e9c052bf94
Add the comparison operations. ( #207 )
...
* Add the comparison operations.
* Add the helper functions on the tensor side.
* More cmp operations.
* Cpu implementation for the comparison operations.
2023-07-20 09:40:31 +01:00
ad12e20f6b
Add cpu support for min and max. ( #202 )
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* Add cpu support for min and max.
* Add min/max all.
2023-07-19 17:11:44 +01:00
cb687b4897
Add some more developed training examples. ( #199 )
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* Use contiguous tensors for variables.
* Sketch the mnist example.
* Start adding the reduce ops.
* Renaming.
* Refactor the reduce operations.
* Bugfix for the broadcasting vectorization.
2023-07-19 15:37:52 +01:00
67e20c3792
Sum over more dims. ( #197 )
2023-07-19 06:46:32 +01:00
76dcc7a381
Test the broadcasting binary ops. ( #196 )
2023-07-19 06:18:36 +01:00
fd55fc9592
Add an optimized case when performing the softmax over the last dimension. ( #195 )
2023-07-18 17:59:50 +01:00
6623c227d8
Allow the compiler to vectorize some broadcasting loops. ( #194 )
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* Allow the compiler to vectorize some broadcasting loops.
* Improve the symmetrical broadcasting case.
2023-07-18 17:12:32 +01:00
79a5b686d0
Properly use the offset when broadcasting on a narrow slice. ( #193 )
2023-07-18 16:36:23 +01:00
a45a3f0312
Optimize the sum for the contiguous case. ( #192 )
2023-07-18 14:57:06 +01:00
ff61a42ad7
Use mkl to accelerate binary ops. ( #190 )
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* Vectorized binary ops with mkl.
* Improve the binary op mkl support.
* Push the support for mkl binary ops.
* Proper vectorization of binary ops.
* Proper mkl'isation when broadcasting binary ops.
2023-07-18 12:04:39 +01:00
b706f32839
Add Shape try into ( #189 )
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* Add the TryInto trait for shapes.
* Use the vectorized operations in block mode too.
2023-07-18 10:52:16 +01:00
d73df74cb2
Preliminary support for mkl based gelu. ( #187 )
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* Preliminary support for mkl based gelu.
* Add the vectorized function for unary ops.
* Get the mkl specialized gelu to work.
2023-07-18 07:48:48 +01:00
acb2f90469
Broadcasting performance optimization (cpu) ( #182 )
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* Avoid recomputing the index from scratch each time.
* More performance optimisations.
2023-07-17 13:41:09 +01:00
5b1c0bc9be
Performance improvement. ( #181 )
2023-07-17 11:07:14 +01:00
28e1c07304
Process unary functions per block ( #180 )
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* Process unary functions per block.
* Add some inline hints.
2023-07-17 10:22:33 +01:00
18ea92d83b
Iteration over strided blocks ( #175 )
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* Introduce the strided blocks.
* Use the strided blocks to fasten the copy.
* Add more testing.
2023-07-15 21:30:35 +01:00
d88b6cdca9
Add backtrace information to errors where relevant. ( #166 )
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* Add backtrace information to errors where relevant.
* More backtrace information.
* Add to the FAQ.
2023-07-14 09:31:25 +01:00
bcf96e3cf3
Implement the backend trait for the cpu backend. ( #143 )
2023-07-12 09:54:33 +01:00
a76ec797da
Cleanup the main crate error and add a couple dedicated ones ( #142 )
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* Cosmetic cleanups to the error enum.
* More error cleanup.
* Proper error handling rather than panicing.
* Add some conv1d dedicated error.
2023-07-12 09:17:08 +01:00
ae79c00e48
Allow for uniform initialization in a single step. ( #136 )
2023-07-11 08:52:29 +01:00
f29b77ec19
Random initializers. ( #128 )
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* Random initialization.
* CPU rng generation.
2023-07-10 18:26:21 +01:00
548b1df7ea
Remove the dependency to blas and use mkl directly. ( #125 )
2023-07-10 15:52:03 +01:00
221b1aff65
Support dgemm in mkl matmul. ( #122 )
2023-07-10 15:02:37 +01:00
270997a055
Add the elu op. ( #113 )
2023-07-09 21:56:31 +01:00
dd60bd84bb
MKL adjustments. ( #87 )
2023-07-06 11:37:27 +01:00
c297a50960
Add mkl support for matrix multiply. ( #86 )
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* Fix some rebase issues.
* Use mkl instead.
* Use mkl in bert.
* Add the optional mkl feature.
* Conditional compilation based on the mkl feature.
* Add more mkl support.
2023-07-06 11:05:05 +01:00
459e2e1ae3
Properly handle the stride in conv1d.
2023-07-04 15:05:04 +01:00
b3d4d0fd0f
Very inefficient conv1d implementation.
2023-07-04 13:50:41 +01:00
950b4af49e
Proper conv1d dispatch.
2023-07-04 11:29:28 +01:00
a424d95473
Add more of the conv1d op.
2023-07-04 11:15:45 +01:00
3aac1047fe
Sketch the conv1d op.
2023-07-04 10:52:34 +01:00
a57b314780
Add a batch dimension on the bert example.
2023-07-04 06:10:52 +01:00
86d691c74c
Better handling of the batch dimension in matmul.
2023-07-03 22:51:40 +01:00
bbe0c5fbaa
Do not use rayon for a single thread (bis).
2023-06-30 18:47:22 +01:00
6b67d25d9f
Do not use rayon for a single thread.
2023-06-30 18:46:32 +01:00
fbc329ed85
Add the verbose cpu cast operations.
2023-06-30 10:33:29 +01:00
8ad47907f3
Add the kernels.
2023-06-30 10:26:56 +01:00
b4aab7b95f
Put more requirements on the withdtype trait.
2023-06-29 11:37:42 +01:00
eaa3ce359e
Cosmetic change.
2023-06-28 22:02:23 +01:00
1328b5cb20
Factor some code out.
2023-06-28 21:56:44 +01:00
c583ee0f2c
Add map2.
2023-06-28 21:38:01 +01:00
46c07b924c
Tweak some comment.
2023-06-28 21:10:54 +01:00
2ae368e98e
Switch from a macro to a trait to make things more generic.
2023-06-28 21:06:56 +01:00
3f0d9fbb25
Adapt the cuda bits.
2023-06-28 15:43:03 +01:00
cca699be6c
Fix some cpu issue.
2023-06-28 15:09:15 +01:00
1c755c0e5b
Remove some todos.
2023-06-28 14:33:06 +01:00
caafef6cc1
Get the cpu tests to run.
2023-06-28 14:32:02 +01:00
14449ff80c
Get the cpu backend to compile.
2023-06-28 14:12:38 +01:00
54a6c40f27
Propagate the changes on the cpu backend.
2023-06-28 14:00:49 +01:00
303b853098
Propagate the layout refactoring.
2023-06-28 13:42:23 +01:00
