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path: "tensorflow.train.GradientDescentOptimizer"
tf_class {
is_instance: "<class \'tensorflow.python.training.gradient_descent.GradientDescentOptimizer\'>"
is_instance: "<class \'tensorflow.python.training.optimizer.Optimizer\'>"
is_instance: "<class \'tensorflow.python.training.checkpointable.base.CheckpointableBase\'>"
is_instance: "<type \'object\'>"
member {
name: "GATE_GRAPH"
mtype: "<type \'int\'>"
}
member {
name: "GATE_NONE"
mtype: "<type \'int\'>"
}
member {
name: "GATE_OP"
mtype: "<type \'int\'>"
}
member_method {
name: "__init__"
argspec: "args=[\'self\', \'learning_rate\', \'use_locking\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'GradientDescent\'], "
}
member_method {
name: "apply_gradients"
argspec: "args=[\'self\', \'grads_and_vars\', \'global_step\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
}
member_method {
name: "compute_gradients"
argspec: "args=[\'self\', \'loss\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'1\', \'None\', \'False\', \'None\'], "
}
member_method {
name: "get_name"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "get_slot"
argspec: "args=[\'self\', \'var\', \'name\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "get_slot_names"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "minimize"
argspec: "args=[\'self\', \'loss\', \'global_step\', \'var_list\', \'gate_gradients\', \'aggregation_method\', \'colocate_gradients_with_ops\', \'name\', \'grad_loss\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'1\', \'None\', \'False\', \'None\', \'None\'], "
}
member_method {
name: "variables"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
}
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