public static Tensor _constant_impl(object value, TF_DataType dtype, int[] shape, string name, bool verify_shape, bool allow_broadcast)
{
if (tf.context.executing_eagerly())
{
}
Graph g = ops.get_default_graph();
var tensor_value = new AttrValue();
tensor_value.Tensor = tensor_util.make_tensor_proto(value,
dtype: dtype,
shape: shape,
verify_shape: verify_shape,
allow_broadcast: allow_broadcast);
var dtype_value = new AttrValue
{
Type = tensor_value.Tensor.Dtype,
};
var attrs = new Dictionary <string, AttrValue>();
attrs["value"] = tensor_value;
attrs["dtype"] = dtype_value;
var op = g.create_op("Const",
new Tensor[0],
new TF_DataType[] { dtype_value.Type.as_tf_dtype() },
attrs: attrs,
name: name);
return(op.outputs[0]);
}
/// <summary>
/// Creates a constant tensor.
///
/// The resulting tensor is populated with values of type `dtype`, as
/// specified by arguments `value` and (optionally) `shape`
/// </summary>
/// <param name="value">A constant value (or list) of output type `dtype`.</param>
/// <param name="dtype">The type of the elements of the resulting tensor.</param>
/// <param name="shape">Optional dimensions of resulting tensor.</param>
/// <param name="name">Optional name for the tensor.</param>
/// <param name="verify_shape">Boolean that enables verification of a shape of values.</param>
/// <returns></returns>
public static Tensor Constant(NDArray nd, string name = "Const", bool verify_shape = false)
{
Graph g = ops.get_default_graph();
var tensor_pb = tensor_util.make_tensor_proto(nd, verify_shape);
var tensor_value = new AttrValue
{
Type = tensor_pb.Dtype,
Tensor = tensor_pb
};
var dtype_value = new AttrValue
{
Type = tensor_value.Tensor.Dtype,
};
var attrs = new Dictionary <string, AttrValue>();
attrs["value"] = tensor_value;
attrs["dtype"] = dtype_value;
var op = g.create_op("Const",
null,
new TF_DataType[] { (TF_DataType)dtype_value.Type },
attrs: attrs,
name: name);
return(op.outputs[0]);
}
/// <param name="verify_shape">Boolean that enables verification of a shape of values.</param>
public static Tensor _constant_impl(object value,
TF_DataType dtype,
TensorShape shape,
string name,
bool verify_shape,
bool allow_broadcast)
{
if (tf.Context.executing_eagerly())
{
var t = convert_to_eager_tensor(value, tf.Context, dtype: dtype);
if (shape == null)
{
return(t);
}
if (t.shape.SequenceEqual(shape.dims))
{
return(t);
}
if (verify_shape)
{
throw new TypeError($"Expected Tensor's shape: {shape}, got {t.shape}.");
}
var num_t = t.TensorShape.num_elements();
if (num_t == shape.num_elements())
{
return(_eager_reshape(t, shape, tf.Context));
}
if (num_t == 1)
{
if (t.dtype == dtypes.@bool)
{
throw new NotImplementedException("");
}
else
{
return(_eager_fill(shape, t, tf.Context));
}
}
}
Graph g = ops.get_default_graph();
var tensor_value = new AttrValue();
tensor_value.Tensor = tensor_util.make_tensor_proto(value,
dtype: dtype,
shape: shape,
verify_shape: verify_shape,
allow_broadcast: allow_broadcast);
var dtype_value = new AttrValue
{
Type = tensor_value.Tensor.Dtype,
};
var attrs = new Dictionary <string, AttrValue>();
attrs["value"] = tensor_value;
attrs["dtype"] = dtype_value;
var op = g.create_op("Const",
new Tensor[0],
new TF_DataType[] { dtype_value.Type.as_tf_dtype() },
attrs: attrs,
name: name);
return(op.outputs[0]);
}