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make style

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This commit is contained in:
Patrick von Platen
2023-02-07 08:11:22 +00:00
parent 717a956a02
commit 3b66cc0fc1
6 changed files with 12 additions and 19 deletions
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6
examples/research_projects/onnxruntime/textual_inversion/textual_inversion.py
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@@ -752,9 +752,9 @@ def main():
# Let's make sure we don't update any embedding weights besides the newly added token
index_no_updates = torch.arange(len(tokenizer)) != placeholder_token_id
with torch.no_grad():
accelerator.unwrap_model(text_encoder).get_input_embeddings().weight[index_no_updates] = (
orig_embeds_params[index_no_updates]
)
accelerator.unwrap_model(text_encoder).get_input_embeddings().weight[
index_no_updates
] = orig_embeds_params[index_no_updates]
# Checks if the accelerator has performed an optimization step behind the scenes
if accelerator.sync_gradients:

6
examples/textual_inversion/textual_inversion.py
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@@ -749,9 +749,9 @@ def main():
# Let's make sure we don't update any embedding weights besides the newly added token
index_no_updates = torch.arange(len(tokenizer)) != placeholder_token_id
with torch.no_grad():
accelerator.unwrap_model(text_encoder).get_input_embeddings().weight[index_no_updates] = (
orig_embeds_params[index_no_updates]
)
accelerator.unwrap_model(text_encoder).get_input_embeddings().weight[
index_no_updates
] = orig_embeds_params[index_no_updates]
# Checks if the accelerator has performed an optimization step behind the scenes
if accelerator.sync_gradients:

10
src/diffusers/pipelines/alt_diffusion/pipeline_alt_diffusion_img2img.py
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@@ -418,9 +418,6 @@ class AltDiffusionImg2ImgPipeline(DiffusionPipeline):
def check_inputs(
self, prompt, strength, callback_steps, negative_prompt=None, prompt_embeds=None, negative_prompt_embeds=None
):
if not isinstance(prompt, str) and not isinstance(prompt, list):
raise ValueError(f"`prompt` has to be of type `str` or `list` but is {type(prompt)}")
if strength < 0 or strength > 1:
raise ValueError(f"The value of strength should in [0.0, 1.0] but is {strength}")
@@ -613,7 +610,12 @@ class AltDiffusionImg2ImgPipeline(DiffusionPipeline):
self.check_inputs(prompt, strength, callback_steps, negative_prompt, prompt_embeds, negative_prompt_embeds)
# 2. Define call parameters
batch_size = 1 if isinstance(prompt, str) else len(prompt)
if prompt is not None and isinstance(prompt, str):
batch_size = 1
elif prompt is not None and isinstance(prompt, list):
batch_size = len(prompt)
else:
batch_size = prompt_embeds.shape[0]
device = self._execution_device
# here `guidance_scale` is defined analog to the guidance weight `w` of equation (2)
# of the Imagen paper: https://arxiv.org/pdf/2205.11487.pdf . `guidance_scale = 1`

3
src/diffusers/pipelines/stable_diffusion/pipeline_cycle_diffusion.py
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@@ -403,9 +403,6 @@ class CycleDiffusionPipeline(DiffusionPipeline):
def check_inputs(
self, prompt, strength, callback_steps, negative_prompt=None, prompt_embeds=None, negative_prompt_embeds=None
):
if not isinstance(prompt, str) and not isinstance(prompt, list):
raise ValueError(f"`prompt` has to be of type `str` or `list` but is {type(prompt)}")
if strength < 0 or strength > 1:
raise ValueError(f"The value of strength should in [0.0, 1.0] but is {strength}")

3
src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_depth2img.py
View File

@@ -339,9 +339,6 @@ class StableDiffusionDepth2ImgPipeline(DiffusionPipeline):
def check_inputs(
self, prompt, strength, callback_steps, negative_prompt=None, prompt_embeds=None, negative_prompt_embeds=None
):
if not isinstance(prompt, str) and not isinstance(prompt, list):
raise ValueError(f"`prompt` has to be of type `str` or `list` but is {type(prompt)}")
if strength < 0 or strength > 1:
raise ValueError(f"The value of strength should in [0.0, 1.0] but is {strength}")

3
src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint_legacy.py
View File

@@ -414,9 +414,6 @@ class StableDiffusionInpaintPipelineLegacy(DiffusionPipeline):
def check_inputs(
self, prompt, strength, callback_steps, negative_prompt=None, prompt_embeds=None, negative_prompt_embeds=None
):
if not isinstance(prompt, str) and not isinstance(prompt, list):
raise ValueError(f"`prompt` has to be of type `str` or `list` but is {type(prompt)}")
if strength < 0 or strength > 1:
raise ValueError(f"The value of strength should in [0.0, 1.0] but is {strength}")