path: "tensorflow.keras.layers.Convolution3DTranspose" tf_class { 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: "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: "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\', \'filters\', \'kernel_size\', \'strides\', \'padding\', \'output_padding\', \'data_format\', \'dilation_rate\', \'activation\', \'use_bias\', \'kernel_initializer\', \'bias_initializer\', \'kernel_regularizer\', \'bias_regularizer\', \'activity_regularizer\', \'kernel_constraint\', \'bias_constraint\'], varargs=None, keywords=kwargs, defaults=[\'(1, 1, 1)\', \'valid\', \'None\', \'None\', \'(1, 1, 1)\', \'None\', \'True\', \'glorot_uniform\', \'zeros\', \'None\', \'None\', \'None\', \'None\', \'None\'], " } member_method { name: "add_loss" argspec: "args=[\'self\', \'losses\'], varargs=None, keywords=kwargs, 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\'], varargs=None, keywords=kwargs, defaults=[\'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'None\', \'VariableSynchronization.AUTO\', \'VariableAggregation.NONE\'], " } member_method { name: "apply" argspec: "args=[\'self\', 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"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" } }