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https://github.com/lucidrains/DALLE2-pytorch.git
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some extra asserts for text encoding of diffusion prior and decoder
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@@ -783,6 +783,7 @@ class DiffusionPrior(BaseGaussianDiffusion):
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text_cond = dict(text_embed = text_embed)
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if self.condition_on_text_encodings:
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assert exists(text_encodings), 'text encodings must be present for diffusion prior if specified'
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text_cond = {**text_cond, 'text_encodings': text_encodings, 'mask': text_mask}
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# timestep conditioning from ddpm
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@@ -792,8 +793,7 @@ class DiffusionPrior(BaseGaussianDiffusion):
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# calculate forward loss
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loss = self.p_losses(image_embed, times, text_cond = text_cond, *args, **kwargs)
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return loss
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return self.p_losses(image_embed, times, text_cond = text_cond, *args, **kwargs)
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# decoder
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@@ -1418,6 +1418,7 @@ class Decoder(BaseGaussianDiffusion):
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_, text_encodings = self.clip.embed_text(text)
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assert not (self.condition_on_text_encodings and not exists(text_encodings)), 'text or text encodings must be passed into decoder if specified'
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assert not (not self.condition_on_text_encodings and exists(text_encodings)), 'decoder specified not to be conditioned on text, yet it is presented'
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img = None
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@@ -1485,6 +1486,7 @@ class Decoder(BaseGaussianDiffusion):
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_, text_encodings = self.clip.embed_text(text)
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assert not (self.condition_on_text_encodings and not exists(text_encodings)), 'text or text encodings must be passed into decoder if specified'
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assert not (not self.condition_on_text_encodings and exists(text_encodings)), 'decoder specified not to be conditioned on text, yet it is presented'
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lowres_cond_img = self.to_lowres_cond(image, target_image_size = target_image_size, downsample_image_size = self.image_sizes[unet_index - 1]) if unet_number > 1 else None
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image = resize_image_to(image, target_image_size)
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