Unify logic for detecting pixelshuffle

libs/spandrel/spandrel/architectures/ATD/__init__.py

@@ -2,7 +2,7 @@
 
 from typing_extensions import override
 
-from spandrel.util import KeyCondition, get_seq_len
+from spandrel.util import KeyCondition, get_pixelshuffle_params, get_seq_len
 
 from ...__helpers.model_descriptor import (
     Architecture,
@@ -114,15 +114,7 @@ def load(self, state_dict: StateDict) -> ImageModelDescriptor[ATD]:
             upscale = 4
         elif "conv_before_upsample.0.weight" in state_dict:
             upsampler = "pixelshuffle"
-            upscale = 1
-            for i in range(0, 10, 2):
-                if f"upsample.{i}.weight" not in state_dict:
-                    break
-                num_feat = state_dict[f"upsample.{i}.weight"].shape[1]
-
-                upscale *= math.isqrt(
-                    state_dict[f"upsample.{i}.weight"].shape[0] // num_feat
-                )
+            upscale, _ = get_pixelshuffle_params(state_dict, "upsample")
         elif "conv_last.weight" in state_dict:
             upsampler = ""
             upscale = 1

libs/spandrel/spandrel/architectures/DAT/__init__.py

@@ -2,7 +2,7 @@
 
 from typing_extensions import override
 
-from spandrel.util import KeyCondition, get_seq_len
+from spandrel.util import KeyCondition, get_pixelshuffle_params, get_seq_len
 
 from ...__helpers.model_descriptor import (
     Architecture,
@@ -107,11 +107,7 @@ def load(self, state_dict: StateDict) -> ImageModelDescriptor[DAT]:
         resi_connection = "1conv" if "conv_after_body.weight" in state_dict else "3conv"
 
         if upsampler == "pixelshuffle":
-            upscale = 1
-            for i in range(0, get_seq_len(state_dict, "upsample"), 2):
-                num_feat = state_dict[f"upsample.{i}.weight"].shape[1]
-                shape = state_dict[f"upsample.{i}.weight"].shape[0]
-                upscale *= int(math.sqrt(shape // num_feat))
+            upscale, num_feat = get_pixelshuffle_params(state_dict, "upsample")
         elif upsampler == "pixelshuffledirect":
             num_feat = state_dict["upsample.0.weight"].shape[1]
             upscale = int(

libs/spandrel/spandrel/architectures/DRCT/__init__.py

@@ -2,7 +2,7 @@
 
 from typing_extensions import override
 
-from spandrel.util import KeyCondition, get_seq_len
+from spandrel.util import KeyCondition, get_pixelshuffle_params, get_seq_len
 
 from ...__helpers.model_descriptor import (
     Architecture,
@@ -13,23 +13,6 @@
 from .arch.drct_arch import DRCT
 
 
-def _get_upscale_pixelshuffle(
-    state_dict: StateDict, key_prefix: str = "upsample"
-) -> int:
-    upscale = 1
-
-    for i in range(0, 10, 2):
-        key = f"{key_prefix}.{i}.weight"
-        if key not in state_dict:
-            break
-
-        shape = state_dict[key].shape
-        num_feat = shape[1]
-        upscale *= math.isqrt(shape[0] // num_feat)
-
-    return upscale
-
-
 class DRCTArch(Architecture[DRCT]):
     def __init__(self) -> None:
         super().__init__(
@@ -105,7 +88,7 @@ def load(self, state_dict: StateDict) -> ImageModelDescriptor[DRCT]:
 
         if "conv_last.weight" in state_dict:
             upsampler = "pixelshuffle"
-            upscale = _get_upscale_pixelshuffle(state_dict, "upsample")
+            upscale, _ = get_pixelshuffle_params(state_dict, "upsample")
         else:
             upsampler = ""
             upscale = 1

libs/spandrel/spandrel/architectures/GRL/__init__.py

@@ -6,7 +6,12 @@
 import torch
 from typing_extensions import override
 
-from spandrel.util import KeyCondition, get_scale_and_output_channels, get_seq_len
+from spandrel.util import (
+    KeyCondition,
+    get_pixelshuffle_params,
+    get_scale_and_output_channels,
+    get_seq_len,
+)
 
 from ...__helpers.canonicalize import remove_common_prefix
 from ...__helpers.model_descriptor import Architecture, ImageModelDescriptor, StateDict
@@ -50,18 +55,14 @@ def _get_output_params(state_dict: StateDict, in_channels: int):
     upsampler: str
     upscale: int
 
-    num_out_feats = 64  # hard-coded
     if (
         "conv_before_upsample.0.weight" in state_dict
         and "upsample.up.0.weight" in state_dict
     ):
         upsampler = "pixelshuffle"
         out_channels = state_dict["conv_last.weight"].shape[0]
 
-        upscale = 1
-        for i in range(0, get_seq_len(state_dict, "upsample.up"), 2):
-            shape = state_dict[f"upsample.up.{i}.weight"].shape[0]
-            upscale *= int(math.sqrt(shape // num_out_feats))
+        upscale, _ = get_pixelshuffle_params(state_dict, "upsample.up")
     elif "upsample.up.0.weight" in state_dict:
         upsampler = "pixelshuffledirect"
         upscale, out_channels = get_scale_and_output_channels(

libs/spandrel/spandrel/architectures/HAT/__init__.py

@@ -2,7 +2,7 @@
 
 from typing_extensions import override
 
-from spandrel.util import KeyCondition, get_seq_len
+from spandrel.util import KeyCondition, get_pixelshuffle_params, get_seq_len
 
 from ...__helpers.model_descriptor import (
     Architecture,
@@ -109,10 +109,7 @@ def load(self, state_dict: StateDict) -> ImageModelDescriptor[HAT]:
         embed_dim = state_dict["conv_first.weight"].shape[0]
 
         num_feat = state_dict["conv_last.weight"].shape[1]
-        upscale = 1
-        for i in range(0, get_seq_len(state_dict, "upsample"), 2):
-            shape = state_dict[f"upsample.{i}.weight"].shape[0]
-            upscale *= int(math.sqrt(shape // num_feat))
+        upscale, _ = get_pixelshuffle_params(state_dict, "upsample", num_feat)
 
         window_size = int(math.sqrt(state_dict["relative_position_index_SA"].shape[0]))
         overlap_ratio = _get_overlap_ratio(

libs/spandrel/spandrel/architectures/RGT/__init__.py

@@ -4,7 +4,7 @@
 
 from typing_extensions import override
 
-from spandrel.util import KeyCondition, get_seq_len
+from spandrel.util import KeyCondition, get_pixelshuffle_params, get_seq_len
 
 from ...__helpers.model_descriptor import (
     Architecture,
@@ -133,13 +133,7 @@ def load(self, state_dict: StateDict) -> ImageModelDescriptor[RGT]:
                 )
                 break
 
-        upscale = 1
-        for i in range(0, 10, 2):
-            key = f"upsample.{i}.weight"
-            if key in state_dict:
-                shape = state_dict[key].shape
-                num_feat = shape[1]
-                upscale *= math.isqrt(shape[0] // num_feat)
+        upscale, _ = get_pixelshuffle_params(state_dict, "upsample")
 
         split_size = _get_split_size(state_dict)
 

libs/spandrel/spandrel/architectures/Swin2SR/__init__.py

@@ -2,7 +2,7 @@
 
 from typing_extensions import override
 
-from spandrel.util import KeyCondition, get_seq_len
+from spandrel.util import KeyCondition, get_pixelshuffle_params, get_seq_len
 
 from ...__helpers.model_descriptor import (
     Architecture,
@@ -102,11 +102,7 @@ def load(self, state_dict: StateDict) -> ImageModelDescriptor[Swin2SR]:
                 math.sqrt(state_dict["upsample.0.weight"].shape[0] // in_chans)
             )
         else:
-            num_feat = 64  # hard-coded constant
-            upscale = 1
-            for i in range(0, get_seq_len(state_dict, "upsample"), 2):
-                shape = state_dict[f"upsample.{i}.weight"].shape[0]
-                upscale *= int(math.sqrt(shape // num_feat))
+            upscale, _ = get_pixelshuffle_params(state_dict, "upsample")
 
         window_size = int(
             math.sqrt(

libs/spandrel/spandrel/architectures/SwinIR/__init__.py

@@ -3,7 +3,7 @@
 from torch import nn
 from typing_extensions import override
 
-from spandrel.util import KeyCondition, get_seq_len
+from spandrel.util import KeyCondition, get_pixelshuffle_params, get_seq_len
 
 from ...__helpers.model_descriptor import (
     Architecture,
@@ -84,15 +84,7 @@ def load(self, state_dict: StateDict) -> ImageModelDescriptor[SwinIR]:
             for _upsample_key in upsample_keys:
                 upscale *= 2
         elif upsampler == "pixelshuffle":
-            upsample_keys = [
-                x
-                for x in state_dict
-                if "upsample" in x and "conv" not in x and "bias" not in x
-            ]
-            for upsample_key in upsample_keys:
-                shape = state_dict[upsample_key].shape[0]
-                upscale *= math.sqrt(shape // num_feat)
-            upscale = int(upscale)
+            upscale, num_feat = get_pixelshuffle_params(state_dict, "upsample")
         elif upsampler == "pixelshuffledirect":
             upscale = int(
                 math.sqrt(state_dict["upsample.0.bias"].shape[0] // num_out_ch)

libs/spandrel/spandrel/util/__init__.py

@@ -111,6 +111,35 @@ def is_square(n: int) -> bool:
     )
 
 
+def get_pixelshuffle_params(
+    state_dict: Mapping[str, object],
+    upsample_key: str = "upsample",
+    default_nf: int = 64,
+) -> tuple[int, int]:
+    """
+    This will detect the upscale factor and number of features of a pixelshuffle module in the state dict.
+
+    A pixelshuffle module is a sequence of alternating up convolutions and pixelshuffle.
+    The class of this module is commonyl called `Upsample`.
+    Examples of such modules can be found in most SISR architectures, such as SwinIR, HAT, RGT, and many more.
+    """
+    upscale = 1
+    num_feat = default_nf
+
+    for i in range(0, 10, 2):
+        key = f"{upsample_key}.{i}.weight"
+        if key not in state_dict:
+            break
+
+        tensor = state_dict[key]
+        # we'll assume that the state dict contains tensors
+        shape: tuple[int, ...] = tensor.shape  # type: ignore
+        num_feat = shape[1]
+        upscale *= math.isqrt(shape[0] // num_feat)
+
+    return upscale, num_feat
+
+
 def store_hyperparameters(*, extra_parameters: Mapping[str, object] = {}):
     """
     Stores the hyperparameters of a class in a `hyperparameters` attribute.
@@ -170,9 +199,10 @@ def new_init(self: C, **kwargs):
 
 
 __all__ = [
-    "KeyCondition",
     "get_first_seq_index",
-    "get_seq_len",
+    "get_pixelshuffle_params",
     "get_scale_and_output_channels",
+    "get_seq_len",
+    "KeyCondition",
     "store_hyperparameters",
 ]

libs/spandrel_extra_arches/spandrel_extra_arches/architectures/SRFormer/__init__.py

@@ -8,7 +8,7 @@
     SizeRequirements,
     StateDict,
 )
-from spandrel.util import KeyCondition, get_seq_len
+from spandrel.util import KeyCondition, get_pixelshuffle_params, get_seq_len
 
 from .arch.SRFormer import SRFormer
 
@@ -76,12 +76,7 @@ def load(self, state_dict: StateDict) -> ImageModelDescriptor[SRFormer]:
             upscale = 4  # only supported scale
         elif "conv_before_upsample.0.weight" in state_dict:
             upsampler = "pixelshuffle"
-
-            num_feat = 64  # hard-coded constant
-            upscale = 1
-            for i in range(0, get_seq_len(state_dict, "upsample"), 2):
-                shape = state_dict[f"upsample.{i}.weight"].shape[0]
-                upscale *= int(math.sqrt(shape // num_feat))
+            upscale, _ = get_pixelshuffle_params(state_dict, "upsample")
         elif "upsample.0.weight" in state_dict:
             upsampler = "pixelshuffledirect"
             upscale = int(