[PyTorch] Use DimVector in at::matmul#72230
Closed
swolchok wants to merge 5 commits intogh/swolchok/444/basefrom
Closed
[PyTorch] Use DimVector in at::matmul#72230swolchok wants to merge 5 commits intogh/swolchok/444/basefrom
swolchok wants to merge 5 commits intogh/swolchok/444/basefrom
Conversation
Here's a small PR that only fixes the extra heap allocations for shapes. Hopefully won't get stuck like #64387. Differential Revision: [D33962610](https://our.internmc.facebook.com/intern/diff/D33962610/) [ghstack-poisoned]
Contributor
🔗 Helpful links
💊 CI failures summary and remediationsAs of commit bb30773 (more details on the Dr. CI page):
🕵️ 3 new failures recognized by patternsThe following CI failures do not appear to be due to upstream breakages:
|
CI Flow Status⚛️ CI FlowRuleset - Version:
|
swolchok
added a commit
that referenced
this pull request
Feb 3, 2022
Here's a small PR that only fixes the extra heap allocations for shapes. Hopefully won't get stuck like #64387. Differential Revision: [D33962610](https://our.internmc.facebook.com/intern/diff/D33962610/) ghstack-source-id: 148261442 Pull Request resolved: #72230
ngimel
approved these changes
Feb 3, 2022
Collaborator
|
I should spend some time splitting that PR into more manageable chunks to be able to isolate that mobile failure... |
IvanYashchuk
approved these changes
Feb 3, 2022
Collaborator
IvanYashchuk
left a comment
There was a problem hiding this comment.
Maybe tensor.sizes().vec() should be disallowed? :)
Here's a small PR that only fixes the extra heap allocations for shapes. Hopefully won't get stuck like #64387. Differential Revision: [D33962610](https://our.internmc.facebook.com/intern/diff/D33962610/) [ghstack-poisoned]
swolchok
added a commit
that referenced
this pull request
Feb 3, 2022
Pull Request resolved: #72230 Here's a small PR that only fixes the extra heap allocations for shapes. Hopefully won't get stuck like #64387. ghstack-source-id: 148314580 Differential Revision: [D33962610](https://our.internmc.facebook.com/intern/diff/D33962610/)
Here's a small PR that only fixes the extra heap allocations for shapes. Hopefully won't get stuck like #64387. Differential Revision: [D33962610](https://our.internmc.facebook.com/intern/diff/D33962610/) [ghstack-poisoned]
swolchok
added a commit
that referenced
this pull request
Feb 4, 2022
Pull Request resolved: #72230 Here's a small PR that only fixes the extra heap allocations for shapes. Hopefully won't get stuck like #64387. ghstack-source-id: 148446641 Differential Revision: [D33962610](https://our.internmc.facebook.com/intern/diff/D33962610/)
Here's a small PR that only fixes the extra heap allocations for shapes. Hopefully won't get stuck like #64387. Differential Revision: [D33962610](https://our.internmc.facebook.com/intern/diff/D33962610/) [ghstack-poisoned]
swolchok
added a commit
that referenced
this pull request
Feb 7, 2022
Pull Request resolved: #72230 Here's a small PR that only fixes the extra heap allocations for shapes. Hopefully won't get stuck like #64387. ghstack-source-id: 148556529 Differential Revision: [D33962610](https://our.internmc.facebook.com/intern/diff/D33962610/)
Here's a small PR that only fixes the extra heap allocations for shapes. Hopefully won't get stuck like #64387. Differential Revision: [D33962610](https://our.internmc.facebook.com/intern/diff/D33962610/) [ghstack-poisoned]
swolchok
added a commit
that referenced
this pull request
Feb 14, 2022
Pull Request resolved: #72230 Here's a small PR that only fixes the extra heap allocations for shapes. Hopefully won't get stuck like #64387. ghstack-source-id: 149069527 Differential Revision: [D33962610](https://our.internmc.facebook.com/intern/diff/D33962610/)
facebook-github-bot
pushed a commit
that referenced
this pull request
Feb 15, 2022
Summary: Pull Request resolved: #72230 Here's a small PR that only fixes the extra heap allocations for shapes. Hopefully won't get stuck like #64387. ghstack-source-id: 149069527 Test Plan: CI Reviewed By: ngimel Differential Revision: D33962610 fbshipit-source-id: 51e200f5237bdf225bfb2445e1e36bacd0e65e92
Contributor
|
Hey @swolchok. |
cyyever
pushed a commit
to cyyever/pytorch_private
that referenced
this pull request
Feb 15, 2022
Summary: Pull Request resolved: pytorch/pytorch#72230 Here's a small PR that only fixes the extra heap allocations for shapes. Hopefully won't get stuck like #64387. ghstack-source-id: 149069527 Test Plan: CI Reviewed By: ngimel Differential Revision: D33962610 fbshipit-source-id: 51e200f5237bdf225bfb2445e1e36bacd0e65e92 (cherry picked from commit 027537f32965d23fc78a36fec71be41cd5cbce3d)
cyyever
pushed a commit
to cyyever/pytorch_private
that referenced
this pull request
Feb 15, 2022
Summary: Pull Request resolved: pytorch/pytorch#72230 Here's a small PR that only fixes the extra heap allocations for shapes. Hopefully won't get stuck like #64387. ghstack-source-id: 149069527 Test Plan: CI Reviewed By: ngimel Differential Revision: D33962610 fbshipit-source-id: 51e200f5237bdf225bfb2445e1e36bacd0e65e92 (cherry picked from commit 027537f32965d23fc78a36fec71be41cd5cbce3d)
cyyever
pushed a commit
to cyyever/pytorch_private
that referenced
this pull request
Feb 15, 2022
Summary: Pull Request resolved: pytorch/pytorch#72230 Here's a small PR that only fixes the extra heap allocations for shapes. Hopefully won't get stuck like #64387. ghstack-source-id: 149069527 Test Plan: CI Reviewed By: ngimel Differential Revision: D33962610 fbshipit-source-id: 51e200f5237bdf225bfb2445e1e36bacd0e65e92 (cherry picked from commit 027537f32965d23fc78a36fec71be41cd5cbce3d)
cyyever
pushed a commit
to cyyever/pytorch_private
that referenced
this pull request
Feb 16, 2022
Summary: Pull Request resolved: pytorch/pytorch#72230 Here's a small PR that only fixes the extra heap allocations for shapes. Hopefully won't get stuck like #64387. ghstack-source-id: 149069527 Test Plan: CI Reviewed By: ngimel Differential Revision: D33962610 fbshipit-source-id: 51e200f5237bdf225bfb2445e1e36bacd0e65e92 (cherry picked from commit 027537f32965d23fc78a36fec71be41cd5cbce3d)
cyyever
pushed a commit
to cyyever/pytorch_private
that referenced
this pull request
Feb 16, 2022
Summary: Pull Request resolved: pytorch/pytorch#72230 Here's a small PR that only fixes the extra heap allocations for shapes. Hopefully won't get stuck like #64387. ghstack-source-id: 149069527 Test Plan: CI Reviewed By: ngimel Differential Revision: D33962610 fbshipit-source-id: 51e200f5237bdf225bfb2445e1e36bacd0e65e92 (cherry picked from commit 027537f32965d23fc78a36fec71be41cd5cbce3d)
cyyever
pushed a commit
to cyyever/pytorch_private
that referenced
this pull request
Feb 17, 2022
Summary: Pull Request resolved: pytorch/pytorch#72230 Here's a small PR that only fixes the extra heap allocations for shapes. Hopefully won't get stuck like #64387. ghstack-source-id: 149069527 Test Plan: CI Reviewed By: ngimel Differential Revision: D33962610 fbshipit-source-id: 51e200f5237bdf225bfb2445e1e36bacd0e65e92 (cherry picked from commit 027537f32965d23fc78a36fec71be41cd5cbce3d)
lezcano
added a commit
that referenced
this pull request
Apr 4, 2022
This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
Apr 5, 2022
…ic boogaloo" This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
Apr 5, 2022
This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
Apr 5, 2022
This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. ghstack-source-id: 0808c8f Pull Request resolved: #75197
lezcano
added a commit
that referenced
this pull request
Apr 5, 2022
…ic boogaloo" This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
Apr 5, 2022
This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
Apr 6, 2022
…ic boogaloo" This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
Apr 6, 2022
This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. ghstack-source-id: 4f44593 Pull Request resolved: #75197
lezcano
added a commit
that referenced
this pull request
Apr 6, 2022
This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
Apr 6, 2022
…ic boogaloo" This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
Apr 6, 2022
This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. ghstack-source-id: 429f9e4 Pull Request resolved: #75197
lezcano
added a commit
that referenced
this pull request
Apr 6, 2022
This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
Apr 21, 2022
…ic boogaloo" This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
Apr 21, 2022
This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
Apr 21, 2022
This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. ghstack-source-id: 1d8dadd Pull Request resolved: #75197
lezcano
added a commit
that referenced
this pull request
May 4, 2022
…ic boogaloo" This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
May 4, 2022
This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
May 5, 2022
…ic boogaloo" This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
May 5, 2022
This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
May 10, 2022
…ic boogaloo" This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
May 10, 2022
This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
May 10, 2022
…ic boogaloo" This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
May 10, 2022
This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
May 10, 2022
…ic boogaloo" This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
May 10, 2022
This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
May 11, 2022
…ic boogaloo" This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
May 11, 2022
This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
May 11, 2022
…ic boogaloo" This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
May 11, 2022
This PR implements the bulk of #64387 Part of the optimisations were already merged in #72230 A number of these optimisations include: - Make the code `const` correct. - Create `DimVector`'s more efficiently (e.g. prefer `append` over `insert`). - Access sizes of the tensors via `sizes().front()` / `sizes().back()` / `sizes().end()[-2]` - Do not create intermediary tensors / vectors when it can be avoided. - Call `reshape` rather than `expect_contiguous` + `view` On top of these, it fixes a correctness issue of `matmul_out`, where the out parameter was not resized correctly when passed to the backends. This involves removing the use of `set_` from the calling code, as requested by ezyang, and it incurs on most of the complexity of the code that this PR adds. [ghstack-poisoned]
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
5 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Stack from ghstack:
Here's a small PR that only fixes the extra heap allocations for shapes. Hopefully won't get stuck like #64387.
Differential Revision: D33962610