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Fixed issue that sometimes happens in qwen image where text seq length is wrong
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@@ -256,8 +256,11 @@ class QwenImageModel(BaseModel):
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latent_model_input = latent_model_input.permute(0, 2, 4, 1, 3, 5)
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latent_model_input = latent_model_input.reshape(batch_size, (height // 2) * (width // 2), num_channels_latents * 4)
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prompt_embeds_mask = text_embeddings.attention_mask.to(self.device_torch, dtype=torch.int64)
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# make txt_seq_lens match the actual encoder_hidden_states length, and clamp the mask ---
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seq_len = text_embeddings.text_embeds.shape[1]
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prompt_embeds_mask = text_embeddings.attention_mask.to(self.device_torch, dtype=torch.int64)[:, :seq_len]
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txt_seq_lens = [seq_len] * batch_size
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img_shapes = [(1, height // 2, width // 2)] * batch_size
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noise_pred = self.transformer(
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@@ -267,12 +270,11 @@ class QwenImageModel(BaseModel):
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encoder_hidden_states=text_embeddings.text_embeds.to(self.device_torch, self.torch_dtype),
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encoder_hidden_states_mask=prompt_embeds_mask,
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img_shapes=img_shapes,
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txt_seq_lens=prompt_embeds_mask.sum(dim=1).tolist(),
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txt_seq_lens=txt_seq_lens,
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return_dict=False,
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**kwargs,
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)[0]
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# unpack the noise prediction
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noise_pred = noise_pred.view(batch_size, height // 2, width // 2, num_channels_latents, 2, 2)
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noise_pred = noise_pred.permute(0, 3, 1, 4, 2, 5)
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noise_pred = noise_pred.reshape(batch_size, num_channels_latents, height, width)
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