path: "tensorflow.layers.MaxPooling1D" tf_class { is_instance: "" is_instance: "" is_instance: "" is_instance: "" is_instance: "" is_instance: "" is_instance: "" is_instance: "" is_instance: "" is_instance: "" member { name: "activity_regularizer" mtype: "" } member { name: "compute_dtype" mtype: "" } member { name: "dtype" mtype: "" } member { name: "dtype_policy" mtype: "" } member { name: "dynamic" mtype: "" } member { name: "graph" mtype: "" } member { name: "inbound_nodes" mtype: "" } member { name: "input" mtype: "" } member { name: "input_mask" mtype: "" } member { name: "input_shape" mtype: "" } member { name: "input_spec" mtype: "" } member { name: "losses" mtype: "" } member { name: "metrics" mtype: "" } member { name: "name" mtype: "" } member { name: "name_scope" mtype: "" } member { name: "non_trainable_variables" mtype: "" } member { name: "non_trainable_weights" mtype: "" } member { name: "outbound_nodes" mtype: "" } member { name: "output" mtype: "" } member { name: "output_mask" mtype: "" } member { name: "output_shape" mtype: "" } member { name: "scope_name" mtype: "" } member { name: "stateful" mtype: "" } member { name: "submodules" mtype: "" } member { name: "supports_masking" mtype: "" } member { name: "trainable" mtype: "" } member { name: "trainable_variables" mtype: "" } member { name: "trainable_weights" mtype: "" } member { name: "updates" mtype: "" } member { name: "variable_dtype" mtype: "" } member { name: "variables" mtype: "" } member { name: "weights" mtype: "" } member_method { name: "__init__" argspec: "args=[\'self\', \'pool_size\', \'strides\', \'padding\', \'data_format\', \'name\'], varargs=None, keywords=kwargs, defaults=[\'valid\', \'channels_last\', \'None\'], " } member_method { name: "add_loss" argspec: "args=[\'self\', \'losses\', \'inputs\'], varargs=None, keywords=None, defaults=[\'None\'], " } member_method { name: "add_metric" argspec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=kwargs, 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\', \'synchronization\', \'aggregation\', \'partitioner\'], varargs=None, keywords=kwargs, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'VariableSynchronization.AUTO\', \'VariableAggregation.NONE\', \'None\'], " } member_method { name: "apply" argspec: "args=[\'self\', \'inputs\'], varargs=args, keywords=kwargs, defaults=None" } member_method { name: "build" argspec: "args=[\'self\', \'input_shape\'], varargs=None, keywords=None, defaults=None" } member_method { name: "call" argspec: "args=[\'self\', \'inputs\'], 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: "compute_output_signature" argspec: "args=[\'self\', \'input_signature\'], 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: "with_name_scope" argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None" } }