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ones_like fix #736

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Merged
merged 2 commits into from
Jan 30, 2021
Merged

ones_like fix #736

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bee3a10
ones_like fix
MPnoy Jan 28, 2021
a11cb71
Merge branch 'master' into ones_like-fix
Oceania2018 Jan 30, 2021
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3 changes: 3 additions & 0 deletions src/TensorFlowNET.Core/Gradients/math_grad.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -138,6 +138,9 @@ public static Tensor[] _ExpGrad(Operation op, Tensor[] grads)
[RegisterNoGradient("GreaterEqual")]
public static Tensor[] _GreaterEqualGrad(Operation op, Tensor[] grads) => null;

[RegisterNoGradient("OnesLike")]
public static Tensor[] _OnesLike(Operation op, Tensor[] grads) => null;

[RegisterNoGradient("ZerosLike")]
public static Tensor[] _ZerosLike(Operation op, Tensor[] grads) => null;

Expand Down
38 changes: 31 additions & 7 deletions src/TensorFlowNET.Core/Operations/array_ops.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -274,7 +274,7 @@ public static Tensor _autopacking_helper(IEnumerable<object> list_or_tuple, TF_D
{
if (elem is EagerTensor eager_tensor)
{
if(switch_to_graph)
if (switch_to_graph)
elems_as_tensors.Add(constant_op.constant(eager_tensor.numpy(), dtype: dtype, name: i.ToString()));
else
elems_as_tensors.Add(eager_tensor);
Expand Down Expand Up @@ -366,8 +366,30 @@ public static Tensor rank_internal(Tensor input, string name = null, bool optimi
/// <param name="name"></param>
/// <param name="optimize"></param>
/// <returns></returns>
public static Tensor ones_like<T>(T tensor, TF_DataType dtype = TF_DataType.DtInvalid, string name = null, bool optimize = true)
=> ones_like_impl(tensor, dtype, name, optimize);
public static Tensor ones_like(Tensor tensor, TF_DataType dtype = TF_DataType.DtInvalid, string name = null, bool optimize = true)
{
return tf_with(ops.name_scope(name, "ones_like", new Tensor[] { tensor }), scope =>
{
name = scope;
tensor = ops.convert_to_tensor(tensor, name: "tensor");

// is_fully_defined return unexpected value.
if (optimize && tensor_util.to_shape(tensor.shape).is_fully_defined() && dtype != TF_DataType.TF_VARIANT)
{

}

if (dtype != TF_DataType.DtInvalid && dtype != tensor.dtype && dtype != TF_DataType.TF_VARIANT)
{
throw new NotImplementedException("ones_like");
// return ones(shape_internal(tensor, optimize: optimize), dtype: dtype, name: name);
}
else
{
return gen_array_ops.ones_like(tensor, name: name);
}
});
}

public static Tensor reshape(Tensor tensor, Tensor shape, string name = null)
=> gen_array_ops.reshape(tensor, shape, name: name);
Expand Down Expand Up @@ -888,7 +910,7 @@ public static Tensor transpose<T1>(T1 a, TensorShape perm, string name = "transp
return tf_with(ops.name_scope(name, "transpose", new { a }), scope =>
{
var a_tensor = ops.convert_to_tensor(a);
if(perm == null)
if (perm == null)
{
var rank = a_tensor.rank;
perm = range(0, rank).OrderByDescending(x => x).ToArray();
Expand Down Expand Up @@ -950,7 +972,9 @@ public static Tensor slice(Tensor input, Tensor begin, Tensor size, string name
=> tf.Context.RunInAutoMode2(
() => tf.OpDefLib._apply_op_helper("Slice", name, new
{
input, begin, size
input,
begin,
size
}).output,
() => tf.Runner.TFE_FastPathExecute(tf.Context, tf.Context.DeviceName,
"Slice", name,
Expand All @@ -966,8 +990,8 @@ public static Tensor slice(Tensor input, Tensor begin, Tensor size, string name
tf.Runner.RecordGradient("Slice", op.inputs, attrs, op.outputs);
},
new Tensors(input, begin, size));
public static Tensor stack(object values, int axis = 0, string name = "stack")

public static Tensor stack(object values, int axis = 0, string name = "stack")
{
if (axis == 0)
// If the input is a constant list, it can be converted to a constant op
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9 changes: 9 additions & 0 deletions src/TensorFlowNET.Core/Operations/gen_array_ops.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -591,6 +591,15 @@ public static Tensor transpose<T1>(Tensor x, T1 perm, string name = null)
return _op.outputs[0];
}

public static Tensor ones_like(Tensor x, string name = null)
=> tf.Context.RunInAutoMode(()
=> tf.OpDefLib._apply_op_helper("OnesLike", name, new { x }).output, ()
=> tf.Runner.TFE_FastPathExecute(tf.Context, tf.Context.DeviceName,
"OnesLike", name,
null,
x).FirstOrDefault(),
x);

public static Tensor zeros_like(Tensor x, string name = null)
=> tf.Context.RunInAutoMode(()
=> tf.OpDefLib._apply_op_helper("ZerosLike", name, new { x }).output, ()
Expand Down