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@@ -13,7 +13,7 @@ compute graph is recorded. The actual computation only happens if an
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:func:`eval` is performed.
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MLX uses lazy evaluation because it has some nice features, some of which we
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describe below.
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describe below.
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Transforming Compute Graphs
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^^^^^^^^^^^^^^^^^^^^^^^^^^^
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@@ -116,7 +116,7 @@ saving functions) will also evaluate the array.
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Calling :func:`array.item` on a scalar array will also evaluate it. In the
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example above, printing the loss (``print(loss)``) or adding the loss scalar to
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a list (``losses.append(loss.item())``) would cause a graph evaluation. If
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a list (``losses.append(loss.item())``) would cause a graph evaluation. If
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these lines are before ``mx.eval(loss, model.parameters())`` then this
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will be a partial evaluation, computing only the forward pass.
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