tf.minimize

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Add operations to minimize loss by updating var_list.
This method simply combines calls compute_gradients() and
apply_gradients(). If you want to process the gradient before applying
them call compute_gradients() and apply_gradients() explicitly instead
of using this function.
Args:
loss: A Tensor containing the value to minimize.
global_step: Optional Variable to increment by one after the
variables have been updated.
var_list: Optional list or tuple of Variable objects to update to
minimize loss. Defaults to the list of variables collected in
the graph under the key GraphKeys.TRAINABLE_VARIABLES.
GATE_NONE, GATE_OP, or GATE_GRAPH.
aggregation_method: Specifies the method used to combine gradient terms.
Valid values are defined in the class AggregationMethod.
the corresponding op.
name: Optional name for the returned operation.
grad_loss: Optional. A Tensor holding the gradient computed for loss.
Returns:
An Operation that updates the variables in var_list. If global_step
was not None, that operation also increments global_step.

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