3ba37443e5
Bugfix for applying the bias in conv1d-transpose. ( #1732 )
2024-02-18 22:51:20 +01:00
1fb728772d
Support for groups in conv-transpose1d. ( #1731 )
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* Groups support in conv-transpose-1d.
* Remove dangling file.
2024-02-18 21:28:07 +01:00
678d44a7f6
Expose the weights and biases in transposed convolutions. ( #1727 )
2024-02-18 10:35:01 +01:00
41416d2376
Expose more conv1d functions/structs. ( #1726 )
2024-02-17 18:50:55 +01:00
3b0d1e7d03
Transposed conv1d in candle-nn. ( #1252 )
2023-11-03 11:18:25 +01:00
b3181455d5
Add fuse-conv-bn method for Conv2d ( #1196 )
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* Add fuse-conv-bn method for Conv2d
* no unwrap
* run rustfmp and clippy
2023-10-27 15:56:50 +01:00
7b1ddcff47
Add clone to various nn layers. ( #910 )
2023-09-20 11:33:51 +01:00
06cc329e71
Remove the parameters for the Wuerstchen layer-norm. ( #879 )
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* Remove the parameters for the Wuerstchen layer-norm.
* Fixes.
* More fixes (including conv-transpose2d.
* More fixes.
* Again more fixes.
2023-09-17 15:59:27 +01:00
59e63d690c
Add weight, bias, and hidden_size methods ( #816 )
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* Add weight, bias methods to Conv(1|2)
* Add hidden_size method to Embedding
* Expose hidden_size
2023-09-11 16:01:11 +01:00
b7cd58473b
TinyViT backbone for segment-anything. ( #787 )
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* TinyViT.
* More TinyViT.
* Add more to the tinyvit backbone.
* Proper padding.
* Plus ViT.
* Add the tiniest vit spec.
2023-09-09 15:10:06 +01:00
8c991df394
More segment-anything. ( #763 )
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* More segment-anything.
* Split the model in multiple files.
* Start adding the transformer.
* Add the attention block.
* Move the MLP Block.
2023-09-07 07:28:30 +01:00
000fa00e31
Expose the conv2d-transpose layers. ( #761 )
2023-09-07 06:04:52 +01:00
a17a7c42c1
Add a nn layer for conv-transpose2d. ( #760 )
2023-09-07 05:47:28 +01:00
a044907ffc
Dilated convolutions ( #657 )
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* Add the dilation parameter.
* Restore the basic optimizer example.
* Dilation support in cudnn.
* Use the dilation parameter in the cpu backend.
* More dilation support.
* No support for dilation in transposed convolutions.
* Add dilation to a test.
* Remove a print.
* Helper function.
2023-08-29 16:12:11 +01:00
4c338b0cd9
VarBuilder cleanup ( #627 )
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* VarBuilder cleanup.
* Implement the basic varbuilders.
* Add the sharded code.
* Proper support for tensor sharding.
2023-08-27 18:03:26 +01:00
431051cc32
Add Efficientnet ( #572 )
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* EfficientNet.
* Complete the efficientnet implementation.
* Improve group handling.
* Get the efficientnet to work.
2023-08-23 18:02:58 +01:00
aba1e90797
Add some group parameter to convolutions. ( #566 )
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* Add some group parameter to convolutions.
* Avoid some unnecessary groups checks.
* Move the tensor convolution bits.
* Properh handling of groups.
* Bump the crate version.
* And add a changelog.
2023-08-23 12:58:55 +01:00
e3d2786ffb
Add a couple functions required for yolo. ( #527 )
2023-08-20 17:02:05 +01:00
c78ce76501
Add a simple Module trait and implement it for the various nn layers ( #500 )
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* Start adding the module trait.
* Use the module trait.
* Implement module for qmatmul.
2023-08-18 09:38:22 +01:00
2345b8ce3f
Skeleton for the avg-pool2d and upsample-nearest2d ops. ( #337 )
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* Skeleton for the avg-pool2d and upsample-nearest2d ops.
* Preliminary conv2d support.
2023-08-07 16:15:38 +01:00
d34039e352
Add a stable diffusion example ( #328 )
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* Start adding a stable-diffusion example.
* Proper computation of the causal mask.
* Add the chunk operation.
* Work in progress: port the attention module.
* Add some dummy modules for conv2d and group-norm, get the attention module to compile.
* Re-enable the 2d convolution.
* Add the embeddings module.
* Add the resnet module.
* Add the unet blocks.
* Add the unet.
* And add the variational auto-encoder.
* Use the pad function from utils.
2023-08-06 17:49:43 +01:00
43c7223292
Rename the .r functions to .dims so as to be a bit more explicit. ( #220 )
2023-07-22 10:39:27 +01:00
465fc8c0c5
Add some documentation and test to the linear layer. ( #151 )
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* Add some documentation and test to the linear layer.
* Layer norm doc.
* Minor tweaks.
2023-07-12 20:24:23 +01:00
89a5b602a6
Move the conv1d layer to candle_nn. ( #117 )
2023-07-10 11:02:06 +01:00
