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using NumSharp;
using System;
using System.Collections.Generic;
using Tensorflow;
using Tensorflow.Keras.Constraints;
using Tensorflow.Keras.Initializers;
using Tensorflow.Keras.Losses;
using Tensorflow.Keras.Metrics;
using Tensorflow.Keras.Regularizers;
namespace Keras.Layers
{
public abstract class Layer
{
public TF_DataType dtype
{
get
{
throw new NotImplementedException();
}
}
public string name
{
get
{
throw new NotImplementedException();
}
}
public bool stateful
{
get
{
throw new NotImplementedException();
}
set
{
throw new NotImplementedException();
}
}
public bool trainable
{
get
{
throw new NotImplementedException();
}
}
public Regularizer activity_regularizer
{
get
{
throw new NotImplementedException();
}
set
{
throw new NotImplementedException();
}
}
public dynamic input_spec
{
get
{
throw new NotImplementedException();
}
set
{
throw new NotImplementedException();
}
}
public Tensor[] trainable_weights
{
get
{
throw new NotImplementedException();
}
}
public Tensor[] non_trainable_weights
{
get
{
throw new NotImplementedException();
}
}
private Tensor[] _weights
{
get
{
throw new NotImplementedException();
}
}
public Func<bool>[] updates
{
get
{
throw new NotImplementedException();
}
}
public Tensor[] losses
{
get
{
throw new NotImplementedException();
}
}
public Tensor[] metrics
{
get
{
throw new NotImplementedException();
}
}
public Tensor[] input_mask
{
get
{
throw new NotImplementedException();
}
}
public Tensor[] output_mask
{
get
{
throw new NotImplementedException();
}
}
public Tensor[] input
{
get
{
throw new NotImplementedException();
}
}
public Tensor[] output
{
get
{
throw new NotImplementedException();
}
}
public TensorShape[] input_shape
{
get
{
throw new NotImplementedException();
}
}
public TensorShape[] output_shape
{
get
{
throw new NotImplementedException();
}
}
public Tensor[] variables
{
get
{
return _weights;
}
}
public Tensor[] trainable_variables
{
get
{
return trainable_weights;
}
}
public Tensor[] non_trainable_variables
{
get
{
return non_trainable_weights;
}
}
private string _compute_dtype
{
get
{
throw new NotImplementedException();
}
}
public Layer(bool trainable = true, string name = null, string dtype = null, bool @dynamic = false, Dictionary<string, object> kwargs = null)
{
}
public void build(TensorShape shape) => throw new NotImplementedException();
public virtual void call(Tensor[] inputs) => throw new NotImplementedException();
public void _add_trackable(dynamic trackable_object, bool trainable) => throw new NotImplementedException();
public void add_weight(string name= null, TensorShape shape= null, string dtype= null, Initializer initializer = null,
Regularizer regularizer = null, bool? trainable = null, ConstraintBase constraint = null,
dynamic partitioner= null, bool? use_resource= null, VariableSynchronization synchronization= VariableSynchronization.Auto,
VariableAggregation aggregation= VariableAggregation.None, Dictionary<string, object> kwargs = null) => throw new NotImplementedException();
public virtual Dictionary<string, object> get_config() => throw new NotImplementedException();
public Layer from_config(Dictionary<string, object> config) => throw new NotImplementedException();
public TensorShape compute_output_shape(TensorShape input_shape) => throw new NotImplementedException();
public dynamic compute_output_signature(dynamic input_signature) => throw new NotImplementedException();
public Tensor[] compute_mask(Tensor[] inputs, Tensor[] mask = null) => throw new NotImplementedException();
public void __call__(Tensor[] inputs) => throw new NotImplementedException();
public void add_loss(Loss[] losses, Tensor[] inputs = null) => throw new NotImplementedException();
public void _clear_losses() => throw new NotImplementedException();
public void add_metric(Tensor value, string aggregation= null, string name= null) => throw new NotImplementedException();
public void add_update(Func<bool>[] updates) => throw new NotImplementedException();
public void set_weights(NDArray[] weights) => throw new NotImplementedException();
public NDArray[] get_weights() => throw new NotImplementedException();
public Func<bool>[] get_updates_for(Tensor[] inputs) => throw new NotImplementedException();
public Tensor[] get_losses_for(Tensor[] inputs) => throw new NotImplementedException();
public Tensor[] get_input_mask_at(int node_index) => throw new NotImplementedException();
public Tensor[] get_output_mask_at(int node_index) => throw new NotImplementedException();
public TensorShape[] get_input_shape_at(int node_index) => throw new NotImplementedException();
public TensorShape[] get_output_shape_at(int node_index) => throw new NotImplementedException();
public Tensor[] get_input_at(int node_index) => throw new NotImplementedException();
public Tensor[] get_output_at(int node_index) => throw new NotImplementedException();
public int count_params() => throw new NotImplementedException();
private void _set_dtype_policy(string dtype) => throw new NotImplementedException();
private Tensor _maybe_cast_inputs(Tensor inputs) => throw new NotImplementedException();
private void _warn_about_input_casting(string input_dtype) => throw new NotImplementedException();
private string _name_scope()
{
return name;
}
private string _obj_reference_counts
{
get
{
throw new NotImplementedException();
}
}
private dynamic _attribute_sentinel
{
get
{
throw new NotImplementedException();
}
}
private dynamic _call_full_argspec
{
get
{
throw new NotImplementedException();
}
}
private string[] _call_fn_args
{
get
{
throw new NotImplementedException();
}
}
private string[] _call_accepts_kwargs
{
get
{
throw new NotImplementedException();
}
}
private bool _should_compute_mask
{
get
{
throw new NotImplementedException();
}
}
private Tensor[] _eager_losses
{
get
{
throw new NotImplementedException();
}
set
{
throw new NotImplementedException();
}
}
private dynamic _trackable_saved_model_saver
{
get
{
throw new NotImplementedException();
}
}
private string _object_identifier
{
get
{
throw new NotImplementedException();
}
}
private string _tracking_metadata
{
get
{
throw new NotImplementedException();
}
}
public Dictionary<string, bool> state
{
get
{
throw new NotImplementedException();
}
set
{
throw new NotImplementedException();
}
}
private void _init_set_name(string name, bool zero_based= true) => throw new NotImplementedException();
private Metric _get_existing_metric(string name = null) => throw new NotImplementedException();
private void _eager_add_metric(Metric value, string aggregation= null, string name= null) => throw new NotImplementedException();
private void _symbolic_add_metric(Metric value, string aggregation = null, string name = null) => throw new NotImplementedException();
private void _handle_weight_regularization(string name, VariableV1 variable, Regularizer regularizer) => throw new NotImplementedException();
private void _handle_activity_regularization(Tensor[] inputs, Tensor[] outputs) => throw new NotImplementedException();
private void _set_mask_metadata(Tensor[] inputs, Tensor[] outputs, Tensor previous_mask) => throw new NotImplementedException();
private Tensor[] _collect_input_masks(Tensor[] inputs, Dictionary<string, object> args, Dictionary<string, object> kwargs) => throw new NotImplementedException();
private bool _call_arg_was_passed(string arg_name, Dictionary<string, object> args, Dictionary<string, object> kwargs, bool inputs_in_args= false) => throw new NotImplementedException();
private T _get_call_arg_value<T>(string arg_name, Dictionary<string, object> args, Dictionary<string, object> kwargs, bool inputs_in_args = false) => throw new NotImplementedException();
private (Tensor[], Tensor[]) _set_connectivity_metadata_(Tensor[] inputs, Tensor[] outputs, Dictionary<string, object> args, Dictionary<string, object> kwargs) => throw new NotImplementedException();
private void _add_inbound_node(Tensor[] input_tensors, Tensor[] output_tensors, Dictionary<string, object> args = null) => throw new NotImplementedException();
private AttrValue _get_node_attribute_at_index(int node_index, string attr, string attr_name) => throw new NotImplementedException();
private void _maybe_build(Tensor[] inputs) => throw new NotImplementedException();
private void _symbolic_call(Tensor[] inputs) => throw new NotImplementedException();
private Dictionary<Layer, bool> _get_trainable_state() => throw new NotImplementedException();
private void _set_trainable_state(bool trainable_state) => throw new NotImplementedException();
private void _maybe_create_attribute(string name, object default_value) => throw new NotImplementedException();
private void __delattr__(string name) => throw new NotImplementedException();
private void __setattr__(string name, object value) => throw new NotImplementedException();
private List<AttrValue> _gather_children_attribute(string attribute) => throw new NotImplementedException();
private List<Layer> _gather_unique_layers() => throw new NotImplementedException();
private List<Layer> _gather_layers() => throw new NotImplementedException();
private bool _is_layer() => throw new NotImplementedException();
private void _init_call_fn_args() => throw new NotImplementedException();
public dynamic _list_extra_dependencies_for_serialization(dynamic serialization_cache) => throw new NotImplementedException();
public dynamic _list_functions_for_serialization(dynamic serialization_cache) => throw new NotImplementedException();
}
}