io.hydrosphere.serving.tensorflow.tensor_shape
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor.
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
If true, the number of dimensions in the shape is unknown.
If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.
(Since version 0.6.0) Use toPMessage
(Since version 0.6.0) Use getField that accepts a ScalaPB descriptor and returns PValue
Dimensions of a tensor.
Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. If an entry has size -1, this corresponds to a dimension of unknown size. The names are optional. The order of entries in "dim" matters: It indicates the layout of the values in the tensor in-memory representation. The first entry in "dim" is the outermost dimension used to layout the values, the last entry is the innermost dimension. This matches the in-memory layout of RowMajor Eigen tensors. If "dim.size()" > 0, "unknown_rank" must be false.
If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.