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path: "tensorflow.nn.rnn_cell.DropoutWrapper"
tf_class {
is_instance: "<class \'tensorflow.python.ops.rnn_cell_impl.DropoutWrapper\'>"
is_instance: "<class \'tensorflow.python.ops.rnn_cell_impl.RNNCell\'>"
is_instance: "<class \'tensorflow.python.layers.base.Layer\'>"
is_instance: "<type \'object\'>"
member {
name: "graph"
mtype: "<type \'property\'>"
}
member {
name: "losses"
mtype: "<type \'property\'>"
}
member {
name: "non_trainable_variables"
mtype: "<type \'property\'>"
}
member {
name: "non_trainable_weights"
mtype: "<type \'property\'>"
}
member {
name: "output_size"
mtype: "<type \'property\'>"
}
member {
name: "scope_name"
mtype: "<type \'property\'>"
}
member {
name: "state_size"
mtype: "<type \'property\'>"
}
member {
name: "trainable_variables"
mtype: "<type \'property\'>"
}
member {
name: "trainable_weights"
mtype: "<type \'property\'>"
}
member {
name: "updates"
mtype: "<type \'property\'>"
}
member {
name: "variables"
mtype: "<type \'property\'>"
}
member {
name: "weights"
mtype: "<type \'property\'>"
}
member_method {
name: "__init__"
argspec: "args=[\'self\', \'cell\', \'input_keep_prob\', \'output_keep_prob\', \'state_keep_prob\', \'variational_recurrent\', \'input_size\', \'dtype\', \'seed\'], varargs=None, keywords=None, defaults=[\'1.0\', \'1.0\', \'1.0\', \'False\', \'None\', \'None\', \'None\'], "
}
member_method {
name: "add_loss"
argspec: "args=[\'self\', \'losses\', \'inputs\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "add_update"
argspec: "args=[\'self\', \'updates\', \'inputs\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "add_variable"
argspec: "args=[\'self\', \'name\', \'shape\', \'dtype\', \'initializer\', \'regularizer\', \'trainable\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'True\'], "
}
member_method {
name: "apply"
argspec: "args=[\'self\', \'inputs\'], varargs=args, keywords=kwargs, defaults=None"
}
member_method {
name: "build"
argspec: "args=[\'self\', \'_\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "call"
argspec: "args=[\'self\', \'inputs\'], varargs=None, keywords=kwargs, defaults=None"
}
member_method {
name: "get_losses_for"
argspec: "args=[\'self\', \'inputs\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "get_updates_for"
argspec: "args=[\'self\', \'inputs\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "zero_state"
argspec: "args=[\'self\', \'batch_size\', \'dtype\'], varargs=None, keywords=None, defaults=None"
}
}
|
