public Tensor forward(Tensor input, Tensor?h0 = null)
{
var hN = THSNN_RNNCell_forward(handle, input.Handle, h0?.Handle ?? IntPtr.Zero);
if (hN == IntPtr.Zero)
{
torch.CheckForErrors();
}
return(new Tensor(hN));
}
public static Tensor binary_cross_entropy(Tensor src, Tensor target, Tensor?weight = null, Reduction reduction = Reduction.Mean)
{
var res = THSNN_binary_cross_entropy(src.Handle, target.Handle, weight?.Handle ?? IntPtr.Zero, (long)reduction);
if (res == IntPtr.Zero)
{
torch.CheckForErrors();
}
return(new Tensor(res));
}
public (Tensor, Tensor) forward(Tensor input, Tensor?h0 = null)
{
var res = THSNN_GRU_forward(handle, input.Handle, h0?.Handle ?? IntPtr.Zero, out IntPtr hN);
if (res == IntPtr.Zero || hN == IntPtr.Zero)
{
torch.CheckForErrors();
}
return(new Tensor(res), new Tensor(hN));
}
public static Loss binary_cross_entropy_with_logits_loss(Tensor?weight = null, Reduction reduction = Reduction.Mean, Tensor?posWeights = null)
{
return((Tensor src, Tensor target) => {
var res = THSNN_binary_cross_entropy_with_logits(src.Handle, target.Handle, weight?.Handle ?? IntPtr.Zero, (long)reduction, posWeights?.Handle ?? IntPtr.Zero);
if (res == IntPtr.Zero)
{
torch.CheckForErrors();
}
return new Tensor(res);
});
}
public static Loss nll_loss(Tensor?weight = null, Reduction reduction = Reduction.Mean)
{
return((Tensor src, Tensor target) => {
var res = THSNN_nll_loss(src.Handle, target.Handle, weight?.Handle ?? IntPtr.Zero, (long)reduction);
if (res == IntPtr.Zero)
{
torch.CheckForErrors();
}
return new Tensor(res);
});
}
public static Loss cross_entropy_loss(Tensor?weight = null, long?ignore_index = null, Reduction reduction = Reduction.Mean)
{
return((Tensor src, Tensor target) => {
var ii = ignore_index.HasValue ? ignore_index.Value : -100;
var res = THSNN_cross_entropy(src.Handle, target.Handle, weight?.Handle ?? IntPtr.Zero, ii, ignore_index.HasValue, (long)reduction);
if (res == IntPtr.Zero)
{
torch.CheckForErrors();
}
return new Tensor(res);
});
}
public static Loss multi_margin_loss(int p = 1, double margin = 1.0, Tensor?weight = null, Reduction reduction = Reduction.Mean)
{
IntPtr h = (weight is null) ? IntPtr.Zero : weight.Handle;
return((Tensor input, Tensor target) => {
var res = THSNN_multi_margin_loss(input.Handle, target.Handle, p, margin, h, (long)reduction);
if (res == IntPtr.Zero)
{
torch.CheckForErrors();
}
return new Tensor(res);
});
}
public Tensor forward(Tensor src, Tensor?src_mask = null, Tensor?src_key_padding_mask = null)
{
var res = THSNN_TransformerEncoder_forward(handle,
src.Handle,
src_mask?.Handle ?? IntPtr.Zero,
src_key_padding_mask?.Handle ?? IntPtr.Zero);
if (res == IntPtr.Zero)
{
torch.CheckForErrors();
}
return(new Tensor(res));
}
public Tensor forward(Tensor tgt, Tensor memory, Tensor?tgt_mask = null, Tensor?memory_mask = null, Tensor?tgt_key_padding_mask = null, Tensor?memory_key_padding_mask = null)
{
var res = THSNN_TransformerDecoder_forward(handle,
tgt.Handle,
memory.Handle,
tgt_mask?.Handle ?? IntPtr.Zero,
memory_mask?.Handle ?? IntPtr.Zero,
tgt_key_padding_mask?.Handle ?? IntPtr.Zero,
memory_key_padding_mask?.Handle ?? IntPtr.Zero);
if (res == IntPtr.Zero)
{
torch.CheckForErrors();
}
return(new Tensor(res));
}
public new (Tensor, Tensor) forward(Tensor input, Tensor?h0 = null)
{
if (h0 is null)
{
var N = _batch_first ? input.shape[0] : input.shape[1];
var D = _bidirectional ? 2 : 1;
h0 = torch.zeros(new long[] { D *_num_layers, N, _hidden_size });
}
var res = THSNN_RNN_forward(handle, input.Handle, h0.Handle, out IntPtr hN);
if (res == IntPtr.Zero || hN == IntPtr.Zero)
{
torch.CheckForErrors();
}
return(new Tensor(res), new Tensor(hN));
}
public void set_bias_hh(Tensor?value, long idx)
{
THSNN_RNN_set_bias_hh(handle, (value is null ? IntPtr.Zero : value.Handle), idx);
torch.CheckForErrors();
ConditionallyRegisterParameter($"bias_hh_l{idx}", value);
}
public Tuple <Tensor, Tensor> forward(Tensor query, Tensor key, Tensor value, Tensor?key_padding_mask = null, bool need_weights = true, Tensor?attn_mask = null)
{
THSNN_MultiheadAttention_forward(handle,
query.Handle,
key.Handle,
value.Handle,
key_padding_mask?.Handle ?? IntPtr.Zero,
need_weights,
attn_mask?.Handle ?? IntPtr.Zero,
out var res1,
out var res2);
if (res1 == IntPtr.Zero || (need_weights && res2 == IntPtr.Zero))
{
torch.CheckForErrors();
}
return(Tuple.Create(new Tensor(res1), new Tensor(res2)));
}
