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hub / github.com/alibaba/nann / minimize

Method minimize

tensorflow/tensorflow/python/training/optimizer.py:355–413  ·  view source on GitHub ↗

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 fun

(self, loss, global_step=None, var_list=None,
               gate_gradients=GATE_OP, aggregation_method=None,
               colocate_gradients_with_ops=False, name=None,
               grad_loss=None)

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Callers 15

step_fnFunction · 0.45
mainFunction · 0.45
_GetMetaGraphMethod · 0.45
_annotated_graphMethod · 0.45
testSmallNetworkCostMethod · 0.45
bodyMethod · 0.45
_simple_metagraphFunction · 0.45
_trainMethod · 0.45
_ModelFnMethod · 0.45
BuildFullModelFunction · 0.45
_simple_modelMethod · 0.45

Calls 2

compute_gradientsMethod · 0.95
apply_gradientsMethod · 0.95

Tested by 15

_GetMetaGraphMethod · 0.36
_annotated_graphMethod · 0.36
testSmallNetworkCostMethod · 0.36
bodyMethod · 0.36
_simple_metagraphFunction · 0.36
_trainMethod · 0.36
_ModelFnMethod · 0.36
BuildFullModelFunction · 0.36
_simple_modelMethod · 0.36