Add the support for aten::mul operator. (#2905)

src/sdk/pynni/nni/compression/torch/speedup/compress_modules.py

@@ -15,6 +15,7 @@ replace_module = {
     'AdaptiveAvgPool2d': lambda module, mask: no_replace(module, mask),
     'ReLU': lambda module, mask: no_replace(module, mask),
     'ReLU6': lambda module, mask: no_replace(module, mask),
+    'Sigmoid': lambda module, mask: no_replace(module, mask),
     'Linear': lambda module, mask: replace_linear(module, mask),
     'Dropout': lambda module, mask: no_replace(module, mask),
     'Dropout2d': lambda module, mask: no_replace(module, mask),

src/sdk/pynni/nni/compression/torch/speedup/infer_shape.py

@@ -221,12 +221,14 @@ Infer output and weight shape of a module/function from its input shape
 infer_from_inshape = {
     'ReLU': lambda module_masks, mask: relu_inshape(module_masks, mask),
     'ReLU6': lambda module_masks, mask: relu_inshape(module_masks, mask),
+    'Sigmoid': lambda module_masks, mask: relu_inshape(module_masks, mask),
     'aten::relu': lambda module_masks, mask: relu_inshape(module_masks, mask),
     'aten::tanh': lambda module_masks, mask: relu_inshape(module_masks, mask),
     'aten::tanh_': lambda module_masks, mask: relu_inshape(module_masks, mask),
     'aten::hardtanh': lambda module_masks, mask: relu_inshape(module_masks, mask),
     'aten::hardtanh_': lambda module_masks, mask: relu_inshape(module_masks, mask),
     'aten::relu_': lambda module_masks, mask: relu_inshape(module_masks, mask),
+    'aten::sigmoid': lambda module_masks, mask: relu_inshape(module_masks, mask),
     'Conv2d': lambda module_masks, mask: conv2d_inshape(module_masks, mask),
     'MaxPool2d': lambda module_masks, mask: maxpool2d_inshape(module_masks, mask),
     'aten::max_pool2d': lambda module_masks, mask: maxpool2d_inshape(module_masks, mask),
@@ -243,6 +245,10 @@ infer_from_inshape = {
     'BatchNorm2d': lambda module_masks, mask: batchnorm2d_inshape(module_masks, mask),
     'aten::add_': lambda module_masks, mask: add_inshape(module_masks, mask),
     'aten::add': lambda module_mask, mask: add_inshape(module_mask, mask),
+    # mul has the similar behaviour with add, they both request
+    # the input tesors to have the same shape
+    'aten::mul': lambda module_mask, mask: add_inshape(module_mask, mask),
+    'aten::mul_': lambda module_mask, mask: add_inshape(module_mask, mask),
     'aten::cat': lambda module_mask, mask, cat_info, last_visited: cat_inshape(module_mask, mask, cat_info, last_visited),
     'aten::mean': lambda module_masks, mask, shape: mean_inshape(module_masks, mask, shape),
     'Dropout': lambda module_masks, mask: dropout_inshape(module_masks, mask),

src/sdk/pynni/nni/compression/torch/utils/mask_conflict.py

@@ -284,7 +284,7 @@ class ChannelMaskConflict(MaskFix):
                 ori_channels = w_shape[0]
                 for i in channel_remain:
                     mask['weight'][i] = torch.ones(w_shape[1:])
-                    if hasattr(mask, 'bias'):
+                    if 'bias' in mask and mask['bias'] is not None:
                         mask['bias'][i] = 1
             _logger.info(','.join(dset))
             _logger.info('Pruned Filters after fixing conflict:')