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Improve Readability (#133)

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Signed-off-by: Ryan Russell <git@ryanrussell.org>
This commit is contained in:
Ryan Russell
2022-06-01 15:28:02 -05:00
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parent a851168633
commit 1cc288af39
3 changed files with 4 additions and 4 deletions
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4
README.md
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@@ -943,7 +943,7 @@ from dalle2_pytorch.dataloaders import ImageEmbeddingDataset, create_image_embed
# Create a dataloader directly.
dataloader = create_image_embedding_dataloader(
tar_url="/path/or/url/to/webdataset/{0000..9999}.tar", # Uses braket expanding notation. This specifies to read all tars from 0000.tar to 9999.tar
tar_url="/path/or/url/to/webdataset/{0000..9999}.tar", # Uses bracket expanding notation. This specifies to read all tars from 0000.tar to 9999.tar
embeddings_url="path/or/url/to/embeddings/folder", # Included if .npy files are not in webdataset. Left out or set to None otherwise
num_workers=4,
batch_size=32,
@@ -1097,7 +1097,7 @@ This library would not have gotten to this working state without the help of
- [ ] test out grid attention in cascading ddpm locally, decide whether to keep or remove https://arxiv.org/abs/2204.01697
- [ ] interface out the vqgan-vae so a pretrained one can be pulled off the shelf to validate latent diffusion + DALL-E2
- [ ] make sure FILIP works with DALL-E2 from x-clip https://arxiv.org/abs/2111.07783
- [ ] bring in skip-layer excitatons (from lightweight gan paper) to see if it helps for either decoder of unet or vqgan-vae training
- [ ] bring in skip-layer excitations (from lightweight gan paper) to see if it helps for either decoder of unet or vqgan-vae training
- [ ] decoder needs one day worth of refactor for tech debt
- [ ] allow for unet to be able to condition non-cross attention style as well
- [ ] read the paper, figure it out, and build it https://github.com/lucidrains/DALLE2-pytorch/issues/89

2
configs/README.md
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@@ -83,7 +83,7 @@ Defines which evaluation metrics will be used to test the model.
Each metric can be enabled by setting its configuration. The configuration keys for each metric are defined by the torchmetrics constructors which will be linked.
| Option | Required | Default | Description |
| ------ | -------- | ------- | ----------- |
| `n_evalation_samples` | No | `1000` | The number of samples to generate to test the model. |
| `n_evaluation_samples` | No | `1000` | The number of samples to generate to test the model. |
| `FID` | No | `None` | Setting to an object enables the [Frechet Inception Distance](https://torchmetrics.readthedocs.io/en/stable/image/frechet_inception_distance.html) metric.
| `IS` | No | `None` | Setting to an object enables the [Inception Score](https://torchmetrics.readthedocs.io/en/stable/image/inception_score.html) metric.
| `KID` | No | `None` | Setting to an object enables the [Kernel Inception Distance](https://torchmetrics.readthedocs.io/en/stable/image/kernel_inception_distance.html) metric. |

2
dalle2_pytorch/dataloaders/README.md
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@@ -15,7 +15,7 @@ from dalle2_pytorch.dataloaders import ImageEmbeddingDataset, create_image_embed
# Create a dataloader directly.
dataloader = create_image_embedding_dataloader(
tar_url="/path/or/url/to/webdataset/{0000..9999}.tar", # Uses braket expanding notation. This specifies to read all tars from 0000.tar to 9999.tar
tar_url="/path/or/url/to/webdataset/{0000..9999}.tar", # Uses bracket expanding notation. This specifies to read all tars from 0000.tar to 9999.tar
embeddings_url="path/or/url/to/embeddings/folder", # Included if .npy files are not in webdataset. Left out or set to None otherwise
num_workers=4,
batch_size=32,