/** * <pre> * Shape of the tensor. TODO(touts): sort out the 0-rank issues. * </pre> * * <code>.tensorflow.TensorShapeProto tensor_shape = 2;</code> */ public org.tensorflow.framework.TensorShapeProtoOrBuilder getTensorShapeOrBuilder() { return getTensorShape(); }
output.writeMessage(2, getTensorShape());
@Override public long[] getShapeFromTensor(NodeDef tensorProto) { if(tensorProto.containsAttr("shape")) { return shapeFromShapeProto(tensorProto.getAttrOrThrow("shape").getShape()); } //yet to be determined shape, or tied to an op where output shape is dynamic else if(!tensorProto.containsAttr("value")) { return null; } else return shapeFromShapeProto(tensorProto.getAttrOrThrow("value").getTensor().getTensorShape()); }
mergeTensorShape(other.getTensorShape());
.computeMessageSize(2, getTensorShape());
result = result && (hasTensorShape() == other.hasTensorShape()); if (hasTensorShape()) { result = result && getTensorShape() .equals(other.getTensorShape());
if (hasTensorShape()) { hash = (37 * hash) + TENSOR_SHAPE_FIELD_NUMBER; hash = (53 * hash) + getTensorShape().hashCode();
public INDArray mapTensorProto(TensorProto tfTensor) { int dims = tfTensor.getTensorShape().getDimCount(); int[] arrayShape = null; List<Integer> dimensions = new ArrayList<>(); int dim = (int) tfTensor.getTensorShape().getDim(e).getSize();
/** * <pre> * Shape of the tensor. TODO(touts): sort out the 0-rank issues. * </pre> * * <code>.tensorflow.TensorShapeProto tensor_shape = 2;</code> */ public org.tensorflow.framework.TensorShapeProtoOrBuilder getTensorShapeOrBuilder() { return getTensorShape(); }
.computeMessageSize(2, getTensorShape());
output.writeMessage(2, getTensorShape());
mergeTensorShape(other.getTensorShape());
result = result && (hasTensorShape() == other.hasTensorShape()); if (hasTensorShape()) { result = result && getTensorShape() .equals(other.getTensorShape());
if (hasTensorShape()) { hash = (37 * hash) + TENSOR_SHAPE_FIELD_NUMBER; hash = (53 * hash) + getTensorShape().hashCode();