Unverified Commit df2bc5ef authored by Sai-Suraj-27's avatar Sai-Suraj-27 Committed by GitHub
Browse files

fix: Fixed few `docstrings` according to the Google Style Guide (#7717)

Fixed few docstrings according to the Google Style Guide.
parent a7bf77fc
...@@ -981,7 +981,7 @@ def collate_fn(examples, with_prior_preservation=False): ...@@ -981,7 +981,7 @@ def collate_fn(examples, with_prior_preservation=False):
class PromptDataset(Dataset): class PromptDataset(Dataset):
"A simple dataset to prepare the prompts to generate class images on multiple GPUs." """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
def __init__(self, prompt, num_samples): def __init__(self, prompt, num_samples):
self.prompt = prompt self.prompt = prompt
......
...@@ -1136,7 +1136,7 @@ def collate_fn(examples, with_prior_preservation=False): ...@@ -1136,7 +1136,7 @@ def collate_fn(examples, with_prior_preservation=False):
class PromptDataset(Dataset): class PromptDataset(Dataset):
"A simple dataset to prepare the prompts to generate class images on multiple GPUs." """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
def __init__(self, prompt, num_samples): def __init__(self, prompt, num_samples):
self.prompt = prompt self.prompt = prompt
......
...@@ -78,7 +78,7 @@ def torch_dfs(model: torch.nn.Module): ...@@ -78,7 +78,7 @@ def torch_dfs(model: torch.nn.Module):
class StableDiffusionReferencePipeline( class StableDiffusionReferencePipeline(
DiffusionPipeline, TextualInversionLoaderMixin, LoraLoaderMixin, IPAdapterMixin, FromSingleFileMixin DiffusionPipeline, TextualInversionLoaderMixin, LoraLoaderMixin, IPAdapterMixin, FromSingleFileMixin
): ):
r""" " r"""
Pipeline for Stable Diffusion Reference. Pipeline for Stable Diffusion Reference.
This model inherits from [`DiffusionPipeline`]. Check the superclass documentation for the generic methods This model inherits from [`DiffusionPipeline`]. Check the superclass documentation for the generic methods
......
...@@ -152,7 +152,7 @@ def collate_fn(examples, with_prior_preservation): ...@@ -152,7 +152,7 @@ def collate_fn(examples, with_prior_preservation):
class PromptDataset(Dataset): class PromptDataset(Dataset):
"A simple dataset to prepare the prompts to generate class images on multiple GPUs." """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
def __init__(self, prompt, num_samples): def __init__(self, prompt, num_samples):
self.prompt = prompt self.prompt = prompt
......
...@@ -742,7 +742,7 @@ def collate_fn(examples, with_prior_preservation=False): ...@@ -742,7 +742,7 @@ def collate_fn(examples, with_prior_preservation=False):
class PromptDataset(Dataset): class PromptDataset(Dataset):
"A simple dataset to prepare the prompts to generate class images on multiple GPUs." """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
def __init__(self, prompt, num_samples): def __init__(self, prompt, num_samples):
self.prompt = prompt self.prompt = prompt
......
...@@ -301,7 +301,7 @@ class DreamBoothDataset(Dataset): ...@@ -301,7 +301,7 @@ class DreamBoothDataset(Dataset):
class PromptDataset(Dataset): class PromptDataset(Dataset):
"A simple dataset to prepare the prompts to generate class images on multiple GPUs." """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
def __init__(self, prompt, num_samples): def __init__(self, prompt, num_samples):
self.prompt = prompt self.prompt = prompt
......
...@@ -680,7 +680,7 @@ def collate_fn(examples, with_prior_preservation=False): ...@@ -680,7 +680,7 @@ def collate_fn(examples, with_prior_preservation=False):
class PromptDataset(Dataset): class PromptDataset(Dataset):
"A simple dataset to prepare the prompts to generate class images on multiple GPUs." """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
def __init__(self, prompt, num_samples): def __init__(self, prompt, num_samples):
self.prompt = prompt self.prompt = prompt
......
...@@ -903,7 +903,7 @@ def collate_fn(examples, with_prior_preservation=False): ...@@ -903,7 +903,7 @@ def collate_fn(examples, with_prior_preservation=False):
class PromptDataset(Dataset): class PromptDataset(Dataset):
"A simple dataset to prepare the prompts to generate class images on multiple GPUs." """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
def __init__(self, prompt, num_samples): def __init__(self, prompt, num_samples):
self.prompt = prompt self.prompt = prompt
......
...@@ -327,7 +327,7 @@ class DreamBoothDataset(Dataset): ...@@ -327,7 +327,7 @@ class DreamBoothDataset(Dataset):
class PromptDataset(Dataset): class PromptDataset(Dataset):
"A simple dataset to prepare the prompts to generate class images on multiple GPUs." """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
def __init__(self, prompt, num_samples): def __init__(self, prompt, num_samples):
self.prompt = prompt self.prompt = prompt
......
...@@ -385,7 +385,7 @@ class DreamBoothDataset(Dataset): ...@@ -385,7 +385,7 @@ class DreamBoothDataset(Dataset):
class PromptDataset(Dataset): class PromptDataset(Dataset):
"A simple dataset to prepare the prompts to generate class images on multiple GPUs." """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
def __init__(self, prompt, num_samples): def __init__(self, prompt, num_samples):
self.prompt = prompt self.prompt = prompt
......
...@@ -384,7 +384,7 @@ class DreamBoothDataset(Dataset): ...@@ -384,7 +384,7 @@ class DreamBoothDataset(Dataset):
class PromptDataset(Dataset): class PromptDataset(Dataset):
"A simple dataset to prepare the prompts to generate class images on multiple GPUs." """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
def __init__(self, prompt, num_samples): def __init__(self, prompt, num_samples):
self.prompt = prompt self.prompt = prompt
......
...@@ -762,7 +762,7 @@ def collate_fn(examples, with_prior_preservation=False): ...@@ -762,7 +762,7 @@ def collate_fn(examples, with_prior_preservation=False):
class PromptDataset(Dataset): class PromptDataset(Dataset):
"A simple dataset to prepare the prompts to generate class images on multiple GPUs." """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
def __init__(self, prompt, num_samples): def __init__(self, prompt, num_samples):
self.prompt = prompt self.prompt = prompt
......
...@@ -700,7 +700,7 @@ def collate_fn(examples, with_prior_preservation=False): ...@@ -700,7 +700,7 @@ def collate_fn(examples, with_prior_preservation=False):
class PromptDataset(Dataset): class PromptDataset(Dataset):
"A simple dataset to prepare the prompts to generate class images on multiple GPUs." """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
def __init__(self, prompt, num_samples): def __init__(self, prompt, num_samples):
self.prompt = prompt self.prompt = prompt
......
...@@ -922,7 +922,7 @@ def collate_fn(examples, with_prior_preservation=False): ...@@ -922,7 +922,7 @@ def collate_fn(examples, with_prior_preservation=False):
class PromptDataset(Dataset): class PromptDataset(Dataset):
"A simple dataset to prepare the prompts to generate class images on multiple GPUs." """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
def __init__(self, prompt, num_samples): def __init__(self, prompt, num_samples):
self.prompt = prompt self.prompt = prompt
......
...@@ -844,7 +844,7 @@ class ShapERenderer(ModelMixin, ConfigMixin): ...@@ -844,7 +844,7 @@ class ShapERenderer(ModelMixin, ConfigMixin):
transmittance(t[i + 1]) := transmittance(t[i]). 4) The last term is integration to infinity (e.g. [t[-1], transmittance(t[i + 1]) := transmittance(t[i]). 4) The last term is integration to infinity (e.g. [t[-1],
math.inf]) that is evaluated by the void_model (i.e. we consider this space to be empty). math.inf]) that is evaluated by the void_model (i.e. we consider this space to be empty).
args: Args:
rays: [batch_size x ... x 2 x 3] origin and direction. sampler: disjoint volume integrals. n_samples: rays: [batch_size x ... x 2 x 3] origin and direction. sampler: disjoint volume integrals. n_samples:
number of ts to sample. prev_model_outputs: model outputs from the previous rendering step, including number of ts to sample. prev_model_outputs: model outputs from the previous rendering step, including
......
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