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Noted place that requires intervention.
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@@ -279,16 +279,16 @@ class LTXConditionedPipeline(LTXPipeline):
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continue
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# change this
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# latent_model_input = torch.cat([latents] * 2) if self.do_classifier_free_guidance else latents
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# latent_model_input = latent_model_input.to(prompt_embeds.dtype)
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#latent_model_input = latent_model_input.to(prompt_embeds.dtype)
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# might be the bug ..
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latent_model_input = noisy_latent_tokens
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latent_model_input = torch.cat([noisy_latent_tokens] * 2) if self.do_classifier_free_guidance else noisy_latent_tokens
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latent_model_input = latent_model_input.to(prompt_embeds.dtype)
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# broadcast to batch dimension in a way that's compatible with ONNX/Core ML
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timestep = t.expand(latent_model_input.shape[0])
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#encoder hidden states are different...
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noise_pred = self.transformer(
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hidden_states=condition_tokens,
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encoder_hidden_states=prompt_embeds,
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