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Add model metrics to docstrings (#145)
Co-authored-by: Lukas Geiger <[email protected]>
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larq_zoo/literature/binary_alex_net.py

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@@ -128,6 +128,12 @@ def BinaryAlexNet(
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/plots/binary_alexnet.vg.json
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```
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# ImageNet Metrics
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| Top-1 Accuracy | Top-5 Accuracy | Parameters | Memory |
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| -------------- | -------------- | ---------- | ------- |
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| 36.30 % | 61.53 % | 61 859 192 | 7.49 MB |
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# Arguments
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input_shape: Optional shape tuple, to be specified if you would like to use a model
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with an input image resolution that is not (224, 224, 3).

larq_zoo/literature/birealnet.py

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@@ -134,6 +134,12 @@ def BiRealNet(
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/plots/birealnet.vg.json
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```
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# ImageNet Metrics
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| Top-1 Accuracy | Top-5 Accuracy | Parameters | Memory |
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| -------------- | -------------- | ---------- | ------- |
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| 57.47 % | 79.84 % | 11 699 112 | 4.03 MB |
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# Arguments
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input_shape: Optional shape tuple, to be specified if you would like to use a model
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with an input image resolution that is not (224, 224, 3).

larq_zoo/literature/densenet.py

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@@ -248,6 +248,12 @@ def BinaryDenseNet28(
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/plots/densenet_28.vg.json
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```
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# ImageNet Metrics
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| Top-1 Accuracy | Top-5 Accuracy | Parameters | Memory |
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| -------------- | -------------- | ---------- | ------- |
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| 60.91 % | 82.83 % | 5 150 504 | 4.12 MB |
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# Arguments
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input_shape: Optional shape tuple, to be specified if you would like to use a model
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with an input image resolution that is not (224, 224, 3).
@@ -298,6 +304,12 @@ def BinaryDenseNet37(
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/plots/densenet_37.vg.json
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```
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# ImageNet Metrics
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| Top-1 Accuracy | Top-5 Accuracy | Parameters | Memory |
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| -------------- | -------------- | ---------- | ------- |
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| 62.89 % | 84.19 % | 8 734 120 | 5.25 MB |
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# Arguments
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input_shape: Optional shape tuple, to be specified if you would like to use a model
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with an input image resolution that is not (224, 224, 3).
@@ -348,6 +360,12 @@ def BinaryDenseNet37Dilated(
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/plots/densenet_37_dilated.vg.json
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```
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# ImageNet Metrics
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| Top-1 Accuracy | Top-5 Accuracy | Parameters | Memory |
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| -------------- | -------------- | ---------- | ------- |
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| 64.34 % | 85.15 % | 8 734 120 | 5.25 MB |
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# Arguments
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input_shape: Optional shape tuple, to be specified if you would like to use a model
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with an input image resolution that is not (224, 224, 3).
@@ -398,6 +416,12 @@ def BinaryDenseNet45(
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/plots/densenet_45.vg.json
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```
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# ImageNet Metrics
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| Top-1 Accuracy | Top-5 Accuracy | Parameters | Memory |
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| -------------- | -------------- | ---------- | ------- |
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| 64.59 % | 85.21 % | 13 939 240 | 7.54 MB |
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# Arguments
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input_shape: Optional shape tuple, to be specified if you would like to use a model
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with an input image resolution that is not (224, 224, 3).

larq_zoo/literature/dorefanet.py

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@@ -141,6 +141,12 @@ def DoReFaNet(
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/plots/dorefanet.vg.json
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```
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# ImageNet Metrics
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| Top-1 Accuracy | Top-5 Accuracy | Parameters | Memory |
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| -------------- | -------------- | ---------- | ------- |
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| 53.39 % | 76.50 % | 62 403 912 | 22.84 MB |
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# Arguments
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input_shape: Optional shape tuple, to be specified if you would like to use a model
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with an input image resolution that is not (224, 224, 3).

larq_zoo/literature/resnet_e.py

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@@ -154,6 +154,12 @@ def BinaryResNetE18(
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/plots/resnet_e_18.vg.json
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```
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# ImageNet Metrics
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| Top-1 Accuracy | Top-5 Accuracy | Parameters | Memory |
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| -------------- | -------------- | ---------- | ------- |
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| 58.32 % | 80.79 % | 11 699 368 | 4.03 MB |
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# Arguments
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input_shape: Optional shape tuple, to be specified if you would like to use a model
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with an input image resolution that is not (224, 224, 3).

larq_zoo/literature/xnornet.py

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@@ -148,6 +148,12 @@ def XNORNet(
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/plots/xnornet.vg.json
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```
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# ImageNet Metrics
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| Top-1 Accuracy | Top-5 Accuracy | Parameters | Memory |
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| -------------- | -------------- | ---------- | ------- |
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| 44.96 % | 69.18 % | 62 396 768 | 22.81 MB |
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# Arguments
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input_shape: Optional shape tuple, to be specified if you would like to use a model
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with an input image resolution that is not (224, 224, 3).

larq_zoo/sota/quicknet.py

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@@ -305,6 +305,12 @@ def QuickNet(
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quicknet-v0.2.0/quicknet.json
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```
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# ImageNet Metrics
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| Top-1 Accuracy | Top-5 Accuracy | Parameters | Memory |
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| -------------- | -------------- | ---------- | ------- |
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| 58.6 % | 81.0 % | 10 518 528 | 3.21 MB |
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# Arguments
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input_shape: Optional shape tuple, to be specified if you would like to use a model
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with an input image resolution that is not (224, 224, 3).
@@ -348,6 +354,12 @@ def QuickNetLarge(
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quicknet_large-v0.2.0/quicknet_large.json
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```
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# ImageNet Metrics
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| Top-1 Accuracy | Top-5 Accuracy | Parameters | Memory |
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| -------------- | -------------- | ---------- | ------- |
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| 62.7 % | 84.0 % | 11 837 696 | 4.56 MB |
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# Arguments
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input_shape: Optional shape tuple, to be specified if you would like to use a model
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with an input image resolution that is not (224, 224, 3).
@@ -391,6 +403,12 @@ def QuickNetXL(
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quicknet_xl-v0.1.0/quicknet_xl.json
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```
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# ImageNet Metrics
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| Top-1 Accuracy | Top-5 Accuracy | Parameters | Memory |
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| -------------- | -------------- | ---------- | ------- |
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| 67.0 % | 87.3 % | 22 058 368 | 6.22 MB |
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# Arguments
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input_shape: Optional shape tuple, to be specified if you would like to use a model
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with an input image resolution that is not (224, 224, 3).

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