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WhileContext

tags/v0.12
Oceania2018 6 years ago
parent
59b7eb0365
commit
efed25863a
15 changed files with 256 additions and 196 deletions
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  1. +1
    -1
      README.md
  2. +17
    -0
      src/TensorFlowNET.Core/Binding.Util.cs
  3. +10
    -51
      src/TensorFlowNET.Core/Operations/ControlFlows/ControlFlowState.cs
  4. +95
    -114
      src/TensorFlowNET.Core/Operations/ControlFlows/GradLoopState.cs
  5. +2
    -3
      src/TensorFlowNET.Core/Operations/ControlFlows/WhileContext.cs
  6. +34
    -8
      src/TensorFlowNET.Core/Operations/NnOps/rnn.cs
  7. +29
    -0
      src/TensorFlowNET.Core/Operations/NnOps/rnn_cell_impl.cs
  8. +9
    -0
      src/TensorFlowNET.Core/Operations/Operation.Control.cs
  9. +13
    -8
      src/TensorFlowNET.Core/Operations/Operation.Instance.cs
  10. +4
    -5
      src/TensorFlowNET.Core/Operations/Operation.cs
  11. +1
    -1
      src/TensorFlowNET.Core/Operations/gen_array_ops.cs
  12. +6
    -4
      src/TensorFlowNET.Core/Operations/gen_control_flow_ops.cs
  13. +26
    -0
      src/TensorFlowNET.Core/Operations/gen_data_flow_ops.cs
  14. +1
    -1
      src/TensorFlowNET.Core/Operations/gen_math_ops.cs
  15. +8
    -0
      src/TensorFlowNET.Core/Util/nest.py.cs

+ 1
- 1
README.md View File

@@ -9,7 +9,7 @@
[![Documentation Status](https://readthedocs.org/projects/tensorflownet/badge/?version=latest)](https://tensorflownet.readthedocs.io/en/latest/?badge=latest)
[![Badge](https://img.shields.io/badge/link-996.icu-red.svg)](https://996.icu/#/en_US)

TF.NET is a member project of [SciSharp STACK](https://github.com/SciSharp). <a href="http://scisharpstack.org"><img src="https://github.com/SciSharp/SciSharp/blob/master/art/scisharp_badge.png" width="200" height="200" align="right" /></a>
TF.NET is a member project of [SciSharp STACK](https://github.com/SciSharp).


![tensors_flowing](docs/assets/tensors_flowing.gif)


+ 17
- 0
src/TensorFlowNET.Core/Binding.Util.cs View File

@@ -30,6 +30,20 @@ namespace Tensorflow
/// </summary>
public static partial class Binding
{
public static T2 get<T1, T2>(this Dictionary<T1, T2> dict, T1 key)
=> key == null ?
default(T2) :
(dict.ContainsKey(key) ? dict[key] : default(T2));

public static void add<T>(this IList<T> list, T element)
=> list.Add(element);

public static void append<T>(this IList<T> list, T element)
=> list.Add(element);

public static void extend<T>(this List<T> list, IEnumerable<T> elements)
=> list.AddRange(elements);

private static string _tostring(object obj)
{
switch (obj)
@@ -81,6 +95,9 @@ namespace Tensorflow
throw new NotImplementedException("len() not implemented for type: " + a.GetType());
}

public static T[] list<T>(IEnumerable<T> list)
=> list.ToArray();

public static IEnumerable<int> range(int end)
{
return Enumerable.Range(0, end);


+ 10
- 51
src/TensorFlowNET.Core/Operations/ControlFlows/ControlFlowState.cs View File

@@ -109,11 +109,12 @@ namespace Tensorflow.Operations.ControlFlows
grad_state.grad_context.Enter();
}
// def ExitGradWhileContext(self, op, before):
// """Exit the WhileContext for gradient computation."""
// grad_state = self.GetGradState(op, before)
// if grad_state:
// grad_state.grad_context.Exit()
public void ExitGradWhileContext(Operation op, bool before)
{
var grad_state = GetGradState(op, before);
if (grad_state != null)
grad_state.grad_context.Exit();
}
// def AddWhileContext(self, op, between_op_list, between_ops):
// """Add the grad state for the while loop that op belongs to.
@@ -287,51 +288,9 @@ namespace Tensorflow.Operations.ControlFlows
return result;
}
// def PostProcessing(self):
// """Perform postprocessing at the end of gradients().
// We have created the gradient graph at this point. So this function
// can be used to perform any postprocessing on the gradient graph.
// We currently perform the following postprocessing:
// 1. Patch the gradient graph if the output of a loop variable
// doesn't depend on its input.
// """
// for _, grad_state in self._map.items():
// for _, b_merge in grad_state.switch_map.items():
// if b_merge.op.inputs[0] == b_merge.op.inputs[1]:
// # The value of this loop variable at iteration i+1 doesn't
// # depend on its value at iteration i. So use zeros as the
// # gradients for all iterations > 0.
// dtype = b_merge.op.inputs[0].dtype
// shape = b_merge.op.inputs[0].get_shape()
// # pylint: disable=protected-access
// if shape.is_fully_defined():
// grad_state.grad_context.Enter()
// # Create a zeros and use it for iterations > 0.
// grad_val = constant_op.constant(0, dtype=dtype, shape=shape)
// next_grad_val = _NextIteration(grad_val)
// grad_state.grad_context.Exit()
// else:
// # Create a zeros in the outer grad context.
// outer_grad_ctxt = grad_state.grad_context.outer_context
// if outer_grad_ctxt:
// outer_grad_ctxt.Enter()
// enter_grad_op = b_merge.op.inputs[0].op
// enter_grad = enter_grad_op.inputs[0]
// grad_shape = array_ops.shape_internal(enter_grad, optimize=False)
// grad_val = array_ops.zeros(grad_shape)
// if outer_grad_ctxt:
// outer_grad_ctxt.Exit()
// # Use the zeros for iterations > 0.
// grad_state.grad_context.Enter()
// next_grad_val = _NextIteration(grad_val)
// grad_state.grad_context.Exit()
// b_merge.op._update_input(1, next_grad_val)
// # pylint: enable=protected-access
public void PostProcessing()
{
throw new NotImplementedException("PostProcessing");
}
}
}

+ 95
- 114
src/TensorFlowNET.Core/Operations/ControlFlows/GradLoopState.cs View File

@@ -17,7 +17,9 @@
using System;
using System.Collections;
using System.Collections.Generic;
using System.Linq;
using static Tensorflow.Binding;
using util = Tensorflow.control_flow_util;
namespace Tensorflow.Operations.ControlFlows
{
@@ -56,6 +58,7 @@ namespace Tensorflow.Operations.ControlFlows
public GradLoopState outer_grad_state => _outer_grad_state;
Tensor _forward_index;
public Tensor forward_index => _forward_index;
Tensor _grad_index;
Tensor[] _forward_loop_exits;
@@ -152,63 +155,52 @@ namespace Tensorflow.Operations.ControlFlows
/// <returns>The stack that contains the accumulated history of the tensor.</returns>
public Tensor AddForwardAccumulator(Tensor value, bool dead_branch = false)
{
throw new NotImplementedException("AddForwardAccumulator");
// # curr_ctxt is the context that tf.gradients was called in.
// with self._forward_index.graph.as_default():
// curr_ctxt = ops.get_default_graph()._get_control_flow_context() # pylint: disable=protected-access
// with ops.control_dependencies(None):
// if curr_ctxt:
// curr_ctxt.Enter()
// with ops.colocate_with(value):
// # We only need to pass maximum_iterations to the stack if
// # we're inside an XLA context.
// if not util.IsInXLAContext(value.op):
// max_size = constant_op.constant(-1, dtypes.int32)
// else:
// max_size = GetMaxSizeFromNestedMaximumIterations(
// value, self.forward_context)
// acc = gen_data_flow_ops.stack_v2(
// max_size=max_size, elem_type=value.dtype.base_dtype, name="f_acc")
// if curr_ctxt:
// curr_ctxt.Exit()
// # Make acc available in the forward context.
// enter_acc = self.forward_context.AddValue(acc)
// # Add the stack_push op in the context of value.op.
// swap_enabled = self.forward_context.swap_memory
// value_ctxt = util.GetOutputContext(value.op)
// if value_ctxt == self.forward_context:
// # value is not nested in the forward context.
// self.forward_context.Enter()
// push = gen_data_flow_ops.stack_push_v2(
// enter_acc, value, swap_memory=swap_enabled)
// self.forward_context.Exit()
// # Protect stack push and order it before forward_index.
// self.forward_index.op._add_control_input(push.op)
// else:
// # value is in a cond context within the forward context.
// if not isinstance(value_ctxt, CondContext):
// raise TypeError("value_ctxt is not a CondContext: %s" % value_ctxt)
// if dead_branch:
// # The special case for creating a zero tensor for a dead
// # branch of a switch. See ControlFlowState.ZerosLike().
// value_ctxt.outer_context.Enter()
// push = gen_data_flow_ops.stack_push_v2(
// enter_acc, value, swap_memory=swap_enabled)
// value_ctxt.outer_context.Exit()
// push.op._set_control_flow_context(value_ctxt)
// else:
// value_ctxt.Enter()
// push = gen_data_flow_ops.stack_push_v2(
// enter_acc, value, swap_memory=swap_enabled)
// value_ctxt.Exit()
// # Protect stack push and order it before forward_sync.
// self.forward_sync._add_control_input(push.op)
// # Order stack push after the successor of forward_index
// add_op = self.forward_index.op.inputs[0].op
// push.op._add_control_input(add_op)
// return acc
using (_forward_index.graph.as_default())
{
var curr_ctxt = ops.get_default_graph()._get_control_flow_context();
return tf_with(ops.control_dependencies(null), delegate
{
Tensor acc = null;
Tensor push = null;
if (curr_ctxt != null)
curr_ctxt.Enter();
ops.colocate_with(value);
{
// We only need to pass maximum_iterations to the stack if
// we're inside an XLA context.
var max_size = constant_op.constant(-1, dtypes.int32);
acc = gen_data_flow_ops.stack_v2(
max_size: max_size, elem_type: value.dtype.as_base_dtype(), name: "f_acc");
}
if (curr_ctxt != null)
curr_ctxt.Exit();
// Make acc available in the forward context.
var enter_acc = forward_context.AddValue(acc);
// Add the stack_push op in the context of value.op.
var swap_enabled = forward_context.swap_memory;
var value_ctxt = util.GetOutputContext(value.op);
if(value_ctxt == forward_context)
{
// value is not nested in the forward context.
forward_context.Enter();
push = gen_data_flow_ops.stack_push_v2(enter_acc, value, swap_memory: swap_enabled);
forward_context.Exit();
// Protect stack push and order it before forward_index.
forward_index.op._add_control_input(push.op);
}
else
{
throw new NotImplementedException("AddForwardAccumulator");
}
// Order stack push after the successor of forward_index
var add_op = forward_index.op.inputs[0].op;
push.op._add_control_input(add_op);
return acc;
});
}
}
// """Add the getter for an accumulated value in the grad context.
@@ -225,6 +217,7 @@ namespace Tensorflow.Operations.ControlFlows
// Returns:
// The current value (the top of the stack).
// """
public Tensor AddBackpropAccumulatedValue(Tensor history_value, Tensor value, bool dead_branch= false)
{
throw new NotImplementedException();
@@ -261,62 +254,50 @@ namespace Tensorflow.Operations.ControlFlows
// return pop
}
// def GetRealValue(self, value):
// """Get the real value of `value`.
// If backprop "uses" a value produced by forward inference, an accumulator
// is added in the forward loop to accumulate its values. We use the
// accumulated value. This method must be called in the grad loop context.
// `value` must be in forward and needed for backprop.
// Args:
// value: A tensor to be captured.
// Returns:
// The same tensor obtained from the saved history.
// """
// assert value.op.type not in ["Variable", "VariableV2"]
// real_value = self._history_map.get(value.name)
// if real_value is None:
// cur_value = value
// cur_grad_state = self
// while True:
// enter_op = util.GetLoopConstantEnter(cur_value)
// if enter_op:
// # Special case: cur_value comes from a constant Enter node.
// cur_value = enter_op.inputs[0]
// cur_grad_state = cur_grad_state.outer_grad_state
// if cur_grad_state is None:
// # We are now outside all nested loops for this gradient(),
// # so `value` is a loop invariant and there is no need to
// # save the history of value. Just make cur_value to enter
// # the right control flow context.
// real_value = self._grad_context.AddValue(cur_value)
// break
// elif constant_op.is_constant(cur_value):
// # If the value to be forwarded is a constant, clone the constant in
// # the gradient loop rather than using a stack.
// # TODO(phawkins): consider hoisting the constant out of the loop
// # instead.
// real_value = constant_op.constant(
// tensor_util.constant_value(cur_value), dtype=cur_value.dtype)
// break
// else:
// # Record the history of this value in forward_ctxt.
// self._grad_context.Exit()
// history_value = cur_grad_state.AddForwardAccumulator(cur_value)
// self._grad_context.Enter()
// break
// if real_value is None:
// # Add the stack pop op in the grad context.
// real_value = cur_grad_state.AddBackpropAccumulatedValue(
// history_value, cur_value)
// if cur_grad_state != self:
// real_value = self._grad_context.AddValue(real_value)
// self._history_map[value.name] = real_value
// return real_value
/// <summary>
/// Get the real value of `value`.
/// </summary>
/// <param name="value">A tensor to be captured.</param>
/// <returns>The same tensor obtained from the saved history.</returns>
public Tensor GetRealValue(Tensor value)
{
Tensor real_value = null;
if(real_value == null)
{
var cur_value = value;
var cur_grad_state = this;
Tensor history_value = null;
while (true)
{
var enter_op = util.GetLoopConstantEnter(cur_value);
if(enter_op != null)
{
throw new NotImplementedException("GetRealValue");
}
else if (constant_op.is_constant(cur_value))
{
throw new NotImplementedException("GetRealValue");
}
else
{
// Record the history of this value in forward_ctxt.
_grad_context.Exit();
history_value = cur_grad_state.AddForwardAccumulator(cur_value);
_grad_context.Enter();
break;
}
}
if(real_value == null)
{
// Add the stack pop op in the grad context.
real_value = cur_grad_state.AddBackpropAccumulatedValue(history_value, cur_value);
if (cur_grad_state != this)
real_value = _grad_context.AddValue(real_value);
}
_history_map[value.name] = real_value;
}
return real_value;
}
}
}

+ 2
- 3
src/TensorFlowNET.Core/Operations/ControlFlows/WhileContext.cs View File

@@ -530,10 +530,9 @@ namespace Tensorflow.Operations
}
if(forward_ctxt == grad_ctxt.grad_state.forward_context)
{
throw new NotImplementedException("forward_ctxt == grad_ctxt.grad_state.forward_context");
/*real_val = grad_ctxt.grad_state.GetRealValue(val);
var real_val = grad_ctxt.grad_state.GetRealValue(val);
_external_values[val.name] = real_val;
return real_val;*/
return real_val;
}
}
}


+ 34
- 8
src/TensorFlowNET.Core/Operations/NnOps/rnn.cs View File

@@ -30,7 +30,7 @@ namespace Tensorflow.Operations
TF_DataType dtype = TF_DataType.DtInvalid,
int? parallel_iterations = null, bool swap_memory = false, bool time_major = false)
{
tf_with(tf.variable_scope("rnn"), scope =>
return tf_with(tf.variable_scope("rnn"), scope =>
{
VariableScope varscope = scope;
var flat_input = nest.flatten(inputs_tensor);
@@ -64,9 +64,12 @@ namespace Tensorflow.Operations
swap_memory: swap_memory,
sequence_length: sequence_length,
dtype: dtype);
});

throw new NotImplementedException("");
if (!time_major)
outputs = nest.map_structure(_transpose_batch_time, outputs);

return (outputs, final_state);
});
}

/// <summary>
@@ -210,16 +213,28 @@ namespace Tensorflow.Operations
var input_t_t = nest.pack_sequence_as2(structure: inputs, flat_sequence: input_t);
// Keras RNN cells only accept state as list, even if it's a single tensor.
// var is_keras_rnn_cell = _is_keras_rnn_cell(cell);
(Tensor, Tensor) a = (null, null);
Tensor[] outputs = null;
if (sequence_length != null)
throw new NotImplementedException("sequence_length != null");
else
a = cell.__call__(input_t_t, state: state1);
outputs = cell.__call__(input_t_t, state: state1);

var (output, new_state) = (outputs[0], outputs[1]);
// Keras cells always wrap state as list, even if it's a single tensor.
// if(is_keras_rnn_cell && len(new_state)) == 1
// Pack state if using state tuples
outputs = nest.flatten2(output).Select(x => x as Tensor).ToArray();

return item;
output_ta_t = zip(output_ta_t, outputs).Select(x =>
{
var(ta, @out) = (x.Item1, x.Item2);
return ta.write(item.time, @out);
}).ToArray();

return new BodyItemInRnnWhileLoop(item.time + 1, output_ta_t, new_state);
};

control_flow_ops.while_loop(
var while_loop_result = control_flow_ops.while_loop(
cond: cond,
body: _time_step,
loop_vars: new BodyItemInRnnWhileLoop(time, output_ta.ToArray(), state),
@@ -227,7 +242,18 @@ namespace Tensorflow.Operations
maximum_iterations: time_steps,
swap_memory: swap_memory);

throw new NotImplementedException("");
(_, TensorArray[] output_final_ta, Tensor final_state) = (while_loop_result.time, while_loop_result.output_ta_t, while_loop_result.state);

// Unpack final output if not using output tuples.
var final_outputs = output_final_ta.Select(ta => ta.stack()).ToArray();
// Restore some shape information
foreach (var (output, output_size) in zip(final_outputs, flat_output_size))
{
var shape = rnn_cell_impl._concat(new[] { const_time_steps, const_batch_size }, output_size, @static: true);
output.set_shape(shape);
}

return (final_outputs[0], final_state);
}

private static TensorShape _maybe_tensor_shape_from_tensor(Tensor shape)


+ 29
- 0
src/TensorFlowNET.Core/Operations/NnOps/rnn_cell_impl.cs View File

@@ -53,5 +53,34 @@ namespace Tensorflow.Operations
return array_ops.concat(new[] { p, s }, 0);
}
}

public static TensorShape _concat(int[] prefix, int suffix, bool @static = false)
{
var p = new TensorShape(prefix);
var p_static = prefix;
var p_tensor = p.is_fully_defined() ? constant_op.constant(p.as_list(), dtype: dtypes.int32) : null;

var s_tensor_shape = new TensorShape(suffix);
var s_static = s_tensor_shape.ndim > -1 ?
s_tensor_shape.dims :
null;
var s_tensor = s_tensor_shape.is_fully_defined() ?
constant_op.constant(s_tensor_shape.dims, dtype: dtypes.int32) :
null;

if (@static)
{
if (p_static is null) return null;
var shape = new TensorShape(p_static).concatenate(s_static);
return shape;
}
else
{
if (p is null || s_tensor is null)
throw new ValueError($"Provided a prefix or suffix of None: {prefix} and {suffix}");
// return array_ops.concat(new[] { p_tensor, s_tensor }, 0);
throw new NotImplementedException("");
}
}
}
}

+ 9
- 0
src/TensorFlowNET.Core/Operations/Operation.Control.cs View File

@@ -52,6 +52,10 @@ namespace Tensorflow
public void _set_control_flow_context(ControlFlowContext ctx)
{
if (name.Contains("gradients/rnn/while/basic_rnn_cell/Tanh_grad/TanhGrad/f_acc"))
{
}
_control_flow_context = ctx;
}
@@ -59,5 +63,10 @@ namespace Tensorflow
{
return _control_flow_context;
}
public WhileContext GetWhileContext()
{
return _control_flow_context as WhileContext;
}
}
}

+ 13
- 8
src/TensorFlowNET.Core/Operations/Operation.Instance.cs View File

@@ -15,17 +15,14 @@
******************************************************************************/

using System;
using System.Linq;
using System.Collections.Generic;
using static Tensorflow.Binding;

namespace Tensorflow
{
public partial class Operation
{
// cache the mapping between managed and unmanaged op
// some data is stored in managed instance, so when
// create Operation by IntPtr, it will lost some data.
private static Dictionary<IntPtr, Operation> OpInstances = new Dictionary<IntPtr, Operation>();

/// <summary>
/// Get operation by handle
/// </summary>
@@ -33,9 +30,17 @@ namespace Tensorflow
/// <returns></returns>
public Operation GetOperation(IntPtr handle)
{
return OpInstances.ContainsKey(handle) ?
OpInstances[handle] :
new Operation(handle);
var nodes = tf.get_default_graph()._nodes_by_name;
foreach(var node in nodes.Values)
{
if (node is Operation op)
{
if (op == handle)
return op;
}
}

return null;
}
}
}

+ 4
- 5
src/TensorFlowNET.Core/Operations/Operation.cs View File

@@ -106,7 +106,6 @@ namespace Tensorflow
_control_flow_context = _graph._get_control_flow_context();

// Note: _control_flow_post_processing() must not be called here, the caller is responsible for calling it when using this constructor.
OpInstances[_handle] = this;
}

/*public Operation(Graph g, string opType, string oper_name)
@@ -183,10 +182,12 @@ namespace Tensorflow
// This will be set by self.inputs.
if (op_def == null)
op_def = g.GetOpDef(node_def.Op);

if(node_def.Name == "gradients/rnn/while/basic_rnn_cell/Tanh_grad/TanhGrad/f_acc")
{
}
var grouped_inputs = _reconstruct_sequence_inputs(op_def, inputs, node_def.Attr);
_handle = ops._create_c_op(g, node_def, grouped_inputs, control_input_ops.ToArray());

_is_stateful = op_def.IsStateful;

// Initialize self._outputs.
@@ -202,8 +203,6 @@ namespace Tensorflow

if (_handle != IntPtr.Zero)
_control_flow_post_processing();

OpInstances[_handle] = this;
}

public void run(FeedItem[] feed_dict = null, Session session = null)


+ 1
- 1
src/TensorFlowNET.Core/Operations/gen_array_ops.cs View File

@@ -183,7 +183,7 @@ namespace Tensorflow
{
var _op = _op_def_lib._apply_op_helper("Identity", name, new { input });

return _op.outputs[0];
return _op.output;
}

public static Tensor invert_permutation(Tensor x, string name = null)


+ 6
- 4
src/TensorFlowNET.Core/Operations/gen_control_flow_ops.cs View File

@@ -14,6 +14,8 @@
limitations under the License.
******************************************************************************/

using Tensorflow.Operations;

namespace Tensorflow
{
public class gen_control_flow_ops
@@ -148,18 +150,18 @@ namespace Tensorflow
return new []{_op.outputs[0], _op.outputs[1]};
}

public static Tensor[] ref_merge(Tensor[] inputs, string name = null)
public static MergeOutput ref_merge(Tensor[] inputs, string name = null)
{
var _op = _op_def_lib._apply_op_helper("RefMerge", name, new { inputs });

return _op.outputs;
return new MergeOutput(_op.outputs);
}

public static Tensor[] merge(Tensor[] inputs, string name = null)
public static MergeOutput merge(Tensor[] inputs, string name = null)
{
var _op = _op_def_lib._apply_op_helper("Merge", name, new { inputs });

return _op.outputs;
return new MergeOutput(_op.outputs);
}
}
}

+ 26
- 0
src/TensorFlowNET.Core/Operations/gen_data_flow_ops.cs View File

@@ -259,5 +259,31 @@ namespace Tensorflow

return _op.output;
}

public static Tensor stack_v2(Tensor max_size, TF_DataType elem_type, string stack_name = "",
string name = null)
{
var _op = _op_def_lib._apply_op_helper("StackV2", name, new
{
max_size,
elem_type,
stack_name
});

return _op.output;
}

public static Tensor stack_push_v2(Tensor handle, Tensor elem, bool swap_memory = false,
string name = null)
{
var _op = _op_def_lib._apply_op_helper("StackPushV2", name, new
{
handle,
elem,
swap_memory
});

return _op.output;
}
}
}

+ 1
- 1
src/TensorFlowNET.Core/Operations/gen_math_ops.cs View File

@@ -282,7 +282,7 @@ namespace Tensorflow
/// <param name="dy"></param>
/// <param name="name"></param>
/// <returns></returns>
public static Tensor tanh_grad(Tensor y, Tensor dy, string name = "TanhGrad")
public static Tensor tanh_grad(Tensor y, Tensor dy, string name = null)
=> _op_def_lib._apply_op_helper("TanhGrad", name: name, args: new { y, dy }).output;
public static Tensor floor(Tensor x, string name = null)


+ 8
- 0
src/TensorFlowNET.Core/Util/nest.py.cs View File

@@ -526,6 +526,14 @@ namespace Tensorflow.Util
return pack_sequence_as(structure, mapped_flat_structure) as Tensor;
}
public static Tensor map_structure2<T>(Func<T, Tensor> func, T structure)
{
var flat_structure = flatten(structure);
var mapped_flat_structure = flat_structure.Select(func).ToList();
return pack_sequence_as(structure, mapped_flat_structure) as Tensor;
}
/// <summary>
/// Same as map_structure, but with only one structure (no combining of multiple structures)
/// </summary>


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