Fixed linter issues

src/bindings/python/src/openvino/frontend/pytorch/torchdynamo/decompositions.py

@@ -1,6 +1,7 @@
 import torch
 from torch._decomp.decompositions import aten, pw_cast_for_opmath
-from torch._decomp import decomposition_table, register_decomposition, get_decompositions
+from torch._decomp import register_decomposition
+
 
 @register_decomposition(aten.convolution_backward)
 @pw_cast_for_opmath
@@ -27,7 +28,7 @@ def convolution_backward(
 
     # Compute the gradient of the weight tensor
     grad_weight = torch.nn.functional.conv_transpose2d(
-        input, weight.transpose(0,1), stride=stride, padding=padding, dilation=dilation, groups=groups, output_padding=output_padding
+        input, weight.transpose(0, 1), stride=stride, padding=padding, dilation=dilation, groups=groups, output_padding=output_padding
     )
 
     # Compute the gradient of the bias tensor
@@ -39,19 +40,17 @@ def convolution_backward(
     return grad_input, grad_weight, grad_bias
 
 
-
 @register_decomposition(aten._scaled_dot_product_flash_attention.default)
 def scaled_dot_product_flash_attention(
     query,
     key,
     value,
-    dropout_p = 0.0,
-    is_causal = False,
+    dropout_p=0.0,
+    is_causal=False,
     *,
-    return_debug_mask = False,
-    scale = None,
+    return_debug_mask=False,
+    scale=None,
 ):
-    dtype = query.dtype
     batchSize, num_head, qSize, headSize = (
         query.shape[0],
         query.shape[1],
@@ -77,7 +76,7 @@ def scaled_dot_product_flash_attention(
         query, key, value, None, dropout_p, is_causal, None, scale=scale
     )
 
-    scores = torch.matmul(query, key.transpose(-2,-1))/ (key.size(-1) ** 0.5)
+    scores = torch.matmul(query, key.transpose(-2, -1)) / (key.size(-1) ** 0.5)
     logsumexp = torch.logsumexp(scores, dim=-1)
 
     output = output.transpose(1, 2).contiguous(memory_format=torch.contiguous_format)
@@ -93,6 +92,7 @@ def scaled_dot_product_flash_attention(
         debug_attn_mask,
     )
 
+
 def get_aot_decomposition_list():
     return ([torch.ops.aten._scaled_dot_product_flash_attention.default,
              torch.ops.aten._softmax.default,