diff --git a/configs/EfficientNet/EfficientNetB0.yaml b/configs/EfficientNet/EfficientNetB0.yaml index 01932d43a591f300d0aa7e21784c41ef94479572..bc64e70d333eef31c7b3c4248a24239cb5dec683 100644 --- a/configs/EfficientNet/EfficientNetB0.yaml +++ b/configs/EfficientNet/EfficientNetB0.yaml @@ -2,7 +2,6 @@ mode: 'train' ARCHITECTURE: name: "EfficientNetB0" params: - is_test: False padding_type : "SAME" override_params: drop_connect_rate: 0.1 diff --git a/ppcls/modeling/architectures/efficientnet.py b/ppcls/modeling/architectures/efficientnet.py index eee1a76f97c6a81434316c46371c610014d1c27b..8b3c63df73cbd4cd0cbe3763d04863500e9bb5c3 100644 --- a/ppcls/modeling/architectures/efficientnet.py +++ b/ppcls/modeling/architectures/efficientnet.py @@ -518,7 +518,6 @@ class MbConvBlock(nn.Layer): use_se, name=None, drop_connect_rate=None, - is_test=False, model_name=None, cur_stage=None): super(MbConvBlock, self).__init__() @@ -530,7 +529,6 @@ class MbConvBlock(nn.Layer): self.id_skip = block_args.id_skip self.expand_ratio = block_args.expand_ratio self.drop_connect_rate = drop_connect_rate - self.is_test = is_test if self.expand_ratio != 1: self._ecn = ExpandConvNorm( @@ -583,7 +581,7 @@ class MbConvBlock(nn.Layer): self.block_args.stride == 1 and \ self.block_args.input_filters == self.block_args.output_filters: if self.drop_connect_rate: - x = _drop_connect(x, self.drop_connect_rate, self.is_test) + x = _drop_connect(x, self.drop_connect_rate, not self.training) x = paddle.elementwise_add(x, inputs) return x @@ -623,7 +621,6 @@ class ExtractFeatures(nn.Layer): _global_params, padding_type, use_se, - is_test, model_name=None): super(ExtractFeatures, self).__init__() @@ -661,7 +658,7 @@ class ExtractFeatures(nn.Layer): num_repeat=round_repeats(block_args.num_repeat, _global_params)) - drop_connect_rate = self._global_params.drop_connect_rate if not is_test else 0 + drop_connect_rate = self._global_params.drop_connect_rate if drop_connect_rate: drop_connect_rate *= float(idx) / block_size @@ -682,7 +679,7 @@ class ExtractFeatures(nn.Layer): block_args = block_args._replace( input_filters=block_args.output_filters, stride=1) for _ in range(block_args.num_repeat - 1): - drop_connect_rate = self._global_params.drop_connect_rate if not is_test else 0 + drop_connect_rate = self._global_params.drop_connect_rate if drop_connect_rate: drop_connect_rate *= float(idx) / block_size _mc_block = self.add_sublayer( @@ -711,7 +708,6 @@ class ExtractFeatures(nn.Layer): class EfficientNet(nn.Layer): def __init__(self, name="b0", - is_test=True, padding_type="SAME", override_params=None, use_se=True, @@ -724,7 +720,6 @@ class EfficientNet(nn.Layer): model_name, override_params) self.padding_type = padding_type self.use_se = use_se - self.is_test = is_test self._ef = ExtractFeatures( 3, @@ -732,7 +727,6 @@ class EfficientNet(nn.Layer): self._global_params, self.padding_type, self.use_se, - self.is_test, model_name=self.name) output_channels = round_filters(1280, self._global_params) @@ -785,14 +779,12 @@ class EfficientNet(nn.Layer): return x -def EfficientNetB0_small(is_test=True, - padding_type='DYNAMIC', +def EfficientNetB0_small(padding_type='DYNAMIC', override_params=None, use_se=False, **args): model = EfficientNet( name='b0', - is_test=is_test, padding_type=padding_type, override_params=override_params, use_se=use_se, @@ -800,14 +792,12 @@ def EfficientNetB0_small(is_test=True, return model -def EfficientNetB0(is_test=False, - padding_type='SAME', +def EfficientNetB0(padding_type='SAME', override_params=None, use_se=True, **args): model = EfficientNet( name='b0', - is_test=is_test, padding_type=padding_type, override_params=override_params, use_se=use_se, @@ -815,14 +805,12 @@ def EfficientNetB0(is_test=False, return model -def EfficientNetB1(is_test=False, - padding_type='SAME', +def EfficientNetB1(padding_type='SAME', override_params=None, use_se=True, **args): model = EfficientNet( name='b1', - is_test=is_test, padding_type=padding_type, override_params=override_params, use_se=use_se, @@ -830,14 +818,12 @@ def EfficientNetB1(is_test=False, return model -def EfficientNetB2(is_test=False, - padding_type='SAME', +def EfficientNetB2(padding_type='SAME', override_params=None, use_se=True, **args): model = EfficientNet( name='b2', - is_test=is_test, padding_type=padding_type, override_params=override_params, use_se=use_se, @@ -845,14 +831,12 @@ def EfficientNetB2(is_test=False, return model -def EfficientNetB3(is_test=False, - padding_type='SAME', +def EfficientNetB3(padding_type='SAME', override_params=None, use_se=True, **args): model = EfficientNet( name='b3', - is_test=is_test, padding_type=padding_type, override_params=override_params, use_se=use_se, @@ -860,14 +844,12 @@ def EfficientNetB3(is_test=False, return model -def EfficientNetB4(is_test=False, - padding_type='SAME', +def EfficientNetB4(padding_type='SAME', override_params=None, use_se=True, **args): model = EfficientNet( name='b4', - is_test=is_test, padding_type=padding_type, override_params=override_params, use_se=use_se, @@ -875,14 +857,12 @@ def EfficientNetB4(is_test=False, return model -def EfficientNetB5(is_test=False, - padding_type='SAME', +def EfficientNetB5(padding_type='SAME', override_params=None, use_se=True, **args): model = EfficientNet( name='b5', - is_test=is_test, padding_type=padding_type, override_params=override_params, use_se=use_se, @@ -890,14 +870,12 @@ def EfficientNetB5(is_test=False, return model -def EfficientNetB6(is_test=False, - padding_type='SAME', +def EfficientNetB6(padding_type='SAME', override_params=None, use_se=True, **args): model = EfficientNet( name='b6', - is_test=is_test, padding_type=padding_type, override_params=override_params, use_se=use_se, @@ -905,14 +883,12 @@ def EfficientNetB6(is_test=False, return model -def EfficientNetB7(is_test=False, - padding_type='SAME', +def EfficientNetB7(padding_type='SAME', override_params=None, use_se=True, **args): model = EfficientNet( name='b7', - is_test=is_test, padding_type=padding_type, override_params=override_params, use_se=use_se,