docs: `src/diffusers` readability improvements (#629)
* docs: `src/diffusers` readability improvements Signed-off-by: Ryan Russell <git@ryanrussell.org> * docs: `make style` lint Signed-off-by: Ryan Russell <git@ryanrussell.org> Signed-off-by: Ryan Russell <git@ryanrussell.org>
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@ -436,7 +436,7 @@ class FlaxModelMixin:
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)
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cls._missing_keys = missing_keys
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# Mistmatched keys contains tuples key/shape1/shape2 of weights in the checkpoint that have a shape not
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# Mismatched keys contains tuples key/shape1/shape2 of weights in the checkpoint that have a shape not
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# matching the weights in the model.
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mismatched_keys = []
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for key in state.keys():
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@ -244,8 +244,8 @@ class FlaxDiffusionPipeline(ConfigMixin):
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kwargs (remaining dictionary of keyword arguments, *optional*):
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Can be used to overwrite load - and saveable variables - *i.e.* the pipeline components - of the
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specific pipeline class. The overritten components are then directly passed to the pipelines `__init__`
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method. See example below for more information.
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specific pipeline class. The overwritten components are then directly passed to the pipelines
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`__init__` method. See example below for more information.
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<Tip>
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@ -235,8 +235,8 @@ class DiffusionPipeline(ConfigMixin):
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kwargs (remaining dictionary of keyword arguments, *optional*):
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Can be used to overwrite load - and saveable variables - *i.e.* the pipeline components - of the
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specific pipeline class. The overritten components are then directly passed to the pipelines `__init__`
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method. See example below for more information.
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specific pipeline class. The overwritten components are then directly passed to the pipelines
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`__init__` method. See example below for more information.
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<Tip>
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@ -27,7 +27,7 @@ class LDMTextToImagePipeline(DiffusionPipeline):
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vqvae ([`VQModel`]):
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Vector-quantized (VQ) Model to encode and decode images to and from latent representations.
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bert ([`LDMBertModel`]):
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Text-encoder model based on [BERT](ttps://huggingface.co/docs/transformers/model_doc/bert) architecture.
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Text-encoder model based on [BERT](https://huggingface.co/docs/transformers/model_doc/bert) architecture.
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tokenizer (`transformers.BertTokenizer`):
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Tokenizer of class
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[BertTokenizer](https://huggingface.co/docs/transformers/model_doc/bert#transformers.BertTokenizer).
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@ -397,7 +397,7 @@ class LDMBertAttention(nn.Module):
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attn_output = attn_output.transpose(1, 2)
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# Use the `embed_dim` from the config (stored in the class) rather than `hidden_state` because `attn_output` can be
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# partitioned aross GPUs when using tensor-parallelism.
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# partitioned across GPUs when using tensor-parallelism.
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attn_output = attn_output.reshape(bsz, tgt_len, self.inner_dim)
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attn_output = self.out_proj(attn_output)
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@ -266,7 +266,7 @@ def reset_format() -> None:
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def warning_advice(self, *args, **kwargs):
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"""
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This method is identical to `logger.warninging()`, but if env var DIFFUSERS_NO_ADVISORY_WARNINGS=1 is set, this
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This method is identical to `logger.warning()`, but if env var DIFFUSERS_NO_ADVISORY_WARNINGS=1 is set, this
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warning will not be printed
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"""
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no_advisory_warnings = os.getenv("DIFFUSERS_NO_ADVISORY_WARNINGS", False)
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