Examples with TFTensorConversionUtils com.alibaba.alink.common.dl.utils.TFTensorConversionUtils used on opensource projects

Example 1 with TFTensorConversionUtils

use of com.alibaba.alink.common.dl.utils.TFTensorConversionUtils in project Alink by alibaba.

the class StringTFTensorConversionImpl method encodeBatchTensor.

@Override
public String[] encodeBatchTensor(Tensor<?> tensor, int batchAxis) {
    long[] shape = tensor.shape().asArray();
    long batchSize = shape[batchAxis];
    if (TString.DTYPE.equals(tensor.dataType())) {
        StringTensor stringTensor = (StringTensor) TFTensorConversionUtils.fromTFTensor(tensor);
        StringTensor[] stringTensors = unstack(stringTensor, batchAxis, null);
        return Arrays.stream(stringTensors).map(TFTensorConversionUtils::toTFTensor).map(TF2TensorUtils::squeezeTensor).map(d -> StdArrays.array1dCopyOf((TString) d.data(), String.class)).map(d -> String.join(SEP_CHAR, d)).toArray(String[]::new);
    } else if (TBool.DTYPE.equals(tensor.dataType())) {
        BoolTensor boolTensor = (BoolTensor) TFTensorConversionUtils.fromTFTensor(tensor);
        BoolTensor[] boolTensors = unstack(boolTensor, batchAxis, null);
        return Arrays.stream(boolTensors).map(TFTensorConversionUtils::toTFTensor).map(TF2TensorUtils::squeezeTensor).map(d -> StdArrays.array1dCopyOf((TBool) d.data())).map(d -> Booleans.join(SEP_CHAR, d)).toArray(String[]::new);
    } else if (TInt32.DTYPE.equals(tensor.dataType())) {
        IntTensor intTensor = (IntTensor) TFTensorConversionUtils.fromTFTensor(tensor);
        IntTensor[] intTensors = unstack(intTensor, batchAxis, null);
        return Arrays.stream(intTensors).map(TFTensorConversionUtils::toTFTensor).map(TF2TensorUtils::squeezeTensor).map(d -> StdArrays.array1dCopyOf((TInt32) d.data())).map(d -> Ints.join(SEP_CHAR, d)).toArray(String[]::new);
    } else if (TInt64.DTYPE.equals(tensor.dataType())) {
        LongTensor longTensor = (LongTensor) TFTensorConversionUtils.fromTFTensor(tensor);
        LongTensor[] longTensors = unstack(longTensor, batchAxis, null);
        return Arrays.stream(longTensors).map(TFTensorConversionUtils::toTFTensor).map(TF2TensorUtils::squeezeTensor).map(d -> StdArrays.array1dCopyOf((TInt64) d.data())).map(d -> Longs.join(SEP_CHAR, d)).toArray(String[]::new);
    } else if (TFloat32.DTYPE.equals(tensor.dataType())) {
        FloatTensor floatTensor = (FloatTensor) TFTensorConversionUtils.fromTFTensor(tensor);
        FloatTensor[] floatTensors = unstack(floatTensor, batchAxis, null);
        return Arrays.stream(floatTensors).map(TFTensorConversionUtils::toTFTensor).map(TF2TensorUtils::squeezeTensor).map(d -> StdArrays.array1dCopyOf((TFloat32) d.data())).map(d -> Floats.join(SEP_CHAR, d)).toArray(String[]::new);
    } else if (TFloat64.DTYPE.equals(tensor.dataType())) {
        DoubleTensor doubleTensor = (DoubleTensor) TFTensorConversionUtils.fromTFTensor(tensor);
        DoubleTensor[] doubleTensors = unstack(doubleTensor, batchAxis, null);
        return Arrays.stream(doubleTensors).map(TFTensorConversionUtils::toTFTensor).map(TF2TensorUtils::squeezeTensor).map(d -> StdArrays.array1dCopyOf((TFloat64) d.data())).map(d -> Doubles.join(SEP_CHAR, d)).toArray(String[]::new);
    }
    throw new UnsupportedOperationException("Unsupported dtype: " + tensor.dataType());
}