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SDK for PAI-EAS online inference services
package com.aliyun.openservices.eas.predict.request;
import com.aliyun.openservices.eas.predict.proto.TorchPredictProtos.ArrayShape;
import com.aliyun.openservices.eas.predict.proto.TorchPredictProtos.ArrayDataType;
import com.aliyun.openservices.eas.predict.proto.TorchPredictProtos.ArrayProto;
import com.aliyun.openservices.eas.predict.proto.TorchPredictProtos.PredictRequest;
import shade.protobuf.ByteString;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import java.util.List;
public class TorchRequest {
private PredictRequest.Builder request = PredictRequest.newBuilder();
private static Log log = LogFactory.getLog(TFRequest.class);
public void setDebugLevel(int level) {
request.setDebugLevel(level);
}
public void addFetch(int value) {
request.addOutputFilter(value);
}
public void addFeed(int index, TorchDataType dataType, long[] shape, float[] content) {
ArrayProto.Builder requestProto = ArrayProto.newBuilder();
if (dataType == TorchDataType.DT_FLOAT) {
requestProto.setDtype(ArrayDataType.DT_FLOAT);
} else {
log.error("call addFeed Error: TorchDataType and content mismatch!");
throw new RuntimeException("call addFeed Error: TorchDataType and content mismatch!");
}
ArrayShape.Builder arrayShape = ArrayShape.newBuilder();
for (long l : shape) {
arrayShape.addDim(l);
}
requestProto.mergeArrayShape(arrayShape.build());
for (float v : content) {
requestProto.addFloatVal(v);
}
request.addInputs(index, requestProto.build());
}
public void addFeed(int index, TorchDataType dataType, long[] shape, double[] content) {
ArrayProto.Builder requestProto = ArrayProto.newBuilder();
if (dataType == TorchDataType.DT_DOUBLE) {
requestProto.setDtype(ArrayDataType.DT_DOUBLE);
} else {
log.error("call addFeed Error: TorchDataType and content mismatch!");
throw new RuntimeException("call addFeed Error: TorchDataType and content mismatch!");
}
ArrayShape.Builder arrayShape = ArrayShape.newBuilder();
for (long l : shape) {
arrayShape.addDim(l);
}
requestProto.mergeArrayShape(arrayShape.build());
for (double v : content) {
requestProto.addDoubleVal(v);
}
request.addInputs(index, requestProto.build());
}
public void addFeed(int index, TorchDataType dataType, long[] shape, int[] content) {
ArrayProto.Builder requestProto = ArrayProto.newBuilder();
if (dataType == TorchDataType.DT_INT32) {
requestProto.setDtype(ArrayDataType.DT_INT32);
} else if (dataType == TorchDataType.DT_UINT8) {
requestProto.setDtype(ArrayDataType.DT_UINT8);
} else if (dataType == TorchDataType.DT_INT16) {
requestProto.setDtype(ArrayDataType.DT_INT16);
} else if (dataType == TorchDataType.DT_INT8) {
requestProto.setDtype(ArrayDataType.DT_INT8);
} else {
log.error("call addFeed Error: TorchDataType and content mismatch");
throw new RuntimeException("call addFeed Error: TorchDataType and content mismatch");
}
ArrayShape.Builder arrayShape = ArrayShape.newBuilder();
for (long l : shape) {
arrayShape.addDim(l);
}
requestProto.mergeArrayShape(arrayShape.build());
for (int value : content) {
requestProto.addIntVal(value);
}
request.addInputs(index, requestProto.build());
}
public void addFeed(int index, TorchDataType dataType, long[] shape, long[] content) {
ArrayProto.Builder requestProto = ArrayProto.newBuilder();
if (dataType == TorchDataType.DT_INT64) {
requestProto.setDtype(ArrayDataType.DT_INT64);
} else {
log.error("call addFeed Error: TorchDataType and content mismatch");
throw new RuntimeException("call addFeed Error: TorchDataType and content mismatch");
}
ArrayShape.Builder arrayShape = ArrayShape.newBuilder();
for (long value : shape) {
arrayShape.addDim(value);
}
requestProto.mergeArrayShape(arrayShape.build());
for (long l : content) {
requestProto.addInt64Val(l);
}
request.addInputs(index, requestProto.build());
}
public void addFeedMap(String index, TorchDataType dataType, long[] shape, long[] content) {
ArrayProto.Builder requestProto = ArrayProto.newBuilder();
if (dataType == TorchDataType.DT_INT64) {
requestProto.setDtype(ArrayDataType.DT_INT64);
} else {
log.error("call addFeed Error: TorchDataType and content mismatch");
throw new RuntimeException("call addFeed Error: TorchDataType and content mismatch");
}
ArrayShape.Builder arrayShape = ArrayShape.newBuilder();
for (long value : shape) {
arrayShape.addDim(value);
}
requestProto.mergeArrayShape(arrayShape.build());
for (long l : content) {
requestProto.addInt64Val(l);
}
request.putMapInputs(index, requestProto.build());
}
public void addFeedMap(String index, TorchDataType dataType, long[] shape, float[] content) {
ArrayProto.Builder requestProto = ArrayProto.newBuilder();
if (dataType == TorchDataType.DT_FLOAT) {
requestProto.setDtype(ArrayDataType.DT_FLOAT);
} else {
log.error("call addFeed Error: TorchDataType and content mismatch!");
throw new RuntimeException("call addFeed Error: TorchDataType and content mismatch!");
}
ArrayShape.Builder arrayShape = ArrayShape.newBuilder();
for (long l : shape) {
arrayShape.addDim(l);
}
requestProto.mergeArrayShape(arrayShape.build());
for (float v : content) {
requestProto.addFloatVal(v);
}
request.putMapInputs(index, requestProto.build());
}
public void addFeedMap(String index, TorchDataType dataType, long[] shape, double[] content) {
ArrayProto.Builder requestProto = ArrayProto.newBuilder();
if (dataType == TorchDataType.DT_DOUBLE) {
requestProto.setDtype(ArrayDataType.DT_DOUBLE);
} else {
log.error("call addFeed Error: TorchDataType and content mismatch!");
throw new RuntimeException("call addFeed Error: TorchDataType and content mismatch!");
}
ArrayShape.Builder arrayShape = ArrayShape.newBuilder();
for (long l : shape) {
arrayShape.addDim(l);
}
requestProto.mergeArrayShape(arrayShape.build());
for (double v : content) {
requestProto.addDoubleVal(v);
}
request.putMapInputs(index, requestProto.build());
}
public void addFeedMap(String index, TorchDataType dataType, long[] shape, int[] content) {
ArrayProto.Builder requestProto = ArrayProto.newBuilder();
if (dataType == TorchDataType.DT_INT32) {
requestProto.setDtype(ArrayDataType.DT_INT32);
} else if (dataType == TorchDataType.DT_UINT8) {
requestProto.setDtype(ArrayDataType.DT_UINT8);
} else if (dataType == TorchDataType.DT_INT16) {
requestProto.setDtype(ArrayDataType.DT_INT16);
} else if (dataType == TorchDataType.DT_INT8) {
requestProto.setDtype(ArrayDataType.DT_INT8);
} else {
log.error("call addFeed Error: TorchDataType and content mismatch");
throw new RuntimeException("call addFeed Error: TorchDataType and content mismatch");
}
ArrayShape.Builder arrayShape = ArrayShape.newBuilder();
for (long l : shape) {
arrayShape.addDim(l);
}
requestProto.mergeArrayShape(arrayShape.build());
for (int value : content) {
requestProto.addIntVal(value);
}
request.putMapInputs(index, requestProto.build());
}
public PredictRequest getRequest() {
return request.build();
}
}