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@ -104,7 +104,7 @@ Contributing & Help
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<a class="edit-page" href="https://github.com/MikeInnes/Flux.jl/tree/d6bc10e3be6f43cec501ff6720cc2386284d0963/docs/src/contributing.md">
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<a class="edit-page" href="https://github.com/MikeInnes/Flux.jl/tree/90616a3c5a98d2f1ea35c7ba046df0ffd8358130/docs/src/contributing.md">
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@ -107,7 +107,7 @@ Logistic Regression
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<a class="edit-page" href="https://github.com/MikeInnes/Flux.jl/tree/d6bc10e3be6f43cec501ff6720cc2386284d0963/docs/src/examples/logreg.md">
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<a class="edit-page" href="https://github.com/MikeInnes/Flux.jl/tree/90616a3c5a98d2f1ea35c7ba046df0ffd8358130/docs/src/examples/logreg.md">
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@ -104,7 +104,7 @@ Home
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<a class="edit-page" href="https://github.com/MikeInnes/Flux.jl/tree/d6bc10e3be6f43cec501ff6720cc2386284d0963/docs/src/index.md">
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<a class="edit-page" href="https://github.com/MikeInnes/Flux.jl/tree/90616a3c5a98d2f1ea35c7ba046df0ffd8358130/docs/src/index.md">
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@ -104,7 +104,7 @@ Internals
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<a class="edit-page" href="https://github.com/MikeInnes/Flux.jl/tree/d6bc10e3be6f43cec501ff6720cc2386284d0963/docs/src/internals.md">
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<a class="edit-page" href="https://github.com/MikeInnes/Flux.jl/tree/90616a3c5a98d2f1ea35c7ba046df0ffd8358130/docs/src/internals.md">
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@ -133,7 +133,7 @@ First Steps
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<a class="edit-page" href="https://github.com/MikeInnes/Flux.jl/tree/d6bc10e3be6f43cec501ff6720cc2386284d0963/docs/src/models/basics.md">
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<a class="edit-page" href="https://github.com/MikeInnes/Flux.jl/tree/90616a3c5a98d2f1ea35c7ba046df0ffd8358130/docs/src/models/basics.md">
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@ -266,7 +266,7 @@ mymodel2(x2) # [0.187935, 0.232237, 0.169824, 0.230589, 0.179414]</code></pre>
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Affine(5, 5), σ,
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Affine(5, 5), softmax)</code></pre>
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<p>
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You now know understand enough to take a look at the
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You now know enough to take a look at the
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<a href="../examples/logreg.html">
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logistic regression
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@ -107,7 +107,7 @@ Debugging
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@ -107,7 +107,7 @@ Recurrence
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@ -53,7 +53,7 @@ var documenterSearchIndex = {"docs": [
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"page": "First Steps",
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"title": "Combining Models",
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"category": "section",
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"text": "... Inflating Graviton Zeppelins ...A more complex model usually involves many basic layers like affine, where we use the output of one layer as the input to the next:mymodel1(x) = softmax(affine2(σ(affine1(x))))\nmymodel1(x1) # [0.187935, 0.232237, 0.169824, 0.230589, 0.179414]This syntax is again a little unwieldy for larger networks, so Flux provides another template of sorts to create the function for us:mymodel2 = Chain(affine1, σ, affine2, softmax)\nmymodel2(x2) # [0.187935, 0.232237, 0.169824, 0.230589, 0.179414]mymodel2 is exactly equivalent to mymodel1 because it simply calls the provided functions in sequence. We don't have to predefine the affine layers and can also write this as:mymodel3 = Chain(\n Affine(5, 5), σ,\n Affine(5, 5), softmax)You now know understand enough to take a look at the logistic regression example, if you haven't already."
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"text": "... Inflating Graviton Zeppelins ...A more complex model usually involves many basic layers like affine, where we use the output of one layer as the input to the next:mymodel1(x) = softmax(affine2(σ(affine1(x))))\nmymodel1(x1) # [0.187935, 0.232237, 0.169824, 0.230589, 0.179414]This syntax is again a little unwieldy for larger networks, so Flux provides another template of sorts to create the function for us:mymodel2 = Chain(affine1, σ, affine2, softmax)\nmymodel2(x2) # [0.187935, 0.232237, 0.169824, 0.230589, 0.179414]mymodel2 is exactly equivalent to mymodel1 because it simply calls the provided functions in sequence. We don't have to predefine the affine layers and can also write this as:mymodel3 = Chain(\n Affine(5, 5), σ,\n Affine(5, 5), softmax)You now know enough to take a look at the logistic regression example, if you haven't already."
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},
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{
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