Pre-commit fixes

Author: i-colbert

src/qonnx/transformation/lower_convs_to_matmul.py

@@ -32,7 +32,8 @@
 
 from qonnx.transformation.base import Transformation
 from qonnx.transformation.extract_conv_bias import ExtractBiasFromConv
-from qonnx.util.basic import get_by_name, auto_pad_to_explicit_padding
+from qonnx.util.basic import auto_pad_to_explicit_padding, get_by_name
+
 
 class LowerConvsToMatMul(Transformation):
     """Replace Conv layers with pairs of Im2Col-MatMul layers, plus Transpose

src/qonnx/transformation/resize_conv_to_deconv.py

@@ -33,7 +33,7 @@
 from qonnx.core.datatype import DataType
 from qonnx.custom_op.general.quant import quant
 from qonnx.transformation.base import Transformation
-from qonnx.util.basic import get_by_name, auto_pad_to_explicit_padding
+from qonnx.util.basic import auto_pad_to_explicit_padding, get_by_name
 
 
 def _weight_convolution(cnv_weights: np.ndarray, scale: int) -> np.ndarray:
@@ -124,8 +124,8 @@ def apply(self, model):
                             continue
 
                     kshape = get_by_name(conv.attribute, "kernel_shape").ints
-                    idim = model.get_tensor_shape(conv.input[0]) # require NCHW
-                    odim = model.get_tensor_shape(conv.output[0]) # require NCHW
+                    idim = model.get_tensor_shape(conv.input[0])  # require NCHW
+                    odim = model.get_tensor_shape(conv.output[0])  # require NCHW
                     if not (len(odim) == len(idim) == 4):
                         warnings.warn("Skipping resize conv, only 2D convolutions supported.")
                         continue

src/qonnx/transformation/subpixel_to_deconv.py

@@ -31,7 +31,7 @@
 from onnx import helper
 
 from qonnx.transformation.base import Transformation
-from qonnx.util.basic import get_by_name, auto_pad_to_explicit_padding
+from qonnx.util.basic import auto_pad_to_explicit_padding, get_by_name
 
 
 def _weight_shuffle(cnv_weights: np.ndarray, block_size: int) -> np.ndarray:
@@ -120,8 +120,8 @@ def apply(self, model):
                             continue
 
                     kshape = get_by_name(n.attribute, "kernel_shape").ints
-                    idim = model.get_tensor_shape(n.input[0]) # require NCHW
-                    odim = model.get_tensor_shape(n.output[0]) # require NCHW
+                    idim = model.get_tensor_shape(n.input[0])  # require NCHW
+                    odim = model.get_tensor_shape(n.output[0])  # require NCHW
                     if not (len(odim) == len(idim) == 4):
                         warnings.warn("Skipping sub-pixel conv, only 2D convolutions supported.")
                         continue

src/qonnx/util/basic.py

@@ -337,4 +337,4 @@ def auto_pad_to_explicit_padding(autopad_str, idim_h, idim_w, k_h, k_w, stride_h
     elif autopad_str == "SAME_LOWER":
         return [pad_half_large_h, pad_half_large_w, pad_half_small_h, pad_half_small_w]
     else:
-        raise Exception("Unsupported auto_pad: " + autopad_str)
+        raise Exception("Unsupported auto_pad: " + autopad_str)