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Examples: Missed some 'epochs' occurrences (#1477)
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docs/demos/pinn_forward/heat.resample.rst

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@@ -110,7 +110,7 @@ We then train the model for 20000 iterations:
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.. code-block:: python
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losshistory, train_state = model.train(epochs=200000, callbacks=[pde_resampler])
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losshistory, train_state = model.train(iterations=200000, callbacks=[pde_resampler])
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After we train the network using Adam, we continue to train the network using L-BFGS to achieve a smaller loss:
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docs/demos/pinn_forward/helmholtz.2d.sound.hard.abc.rst

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@@ -67,7 +67,7 @@ Then, we begin by defining the general parameters for the problem. The PINN will
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.. code-block:: python
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weights = 1
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epochs = 10000
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iterations = 10000
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learning_rate = 1e-3
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num_dense_layers = 3
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num_dense_nodes = 350
@@ -216,7 +216,7 @@ We first train the model for 5000 iterations with Adam optimizer:
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.. code-block:: python
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losshistory, train_state = model.train(epochs=epochs)
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losshistory, train_state = model.train(iterations=iterations)
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Complete code

docs/demos/pinn_inverse/lorenz.inverse.rst

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@@ -124,7 +124,7 @@ We then train the model for 60000 iterations:
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.. code-block:: python
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losshistory, train_state = model.train(epochs=60000, callbacks=[variable])
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losshistory, train_state = model.train(iterations=60000, callbacks=[variable])
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Complete code
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