, 2], | [1, 2, 3], |
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[4, 0, 1], | [-1, -1, -1], |
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[4, 3, 1], | [-1, -1, -1], |
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[4, 2, 1], | [-1, -1, -1], |
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], | [-1, -1, -1], |
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]) | [-1, -1, -1], |
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| ], |
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| [ |
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| [1, 2, 0], |
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| [0, 1, 3], |
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| [2, 3, 1], |
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| [4, 3, 2], |
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| [4, 0, 1], |
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| [4, 3, 1], |
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| [4, 2, 1], |
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| ] |
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| ]) |
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-----------------------------------------------------------------------------
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# SPHINX IGNORE
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List | Padded | Packed
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---------------------------|-------------------------|------------------------
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[[V_1], ... , [V_N]] | size = (N, max(V_n), 3) | size = (sum(V_n), 3)
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| |
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Example for verts: | |
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| |
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V_1 = 3, V_2 = 4, V_3 = 5 | size = (3, 5, 3) | size = (12, 3)
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| |
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List([ | tensor([ | tensor([
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[ | [ | [0.1, 0.3, 0.5],
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[0.1, 0.3, 0.5], | [0.1, 0.3, 0.5], | [0.5, 0.2, 0.1],
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[0.5, 0.2, 0.1], | [0.5, 0.2, 0.1], | [0.6, 0.8, 0.7],
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[0.6, 0.8, 0.7], | [0.6, 0.8, 0.7], | [0.1, 0.3, 0.3],
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], | [0, 0, 0], | [0.6, 0.7, 0.8],
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[ | [0, 0, 0], | [0.2, 0.3, 0.4],
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[0.1, 0.3, 0.3], | ], | [0.1, 0.5, 0.3],
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[0.6, 0.7, 0.8], | [ | [0.7, 0.3, 0.6],
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[0.2, 0.3, 0.4], | [0.1, 0.3, 0.3], | [0.2, 0.4, 0.8],
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[0.1, 0.5, 0.3], | [0.6, 0.7, 0.8], | [0.9, 0.5, 0.2],
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], | [0.2, 0.3, 0.4], | [0.2, 0.3, 0.4],
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[ | [0.1, 0.5, 0.3], | [0.9, 0.3, 0.8],
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[0.7, 0.3, 0.6], | [0, 0, 0], | ])
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[0.2, 0.4, 0.8], | ], |
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[0.9, 0.5, 0.2], | [ |
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[0.2, 0.3, 0.4], | [0.7, 0.3, 0.6], |
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[0.9, 0.3, 0.8], | [0.2, 0.4, 0.8], |
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] | [0.9, 0.5, 0.2], |
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]) | [0.2, 0.3, 0.4], |
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| [0.9, 0.3, 0.8], |
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| ] |
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| ]) |
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Example for faces: | |
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| |
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F_1 = 1, F_2 = 2, F_3 = 7 | size = (3, 7, 3) | size = (10, 3)
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| |
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List([ | tensor([ | tensor([
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[ | [ | [ 0, 1, 2],
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[0, 1, 2], | [0, 1, 2], | [ 3, 4, 5],
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], | [-1, -1, -1], | [ 4, 5, 6],
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[ | [-1, -1, -1] | [ 8, 9, 7],
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[0, 1, 2], | [-1, -1, -1] | [ 7, 8, 10],
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[1, 2, 3], | [-1, -1, -1] | [ 9, 10, 8],
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], | [-1, -1, -1], | [11, 10, 9],
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[ | [-1, -1, -1], | [11, 7, 8],
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[1, 2, 0], | ], | [11, 10, 8],
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[0, 1, 3], | [ | [11, 9, 8],
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[2, 3, 1], | [0, 1, 2], | ])
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[4, 3, 2], | [1, 2, 3], |
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[4, 0, 1], | [-1, -1, -1], |
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[4, 3, 1], | [-1, -1, -1], |
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[4, 2, 1], | [-1, -1, -1], |
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], | [-1, -1, -1], |
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]) | [-1, -1, -1], |
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| ], |
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| [ |
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| [1, 2, 0], |
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| [0, 1, 3], |
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| [2, 3, 1], |
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| [4, 3, 2], |
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| [4, 0, 1], |
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| [4, 3, 1], |
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| [4, 2, 1], |
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| ] |
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| ]) |
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-----------------------------------------------------------------------------
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Auxillary variables for packed representation
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Auxillary variables for packed representation
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Name | Size | Example from above
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-------------------------------|---------------------|-----------------------
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| |
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verts_packed_to_mesh_idx | size = (sum(V_n)) | tensor([
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| | 0, 0, 0, 1, 1, 1,
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| | 1, 2, 2, 2, 2, 2
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| | )]
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| | size = (12)
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| |
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mesh_to_verts_packed_first_idx | size = (N) | tensor([0, 3, 7])
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| | size = (3)
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| |
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num_verts_per_mesh | size = (N) | tensor([3, 4, 5])
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| | size = (3)
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| |
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faces_packed_to_mesh_idx | size = (sum(F_n)) | tensor([
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| | 0, 1, 1, 2, 2, 2,
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| | 2, 2, 2, 2
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| | )]
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| | size = (10)
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| |
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mesh_to_faces_packed_first_idx | size = (N) | tensor([0, 1, 3])
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| | size = (3)
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| |
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num_faces_per_mesh | size = (N) | tensor([1, 2, 7])
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| | size = (3)
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| |
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verts_padded_to_packed_idx | size = (sum(V_n)) | tensor([
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| | 0, 1, 2, 5, 6, 7,
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| | 8, 10, 11, 12, 13,
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| | 14
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| | )]
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| | size = (12)
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-----------------------------------------------------------------------------
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# SPHINX IGNORE
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Name | Size | Example from above
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-------------------------------|---------------------|-----------------------
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| |
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verts_packed_to_mesh_idx | size = (sum(V_n)) | tensor([
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| | 0, 0, 0, 1, 1, 1,
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| | 1, 2, 2, 2, 2, 2
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| | )]
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| | size = (12)
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| |
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mesh_to_verts_packed_first_idx | size = (N) | tensor([0, 3, 7])
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| | size = (3)
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| |
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num_verts_per_mesh | size = (N) | tensor([3, 4, 5])
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| | size = (3)
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| |
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faces_packed_to_mesh_idx | size = (sum(F_n)) | tensor([
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| | 0, 1, 1, 2, 2, 2,
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| | 2, 2, 2, 2
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| | )]
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| | size = (10)
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| |
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mesh_to_faces_packed_first_idx | size = (N) | tensor([0, 1, 3])
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| | size = (3)
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| |
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num_faces_per_mesh | size = (N) | tensor([1, 2, 7])
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| | size = (3)
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| |
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verts_padded_to_packed_idx | size = (sum(V_n)) | tensor([
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| | 0, 1, 2, 5, 6, 7,
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| | 8, 10, 11, 12, 13,
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| | 14
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| | )]
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| | size = (12)
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-----------------------------------------------------------------------------
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# SPHINX IGNORE
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From the faces, edges are computed and have packed and padded
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representations with auxillary variables.
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From the faces, edges are computed and have packed and padded
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representations with auxillary variables.
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E_n = [[E_1], ... , [E_N]]
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where E_1, ... , E_N are the number of unique edges in each mesh.
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Total number of unique edges = sum(E_n)
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E_n = [[E_1], ... , [E_N]]
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where E_1, ... , E_N are the number of unique edges in each mesh.
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Total number of unique edges = sum(E_n)
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# SPHINX IGNORE
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Name | Size | Example from above
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-------------------------------|-------------------------|----------------------
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| |
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edges_packed | size = (sum(E_n), 2) | tensor([
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| | [0, 1],
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| | [0, 2],
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| | [1, 2],
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| | ...
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| | [10, 11],
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| | )]
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| | size = (18, 2)
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| |
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num_edges_per_mesh | size = (N) | tensor([3, 5, 10])
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| | size = (3)
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| |
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edges_packed_to_mesh_idx | size = (sum(E_n)) | tensor([
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| | 0, 0, 0,
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| | . . .
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| | 2, 2, 2
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| | ])
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| | size = (18)
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| |
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faces_packed_to_edges_packed | size = (sum(F_n), 3) | tensor([
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| | [2, 1, 0],
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| | [5, 4, 3],
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| | . . .
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| | [12, 14, 16],
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| | ])
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| | size = (10, 3)
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| |
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mesh_to_edges_packed_first_idx | size = (N) | tensor([0, 3, 8])
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| | size = (3)
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----------------------------------------------------------------------------
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# SPHINX IGNORE
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# SPHINX IGNORE
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Name | Size | Example from above
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-------------------------------|-------------------------|----------------------
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| |
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edges_packed | size = (sum(E_n), 2) | tensor([
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| | [0, 1],
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| | [0, 2],
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| | [1, 2],
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| | ...
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| | [10, 11],
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| | )]
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| | size = (18, 2)
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| |
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num_edges_per_mesh | size = (N) | tensor([3, 5, 10])
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| | size = (3)
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| |
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edges_packed_to_mesh_idx | size = (sum(E_n)) | tensor([
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| | 0, 0, 0,
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| | . . .
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| | 2, 2, 2
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| | ])
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| | size = (18)
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| |
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faces_packed_to_edges_packed | size = (sum(F_n), 3) | tensor([
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| | [2, 1, 0],
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| | [5, 4, 3],
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| | . . .
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| | [12, 14, 16],
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| | ])
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| | size = (10, 3)
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| |
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mesh_to_edges_packed_first_idx | size = (N) | tensor([0, 3, 8])
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| | size = (3)
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----------------------------------------------------------------------------
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# SPHINX IGNORE
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"""
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_INTERNAL_TENSORS = [
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@@ -8,85 +8,85 @@ from . import utils as struct_utils
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class Pointclouds(object):
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"""
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This class provides functions for working with batches of 3d point clouds,
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and converting between representations.
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This class provides functions for working with batches of 3d point clouds,
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and converting between representations.
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Within Pointclouds, there are three different representations of the data.
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Within Pointclouds, there are three different representations of the data.
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List
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- only used for input as a starting point to convert to other representations.
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Padded
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- has specific batch dimension.
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Packed
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- no batch dimension.
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- has auxillary variables used to index into the padded representation.
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List
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- only used for input as a starting point to convert to other representations.
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Padded
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- has specific batch dimension.
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Packed
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- no batch dimension.
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- has auxillary variables used to index into the padded representation.
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Example
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Example
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Input list of points = [[P_1], [P_2], ... , [P_N]]
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where P_1, ... , P_N are the number of points in each cloud and N is the
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number of clouds.
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Input list of points = [[P_1], [P_2], ... , [P_N]]
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where P_1, ... , P_N are the number of points in each cloud and N is the
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number of clouds.
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# SPHINX IGNORE
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List | Padded | Packed
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---------------------------|-------------------------|------------------------
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[[P_1], ... , [P_N]] | size = (N, max(P_n), 3) | size = (sum(P_n), 3)
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| |
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Example for locations | |
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or colors: | |
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| |
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P_1 = 3, P_2 = 4, P_3 = 5 | size = (3, 5, 3) | size = (12, 3)
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| |
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List([ | tensor([ | tensor([
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[ | [ | [0.1, 0.3, 0.5],
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[0.1, 0.3, 0.5], | [0.1, 0.3, 0.5], | [0.5, 0.2, 0.1],
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[0.5, 0.2, 0.1], | [0.5, 0.2, 0.1], | [0.6, 0.8, 0.7],
|
||||
[0.6, 0.8, 0.7] | [0.6, 0.8, 0.7], | [0.1, 0.3, 0.3],
|
||||
], | [0, 0, 0], | [0.6, 0.7, 0.8],
|
||||
[ | [0, 0, 0] | [0.2, 0.3, 0.4],
|
||||
[0.1, 0.3, 0.3], | ], | [0.1, 0.5, 0.3],
|
||||
[0.6, 0.7, 0.8], | [ | [0.7, 0.3, 0.6],
|
||||
[0.2, 0.3, 0.4], | [0.1, 0.3, 0.3], | [0.2, 0.4, 0.8],
|
||||
[0.1, 0.5, 0.3] | [0.6, 0.7, 0.8], | [0.9, 0.5, 0.2],
|
||||
], | [0.2, 0.3, 0.4], | [0.2, 0.3, 0.4],
|
||||
[ | [0.1, 0.5, 0.3], | [0.9, 0.3, 0.8],
|
||||
[0.7, 0.3, 0.6], | [0, 0, 0] | ])
|
||||
[0.2, 0.4, 0.8], | ], |
|
||||
[0.9, 0.5, 0.2], | [ |
|
||||
[0.2, 0.3, 0.4], | [0.7, 0.3, 0.6], |
|
||||
[0.9, 0.3, 0.8], | [0.2, 0.4, 0.8], |
|
||||
] | [0.9, 0.5, 0.2], |
|
||||
]) | [0.2, 0.3, 0.4], |
|
||||
| [0.9, 0.3, 0.8] |
|
||||
| ] |
|
||||
| ]) |
|
||||
-----------------------------------------------------------------------------
|
||||
# SPHINX IGNORE
|
||||
List | Padded | Packed
|
||||
---------------------------|-------------------------|------------------------
|
||||
[[P_1], ... , [P_N]] | size = (N, max(P_n), 3) | size = (sum(P_n), 3)
|
||||
| |
|
||||
Example for locations | |
|
||||
or colors: | |
|
||||
| |
|
||||
P_1 = 3, P_2 = 4, P_3 = 5 | size = (3, 5, 3) | size = (12, 3)
|
||||
| |
|
||||
List([ | tensor([ | tensor([
|
||||
[ | [ | [0.1, 0.3, 0.5],
|
||||
[0.1, 0.3, 0.5], | [0.1, 0.3, 0.5], | [0.5, 0.2, 0.1],
|
||||
[0.5, 0.2, 0.1], | [0.5, 0.2, 0.1], | [0.6, 0.8, 0.7],
|
||||
[0.6, 0.8, 0.7] | [0.6, 0.8, 0.7], | [0.1, 0.3, 0.3],
|
||||
], | [0, 0, 0], | [0.6, 0.7, 0.8],
|
||||
[ | [0, 0, 0] | [0.2, 0.3, 0.4],
|
||||
[0.1, 0.3, 0.3], | ], | [0.1, 0.5, 0.3],
|
||||
[0.6, 0.7, 0.8], | [ | [0.7, 0.3, 0.6],
|
||||
[0.2, 0.3, 0.4], | [0.1, 0.3, 0.3], | [0.2, 0.4, 0.8],
|
||||
[0.1, 0.5, 0.3] | [0.6, 0.7, 0.8], | [0.9, 0.5, 0.2],
|
||||
], | [0.2, 0.3, 0.4], | [0.2, 0.3, 0.4],
|
||||
[ | [0.1, 0.5, 0.3], | [0.9, 0.3, 0.8],
|
||||
[0.7, 0.3, 0.6], | [0, 0, 0] | ])
|
||||
[0.2, 0.4, 0.8], | ], |
|
||||
[0.9, 0.5, 0.2], | [ |
|
||||
[0.2, 0.3, 0.4], | [0.7, 0.3, 0.6], |
|
||||
[0.9, 0.3, 0.8], | [0.2, 0.4, 0.8], |
|
||||
] | [0.9, 0.5, 0.2], |
|
||||
]) | [0.2, 0.3, 0.4], |
|
||||
| [0.9, 0.3, 0.8] |
|
||||
| ] |
|
||||
| ]) |
|
||||
-----------------------------------------------------------------------------
|
||||
|
||||
Auxillary variables for packed representation
|
||||
Auxillary variables for packed representation
|
||||
|
||||
Name | Size | Example from above
|
||||
-------------------------------|---------------------|-----------------------
|
||||
| |
|
||||
packed_to_cloud_idx | size = (sum(P_n)) | tensor([
|
||||
| | 0, 0, 0, 1, 1, 1,
|
||||
| | 1, 2, 2, 2, 2, 2
|
||||
| | )]
|
||||
| | size = (12)
|
||||
| |
|
||||
cloud_to_packed_first_idx | size = (N) | tensor([0, 3, 7])
|
||||
| | size = (3)
|
||||
| |
|
||||
num_points_per_cloud | size = (N) | tensor([3, 4, 5])
|
||||
| | size = (3)
|
||||
| |
|
||||
padded_to_packed_idx | size = (sum(P_n)) | tensor([
|
||||
| | 0, 1, 2, 5, 6, 7,
|
||||
| | 8, 10, 11, 12, 13,
|
||||
| | 14
|
||||
| | )]
|
||||
| | size = (12)
|
||||
-----------------------------------------------------------------------------
|
||||
# SPHINX IGNORE
|
||||
Name | Size | Example from above
|
||||
-------------------------------|---------------------|-----------------------
|
||||
| |
|
||||
packed_to_cloud_idx | size = (sum(P_n)) | tensor([
|
||||
| | 0, 0, 0, 1, 1, 1,
|
||||
| | 1, 2, 2, 2, 2, 2
|
||||
| | )]
|
||||
| | size = (12)
|
||||
| |
|
||||
cloud_to_packed_first_idx | size = (N) | tensor([0, 3, 7])
|
||||
| | size = (3)
|
||||
| |
|
||||
num_points_per_cloud | size = (N) | tensor([3, 4, 5])
|
||||
| | size = (3)
|
||||
| |
|
||||
padded_to_packed_idx | size = (sum(P_n)) | tensor([
|
||||
| | 0, 1, 2, 5, 6, 7,
|
||||
| | 8, 10, 11, 12, 13,
|
||||
| | 14
|
||||
| | )]
|
||||
| | size = (12)
|
||||
-----------------------------------------------------------------------------
|
||||
# SPHINX IGNORE
|
||||
"""
|
||||
|
||||
_INTERNAL_TENSORS = [
|
||||
|
||||
Reference in New Issue
Block a user