Make some imports late to allow a more minimal set of inference requi…

…rements
Stability-AI · Jul 19, 2023 · d843656 · d843656
1 parent e5dc966
commit d843656
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Showing 3 changed files with 7 additions and 5 deletions.
diff --git a/sgm/modules/autoencoding/losses/__init__.py b/sgm/modules/autoencoding/losses/__init__.py
@@ -3,9 +3,6 @@
 import torch
 import torch.nn as nn
 from einops import rearrange
-from taming.modules.discriminator.model import NLayerDiscriminator, weights_init
-from taming.modules.losses.lpips import LPIPS
-from taming.modules.losses.vqperceptual import hinge_d_loss, vanilla_d_loss
 
 from ....util import default, instantiate_from_config
 
@@ -26,6 +23,7 @@ def __init__(
         scale_tgt_to_input_size=False,
         perceptual_weight_on_inputs=0.0,
     ):
+        from taming.modules.losses.lpips import LPIPS  # late import to avoid extra dependency
         super().__init__()
         self.scale_input_to_tgt_size = scale_input_to_tgt_size
         self.scale_tgt_to_input_size = scale_tgt_to_input_size
@@ -101,6 +99,9 @@ def __init__(
         learn_logvar: bool = False,
         regularization_weights: Union[None, dict] = None,
     ):
+        from taming.modules.losses.lpips import LPIPS  # late import to avoid extra dependency
+        from taming.modules.discriminator.model import NLayerDiscriminator, weights_init  # late import to avoid extra dependency
+        from taming.modules.losses.vqperceptual import hinge_d_loss, vanilla_d_loss  # late import to avoid extra dependency
         super().__init__()
         self.dims = dims
         if self.dims > 2:

diff --git a/sgm/modules/diffusionmodules/loss.py b/sgm/modules/diffusionmodules/loss.py
@@ -3,7 +3,6 @@
 import torch
 import torch.nn as nn
 from omegaconf import ListConfig
-from taming.modules.losses.lpips import LPIPS
 
 from ...util import append_dims, instantiate_from_config
 
@@ -26,6 +25,8 @@ def __init__(
         self.offset_noise_level = offset_noise_level
 
         if type == "lpips":
+            from taming.modules.losses.lpips import LPIPS  # late import to avoid extra dependency
+
             self.lpips = LPIPS().eval()
 
         if not batch2model_keys:

diff --git a/sgm/modules/diffusionmodules/sampling_utils.py b/sgm/modules/diffusionmodules/sampling_utils.py
@@ -1,5 +1,4 @@
 import torch
-from scipy import integrate
 
 from ...util import append_dims
 
@@ -10,6 +9,7 @@ def __call__(self, uncond, cond, scale):
 
 
 def linear_multistep_coeff(order, t, i, j, epsrel=1e-4):
+    from scipy import integrate  # late import to avoid extra dependency
     if order - 1 > i:
         raise ValueError(f"Order {order} too high for step {i}")