[quantized] Fix return values of _get_name() in quantized ConvTranspo…

…se (#97678)

This PR fixes incorrect return values of _get_name() in quantized `ConvTranspose?d`.

Pull Request resolved: #97678
Approved by: https://github.com/vkuzo, https://github.com/kit1980

torch/ao/nn/quantized/dynamic/modules/conv.py

@@ -267,7 +267,7 @@ def __init__(self, in_channels, out_channels, kernel_size, stride=1,
             groups, bias, dilation, padding_mode, **factory_kwargs)
 
     def _get_name(self):
-        return 'DynamicQuantizedConvTranpose1d'
+        return 'DynamicQuantizedConvTranspose1d'
 
     def forward(self, input: Tensor, reduce_range: bool = True) -> Tensor:
         # Temporarily using len(shape) instead of ndim due to JIT issue
@@ -328,7 +328,7 @@ def __init__(self, in_channels, out_channels, kernel_size, stride=1,
             groups, bias, dilation, padding_mode, **factory_kwargs)
 
     def _get_name(self):
-        return 'DynamicQuantizedConvTranpose2d'
+        return 'DynamicQuantizedConvTranspose2d'
 
     def forward(self, input: Tensor, reduce_range: bool = True) -> Tensor:
         # Temporarily using len(shape) instead of ndim due to JIT issue
@@ -389,7 +389,7 @@ def __init__(self, in_channels, out_channels, kernel_size, stride=1,
             groups, bias, dilation, padding_mode, **factory_kwargs)
 
     def _get_name(self):
-        return 'DynamicQuantizedConvTranpose3d'
+        return 'DynamicQuantizedConvTranspose3d'
 
     def forward(self, input: Tensor, reduce_range: bool = True) -> Tensor:
         # Temporarily using len(shape) instead of ndim due to JIT issue

torch/ao/nn/quantized/modules/conv.py

@@ -730,7 +730,7 @@ def __init__(self, in_channels, out_channels, kernel_size, stride=1,
             True, output_padding, groups, bias, padding_mode, **factory_kwargs)
 
     def _get_name(self):
-        return 'QuantizedConvTranpose1d'
+        return 'QuantizedConvTranspose1d'
 
     def set_weight_bias(self, w: torch.Tensor, b: Optional[torch.Tensor]) -> None:
         self._packed_params = torch.ops.quantized.conv_transpose1d_prepack(
@@ -821,7 +821,7 @@ def __init__(self, in_channels, out_channels, kernel_size, stride=1,
             True, output_padding, groups, bias, padding_mode, **factory_kwargs)
 
     def _get_name(self):
-        return 'QuantizedConvTranpose2d'
+        return 'QuantizedConvTranspose2d'
 
     def set_weight_bias(self, w: torch.Tensor, b: Optional[torch.Tensor]) -> None:
         self._packed_params = torch.ops.quantized.conv_transpose2d_prepack(
@@ -914,7 +914,7 @@ def __init__(self, in_channels, out_channels, kernel_size, stride=1,
             True, output_padding, groups, bias, padding_mode, **factory_kwargs)
 
     def _get_name(self):
-        return 'QuantizedConvTranpose3d'
+        return 'QuantizedConvTranspose3d'
 
     def set_weight_bias(self, w: torch.Tensor, b: Optional[torch.Tensor]) -> None:
         self._packed_params = torch.ops.quantized.conv_transpose3d_prepack(