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import torch
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import numpy as np
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def faceshifter_batch(source_emb: torch.tensor, 
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                      target: torch.tensor,
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                      G: torch.nn.Module) -> np.ndarray:
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    """
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    Apply faceshifter model for batch of target images
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    """
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    bs = target.shape[0]
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    assert target.ndim == 4, "target should have 4 dimentions -- B x C x H x W"
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    if bs > 1:
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        source_emb = torch.cat([source_emb]*bs)
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    with torch.no_grad():
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        Y_st, _ = G(target, source_emb)
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        Y_st = (Y_st.permute(0, 2, 3, 1)*0.5 + 0.5)*255
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        Y_st = Y_st[:, :, :, [2,1,0]].type(torch.uint8)
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        Y_st = Y_st.cpu().detach().numpy()    
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    return Y_st
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