| /third_party/mindspore/tests/st/ps/multi_full_ps/ |
| D | resnet.py | 34 def _conv1x1(in_channel, out_channel, stride=1): function
88 self.conv1 = _conv1x1(in_channel, channel, stride=1)
94 self.conv3 = _conv1x1(channel, out_channel, stride=1)
106 self.down_sample_layer = nn.SequentialCell([_conv1x1(in_channel, out_channel, stride),
|
| /third_party/mindspore/tests/ut/python/model/ |
| D | resnet.py | 34 def _conv1x1(in_channel, out_channel, stride=1): function
88 self.conv1 = _conv1x1(in_channel, channel, stride=1)
94 self.conv3 = _conv1x1(channel, out_channel, stride=1)
106 self.down_sample_layer = nn.SequentialCell([_conv1x1(in_channel, out_channel, stride),
|
| /third_party/mindspore/tests/st/networks/models/resnet50/src/ |
| D | resnet.py | 34 def _conv1x1(in_channel, out_channel, stride=1): function
88 self.conv1 = _conv1x1(in_channel, channel, stride=1)
94 self.conv3 = _conv1x1(channel, out_channel, stride=1)
106 self.down_sample_layer = nn.SequentialCell([_conv1x1(in_channel, out_channel, stride),
|
| /third_party/mindspore/tests/st/networks/models/resnet50/src_thor/ |
| D | resnet.py | 50 def _conv1x1(in_channel, out_channel, stride=1, use_se=False): function
119 self.conv1 = _conv1x1(in_channel, channel, stride=1, use_se=self.use_se)
128 self.conv3 = _conv1x1(channel, out_channel, stride=1, use_se=self.use_se)
147 self.down_sample_layer = nn.SequentialCell([_conv1x1(in_channel, out_channel,
151 _conv1x1(in_channel, out_channel, 1,
154 … self.down_sample_layer = nn.SequentialCell([_conv1x1(in_channel, out_channel, stride,
|
| /third_party/mindspore/tests/st/auto_parallel/ |
| D | resnet50_expand_loss.py | 51 def _conv1x1(in_channels, out_channels, stride=1, padding=0, pad_mode='same'): function
85 self.down_sample_layer = nn.SequentialCell([_conv1x1(in_channels,
120 self.conv1 = _conv1x1(in_channels, out_chls, stride=1)
124 self.conv3 = _conv1x1(out_chls, out_channels, stride=1)
130 self.conv_down_sample = _conv1x1(in_channels, out_channels,
|
| /third_party/mindspore/tests/ut/python/parallel/ |
| D | test_auto_parallel_resnet_sharding_propagation2.py | 53 def _conv1x1(in_channels, out_channels, stride=1, padding=0, pad_mode='same'): function
83 self.conv1 = _conv1x1(in_channels, out_chls, stride=1)
89 self.conv3 = _conv1x1(out_chls, out_channels, stride=1)
96 self.conv_down_sample = _conv1x1(in_channels, out_channels,
|
| D | test_auto_parallel_resnet_sharding_propagation.py | 54 def _conv1x1(in_channels, out_channels, stride=1, padding=0, pad_mode='same'): function
84 self.conv1 = _conv1x1(in_channels, out_chls, stride=1)
90 self.conv3 = _conv1x1(out_chls, out_channels, stride=1)
97 self.conv_down_sample = _conv1x1(in_channels, out_channels,
|
| D | test_auto_parallel_resnet.py | 53 def _conv1x1(in_channels, out_channels, stride=1, padding=0, pad_mode='same'): function
83 self.conv1 = _conv1x1(in_channels, out_chls, stride=1)
91 self.conv3 = _conv1x1(out_chls, out_channels, stride=1)
99 self.conv_down_sample = _conv1x1(in_channels, out_channels,
|
| /third_party/mindspore/tests/st/quantization/resnet50_quant/ |
| D | resnet_quant_manual.py | 43 def _conv1x1(in_channel, out_channel, stride=1): function
|