Fix failing tests & GitHub warnings

fastmachinelearning · Sep 15, 2023 · 2cf919b · 2cf919b
1 parent 5b4488e
commit 2cf919b
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diff --git a/docs/advanced/model_optimization.rst b/docs/advanced/model_optimization.rst
@@ -109,9 +109,11 @@ Finally, optimizing Vivado DSPs is possible, given a hls4ml config:
     # Note the change from ParameterEstimator to VivadoDSPEstimator
     optimized_model = optimize_keras_for_hls4ml(
         baseline_model, model_attributes, VivadoDSPEstimator, scheduler,
-        X_train, y_train, X_val, y_val, batch_size, epochs, optimizer, loss_fn, metric, increasing, rtol
+        X_train, y_train, X_val, y_val, batch_size, epochs,
+        optimizer, loss_fn, metric, increasing, rtol
     )
 
+
 There are two more Vivado "optimizers" - VivadoFFEstimator, aimed at reducing register utilisation and VivadoMultiObjectiveEstimator, aimed at optimising BRAM and DSP utilisation.
 Note, to ensure DSPs are optimized, "unrolled" Dense multiplication must be used before synthesing HLS, by modifying the config:
 .. code-block:: Python

diff --git a/setup.cfg b/setup.cfg
@@ -41,7 +41,7 @@ pytest_randomly.random_seeder =
 
 [options.extras_require]
 optimization =
-    keras-surgeon@https://github.com/fastmachinelearning/keras-surgeon
+    keras-surgeon@git+https://github.com/fastmachinelearning/keras-surgeon.git
     ortools
     packaging
 profiling =