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|
path: "tensorflow.nn.rnn_cell.LSTMCell"
tf_class {
is_instance: "<class \'tensorflow.python.ops.rnn_cell_impl.LSTMCell\'>"
is_instance: "<class \'tensorflow.python.ops.rnn_cell_impl.LayerRNNCell\'>"
is_instance: "<class \'tensorflow.python.ops.rnn_cell_impl.RNNCell\'>"
is_instance: "<class \'tensorflow.python.layers.base.Layer\'>"
is_instance: "<class \'tensorflow.python.keras.engine.base_layer.Layer\'>"
is_instance: "<class \'tensorflow.python.training.checkpointable.base.CheckpointableBase\'>"
is_instance: "<type \'object\'>"
member {
name: "activity_regularizer"
mtype: "<type \'property\'>"
}
member {
name: "dtype"
mtype: "<type \'property\'>"
}
member {
name: "graph"
mtype: "<type \'property\'>"
}
member {
name: "inbound_nodes"
mtype: "<type \'property\'>"
}
member {
name: "input"
mtype: "<type \'property\'>"
}
member {
name: "input_mask"
mtype: "<type \'property\'>"
}
member {
name: "input_shape"
mtype: "<type \'property\'>"
}
member {
name: "losses"
mtype: "<type \'property\'>"
}
member {
name: "name"
mtype: "<type \'property\'>"
}
member {
name: "non_trainable_variables"
mtype: "<type \'property\'>"
}
member {
name: "non_trainable_weights"
mtype: "<type \'property\'>"
}
member {
name: "outbound_nodes"
mtype: "<type \'property\'>"
}
member {
name: "output"
mtype: "<type \'property\'>"
}
member {
name: "output_mask"
mtype: "<type \'property\'>"
}
member {
name: "output_shape"
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\', \'num_units\', \'use_peepholes\', \'cell_clip\', \'initializer\', \'num_proj\', \'proj_clip\', \'num_unit_shards\', \'num_proj_shards\', \'forget_bias\', \'state_is_tuple\', \'activation\', \'reuse\', \'name\', \'dtype\'], varargs=None, keywords=None, defaults=[\'False\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'1.0\', \'True\', \'None\', \'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\'], varargs=args, keywords=kwargs, defaults=None"
}
member_method {
name: "add_weight"
argspec: "args=[\'self\', \'name\', \'shape\', \'dtype\', \'initializer\', \'regularizer\', \'trainable\', \'constraint\', \'use_resource\', \'partitioner\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'None\', \'True\', \'None\', \'None\', \'None\'], "
}
member_method {
name: "apply"
argspec: "args=[\'self\', \'inputs\'], varargs=args, keywords=kwargs, defaults=None"
}
member_method {
name: "build"
argspec: "args=[\'self\', \'inputs_shape\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "call"
argspec: "args=[\'self\', \'inputs\', \'state\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "compute_mask"
argspec: "args=[\'self\', \'inputs\', \'mask\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "compute_output_shape"
argspec: "args=[\'self\', \'input_shape\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "count_params"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "from_config"
argspec: "args=[\'cls\', \'config\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "get_config"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "get_input_at"
argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "get_input_mask_at"
argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "get_input_shape_at"
argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "get_losses_for"
argspec: "args=[\'self\', \'inputs\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "get_output_at"
argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "get_output_mask_at"
argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "get_output_shape_at"
argspec: "args=[\'self\', \'node_index\'], 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: "get_weights"
argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "set_weights"
argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
}
member_method {
name: "zero_state"
argspec: "args=[\'self\', \'batch_size\', \'dtype\'], varargs=None, keywords=None, defaults=None"
}
}
|
