Public static methods
object disable_v2_dtype_behavior(object fn)
object disable_v2_dtype_behavior_dyn(object fn)
object enable_v2_dtype_behavior_dyn(object fn)
object experimental_run_tf_function_scope_dyn(object value)
IList<object> get_expected_metric_variable_names(IEnumerable<string> var_names, string name_suffix)
object get_model_from_layers(IEnumerable<Dense> layers, Nullable<ValueTuple<int>> input_shape, DType input_dtype, string name, object input_ragged, object input_sparse)
object get_model_from_layers_dyn(object layers, object input_shape, object input_dtype, object name, object input_ragged, object input_sparse)
object get_model_type_dyn()
object get_multi_io_model(IEnumerable<Dense> branch_a, IEnumerable<object> branch_b, object shared_input_branch, object shared_output_branch)
object get_multi_io_model_dyn(object branch_a, object branch_b, object shared_input_branch, object shared_output_branch)
Model get_small_functional_mlp(int num_hidden, int num_classes, Nullable<int> input_dim)
object get_small_functional_mlp_dyn(object num_hidden, object num_classes, object input_dim)
object get_small_mlp(int num_hidden, int num_classes, Nullable<int> input_dim)
object get_small_mlp_dyn(object num_hidden, object num_classes, object input_dim)
Sequential get_small_sequential_mlp(int num_hidden, int num_classes, Nullable<int> input_dim)
object get_small_sequential_mlp_dyn(object num_hidden, object num_classes, object input_dim)
object get_small_subclass_mlp_dyn(object num_hidden, object num_classes)
object get_small_subclass_mlp_with_custom_build_dyn(object num_hidden, object num_classes)
ValueTuple<object, object> get_test_data(int train_samples, int test_samples, ValueTuple<int> input_shape, int num_classes, Nullable<int> random_seed)
object get_test_data_dyn(object train_samples, object test_samples, object input_shape, object num_classes, object random_seed)
object get_v2_optimizer(string name, IDictionary<string, object> kwargs)
object get_v2_optimizer_dyn(object name, IDictionary<string, object> kwargs)
object layer_test(PythonClassContainer layer_cls, IDictionary<string, object> kwargs, Nullable<ValueTuple<int, int, int>> input_shape, PythonClassContainer input_dtype, ndarray input_data, object expected_output, dtype expected_output_dtype, object expected_output_shape, bool validate_training, ndarray adapt_data)
object layer_test(PythonClassContainer layer_cls, IDictionary<string, object> kwargs, Nullable<ValueTuple<int, int, int>> input_shape, string input_dtype, ndarray input_data, object expected_output, dtype expected_output_dtype, object expected_output_shape, bool validate_training, ndarray adapt_data)
object layer_test(PythonClassContainer layer_cls, IDictionary<string, object> kwargs, Nullable<ValueTuple<int, int, int>> input_shape, string input_dtype, ndarray input_data, object expected_output, string expected_output_dtype, object expected_output_shape, bool validate_training, ndarray adapt_data)
object layer_test(PythonClassContainer layer_cls, IDictionary<string, object> kwargs, Nullable<ValueTuple<int, int, int>> input_shape, string input_dtype, ndarray input_data, object expected_output, PythonClassContainer expected_output_dtype, object expected_output_shape, bool validate_training, ndarray adapt_data)
object layer_test(PythonClassContainer layer_cls, IDictionary<string, object> kwargs, Nullable<ValueTuple<int, int, int>> input_shape, dtype input_dtype, ndarray input_data, object expected_output, dtype expected_output_dtype, object expected_output_shape, bool validate_training, ndarray adapt_data)
object layer_test(PythonClassContainer layer_cls, IDictionary<string, object> kwargs, Nullable<ValueTuple<int, int, int>> input_shape, dtype input_dtype, ndarray input_data, object expected_output, PythonClassContainer expected_output_dtype, object expected_output_shape, bool validate_training, ndarray adapt_data)
object layer_test(PythonClassContainer layer_cls, IDictionary<string, object> kwargs, Nullable<ValueTuple<int, int, int>> input_shape, dtype input_dtype, ndarray input_data, object expected_output, string expected_output_dtype, object expected_output_shape, bool validate_training, ndarray adapt_data)
object layer_test(PythonClassContainer layer_cls, IDictionary<string, object> kwargs, Nullable<ValueTuple<int, int, int>> input_shape, PythonClassContainer input_dtype, ndarray input_data, object expected_output, PythonClassContainer expected_output_dtype, object expected_output_shape, bool validate_training, ndarray adapt_data)
object layer_test(PythonClassContainer layer_cls, IDictionary<string, object> kwargs, Nullable<ValueTuple<int, int, int>> input_shape, PythonClassContainer input_dtype, ndarray input_data, object expected_output, string expected_output_dtype, object expected_output_shape, bool validate_training, ndarray adapt_data)
object layer_test_dyn(object layer_cls, object kwargs, object input_shape, object input_dtype, object input_data, object expected_output, object expected_output_dtype, object expected_output_shape, ImplicitContainer<T> validate_training, object adapt_data)
object model_type_scope_dyn(object value)
object run_eagerly_scope_dyn(object value)
bool should_run_eagerly()
object should_run_eagerly_dyn()
bool should_run_tf_function()
object should_run_tf_function_dyn()
Public properties