410 lines
39 KiB
Plaintext
410 lines
39 KiB
Plaintext
Model: "mono-failure"
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__________________________________________________________________________________________________
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Layer (type) Output Shape Param # Connected to
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==================================================================================================
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input_1 (InputLayer) [(None, 105, 174, 8 0 []
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)]
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convnext0 (Functional) (None, 512) 11787584 ['input_1[0][0]']
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cns.stage.bottleneck.dense2 (D (None, 512) 262656 ['convnext0[0][0]']
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ense)
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cns.stage.bottleneck.gelu2 (Ac (None, 512) 0 ['cns.stage.bottleneck.dense2[0][
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tivation) 0]']
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cns.stage.bottleneck.norm2 (La (None, 512) 1024 ['cns.stage.bottleneck.gelu2[0][0
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yerNormalization) ]']
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cns.stage.bottleneck.dropout ( (None, 512) 0 ['cns.stage.bottleneck.norm2[0][0
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Dropout) ]']
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layer_stack2_image (LayerStack (None, 4, 4, 512) 0 ['cns.stage.bottleneck.dropout[0]
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2Image) [0]']
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cns.stage.begin.dense2 (Dense) (None, 4, 4, 512) 262656 ['layer_stack2_image[0][0]']
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cns.stage_begin.relu2 (Activat (None, 4, 4, 512) 0 ['cns.stage.begin.dense2[0][0]']
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ion)
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cns.stage_begin.norm2 (LayerNo (None, 4, 4, 512) 1024 ['cns.stage_begin.relu2[0][0]']
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rmalization)
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cns.stage0.end.convtp (Conv2DT (None, 8, 8, 528) 1081872 ['cns.stage_begin.norm2[0][0]']
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ranspose)
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cns.stage0.end.norm (LayerNorm (None, 8, 8, 528) 1056 ['cns.stage0.end.convtp[0][0]']
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alization)
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cns.stage0.block.0.dwconv (Dep (None, 8, 8, 528) 26400 ['cns.stage0.end.norm[0][0]']
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thwiseConv2D)
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cns.stage0.block.0.norm (Layer (None, 8, 8, 528) 1056 ['cns.stage0.block.0.dwconv[0][0]
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Normalization) ']
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cns.stage0.block.0.pwconv1 (De (None, 8, 8, 2112) 1117248 ['cns.stage0.block.0.norm[0][0]']
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nse)
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cns.stage0.block.0.act (Activa (None, 8, 8, 2112) 0 ['cns.stage0.block.0.pwconv1[0][0
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tion) ]']
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cns.stage0.block.0.pwconv2 (De (None, 8, 8, 528) 1115664 ['cns.stage0.block.0.act[0][0]']
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nse)
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cns.stage0.block.0.gamma (Laye (None, 8, 8, 528) 0 ['cns.stage0.block.0.pwconv2[0][0
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rConvNeXtGamma) ]']
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cns.stage0.block.0.drop_path ( (None, 8, 8, 528) 0 ['cns.stage0.end.norm[0][0]',
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StochasticDepth) 'cns.stage0.block.0.gamma[0][0]'
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]
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cns.stage0.block.1.dwconv (Dep (None, 8, 8, 528) 26400 ['cns.stage0.block.0.drop_path[0]
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thwiseConv2D) [0]']
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cns.stage0.block.1.norm (Layer (None, 8, 8, 528) 1056 ['cns.stage0.block.1.dwconv[0][0]
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Normalization) ']
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cns.stage0.block.1.pwconv1 (De (None, 8, 8, 2112) 1117248 ['cns.stage0.block.1.norm[0][0]']
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nse)
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cns.stage0.block.1.act (Activa (None, 8, 8, 2112) 0 ['cns.stage0.block.1.pwconv1[0][0
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tion) ]']
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cns.stage0.block.1.pwconv2 (De (None, 8, 8, 528) 1115664 ['cns.stage0.block.1.act[0][0]']
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nse)
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cns.stage0.block.1.gamma (Laye (None, 8, 8, 528) 0 ['cns.stage0.block.1.pwconv2[0][0
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rConvNeXtGamma) ]']
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cns.stage0.block.1.drop_path ( (None, 8, 8, 528) 0 ['cns.stage0.block.0.drop_path[0]
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StochasticDepth) [0]',
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'cns.stage0.block.1.gamma[0][0]'
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]
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cns.stage0.block.2.dwconv (Dep (None, 8, 8, 528) 26400 ['cns.stage0.block.1.drop_path[0]
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thwiseConv2D) [0]']
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cns.stage0.block.2.norm (Layer (None, 8, 8, 528) 1056 ['cns.stage0.block.2.dwconv[0][0]
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Normalization) ']
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cns.stage0.block.2.pwconv1 (De (None, 8, 8, 2112) 1117248 ['cns.stage0.block.2.norm[0][0]']
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nse)
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cns.stage0.block.2.act (Activa (None, 8, 8, 2112) 0 ['cns.stage0.block.2.pwconv1[0][0
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tion) ]']
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cns.stage0.block.2.pwconv2 (De (None, 8, 8, 528) 1115664 ['cns.stage0.block.2.act[0][0]']
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nse)
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cns.stage0.block.2.gamma (Laye (None, 8, 8, 528) 0 ['cns.stage0.block.2.pwconv2[0][0
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rConvNeXtGamma) ]']
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cns.stage0.block.2.drop_path ( (None, 8, 8, 528) 0 ['cns.stage0.block.1.drop_path[0]
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StochasticDepth) [0]',
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'cns.stage0.block.2.gamma[0][0]'
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]
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cns.stage1.end.convtp (Conv2DT (None, 16, 16, 264) 557832 ['cns.stage0.block.2.drop_path[0]
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ranspose) [0]']
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cns.stage1.end.norm (LayerNorm (None, 16, 16, 264) 528 ['cns.stage1.end.convtp[0][0]']
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alization)
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cns.stage1.block.0.dwconv (Dep (None, 16, 16, 264) 13200 ['cns.stage1.end.norm[0][0]']
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thwiseConv2D)
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cns.stage1.block.0.norm (Layer (None, 16, 16, 264) 528 ['cns.stage1.block.0.dwconv[0][0]
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Normalization) ']
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cns.stage1.block.0.pwconv1 (De (None, 16, 16, 1056 279840 ['cns.stage1.block.0.norm[0][0]']
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nse) )
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cns.stage1.block.0.act (Activa (None, 16, 16, 1056 0 ['cns.stage1.block.0.pwconv1[0][0
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tion) ) ]']
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cns.stage1.block.0.pwconv2 (De (None, 16, 16, 264) 279048 ['cns.stage1.block.0.act[0][0]']
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nse)
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cns.stage1.block.0.gamma (Laye (None, 16, 16, 264) 0 ['cns.stage1.block.0.pwconv2[0][0
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rConvNeXtGamma) ]']
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cns.stage1.block.0.drop_path ( (None, 16, 16, 264) 0 ['cns.stage1.end.norm[0][0]',
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StochasticDepth) 'cns.stage1.block.0.gamma[0][0]'
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]
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cns.stage1.block.1.dwconv (Dep (None, 16, 16, 264) 13200 ['cns.stage1.block.0.drop_path[0]
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thwiseConv2D) [0]']
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cns.stage1.block.1.norm (Layer (None, 16, 16, 264) 528 ['cns.stage1.block.1.dwconv[0][0]
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Normalization) ']
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cns.stage1.block.1.pwconv1 (De (None, 16, 16, 1056 279840 ['cns.stage1.block.1.norm[0][0]']
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nse) )
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cns.stage1.block.1.act (Activa (None, 16, 16, 1056 0 ['cns.stage1.block.1.pwconv1[0][0
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tion) ) ]']
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cns.stage1.block.1.pwconv2 (De (None, 16, 16, 264) 279048 ['cns.stage1.block.1.act[0][0]']
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nse)
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cns.stage1.block.1.gamma (Laye (None, 16, 16, 264) 0 ['cns.stage1.block.1.pwconv2[0][0
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rConvNeXtGamma) ]']
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cns.stage1.block.1.drop_path ( (None, 16, 16, 264) 0 ['cns.stage1.block.0.drop_path[0]
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StochasticDepth) [0]',
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'cns.stage1.block.1.gamma[0][0]'
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]
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cns.stage1.block.2.dwconv (Dep (None, 16, 16, 264) 13200 ['cns.stage1.block.1.drop_path[0]
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thwiseConv2D) [0]']
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cns.stage1.block.2.norm (Layer (None, 16, 16, 264) 528 ['cns.stage1.block.2.dwconv[0][0]
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Normalization) ']
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cns.stage1.block.2.pwconv1 (De (None, 16, 16, 1056 279840 ['cns.stage1.block.2.norm[0][0]']
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nse) )
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cns.stage1.block.2.act (Activa (None, 16, 16, 1056 0 ['cns.stage1.block.2.pwconv1[0][0
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tion) ) ]']
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cns.stage1.block.2.pwconv2 (De (None, 16, 16, 264) 279048 ['cns.stage1.block.2.act[0][0]']
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nse)
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cns.stage1.block.2.gamma (Laye (None, 16, 16, 264) 0 ['cns.stage1.block.2.pwconv2[0][0
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rConvNeXtGamma) ]']
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cns.stage1.block.2.drop_path ( (None, 16, 16, 264) 0 ['cns.stage1.block.1.drop_path[0]
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StochasticDepth) [0]',
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'cns.stage1.block.2.gamma[0][0]'
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]
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cns.stage1.block.3.dwconv (Dep (None, 16, 16, 264) 13200 ['cns.stage1.block.2.drop_path[0]
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thwiseConv2D) [0]']
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cns.stage1.block.3.norm (Layer (None, 16, 16, 264) 528 ['cns.stage1.block.3.dwconv[0][0]
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Normalization) ']
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cns.stage1.block.3.pwconv1 (De (None, 16, 16, 1056 279840 ['cns.stage1.block.3.norm[0][0]']
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nse) )
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cns.stage1.block.3.act (Activa (None, 16, 16, 1056 0 ['cns.stage1.block.3.pwconv1[0][0
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tion) ) ]']
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cns.stage1.block.3.pwconv2 (De (None, 16, 16, 264) 279048 ['cns.stage1.block.3.act[0][0]']
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nse)
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cns.stage1.block.3.gamma (Laye (None, 16, 16, 264) 0 ['cns.stage1.block.3.pwconv2[0][0
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rConvNeXtGamma) ]']
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cns.stage1.block.3.drop_path ( (None, 16, 16, 264) 0 ['cns.stage1.block.2.drop_path[0]
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StochasticDepth) [0]',
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'cns.stage1.block.3.gamma[0][0]'
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]
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cns.stage1.block.4.dwconv (Dep (None, 16, 16, 264) 13200 ['cns.stage1.block.3.drop_path[0]
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thwiseConv2D) [0]']
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cns.stage1.block.4.norm (Layer (None, 16, 16, 264) 528 ['cns.stage1.block.4.dwconv[0][0]
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Normalization) ']
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cns.stage1.block.4.pwconv1 (De (None, 16, 16, 1056 279840 ['cns.stage1.block.4.norm[0][0]']
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nse) )
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cns.stage1.block.4.act (Activa (None, 16, 16, 1056 0 ['cns.stage1.block.4.pwconv1[0][0
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tion) ) ]']
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cns.stage1.block.4.pwconv2 (De (None, 16, 16, 264) 279048 ['cns.stage1.block.4.act[0][0]']
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nse)
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cns.stage1.block.4.gamma (Laye (None, 16, 16, 264) 0 ['cns.stage1.block.4.pwconv2[0][0
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rConvNeXtGamma) ]']
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cns.stage1.block.4.drop_path ( (None, 16, 16, 264) 0 ['cns.stage1.block.3.drop_path[0]
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StochasticDepth) [0]',
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'cns.stage1.block.4.gamma[0][0]'
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]
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cns.stage1.block.5.dwconv (Dep (None, 16, 16, 264) 13200 ['cns.stage1.block.4.drop_path[0]
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thwiseConv2D) [0]']
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cns.stage1.block.5.norm (Layer (None, 16, 16, 264) 528 ['cns.stage1.block.5.dwconv[0][0]
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Normalization) ']
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cns.stage1.block.5.pwconv1 (De (None, 16, 16, 1056 279840 ['cns.stage1.block.5.norm[0][0]']
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nse) )
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cns.stage1.block.5.act (Activa (None, 16, 16, 1056 0 ['cns.stage1.block.5.pwconv1[0][0
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tion) ) ]']
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cns.stage1.block.5.pwconv2 (De (None, 16, 16, 264) 279048 ['cns.stage1.block.5.act[0][0]']
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nse)
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cns.stage1.block.5.gamma (Laye (None, 16, 16, 264) 0 ['cns.stage1.block.5.pwconv2[0][0
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rConvNeXtGamma) ]']
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cns.stage1.block.5.drop_path ( (None, 16, 16, 264) 0 ['cns.stage1.block.4.drop_path[0]
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StochasticDepth) [0]',
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'cns.stage1.block.5.gamma[0][0]'
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]
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cns.stage2.end.convtp (Conv2DT (None, 32, 32, 132) 139524 ['cns.stage1.block.5.drop_path[0]
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ranspose) [0]']
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cns.stage2.end.norm (LayerNorm (None, 32, 32, 132) 264 ['cns.stage2.end.convtp[0][0]']
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alization)
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cns.stage2.block.0.dwconv (Dep (None, 32, 32, 132) 6600 ['cns.stage2.end.norm[0][0]']
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thwiseConv2D)
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cns.stage2.block.0.norm (Layer (None, 32, 32, 132) 264 ['cns.stage2.block.0.dwconv[0][0]
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Normalization) ']
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cns.stage2.block.0.pwconv1 (De (None, 32, 32, 528) 70224 ['cns.stage2.block.0.norm[0][0]']
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nse)
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cns.stage2.block.0.act (Activa (None, 32, 32, 528) 0 ['cns.stage2.block.0.pwconv1[0][0
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tion) ]']
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cns.stage2.block.0.pwconv2 (De (None, 32, 32, 132) 69828 ['cns.stage2.block.0.act[0][0]']
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nse)
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cns.stage2.block.0.gamma (Laye (None, 32, 32, 132) 0 ['cns.stage2.block.0.pwconv2[0][0
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rConvNeXtGamma) ]']
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cns.stage2.block.0.drop_path ( (None, 32, 32, 132) 0 ['cns.stage2.end.norm[0][0]',
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StochasticDepth) 'cns.stage2.block.0.gamma[0][0]'
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]
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cns.stage2.block.1.dwconv (Dep (None, 32, 32, 132) 6600 ['cns.stage2.block.0.drop_path[0]
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thwiseConv2D) [0]']
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cns.stage2.block.1.norm (Layer (None, 32, 32, 132) 264 ['cns.stage2.block.1.dwconv[0][0]
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Normalization) ']
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cns.stage2.block.1.pwconv1 (De (None, 32, 32, 528) 70224 ['cns.stage2.block.1.norm[0][0]']
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nse)
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cns.stage2.block.1.act (Activa (None, 32, 32, 528) 0 ['cns.stage2.block.1.pwconv1[0][0
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tion) ]']
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cns.stage2.block.1.pwconv2 (De (None, 32, 32, 132) 69828 ['cns.stage2.block.1.act[0][0]']
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nse)
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cns.stage2.block.1.gamma (Laye (None, 32, 32, 132) 0 ['cns.stage2.block.1.pwconv2[0][0
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rConvNeXtGamma) ]']
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cns.stage2.block.1.drop_path ( (None, 32, 32, 132) 0 ['cns.stage2.block.0.drop_path[0]
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StochasticDepth) [0]',
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'cns.stage2.block.1.gamma[0][0]'
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]
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cns.stage2.block.2.dwconv (Dep (None, 32, 32, 132) 6600 ['cns.stage2.block.1.drop_path[0]
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thwiseConv2D) [0]']
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cns.stage2.block.2.norm (Layer (None, 32, 32, 132) 264 ['cns.stage2.block.2.dwconv[0][0]
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Normalization) ']
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cns.stage2.block.2.pwconv1 (De (None, 32, 32, 528) 70224 ['cns.stage2.block.2.norm[0][0]']
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nse)
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cns.stage2.block.2.act (Activa (None, 32, 32, 528) 0 ['cns.stage2.block.2.pwconv1[0][0
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tion) ]']
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cns.stage2.block.2.pwconv2 (De (None, 32, 32, 132) 69828 ['cns.stage2.block.2.act[0][0]']
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nse)
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cns.stage2.block.2.gamma (Laye (None, 32, 32, 132) 0 ['cns.stage2.block.2.pwconv2[0][0
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rConvNeXtGamma) ]']
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cns.stage2.block.2.drop_path ( (None, 32, 32, 132) 0 ['cns.stage2.block.1.drop_path[0]
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StochasticDepth) [0]',
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'cns.stage2.block.2.gamma[0][0]'
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]
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cns.stage3.end.convtp (Conv2DT (None, 64, 64, 66) 34914 ['cns.stage2.block.2.drop_path[0]
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ranspose) [0]']
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cns.stage3.end.norm (LayerNorm (None, 64, 64, 66) 132 ['cns.stage3.end.convtp[0][0]']
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alization)
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cns.stage3.block.0.dwconv (Dep (None, 64, 64, 66) 3300 ['cns.stage3.end.norm[0][0]']
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thwiseConv2D)
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cns.stage3.block.0.norm (Layer (None, 64, 64, 66) 132 ['cns.stage3.block.0.dwconv[0][0]
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Normalization) ']
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cns.stage3.block.0.pwconv1 (De (None, 64, 64, 264) 17688 ['cns.stage3.block.0.norm[0][0]']
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nse)
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cns.stage3.block.0.act (Activa (None, 64, 64, 264) 0 ['cns.stage3.block.0.pwconv1[0][0
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tion) ]']
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cns.stage3.block.0.pwconv2 (De (None, 64, 64, 66) 17490 ['cns.stage3.block.0.act[0][0]']
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nse)
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cns.stage3.block.0.gamma (Laye (None, 64, 64, 66) 0 ['cns.stage3.block.0.pwconv2[0][0
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rConvNeXtGamma) ]']
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cns.stage3.block.0.drop_path ( (None, 64, 64, 66) 0 ['cns.stage3.end.norm[0][0]',
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StochasticDepth) 'cns.stage3.block.0.gamma[0][0]'
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]
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cns.stage3.block.1.dwconv (Dep (None, 64, 64, 66) 3300 ['cns.stage3.block.0.drop_path[0]
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thwiseConv2D) [0]']
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cns.stage3.block.1.norm (Layer (None, 64, 64, 66) 132 ['cns.stage3.block.1.dwconv[0][0]
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Normalization) ']
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cns.stage3.block.1.pwconv1 (De (None, 64, 64, 264) 17688 ['cns.stage3.block.1.norm[0][0]']
|
|
nse)
|
|
|
|
cns.stage3.block.1.act (Activa (None, 64, 64, 264) 0 ['cns.stage3.block.1.pwconv1[0][0
|
|
tion) ]']
|
|
|
|
cns.stage3.block.1.pwconv2 (De (None, 64, 64, 66) 17490 ['cns.stage3.block.1.act[0][0]']
|
|
nse)
|
|
|
|
cns.stage3.block.1.gamma (Laye (None, 64, 64, 66) 0 ['cns.stage3.block.1.pwconv2[0][0
|
|
rConvNeXtGamma) ]']
|
|
|
|
cns.stage3.block.1.drop_path ( (None, 64, 64, 66) 0 ['cns.stage3.block.0.drop_path[0]
|
|
StochasticDepth) [0]',
|
|
'cns.stage3.block.1.gamma[0][0]'
|
|
]
|
|
|
|
cns.stage3.block.2.dwconv (Dep (None, 64, 64, 66) 3300 ['cns.stage3.block.1.drop_path[0]
|
|
thwiseConv2D) [0]']
|
|
|
|
cns.stage3.block.2.norm (Layer (None, 64, 64, 66) 132 ['cns.stage3.block.2.dwconv[0][0]
|
|
Normalization) ']
|
|
|
|
cns.stage3.block.2.pwconv1 (De (None, 64, 64, 264) 17688 ['cns.stage3.block.2.norm[0][0]']
|
|
nse)
|
|
|
|
cns.stage3.block.2.act (Activa (None, 64, 64, 264) 0 ['cns.stage3.block.2.pwconv1[0][0
|
|
tion) ]']
|
|
|
|
cns.stage3.block.2.pwconv2 (De (None, 64, 64, 66) 17490 ['cns.stage3.block.2.act[0][0]']
|
|
nse)
|
|
|
|
cns.stage3.block.2.gamma (Laye (None, 64, 64, 66) 0 ['cns.stage3.block.2.pwconv2[0][0
|
|
rConvNeXtGamma) ]']
|
|
|
|
cns.stage3.block.2.drop_path ( (None, 64, 64, 66) 0 ['cns.stage3.block.1.drop_path[0]
|
|
StochasticDepth) [0]',
|
|
'cns.stage3.block.2.gamma[0][0]'
|
|
]
|
|
|
|
dense (Dense) (None, 64, 64, 32) 2144 ['cns.stage3.block.2.drop_path[0]
|
|
[0]']
|
|
|
|
conv2d (Conv2D) (None, 64, 64, 1) 33 ['dense[0][0]']
|
|
|
|
reshape (Reshape) (None, 64, 64) 0 ['conv2d[0][0]']
|
|
|
|
==================================================================================================
|
|
Total params: 24,906,621
|
|
Trainable params: 24,906,621
|
|
Non-trainable params: 0
|
|
__________________________________________________________________________________________________
|