private unsafe NDArray fetchValue(IntPtr output)
{
var tensor = new Tensor(output);
NDArray nd = null;
Type type = tensor.dtype.as_numpy_datatype();
var ndims = tensor.shape.Select(x => (int)x).ToArray();
switch (tensor.dtype)
{
case TF_DataType.TF_STRING:
var bytes = tensor.Data();
// wired, don't know why we have to start from offset 9.
// length in the begin
var str = UTF8Encoding.Default.GetString(bytes, 9, bytes[8]);
nd = np.array(str).reshape();
break;
case TF_DataType.TF_INT16:
var shorts = new short[tensor.size];
for (ulong i = 0; i < tensor.size; i++)
{
shorts[i] = *(short *)(c_api.TF_TensorData(output) + (int)(tensor.dataTypeSize * i));
}
nd = np.array(shorts).reshape(ndims);
break;
case TF_DataType.TF_INT32:
var ints = new int[tensor.size];
for (ulong i = 0; i < tensor.size; i++)
{
ints[i] = *(int *)(c_api.TF_TensorData(output) + (int)(tensor.dataTypeSize * i));
}
nd = np.array(ints).reshape(ndims);
break;
case TF_DataType.TF_FLOAT:
var floats = new float[tensor.size];
for (ulong i = 0; i < tensor.size; i++)
{
floats[i] = *(float *)(c_api.TF_TensorData(output) + (int)(tensor.dataTypeSize * i));
}
nd = np.array(floats).reshape(ndims);
break;
case TF_DataType.TF_DOUBLE:
var doubles = new double[tensor.size];
for (ulong i = 0; i < tensor.size; i++)
{
doubles[i] = *(double *)(c_api.TF_TensorData(output) + (int)(tensor.dataTypeSize * i));
}
nd = np.array(doubles).reshape(ndims);
break;
default:
throw new NotImplementedException("can't fetch output");
}
return(nd);
}
private unsafe NDArray[] _call_tf_sessionrun(KeyValuePair <TF_Output, Tensor>[] feed_dict, TF_Output[] fetch_list, List <Operation> target_list)
{
// Ensure any changes to the graph are reflected in the runtime.
_extend_graph();
var status = new Status();
var output_values = fetch_list.Select(x => IntPtr.Zero).ToArray();
c_api.TF_SessionRun(_session,
run_options: null,
inputs: feed_dict.Select(f => f.Key).ToArray(),
input_values: feed_dict.Select(f => (IntPtr)f.Value).ToArray(),
ninputs: feed_dict.Length,
outputs: fetch_list,
output_values: output_values,
noutputs: fetch_list.Length,
target_opers: target_list.Select(f => (IntPtr)f).ToArray(),
ntargets: target_list.Count,
run_metadata: IntPtr.Zero,
status: status);
status.Check(true);
var result = new NDArray[fetch_list.Length];
for (int i = 0; i < fetch_list.Length; i++)
{
var tensor = new Tensor(output_values[i]);
switch (tensor.dtype)
{
case TF_DataType.TF_STRING:
{
// wired, don't know why we have to start from offset 9.
var bytes = tensor.Data();
var output = UTF8Encoding.Default.GetString(bytes, 9, bytes.Length - 9);
result[i] = fetchValue(tensor, output);
}
break;
case TF_DataType.TF_FLOAT:
{
var output = *(float *)c_api.TF_TensorData(output_values[i]);
result[i] = fetchValue(tensor, output);
}
break;
case TF_DataType.TF_INT16:
{
var output = *(short *)c_api.TF_TensorData(output_values[i]);
result[i] = fetchValue(tensor, output);
}
break;
case TF_DataType.TF_INT32:
{
var output = *(int *)c_api.TF_TensorData(output_values[i]);
result[i] = fetchValue(tensor, output);
}
break;
default:
throw new NotImplementedException("can't get output");
}
}
return(result);
}