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Posted to commits@singa.apache.org by wa...@apache.org on 2016/06/23 13:38:15 UTC
[1/4] incubator-singa git commit: SINGA-200 - Implement Encoder and
Decoder for data pre-processing
Repository: incubator-singa
Updated Branches:
refs/heads/dev 396f9bf71 -> 833f46195
SINGA-200 - Implement Encoder and Decoder for data pre-processing
Add CMake scripts for singa io libs.
Project: http://git-wip-us.apache.org/repos/asf/incubator-singa/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-singa/commit/bef1db0f
Tree: http://git-wip-us.apache.org/repos/asf/incubator-singa/tree/bef1db0f
Diff: http://git-wip-us.apache.org/repos/asf/incubator-singa/diff/bef1db0f
Branch: refs/heads/dev
Commit: bef1db0fc20145411c41a5d4082e25dab2e13bc8
Parents: 396f9bf
Author: jixin <ji...@comp.nus.edu.sg>
Authored: Mon Jun 20 22:09:58 2016 +0800
Committer: jixin <ji...@comp.nus.edu.sg>
Committed: Thu Jun 23 17:20:17 2016 +0800
----------------------------------------------------------------------
include/singa/io/decoder.h | 45 ++++++++++++++++++++
include/singa/io/encoder.h | 44 ++++++++++++++++++++
include/singa/io/image2jpg_decoder.h | 40 ++++++++++++++++++
include/singa/io/image2jpg_encoder.h | 40 ++++++++++++++++++
src/CMakeLists.txt | 5 +++
src/io/image2jpg_decoder.cc | 54 ++++++++++++++++++++++++
src/io/image2jpg_encoder.cc | 69 +++++++++++++++++++++++++++++++
src/proto/model.proto | 23 +++++++++++
test/singa/test_io.cc | 65 +++++++++++++++++++++++++++++
9 files changed, 385 insertions(+)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/bef1db0f/include/singa/io/decoder.h
----------------------------------------------------------------------
diff --git a/include/singa/io/decoder.h b/include/singa/io/decoder.h
new file mode 100644
index 0000000..8330e34
--- /dev/null
+++ b/include/singa/io/decoder.h
@@ -0,0 +1,45 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef SINGA_IO_DECODER_H_
+#define SINGA_IO_DECODER_H_
+
+#include <vector>
+#include <string>
+#include "singa/core/tensor.h"
+
+namespace singa {
+namespace io {
+
+class Decoder {
+ public:
+ Decoder() { }
+ virtual ~Decoder() { }
+
+ /**
+ * Decode value to get data and labels
+ */
+ virtual std::vector<Tensor> Decode(std::string value) {
+ vector<Tensor> output;
+ return output;
+ }
+};
+
+} // namespace io
+} // namespace singa
+#endif // SINGA_IO_DECODER_H_
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/bef1db0f/include/singa/io/encoder.h
----------------------------------------------------------------------
diff --git a/include/singa/io/encoder.h b/include/singa/io/encoder.h
new file mode 100644
index 0000000..66a2fe5
--- /dev/null
+++ b/include/singa/io/encoder.h
@@ -0,0 +1,44 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef SINGA_IO_ENCODER_H_
+#define SINGA_IO_ENCODER_H_
+
+#include <vector>
+#include <string>
+#include "singa/core/tensor.h"
+
+namespace singa {
+namespace io {
+
+class Encoder {
+ public:
+ Encoder() { }
+ virtual ~Encoder() { }
+
+ /**
+ * Format each sample data as a string,
+ * whose structure depends on the proto definition.
+ * e.g., {key, shape, label, type, data, ...}
+ */
+ virtual std::string Encode(vector<Tensor>& data) { return ""; }
+};
+
+} // namespace io
+} // namespace singa
+#endif // SINGA_IO_ENCODER_H_
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/bef1db0f/include/singa/io/image2jpg_decoder.h
----------------------------------------------------------------------
diff --git a/include/singa/io/image2jpg_decoder.h b/include/singa/io/image2jpg_decoder.h
new file mode 100644
index 0000000..6895c29
--- /dev/null
+++ b/include/singa/io/image2jpg_decoder.h
@@ -0,0 +1,40 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef SINGA_IO_IMAGE2JPG_DECODER_H_
+#define SINGA_IO_IMAGE2JPG_DECODER_H_
+
+#include <vector>
+#include <string>
+#include "singa/core/tensor.h"
+#include "singa/io/decoder.h"
+#include "singa/proto/model.pb.h"
+#include <opencv2/highgui/highgui.hpp>
+#include <opencv2/imgproc/imgproc.hpp>
+
+namespace singa {
+namespace io {
+
+class Image2JPGDecoder : public Decoder {
+ public:
+ std::vector<Tensor> Decode(std::string value) override;
+};
+
+} // namespace io
+} // namespace singa
+#endif // SINGA_IO_IMAGE2JPG_DECODER_H_
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/bef1db0f/include/singa/io/image2jpg_encoder.h
----------------------------------------------------------------------
diff --git a/include/singa/io/image2jpg_encoder.h b/include/singa/io/image2jpg_encoder.h
new file mode 100644
index 0000000..2e94b64
--- /dev/null
+++ b/include/singa/io/image2jpg_encoder.h
@@ -0,0 +1,40 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef SINGA_IO_IMAGE2JPG_ENCODER_H_
+#define SINGA_IO_IMAGE2JPG_ENCODER_H_
+
+#include <vector>
+#include <string>
+#include "singa/core/tensor.h"
+#include "singa/io/encoder.h"
+#include "singa/proto/model.pb.h"
+#include <opencv2/highgui/highgui.hpp>
+#include <opencv2/imgproc/imgproc.hpp>
+
+namespace singa {
+namespace io {
+
+class Image2JPGEncoder : public Encoder {
+ public:
+ std::string Encode(vector<Tensor>& data) override;
+};
+
+} // namespace io
+} // namespace singa
+#endif // SINGA_IO_IMAGE2JPG_ENCODER_H_
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/bef1db0f/src/CMakeLists.txt
----------------------------------------------------------------------
diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt
index a4fa22f..90343d5 100644
--- a/src/CMakeLists.txt
+++ b/src/CMakeLists.txt
@@ -55,6 +55,11 @@ ADD_LIBRARY(singa_model SHARED ${model_source})
TARGET_LINK_LIBRARIES(singa_model ${SINGA_LINKER_LIBS})
LIST(APPEND SINGA_LINKER_LIBS singa_model)
+AUX_SOURCE_DIRECTORY(io io_source)
+ADD_LIBRARY(singa_io SHARED ${io_source})
+TARGET_LINK_LIBRARIES(singa_io ${SINGA_LIBKER_LIBS})
+LIST(APPEND SINGA_LINKER_LIBS singa_io)
+
#ADD_LIBRARY(singa_layer SHARED ${LAYER_SOURCE})
#ADD_LIBRARY(singa_model SHARED ${MODEL_SOURCE})
#ADD_LIBRARY(singa_utils SHARED ${UTILS_SOURCE})
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/bef1db0f/src/io/image2jpg_decoder.cc
----------------------------------------------------------------------
diff --git a/src/io/image2jpg_decoder.cc b/src/io/image2jpg_decoder.cc
new file mode 100644
index 0000000..da0c909
--- /dev/null
+++ b/src/io/image2jpg_decoder.cc
@@ -0,0 +1,54 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "singa/io/image2jpg_decoder.h"
+#include <vector>
+//#include <opencv2/core/core.hpp>
+//#include <opencv2/highgui/highgui.hpp>
+//#include "opencv2/opencv.hpp"
+
+using namespace cv;
+using namespace std;
+
+namespace singa {
+
+namespace io {
+ vector<Tensor> Image2JPGDecoder::Decode(string value) {
+ vector<Tensor> output;
+ RecordProto image;
+ image.ParseFromString(value);
+ Shape shape(image.shape().begin(), image.shape().end());
+ Tensor features(shape), labels(Shape{1});
+
+ //string pixel = image.pixel();
+ vector<unsigned char> pixel(image.pixel().begin(), image.pixel().end());
+ Mat buff(shape[1], shape[2], CV_8UC3, pixel.data());
+ Mat mat = imdecode(buff, CV_LOAD_IMAGE_COLOR);
+ vector<int> data;
+ data.assign(mat.datastart, mat.dataend);
+ //for (size_t i = 0; i < image.pixel().size(); i++)
+ // data[i] = static_cast<int>(static_cast<uint8_t>(pixel[i]));
+ features.CopyDataFromHostPtr<vector<int>>(&data, data.size());
+ int l[1] = {image.label()};
+ labels.CopyDataFromHostPtr(l, 1);
+ output.push_back(features);
+ output.push_back(labels);
+ return output;
+ }
+}
+}
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/bef1db0f/src/io/image2jpg_encoder.cc
----------------------------------------------------------------------
diff --git a/src/io/image2jpg_encoder.cc b/src/io/image2jpg_encoder.cc
new file mode 100644
index 0000000..4a1f428
--- /dev/null
+++ b/src/io/image2jpg_encoder.cc
@@ -0,0 +1,69 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "singa/io/image2jpg_encoder.h"
+//#include <opencv2/core/core.hpp>
+//#include <opencv2/highgui/highgui.hpp>
+//#include "opencv2/opencv.hpp"
+
+using namespace cv;
+using namespace std;
+
+namespace singa {
+
+namespace io{
+ string Image2JPGEncoder::Encode(vector<Tensor>& data) {
+ // suppose data[0]: data, data[1]: label
+ // suppose data[0] has a shape as {channel, height, width}
+ CHECK_EQ(data[0].nDim(), 3u);
+ string output;
+ size_t height = data[0].shape()[1];
+ size_t width = data[0].shape()[2];
+ Mat mat = Mat(height, width, CV_8UC3);
+ Mat resized;
+ resize(mat, resized, Size(256, 256));
+ Mat test = imread("test/samples/test.jpeg", CV_LOAD_IMAGE_COLOR);
+ if (data[0].data_type() == kInt)
+ memcpy(mat.data, data[0].data<const int*>(), data[0].Size()*sizeof(int));
+ else LOG(FATAL) << "Data type is invalid for an raw image";
+ //cout << mat << endl;
+
+ const int* label;
+ // suppose each image is attached with only one label
+ if (data[1].data_type() == kInt)
+ label = data[1].data<const int*>();
+ else LOG(FATAL) << "Data type is invalid for image label";
+
+ vector<uchar> buff;
+ vector<int> param = vector<int>(2);
+ param[0] = CV_IMWRITE_JPEG_QUALITY;
+ param[1] = 95; // default is 95
+ imencode(".jpg", mat, buff, param);
+ string buf(buff.begin(), buff.end());
+
+ RecordProto image;
+ image.set_label(label[0]);
+ for (size_t i = 0; i < data[0].nDim(); i++)
+ image.add_shape(data[0].shape()[i]);
+ image.set_pixel(buf);
+ image.SerializeToString(&output);
+
+ return output;
+ }
+}
+}
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/bef1db0f/src/proto/model.proto
----------------------------------------------------------------------
diff --git a/src/proto/model.proto b/src/proto/model.proto
index c06deec..77a7f75 100644
--- a/src/proto/model.proto
+++ b/src/proto/model.proto
@@ -51,6 +51,29 @@ message BlobProto {
optional int32 width = 4 [default = 0];
}
+/// directly copy from v0.3
+message Record {
+ enum Type {
+ // each record contains image raw feature and its label.
+ kSingleLabelImage = 0;
+ }
+ optional Type type = 1 [default = kSingleLabelImage];
+ optional string user_type =2;
+ // configuration for
+ optional RecordProto image = 5;
+
+ extensions 101 to 200;
+}
+
+// rename SingleLabelImageRecord to RecordProto
+message RecordProto {
+ repeated int32 shape = 1;
+ optional int32 label = 2;
+ optional bytes pixel = 3;
+ repeated float data = 4 [packed = true];
+}
+/// end of copy v0.3
+
message FillerConf {
// The filler type, case insensitive
optional string type = 1 [default = 'constant'];
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/bef1db0f/test/singa/test_io.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_io.cc b/test/singa/test_io.cc
new file mode 100644
index 0000000..16853c4
--- /dev/null
+++ b/test/singa/test_io.cc
@@ -0,0 +1,65 @@
+/************************************************************
+*
+* Licensed to the Apache Software Foundation (ASF) under one
+* or more contributor license agreements. See the NOTICE file
+* distributed with this work for additional information
+* regarding copyright ownership. The ASF licenses this file
+* to you under the Apache License, Version 2.0 (the
+* "License"); you may not use this file except in compliance
+* with the License. You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing,
+* software distributed under the License is distributed on an
+* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+* KIND, either express or implied. See the License for the
+* specific language governing permissions and limitations
+* under the License.
+*
+*************************************************************/
+
+#include "../include/singa/io/image2jpg_encoder.h"
+#include "../include/singa/io/image2jpg_decoder.h"
+#include "gtest/gtest.h"
+#include <opencv2/highgui/highgui.hpp>
+#include <opencv2/imgproc/imgproc.hpp>
+
+using namespace singa;
+using namespace singa::io;
+using namespace cv;
+
+TEST(Decoder, Decode) {
+ Encoder encoder;
+ Decoder decoder;
+ string path = "test/samples/test.jpeg";
+ size_t resize_height = 256;
+ size_t resize_width = 256;
+ size_t channel = 3;
+ int raw_label[] = {1};
+ Mat image = imread(path, CV_LOAD_IMAGE_COLOR);
+ Mat transformed;
+ Size size(resize_height, resize_width);
+ resize(image, transformed, size);
+
+ vector<int> buff;
+ buff.assign(transformed.datastart, transformed.dataend);
+ Shape shape{channel, (size_t)transformed.size().height, (size_t)transformed.size().width};
+ Tensor pixel(shape), label(Shape{1});
+ pixel.CopyDataFromHostPtr<vector<int>>(&buff, buff.size());
+ label.CopyDataFromHostPtr<int>(raw_label, 1);
+
+ vector<Tensor> input;
+ input.push_back(pixel);
+ input.push_back(label);
+ string str0 = encoder.Encode(input);
+ vector<Tensor> output = decoder.Decode(str0);
+ Shape out_shape = output.at(0).shape();
+ const int* out_pixel = output.at(0).data<const int *>();
+ const int* out_label = output.at(1).data<const int *>();
+ EXPECT_EQ(raw_label[0], out_label[0]);
+ for (size_t i = 0; i < shape.size(); i++)
+ EXPECT_EQ(shape[i], out_shape[i]);
+ for(size_t i = 0; i < 10; i++)
+ EXPECT_EQ(buff[i], out_pixel[i]);
+}
[4/4] incubator-singa git commit: SINGA-200 - Implement Encoder and
Decoder for data pre-processing
Posted by wa...@apache.org.
SINGA-200 - Implement Encoder and Decoder for data pre-processing
Improve the JPG2ProtoDecoder and Proto2JPGEncoder to consider the image
dimension order "HWC" or "CHW".
Change the input image Tensor's data type to kUChar, i.e., unsigned char.
Change Tensor::data() API, to cont SType* data<DType>() const;
TODO add other encoding functions to accept other inputs, e.g., cv::Mat.
Project: http://git-wip-us.apache.org/repos/asf/incubator-singa/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-singa/commit/833f4619
Tree: http://git-wip-us.apache.org/repos/asf/incubator-singa/tree/833f4619
Diff: http://git-wip-us.apache.org/repos/asf/incubator-singa/diff/833f4619
Branch: refs/heads/dev
Commit: 833f46195a7a15bc369fb785b638e5f90445ca43
Parents: 13d60b0
Author: Wei Wang <wa...@comp.nus.edu.sg>
Authored: Thu Jun 23 21:33:49 2016 +0800
Committer: Wei Wang <wa...@comp.nus.edu.sg>
Committed: Thu Jun 23 21:33:49 2016 +0800
----------------------------------------------------------------------
CMakeLists.txt | 3 +-
cmake/Templates/singa_config.h.in | 2 +
include/singa/core/tensor.h | 6 +-
include/singa/io/decoder.h | 37 +++++----
include/singa/io/encoder.h | 46 ++++++-----
src/core/tensor/tensor.cc | 2 +
src/io/jpg2proto_encoder.cc | 95 ++++++++++++----------
src/io/proto2jpg_decoder.cc | 78 +++++++++++-------
src/model/layer/prelu.cc | 8 +-
src/model/metric/accuracy.h | 5 +-
src/proto/core.proto | 3 +-
src/proto/model.proto | 15 ----
test/singa/test_activation.cc | 6 +-
test/singa/test_adagrad.cc | 8 +-
test/singa/test_cross_entropy.cc | 8 +-
test/singa/test_cudnn_activation.cc | 6 +-
test/singa/test_cudnn_batchnorm.cc | 8 +-
test/singa/test_cudnn_convolution.cc | 16 ++--
test/singa/test_cudnn_dropout.cc | 10 +--
test/singa/test_cudnn_lrn.cc | 4 +-
test/singa/test_cudnn_pooling.cc | 4 +-
test/singa/test_cudnn_softmax.cc | 12 +--
test/singa/test_decoder.cc | 61 +++++++-------
test/singa/test_dense.cc | 16 ++--
test/singa/test_dropout.cc | 10 +--
test/singa/test_flatten.cc | 8 +-
test/singa/test_initializer.cc | 14 ++--
test/singa/test_mse.cc | 8 +-
test/singa/test_nesterov.cc | 8 +-
test/singa/test_prelu.cc | 12 +--
test/singa/test_rmsprop.cc | 8 +-
test/singa/test_sgd.cc | 16 ++--
test/singa/test_softmax.cc | 6 +-
test/singa/test_tensor_math.cc | 130 +++++++++++++++---------------
34 files changed, 357 insertions(+), 322 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/CMakeLists.txt
----------------------------------------------------------------------
diff --git a/CMakeLists.txt b/CMakeLists.txt
index c61f8a4..87b3a5d 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -18,11 +18,10 @@ SET(SINGA_INCLUDE_DIR "${CMAKE_SOURCE_DIR}/include;${PROJECT_BINARY_DIR}")
#message(STATUS "include path: ${SINGA_INCLUDE_DIR}")
INCLUDE_DIRECTORIES(${SINGA_INCLUDE_DIR})
-#OPTION(CPU_ONLY "use GPU libs" OFF)
OPTION(USE_CBLAS "Use CBlas libs" ON)
OPTION(USE_CUDA "Use Cuda libs" ON)
OPTION(USE_CUDNN "Use Cudnn libs" ON)
-OPTION(USE_OPENCV "Use opencv" ON)
+OPTION(USE_OPENCV "Use opencv" OFF)
OPTION(USE_LMDB "Use LMDB libs" OFF)
OPTION(USE_PYTHON "Generate py wrappers" OFF)
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/cmake/Templates/singa_config.h.in
----------------------------------------------------------------------
diff --git a/cmake/Templates/singa_config.h.in b/cmake/Templates/singa_config.h.in
index 5e8b32d..d6d3eeb 100644
--- a/cmake/Templates/singa_config.h.in
+++ b/cmake/Templates/singa_config.h.in
@@ -7,6 +7,8 @@
#cmakedefine CPU_ONLY
#cmakedefine USE_CBLAS
+
+#cmakedefine USE_OPENCV
// cuda
#cmakedefine USE_CUDA
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/include/singa/core/tensor.h
----------------------------------------------------------------------
diff --git a/include/singa/core/tensor.h b/include/singa/core/tensor.h
index 5dfcab2..7e51f97 100644
--- a/include/singa/core/tensor.h
+++ b/include/singa/core/tensor.h
@@ -34,7 +34,7 @@ namespace singa {
typedef vector<size_t> Shape;
/// hardcode the width of types defined in DataType
const size_t kDataWidth[] = {sizeof(float), sizeof(float) / 2, sizeof(int),
- sizeof(char), sizeof(double)};
+ sizeof(char), sizeof(double), sizeof(unsigned char)};
inline size_t SizeOf(DataType t) {
static_assert(kNumDataType == sizeof(kDataWidth) / sizeof(size_t),
"Num of data types not match num of data width");
@@ -73,8 +73,8 @@ class Tensor {
/// return immutable Tensor values with given type.
template <typename SType>
- SType data() const {
- return static_cast<SType>(block()->data());
+ const SType* data() const {
+ return static_cast<const SType*>(block()->data());
}
/// data type, including kFloat16, kFloat32, kInt
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/include/singa/io/decoder.h
----------------------------------------------------------------------
diff --git a/include/singa/io/decoder.h b/include/singa/io/decoder.h
index 003dd59..dad2231 100644
--- a/include/singa/io/decoder.h
+++ b/include/singa/io/decoder.h
@@ -22,30 +22,35 @@
#include <vector>
#include <string>
#include "singa/core/tensor.h"
-#include "singa/proto/model.pb.h"
+#include "singa/proto/io.pb.h"
namespace singa {
-namespace io {
-
+/// The base decoder that converts a string into a set of tensors.
class Decoder {
- public:
- Decoder() { }
- virtual ~Decoder() { }
+ public:
+ Decoder() { }
+ virtual ~Decoder() { }
- virtual void Setup(const DecoderConf& conf) = 0;
+ virtual void Setup(const DecoderConf& conf) {}
- /**
- * Decode value to get data and labels
- */
- virtual std::vector<Tensor> Decode(std::string value) = 0;
+ /// Decode value to get data and labels
+ virtual std::vector<Tensor> Decode(std::string value) = 0;
};
+#ifdef USE_OPENCV
+/// Decode the string as an ImageRecord object and convert it into a image
+/// tensor (dtype is kFloat32) and a label tensor (dtype is kInt).
class Proto2JPGDecoder : public Decoder {
- public:
- void Setup(const DecoderConf& conf) override;
- std::vector<Tensor> Decode(std::string value) override;
+ public:
+ void Setup(const DecoderConf& conf) override {
+ image_dim_order_ = conf.image_dim_order();
+ }
+ std::vector<Tensor> Decode(std::string value) override;
+
+ private:
+ /// Indicate the dimension order for the output image tensor.
+ std::string image_dim_order_ = "CHW";
};
-
-} // namespace io
+#endif
} // namespace singa
#endif // SINGA_IO_DECODER_H_
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/include/singa/io/encoder.h
----------------------------------------------------------------------
diff --git a/include/singa/io/encoder.h b/include/singa/io/encoder.h
index 5a8dbeb..5c1f242 100644
--- a/include/singa/io/encoder.h
+++ b/include/singa/io/encoder.h
@@ -22,32 +22,40 @@
#include <vector>
#include <string>
#include "singa/core/tensor.h"
-#include "singa/proto/model.pb.h"
+#include "singa/proto/io.pb.h"
namespace singa {
-namespace io {
+/// Base encoder class that convert a set of tensors into string for storage.
class Encoder {
- public:
- Encoder() { }
- virtual ~Encoder() { }
-
- virtual void Setup(const EncoderConf& conf) = 0;
-
- /**
- * Format each sample data as a string,
- * whose structure depends on the proto definition.
- * e.g., {key, shape, label, type, data, ...}
- */
- virtual std::string Encode(vector<Tensor>& data) = 0;
+ public:
+ Encoder() {}
+ virtual ~Encoder() {}
+
+ virtual void Setup(const EncoderConf& conf) {}
+
+ /// Format each sample data as a string,
+ /// whose structure depends on the proto definition.
+ virtual std::string Encode(vector<Tensor>& data) = 0;
};
+#ifdef USE_OPENCV
+/// Convert an image and its label into an ImageRecord (protobuf message).
class JPG2ProtoEncoder : public Encoder {
- public:
- void Setup(const EncoderConf& conf) override;
- std::string Encode(vector<Tensor>& data) override;
-};
+ public:
+ void Setup(const EncoderConf& conf) override {
+ image_dim_order_ = conf.image_dim_order();
+ }
+ /// 'data' has two tesors, one for the image pixels (3D) and one for the
+ /// label. The image tensor's data type is kUChar.
+ /// The dimension order is indicated in the EncoderConf, i.e. image_dim_order.
+ /// The label tensor's data type is kInt.
+ std::string Encode(vector<Tensor>& data) override;
-} // namespace io
+ private:
+ /// Indicate the input image tensor's dimension order.
+ std::string image_dim_order_ = "HWC";
+};
+#endif // USE_OPENCV
} // namespace singa
#endif // SINGA_IO_ENCODER_H_
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/src/core/tensor/tensor.cc
----------------------------------------------------------------------
diff --git a/src/core/tensor/tensor.cc b/src/core/tensor/tensor.cc
index 8afc17c..3aa5c0a 100644
--- a/src/core/tensor/tensor.cc
+++ b/src/core/tensor/tensor.cc
@@ -133,6 +133,8 @@ void Tensor::CopyDataFromHostPtr(const DType *src, const size_t num) {
LOG(WARNING) << "Copy data from null host ptr";
}
}
+template void Tensor::CopyDataFromHostPtr(const unsigned char *src,
+ const size_t num);
template void Tensor::CopyDataFromHostPtr(const float *src, const size_t num);
template void Tensor::CopyDataFromHostPtr(const int *src, const size_t num);
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/src/io/jpg2proto_encoder.cc
----------------------------------------------------------------------
diff --git a/src/io/jpg2proto_encoder.cc b/src/io/jpg2proto_encoder.cc
index 5b006e1..c5d81b8 100644
--- a/src/io/jpg2proto_encoder.cc
+++ b/src/io/jpg2proto_encoder.cc
@@ -17,54 +17,67 @@
*/
#include "singa/io/encoder.h"
-#include "singa/proto/model.pb.h"
+
+#ifdef USE_OPENCV
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
namespace singa {
-namespace io{
- void JPG2ProtoEncoder::Setup(const EncoderConf& conf) { return; }
-
- std::string JPG2ProtoEncoder::Encode(vector<Tensor>& data) {
- // suppose data[0]: data, data[1]: label
- // data[0] has a shape as {height, width, channel}
- CHECK_EQ(data[0].nDim(), 3u);
- int height = data[0].shape()[0];
- int width = data[0].shape()[1];
- int channel = data[0].shape()[2];
- cv::Mat mat = cv::Mat(height, width, CV_8UC3, cv::Scalar(0, 0, 0));
- CHECK_EQ(height, mat.rows);
- CHECK_EQ(width, mat.cols);
- CHECK_EQ(channel, mat.channels());
+std::string JPG2ProtoEncoder::Encode(vector<Tensor>& data) {
+ // suppose image: image, data[1]: label
+ CHECK_LE(data.size(), 2u);
+ const Tensor& image = data.at(0);
+ CHECK_EQ(image.nDim(), 3u);
+ CHECK_EQ(image.data_type(), kUChar) << "Data type " << image.data_type()
+ << " is invalid for an raw image";
+ const auto* raw = image.data<unsigned char>();
+ cv::Mat mat;
+ if (image_dim_order_ == "HWC") {
+ size_t height = image.shape(0), width = image.shape(1),
+ channel = image.shape(2);
+ mat = cv::Mat(height, width, CV_8UC3, cv::Scalar(0, 0, 0));
+ for (size_t i = 0; i < height; i++)
+ for (size_t j = 0; j < width; j++)
+ for (size_t k = 0; k < channel; k++)
+ mat.at<cv::Vec3b>(i, j)[k] =
+ raw[i * width * channel + j * channel + k];
+ } else if (image_dim_order_ == "CHW") {
+ size_t channel = image.shape(0), height = image.shape(1),
+ width = image.shape(2);
+ mat = cv::Mat(height, width, CV_8UC3, cv::Scalar(0, 0, 0));
+ for (size_t i = 0; i < height; i++)
+ for (size_t j = 0; j < width; j++)
+ for (size_t k = 0; k < channel; k++)
+ mat.at<cv::Vec3b>(i, j)[k] = raw[k * height * width + i * width + j];
+ } else {
+ LOG(FATAL) << "Unknow dimension order for images " << image_dim_order_
+ << " Only support 'HWC' and 'CHW'";
+ }
- if (data[0].data_type() != kInt)
- LOG(FATAL) << "Data type " << data[0].data_type() <<" is invalid for an raw image";
- const int* raw = data[0].data<const int*>();
- for (int i = 0; i < height; i++)
- for (int j = 0; j < width; j++)
- for (int k = 0; k < channel; k++)
- mat.at<cv::Vec3b>(i, j)[k] = static_cast<uchar>(raw[i * width * channel + j * channel + k]);
- // suppose each image is attached with only one label
- const int* label = data[1].data<const int*>();
- CHECK_EQ(label[0], 2);
+ // encode image with jpg format
+ std::vector<uchar> buff;
+ std::vector<int> param = std::vector<int>(2);
+ param[0] = CV_IMWRITE_JPEG_QUALITY;
+ param[1] = 100; // default is 95
+ cv::imencode(".jpg", mat, buff, param);
+ std::string buf(buff.begin(), buff.end());
- // encode image with jpg format
- std::vector<uchar> buff;
- std::vector<int> param = std::vector<int>(2);
- param[0] = CV_IMWRITE_JPEG_QUALITY;
- param[1] = 100; // default is 95
- cv::imencode(".jpg", mat, buff, param);
- std::string buf(buff.begin(), buff.end());
+ std::string output;
+ ImageRecord record;
+ for (size_t i = 0; i < image.nDim(); i++)
+ record.add_shape(image.shape(i));
+ record.set_pixel(buf);
- std::string output;
- ImageRecordProto image;
- image.set_label(label[0]);
- for (size_t i = 0; i < data[0].nDim(); i++)
- image.add_shape(data[0].shape()[i]);
- image.set_pixel(buf);
- image.SerializeToString(&output);
- return output;
+ // suppose each image is attached with at most one label
+ if (data.size() == 2) {
+ const int* label = data[1].data<int>();
+ CHECK_EQ(label[0], 2);
+ record.add_label(label[0]);
}
+
+ record.SerializeToString(&output);
+ return output;
}
-}
+} // namespace singa
+#endif // USE_OPENCV
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/src/io/proto2jpg_decoder.cc
----------------------------------------------------------------------
diff --git a/src/io/proto2jpg_decoder.cc b/src/io/proto2jpg_decoder.cc
index fd8d9b3..0125ea3 100644
--- a/src/io/proto2jpg_decoder.cc
+++ b/src/io/proto2jpg_decoder.cc
@@ -17,41 +17,59 @@
*/
#include "singa/io/decoder.h"
-#include "singa/proto/model.pb.h"
+
+#ifdef USE_OPENCV
+
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
namespace singa {
-namespace io {
- void Proto2JPGDecoder::Setup(const DecoderConf& conf) { return; }
-
- std::vector<Tensor> Proto2JPGDecoder::Decode(std::string value) {
- std::vector<Tensor> output;
- ImageRecordProto image;
- image.ParseFromString(value);
- Shape shape(image.shape().begin(), image.shape().end());
- Tensor raw(shape), label(Shape{1});
- std::vector<uchar> pixel(image.pixel().begin(), image.pixel().end());
-
- // decode image
- cv::Mat mat = cv::imdecode(cv::Mat(pixel), CV_LOAD_IMAGE_COLOR);
- int height = mat.rows, width = mat.cols, channel = mat.channels();
- CHECK_EQ(shape[0], height);
- CHECK_EQ(shape[1], width);
- CHECK_EQ(shape[2], channel);
-
- float* data = new float[raw.Size()];
- for (int i = 0; i < height; i++)
- for (int j = 0; j < width; j++)
- for (int k = 0; k < channel; k++)
- data[i * width * channel + j * channel + k] = static_cast<float>(static_cast<int>(mat.at<cv::Vec3b>(i, j)[k]));
- raw.CopyDataFromHostPtr<float>(data, raw.Size());
- float l = static_cast<float>(image.label());
- label.CopyDataFromHostPtr(&l, 1);
- output.push_back(raw);
+std::vector<Tensor> Proto2JPGDecoder::Decode(std::string value) {
+ std::vector<Tensor> output;
+
+ ImageRecord record;
+ record.ParseFromString(value);
+ std::vector<uchar> pixel(record.pixel().begin(), record.pixel().end());
+
+ // decode image
+ cv::Mat mat = cv::imdecode(cv::Mat(pixel), CV_LOAD_IMAGE_COLOR);
+ size_t height = mat.rows, width = mat.cols, channel = mat.channels();
+ Shape shape(record.shape().begin(), record.shape().end());
+ CHECK_EQ(shape[0], height);
+ CHECK_EQ(shape[1], width);
+ CHECK_EQ(shape[2], channel);
+ Tensor image(shape);
+
+ float* data = new float[image.Size()];
+ if (image_dim_order_ == "CHW") {
+ for (size_t i = 0; i < height; i++)
+ for (size_t j = 0; j < width; j++)
+ for (size_t k = 0; k < channel; k++)
+ data[k * height * width + i * width + j] = static_cast<float>(
+ static_cast<int>(mat.at<cv::Vec3b>(i, j)[k]));
+ } else if (image_dim_order_ == "HWC") {
+
+ for (size_t i = 0; i < height; i++)
+ for (size_t j = 0; j < width; j++)
+ for (size_t k = 0; k < channel; k++)
+ data[i * width * channel + j * channel + k] =
+ static_cast<float>(static_cast<int>(mat.at<cv::Vec3b>(i, j)[k]));
+ } else {
+ LOG(FATAL) << "Unknow dimension order for images " << image_dim_order_
+ << " Only support 'HWC' and 'CHW'";
+ }
+ image.CopyDataFromHostPtr<float>(data, image.Size());
+ output.push_back(image);
+ delete data;
+
+ if (record.label_size()) {
+ Tensor label(Shape{1}, &defaultDevice, kInt);
+ int labelid = record.label(0);
+ label.CopyDataFromHostPtr(&labelid, 1);
output.push_back(label);
- return output;
}
+ return output;
}
-}
+} // namespace singa
+#endif
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/src/model/layer/prelu.cc
----------------------------------------------------------------------
diff --git a/src/model/layer/prelu.cc b/src/model/layer/prelu.cc
index 6c58dbb..83a56fa 100644
--- a/src/model/layer/prelu.cc
+++ b/src/model/layer/prelu.cc
@@ -63,7 +63,9 @@ const Tensor PReLU::Forward(int flag, const Tensor &input) {
output = input * ((input > 0.f) + temp);
} else {
// share the first param of Tensor A along all channels
- const float a = a_.data<const float *>()[0];
+ LOG(FATAL) << "Not implemented";
+ // TODO(wangwei) cannot access the data in this way. The data could be on GPU.
+ auto a = a_.data<float>()[0];
output = input * ((input > 0.f) + (input <= 0.f) * a);
}
if (flag & kTrain) buf_.push(input);
@@ -122,7 +124,9 @@ const std::pair<Tensor, vector<Tensor> > PReLU::Backward(int flag,
}
} else {
// share the first param of Tensor A along all channels
- const float a = a_.data<const float *>()[0];
+ LOG(FATAL) << "Not Implemented";
+ // TODO(wangwei) cannot access the data in this way. The data could be on GPU.
+ auto a = a_.data<float>()[0];
input_grad = grad * input * ((input > 0.f) + (input <= 0.f) * a);
Tensor temp = grad * input * (input <= 0.f);
float sum = Sum<float>(temp);
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/src/model/metric/accuracy.h
----------------------------------------------------------------------
diff --git a/src/model/metric/accuracy.h b/src/model/metric/accuracy.h
index fb23634..69bd96b 100644
--- a/src/model/metric/accuracy.h
+++ b/src/model/metric/accuracy.h
@@ -49,7 +49,8 @@ Tensor Accuracy::Match(const Tensor& prediction, const vector<int>& target) {
size_t nb_classes = prediction.Size() / batchsize;
// each row of prediction is the prob distribution for one sample
CHECK_EQ(prediction.shape().at(0), batchsize);
- const float* prob = prediction.data<const float*>();
+ // TODO(wangwei) CloneToDevice(host);
+ const float* prob = prediction.data<float>();
float* score = new float[batchsize];
for (size_t b = 0; b < batchsize; b++) {
vector<std::pair<float, int>> prob_class;
@@ -72,7 +73,7 @@ Tensor Accuracy::Match(const Tensor& prediction, const vector<int>& target) {
Tensor Accuracy::Forward(const Tensor& prediction, const Tensor& target) {
vector<int> target_vec;
// TODO(wangwei) copy target to host.
- const int* target_value = target.data<const int*>();
+ const int* target_value = target.data<int>();
for (size_t i = 0; i < target.Size(); i++)
target_vec.push_back(target_value[i]);
return Match(prediction, target_vec);
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/src/proto/core.proto
----------------------------------------------------------------------
diff --git a/src/proto/core.proto b/src/proto/core.proto
index 88d7f12..3031359 100644
--- a/src/proto/core.proto
+++ b/src/proto/core.proto
@@ -27,7 +27,8 @@ enum DataType {
kInt = 2;
kChar = 3;
kDouble = 4;
- kNumDataType = 5;
+ kUChar = 5;
+ kNumDataType = 6;
}
enum LangType {
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/src/proto/model.proto
----------------------------------------------------------------------
diff --git a/src/proto/model.proto b/src/proto/model.proto
index 8666c30..c06deec 100644
--- a/src/proto/model.proto
+++ b/src/proto/model.proto
@@ -51,21 +51,6 @@ message BlobProto {
optional int32 width = 4 [default = 0];
}
-// rename RecordProto to ImageRecordProto
-message ImageRecordProto {
- repeated int32 shape = 1;
- optional int32 label = 2;
- optional bytes pixel = 3;
-}
-
-message EncoderConf {
- optional string type = 1 [default = 'jpg'];
-}
-
-message DecoderConf {
- optional string type = 1 [default = 'jpg'];
-}
-
message FillerConf {
// The filler type, case insensitive
optional string type = 1 [default = 'constant'];
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_activation.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_activation.cc b/test/singa/test_activation.cc
index 504d599..4b76d68 100644
--- a/test/singa/test_activation.cc
+++ b/test/singa/test_activation.cc
@@ -60,7 +60,7 @@ TEST(Activation, Forward) {
singa::Tensor out = acti.Forward(singa::kTrain, in);
- const float* yptr = out.data<const float*>();
+ const float* yptr = out.data<float>();
EXPECT_EQ(n, out.Size());
float* y = new float[n];
@@ -104,13 +104,13 @@ TEST(Activation, Backward) {
acti.Setup(Shape{n}, conf);
singa::Tensor out = acti.Forward(singa::kTrain, in);
- const float* yptr = out.data<const float*>();
+ const float* yptr = out.data<float>();
const float grad[] = {2.0f, -3.0f, 1.0f, 3.0f, -1.0f, -2.0};
singa::Tensor out_diff(singa::Shape{n});
out_diff.CopyDataFromHostPtr<float>(grad, n);
const auto in_diff = acti.Backward(singa::kTrain, out_diff);
- const float* xptr = in_diff.first.data<const float*>();
+ const float* xptr = in_diff.first.data<float>();
float* dx = new float[n];
if (acti.Mode() == "SIGMOID") {
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_adagrad.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_adagrad.cc b/test/singa/test_adagrad.cc
index ef930d5..642e929 100644
--- a/test/singa/test_adagrad.cc
+++ b/test/singa/test_adagrad.cc
@@ -39,7 +39,7 @@ TEST(Adagrad, ApplyCPU) {
adagrad.Apply(0, lr, "xx", grad, &value);
singa::Tensor v1 = value.Clone();
- const float* newv1 = v1.data<const float*>();
+ const float* newv1 = v1.data<float>();
float history[4];
for (int i = 0; i < 4; ++i) history[i] = g[i] * g[i];
for (int i = 0; i < 4; ++i)
@@ -49,7 +49,7 @@ TEST(Adagrad, ApplyCPU) {
grad.CopyDataFromHostPtr(g, 4);
adagrad.Apply(1, lr, "xx", grad, &value);
singa::Tensor v2 = value.Clone();
- const float* newv2 = v2.data<const float*>();
+ const float* newv2 = v2.data<float>();
for (int i = 0; i < 4; ++i) history[i] += g[i] * g[i];
for (int i = 0; i < 4; ++i)
@@ -75,7 +75,7 @@ TEST(Adagrad, ApplyCUDA) {
singa::Tensor v1 = value.Clone();
v1.ToHost();
- const float* newv1 = v1.data<const float*>();
+ const float* newv1 = v1.data<float>();
float history[4];
for (int i = 0; i < 4; ++i) history[i] = g[i] * g[i];
for (int i = 0; i < 4; ++i)
@@ -86,7 +86,7 @@ TEST(Adagrad, ApplyCUDA) {
adagrad.Apply(1, lr, "xx", grad, &value);
singa::Tensor v2 = value.Clone();
v2.ToHost();
- const float* newv2 = v2.data<const float*>();
+ const float* newv2 = v2.data<float>();
for (int i = 0; i < 4; ++i) history[i] += g[i] * g[i];
for (int i = 0; i < 4; ++i)
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_cross_entropy.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_cross_entropy.cc b/test/singa/test_cross_entropy.cc
index 0eb36e5..ce60f7c 100644
--- a/test/singa/test_cross_entropy.cc
+++ b/test/singa/test_cross_entropy.cc
@@ -45,7 +45,7 @@ TEST_F(TestSoftmaxCrossEntropy, CppForward) {
singa::SoftmaxCrossEntropy cross_entropy;
const Tensor& loss = cross_entropy.Forward(p, t);
- auto ldat = loss.data<const float*>();
+ auto ldat = loss.data<float>();
const float result_test = -log(0.25);
EXPECT_FLOAT_EQ(ldat[0], result_test);
@@ -61,7 +61,7 @@ TEST_F(TestSoftmaxCrossEntropy, CppBackward) {
cross_entropy.Forward(p, t);
const Tensor& grad = cross_entropy.Backward();
- auto gdat = grad.data<const float*>();
+ auto gdat = grad.data<float>();
EXPECT_FLOAT_EQ(gdat[0], -0.75);
EXPECT_FLOAT_EQ(gdat[1], 0.25);
EXPECT_FLOAT_EQ(gdat[2], 0.25);
@@ -84,7 +84,7 @@ TEST_F(TestSoftmaxCrossEntropy, CudaForward) {
Tensor loss = cross_entropy.Forward(p, t);
loss.ToHost();
- auto ldat = loss.data<const float*>();
+ auto ldat = loss.data<float>();
const float result_test = -log(0.25);
EXPECT_FLOAT_EQ(ldat[0], result_test);
@@ -103,7 +103,7 @@ TEST_F(TestSoftmaxCrossEntropy, CudaBackward) {
Tensor grad = cross_entropy.Backward();
grad.ToHost();
- auto gdat = grad.data<const float*>();
+ auto gdat = grad.data<float>();
EXPECT_FLOAT_EQ(gdat[0], -0.75);
EXPECT_FLOAT_EQ(gdat[1], 0.25);
EXPECT_FLOAT_EQ(gdat[2], 0.25);
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_cudnn_activation.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_cudnn_activation.cc b/test/singa/test_cudnn_activation.cc
index da8ec62..940c6b9 100644
--- a/test/singa/test_cudnn_activation.cc
+++ b/test/singa/test_cudnn_activation.cc
@@ -67,7 +67,7 @@ TEST(TCudnnActivation, Forward) {
EXPECT_EQ(n, out.Size());
singa::CppCPU host(0, 1);
out.ToDevice(&host);
- const float* yptr = out.data<const float*>();
+ const float* yptr = out.data<float>();
float* y = new float[n];
if (acti.Mode() == "SIGMOID") {
for (size_t i = 0; i < n; i++) y[i] = 1.f / (1.f + exp(-x[i]));
@@ -105,7 +105,7 @@ TEST(TCudnnActivation, Backward) {
EXPECT_EQ(n, out.Size());
singa::CppCPU host(0, 1);
out.ToDevice(&host);
- const float* yptr = out.data<const float*>();
+ const float* yptr = out.data<float>();
const float grad[] = {2.0f, 1.0f, 2.0f, 0.0f, -2.0f,
-1.0, 1.5, 2.5, -1.5, -2.5};
@@ -114,7 +114,7 @@ TEST(TCudnnActivation, Backward) {
const auto ret = acti.Backward(singa::kTrain, out_diff);
singa::Tensor in_diff = ret.first;
in_diff.ToDevice(&host);
- const float* xptr = in_diff.data<const float*>();
+ const float* xptr = in_diff.data<float>();
float* dx = new float[n];
if (acti.Mode() == "SIGMOID") {
for (size_t i = 0; i < n; i++) dx[i] = grad[i] * yptr[i] * (1. - yptr[i]);
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_cudnn_batchnorm.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_cudnn_batchnorm.cc b/test/singa/test_cudnn_batchnorm.cc
index ba090cb..b3b6477 100644
--- a/test/singa/test_cudnn_batchnorm.cc
+++ b/test/singa/test_cudnn_batchnorm.cc
@@ -77,7 +77,7 @@ TEST(CudnnBatchNorm, Forward) {
singa::Tensor out = batchnorm.Forward(singa::kTrain, in);
singa::CppCPU host(0, 1);
out.ToHost();
- const float *outptr = out.data<const float *>();
+ const float *outptr = out.data<float>();
const auto & shape = out.shape();
EXPECT_EQ(4u, shape.size());
EXPECT_EQ(1u, shape[0]);
@@ -178,7 +178,7 @@ TEST(CudnnBatchNorm, Backward) {
singa::CppCPU host(0, 1);
singa::Tensor dx = ret.first;
dx.ToDevice(&host);
- const float *dxptr = dx.data<const float *>();
+ const float *dxptr = dx.data<float>();
const auto & shape = dx.shape();
EXPECT_EQ(4u, shape.size());
EXPECT_EQ(1u, shape[0]);
@@ -220,7 +220,7 @@ TEST(CudnnBatchNorm, Backward) {
singa::Tensor dbnScale = ret.second.at(0);
dbnScale.ToDevice(&host);
- const float *dbnScaleptr = dbnScale.data<const float *>();
+ const float *dbnScaleptr = dbnScale.data<float>();
const auto & dbnScaleShape = dbnScale.shape();
EXPECT_EQ(4u, dbnScaleShape.size());
EXPECT_EQ(1u, dbnScaleShape[0]);
@@ -233,7 +233,7 @@ TEST(CudnnBatchNorm, Backward) {
singa::Tensor dbnBias = ret.second.at(1);
dbnBias.ToDevice(&host);
- const float *dbnBiasptr = dbnBias.data<const float *>();
+ const float *dbnBiasptr = dbnBias.data<float>();
const auto & dbnBiasShape = dbnBias.shape();
EXPECT_EQ(4u, dbnBiasShape.size());
EXPECT_EQ(1u, dbnBiasShape[0]);
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_cudnn_convolution.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_cudnn_convolution.cc b/test/singa/test_cudnn_convolution.cc
index 3aa70dd..44077b7 100644
--- a/test/singa/test_cudnn_convolution.cc
+++ b/test/singa/test_cudnn_convolution.cc
@@ -99,7 +99,7 @@ TEST(CudnnConvolution, Forward) {
singa::Tensor out1 = conv.Forward(singa::kTrain, in);
singa::CppCPU host(0, 1);
out1.ToDevice(&host);
- const float *outptr1 = out1.data<const float *>();
+ const float *outptr1 = out1.data<float>();
// Input: 3*3; kernel: 3*3; stride: 2*2; padding: 1*1.
EXPECT_EQ(4u, out1.Size());
@@ -161,7 +161,7 @@ TEST(CudnnConvolution, Backward) {
singa::CppCPU host(0, 1);
singa::Tensor in_grad = ret.first;
in_grad.ToDevice(&host);
- const float *dx = in_grad.data<const float *>();
+ const float *dx = in_grad.data<float>();
const float *wptr = we;
EXPECT_EQ(9u, in_grad.Size());
EXPECT_EQ(dy[0] * wptr[4], dx[0]);
@@ -180,10 +180,10 @@ TEST(CudnnConvolution, Backward) {
singa::Tensor db = ret.second[1];
dw.ToDevice(&host);
db.ToDevice(&host);
- const float *dbptr = db.data<const float *>();
+ const float *dbptr = db.data<float>();
EXPECT_EQ(dy[0] + dy[1] + dy[2] + dy[3], dbptr[0]);
- const float *dwptr = dw.data<const float *>();
+ const float *dwptr = dw.data<float>();
EXPECT_EQ(9u, dw.Size());
EXPECT_EQ(dy[3] * x[4], dwptr[0]);
EXPECT_EQ(dy[3] * x[5] + dy[2] * x[3], dwptr[1]);
@@ -271,7 +271,7 @@ TEST(CudnnConvolution_AT, Forward) {
singa::Tensor out1 = conv.Forward(singa::kTrain, in);
singa::CppCPU host(0, 1);
out1.ToDevice(&host);
- const float *outptr1 = out1.data<const float *>();
+ const float *outptr1 = out1.data<float>();
// Input: 3*3; kernel: 3*3; stride: 2*2; padding: 1*1.
EXPECT_EQ(4u, out1.Size());
@@ -333,7 +333,7 @@ TEST(CudnnConvolution_AT, Backward) {
singa::CppCPU host(0, 1);
singa::Tensor in_grad = ret.first;
in_grad.ToDevice(&host);
- const float *dx = in_grad.data<const float *>();
+ const float *dx = in_grad.data<float>();
const float *wptr = we;
EXPECT_EQ(9u, in_grad.Size());
EXPECT_EQ(dy[0] * wptr[4], dx[0]);
@@ -352,10 +352,10 @@ TEST(CudnnConvolution_AT, Backward) {
singa::Tensor db = ret.second[1];
dw.ToDevice(&host);
db.ToDevice(&host);
- const float *dbptr = db.data<const float *>();
+ const float *dbptr = db.data<float>();
EXPECT_EQ(dy[0] + dy[1] + dy[2] + dy[3], dbptr[0]);
- const float *dwptr = dw.data<const float *>();
+ const float *dwptr = dw.data<float>();
EXPECT_EQ(9u, dw.Size());
EXPECT_EQ(dy[3] * x[4], dwptr[0]);
EXPECT_EQ(dy[3] * x[5] + dy[2] * x[3], dwptr[1]);
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_cudnn_dropout.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_cudnn_dropout.cc b/test/singa/test_cudnn_dropout.cc
index b8ce068..419dd0c 100644
--- a/test/singa/test_cudnn_dropout.cc
+++ b/test/singa/test_cudnn_dropout.cc
@@ -64,13 +64,13 @@ TEST(CudnnDropout, Forward) {
singa::Tensor mask(drop.mask().shape(), drop.mask().data_type());
mask.CopyData(drop.mask());
- const char* mptr = mask.data<const char*>();
+ const char* mptr = mask.data<char>();
for (size_t i = 0; i < n; i++)
EXPECT_FLOAT_EQ(0, GetBitValue(mptr, i) * (GetBitValue(mptr, i) - 1));
singa::CppCPU host(0, 1);
out1.ToDevice(&host);
- const float* outptr1 = out1.data<const float*>();
+ const float* outptr1 = out1.data<float>();
EXPECT_EQ(n, out1.Size());
float scale = 1.0f / (1.0f - pdrop);
// the output value should be 0 or the same as the input
@@ -81,7 +81,7 @@ TEST(CudnnDropout, Forward) {
singa::Tensor out2 = drop.Forward(singa::kEval, in);
out2.ToDevice(&host);
EXPECT_EQ(n, out2.Size());
- const float* outptr2 = out2.data<const float*>();
+ const float* outptr2 = out2.data<float>();
// the output value should be the same as the input
EXPECT_EQ(x[0], outptr2[0]);
EXPECT_EQ(x[1], outptr2[1]);
@@ -113,11 +113,11 @@ TEST(CudnnDropout, Backward) {
singa::CppCPU host(0, 1);
singa::Tensor in_grad = ret.first;
in_grad.ToDevice(&host);
- const float* dx = in_grad.data<const float*>();
+ const float* dx = in_grad.data<float>();
singa::Tensor mask(drop.mask().shape(), drop.mask().data_type());
mask.CopyData(drop.mask());
- const char* mptr = mask.data<const char*>();
+ const char* mptr = mask.data<char>();
EXPECT_FLOAT_EQ(dx[0], dy[0] * GetBitValue(mptr, 0) * scale);
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_cudnn_lrn.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_cudnn_lrn.cc b/test/singa/test_cudnn_lrn.cc
index 8576943..f7ec046 100644
--- a/test/singa/test_cudnn_lrn.cc
+++ b/test/singa/test_cudnn_lrn.cc
@@ -73,7 +73,7 @@ TEST(CudnnLRN, Forward) {
singa::Tensor out = lrn.Forward(singa::kTrain, in);
singa::CppCPU host(0, 1);
out.ToDevice(&host);
- const float *outptr = out.data<const float *>();
+ const float *outptr = out.data<float>();
const auto & shape = out.shape();
EXPECT_EQ(4u, shape.size());
EXPECT_EQ(1u, shape[0]);
@@ -159,7 +159,7 @@ TEST(CudnnLRN, Backward) {
singa::CppCPU host(0, 1);
singa::Tensor dx = ret.first;
dx.ToDevice(&host);
- const float *dxptr = dx.data<const float *>();
+ const float *dxptr = dx.data<float>();
const auto & shape = dx.shape();
EXPECT_EQ(4u, shape.size());
EXPECT_EQ(1u, shape[0]);
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_cudnn_pooling.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_cudnn_pooling.cc b/test/singa/test_cudnn_pooling.cc
index c7f9061..2a98ab4 100644
--- a/test/singa/test_cudnn_pooling.cc
+++ b/test/singa/test_cudnn_pooling.cc
@@ -76,7 +76,7 @@ TEST(CudnnPooling, Forward) {
singa::Tensor out1 = pool.Forward(singa::kTrain, in);
singa::CppCPU host(0, 1);
out1.ToDevice(&host);
- const float *outptr1 = out1.data<const float *>();
+ const float *outptr1 = out1.data<float>();
// Input: 3*3; kernel: 2*2; stride: 1*1; no padding.
EXPECT_EQ(4u, out1.Size());
EXPECT_EQ(5.0f, outptr1[0]);
@@ -118,7 +118,7 @@ TEST(CudnnPooling, Backward) {
singa::CppCPU host(0, 1);
singa::Tensor in_grad = ret.first;
in_grad.ToDevice(&host);
- const float *dx = in_grad.data<const float *>();
+ const float *dx = in_grad.data<float>();
EXPECT_EQ(9u, in_grad.Size());
EXPECT_EQ(0.0f, dx[0]);
EXPECT_EQ(0.0f, dx[1]);
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_cudnn_softmax.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_cudnn_softmax.cc b/test/singa/test_cudnn_softmax.cc
index 067491f..53ecb2b 100644
--- a/test/singa/test_cudnn_softmax.cc
+++ b/test/singa/test_cudnn_softmax.cc
@@ -56,7 +56,7 @@ TEST(CudnnSoftmax, Forward1D) {
singa::Tensor out = sft.Forward(singa::kTrain, in);
singa::CppCPU host(0, 1);
out.ToDevice(&host);
- const float* yptr = out.data<const float*>();
+ const float* yptr = out.data<float>();
EXPECT_EQ(n, out.Size());
float* y = new float[n];
@@ -83,7 +83,7 @@ TEST(CudnnSoftmax, Backward1D) {
singa::Tensor out = sft.Forward(singa::kTrain, in);
singa::CppCPU host(0, 1);
out.ToDevice(&host);
- const float* yptr = out.data<const float*>();
+ const float* yptr = out.data<float>();
const float grad[] = {2.f, -3.f, 1.f, 3.f, -1.f, -2.f};
singa::Tensor out_diff(shape, &cuda);
@@ -91,7 +91,7 @@ TEST(CudnnSoftmax, Backward1D) {
const auto ret = sft.Backward(singa::kTrain, out_diff);
singa::Tensor in_diff = ret.first;
in_diff.ToDevice(&host);
- const float* xptr = in_diff.data<const float*>();
+ const float* xptr = in_diff.data<float>();
float* dx = new float[n];
float sigma = 0.f;
@@ -118,7 +118,7 @@ TEST(CudnnSoftmax, Forward2D) {
singa::Tensor out = sft.Forward(singa::kTrain, in);
singa::CppCPU host(0, 1);
out.ToDevice(&host);
- const float* yptr = out.data<const float*>();
+ const float* yptr = out.data<float>();
EXPECT_EQ(n, out.Size());
float* y = new float[n];
@@ -147,7 +147,7 @@ TEST(CudnnSoftmax, Backward2D) {
singa::Tensor out = sft.Forward(singa::kTrain, in);
singa::CppCPU host(0, 1);
out.ToDevice(&host);
- const float* yptr = out.data<const float*>();
+ const float* yptr = out.data<float>();
const float grad[] = {2.f, -3.f, 1.f, 3.f, -1.f, -2.f};
singa::Tensor out_diff(shape, &cuda);
@@ -155,7 +155,7 @@ TEST(CudnnSoftmax, Backward2D) {
const auto ret = sft.Backward(singa::kTrain, out_diff);
singa::Tensor in_diff = ret.first;
in_diff.ToDevice(&host);
- const float* xptr = in_diff.data<const float*>();
+ const float* xptr = in_diff.data<float>();
float* dx = new float[n];
float* sigma = new float[batch];
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_decoder.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_decoder.cc b/test/singa/test_decoder.cc
index 33c4cd4..fa8683f 100644
--- a/test/singa/test_decoder.cc
+++ b/test/singa/test_decoder.cc
@@ -19,18 +19,19 @@
*
*************************************************************/
-#include "../include/singa/io/encoder.h"
-#include "../include/singa/io/decoder.h"
+#include "singa/io/encoder.h"
+#include "singa/io/decoder.h"
#include "gtest/gtest.h"
#include <time.h>
+
+#ifdef USE_OPENCV
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
-
-using namespace singa;
-
+using singa::Shape;
+using singa::Tensor;
TEST(Decoder, Decode) {
- io::JPG2ProtoEncoder encoder;
- io::Proto2JPGDecoder decoder;
+ singa::JPG2ProtoEncoder encoder;
+ singa::Proto2JPGDecoder decoder;
// initial random seed
srand(time(NULL));
@@ -38,50 +39,46 @@ TEST(Decoder, Decode) {
size_t height = 40, width = 30;
size_t nheight = 256, nwidth = 256, channel = 3;
size_t total = nheight * nwidth * channel;
- int raw_label = 2;
- cv::Mat image(height, width, CV_8UC3);
+ cv::Mat image(height, width, CV_8UC3);
for (size_t i = 0; i < height; i++)
for (size_t j = 0; j < width; j++)
for (size_t k = 0; k < channel; k++)
image.at<cv::Vec3b>(i, j)[k] = static_cast<uchar>(rand() % 256);
-
+
cv::Mat transformed;
cv::Size size(nwidth, nheight);
cv::resize(image, transformed, size);
- EXPECT_EQ(nwidth, transformed.cols);
- EXPECT_EQ(nheight, transformed.rows);
- EXPECT_EQ(channel, transformed.channels());
-
+ EXPECT_EQ(static_cast<int>(nwidth), transformed.cols);
+ EXPECT_EQ(static_cast<int>(nheight), transformed.rows);
+ EXPECT_EQ(static_cast<int>(channel), transformed.channels());
+
unsigned char* buff = transformed.data;
- int* buf = new int[total];
- for (size_t i = 0; i < total; i++)
- buf[i] = static_cast<int>(buff[i]);
Shape shape{nheight, nwidth, channel};
- Tensor pixel(shape, kInt), label(Shape{1}, kInt);
- pixel.CopyDataFromHostPtr<int>(buf, total);
+ Tensor pixel(shape, singa::kUChar), label(Shape{1}, singa::kInt);
+ pixel.CopyDataFromHostPtr<unsigned char>(buff, total);
+ int raw_label = 2;
label.CopyDataFromHostPtr<int>(&raw_label, 1);
std::vector<Tensor> input;
input.push_back(pixel);
- input.push_back(label);
- const int* in_pixel = input[0].data<const int *>();
- for(size_t i = 0; i < total; i++)
- EXPECT_EQ(buf[i], in_pixel[i]);
- const int* in_label = input[1].data<const int *>();
+ input.push_back(label);
+ const auto* in_pixel = input[0].data<unsigned char>();
+ for (size_t i = 0; i < total; i++) EXPECT_EQ(buff[i], in_pixel[i]);
+ const int* in_label = input[1].data<int>();
EXPECT_EQ(2, in_label[0]);
- EXPECT_EQ(2, input.size());
+ EXPECT_EQ(2u, input.size());
std::string tmp = encoder.Encode(input);
std::vector<Tensor> output = decoder.Decode(tmp);
- EXPECT_EQ(2, output.size());
- EXPECT_EQ(kFloat32, output[0].data_type());
+ EXPECT_EQ(2u, output.size());
+ EXPECT_EQ(singa::kFloat32, output[0].data_type());
Shape out_shape = output[0].shape();
- for (size_t i = 0; i < shape.size(); i++)
- EXPECT_EQ(shape[i], out_shape[i]);
- const float* out_label = output[1].data<const float*>();
+ for (size_t i = 0; i < shape.size(); i++) EXPECT_EQ(shape[i], out_shape[i]);
+ const int* out_label = output[1].data<int>();
EXPECT_EQ(raw_label, out_label[0]);
// opencv imencode will have some information loss
- //const float* out_pixel = output[0].data<const float*>();
- //for(size_t i = 0; i < total; i++)
+ // const float* out_pixel = output[0].data<const float*>();
+ // for(size_t i = 0; i < total; i++)
// EXPECT_LE(fabs(in_pixel[i]-out_pixel[i]), 10.f);
}
+#endif
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_dense.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_dense.cc b/test/singa/test_dense.cc
index 6f5518e..a5fd960 100644
--- a/test/singa/test_dense.cc
+++ b/test/singa/test_dense.cc
@@ -66,7 +66,7 @@ TEST(Dense, ForwardCpp) {
singa::Tensor out1 = dense.Forward(singa::kTrain, in);
singa::CppCPU host(0, 1);
- const float *outptr1 = out1.data<const float *>();
+ const float *outptr1 = out1.data<float>();
EXPECT_EQ(9u, out1.Size());
for (int i = 0; i < 3; i++)
for (int j = 0; j < 3; j++)
@@ -116,7 +116,7 @@ TEST(Dense, BackwardCpp) {
singa::Tensor in_grad = ret.first;
singa::Tensor dweight = ret.second.at(0);
singa::Tensor dbias = ret.second.at(1);
- const float *dx = in_grad.data<const float *>();
+ const float *dx = in_grad.data<float>();
EXPECT_EQ(6u, in_grad.Size());
for (int i = 0; i < 3; i++)
for (int j = 0; j < 2; j++)
@@ -124,7 +124,7 @@ TEST(Dense, BackwardCpp) {
(dy[i * 3 + 0] * we[0 * 2 + j] + dy[i * 3 + 1] * we[1 * 2 + j] +
dy[i * 3 + 2] * we[2 * 2 + j]),
dx[i * 2 + j]);
- const float *dweightx = dweight.data<const float *>();
+ const float *dweightx = dweight.data<float>();
EXPECT_EQ(6u, dweight.Size());
for (int i = 0; i < 3; i++)
for (int j = 0; j < 2; j++)
@@ -132,7 +132,7 @@ TEST(Dense, BackwardCpp) {
(dy[0 * 3 + i] * x[0 * 2 + j] + dy[1 * 3 + i] * x[1 * 2 + j] +
dy[2 * 3 + i] * x[2 * 2 + j]),
dweightx[i * 2 + j]);
- const float *dbiasx = dbias.data<const float *>();
+ const float *dbiasx = dbias.data<float>();
EXPECT_EQ(3u, dbias.Size());
for (int i = 0; i < 3; i++)
EXPECT_FLOAT_EQ((dy[0 * 3 + i] + dy[1 * 3 + i] + dy[2 * 3 + i]), dbiasx[i]);
@@ -170,7 +170,7 @@ TEST(Dense, ForwardCuda) {
singa::Tensor out1 = dense.Forward(singa::kTrain, in);
singa::CppCPU host(0, 1);
out1.ToDevice(&host);
- const float *outptr1 = out1.data<const float *>();
+ const float *outptr1 = out1.data<float>();
EXPECT_EQ(9u, out1.Size());
for (int i = 0; i < 3; i++)
for (int j = 0; j < 3; j++)
@@ -219,7 +219,7 @@ TEST(Dense, BackwardCuda) {
singa::Tensor dweight = ret.second.at(0);
singa::Tensor dbias = ret.second.at(1);
in_grad.ToDevice(&host);
- const float *dx = in_grad.data<const float *>();
+ const float *dx = in_grad.data<float>();
EXPECT_EQ(6u, in_grad.Size());
for (int i = 0; i < 3; i++)
for (int j = 0; j < 2; j++)
@@ -228,7 +228,7 @@ TEST(Dense, BackwardCuda) {
dy[i * 3 + 2] * we[2 * 2 + j]),
dx[i * 2 + j]);
dweight.ToDevice(&host);
- const float *dweightx = dweight.data<const float *>();
+ const float *dweightx = dweight.data<float>();
EXPECT_EQ(6u, dweight.Size());
for (int i = 0; i < 3; i++)
for (int j = 0; j < 2; j++)
@@ -237,7 +237,7 @@ TEST(Dense, BackwardCuda) {
dy[2 * 3 + i] * x[2 * 2 + j]),
dweightx[i * 2 + j]);
dbias.ToDevice(&host);
- const float *dbiasx = dbias.data<const float *>();
+ const float *dbiasx = dbias.data<float>();
EXPECT_EQ(3u, dbias.Size());
for (int i = 0; i < 3; i++)
EXPECT_FLOAT_EQ((dy[0 * 3 + i] + dy[1 * 3 + i] + dy[2 * 3 + i]), dbiasx[i]);
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_dropout.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_dropout.cc b/test/singa/test_dropout.cc
index b6ae9c6..3dd988a 100644
--- a/test/singa/test_dropout.cc
+++ b/test/singa/test_dropout.cc
@@ -52,11 +52,11 @@ TEST(Dropout, Forward) {
singa::Tensor out1 = drop.Forward(singa::kTrain, in);
- const float* mptr = drop.mask().data<const float*>();
+ const float* mptr = drop.mask().data<float>();
for (size_t i = 0; i < n; i++)
EXPECT_FLOAT_EQ(0, mptr[i] * (mptr[i] - scale));
- const float* outptr1 = out1.data<const float*>();
+ const float* outptr1 = out1.data<float>();
EXPECT_EQ(n, out1.Size());
// the output value should be 0 or the same as the input
EXPECT_EQ(0.f, outptr1[0] * (outptr1[0] - scale * x[0]));
@@ -65,7 +65,7 @@ TEST(Dropout, Forward) {
singa::Tensor out2 = drop.Forward(singa::kEval, in);
EXPECT_EQ(n, out2.Size());
- const float* outptr2 = out2.data<const float*>();
+ const float* outptr2 = out2.data<float>();
// the output value should be the same as the input
EXPECT_EQ(x[0], outptr2[0]);
EXPECT_EQ(x[1], outptr2[1]);
@@ -92,9 +92,9 @@ TEST(Dropout, Backward) {
singa::Tensor grad(singa::Shape{n});
grad.CopyDataFromHostPtr(dy, n);
- const float* mptr = drop.mask().data<const float*>();
+ const float* mptr = drop.mask().data<float>();
const auto ret = drop.Backward(singa::kTrain, grad);
- const float* dx = ret.first.data<const float*>();
+ const float* dx = ret.first.data<float>();
EXPECT_FLOAT_EQ(dx[0], dy[0] * (mptr[0] > 0 ? 1.0f : 0.0f) * scale);
EXPECT_FLOAT_EQ(dx[1], dy[1] * (mptr[1] > 0) * scale);
EXPECT_FLOAT_EQ(dx[7], dy[7] * (mptr[7] > 0) * scale);
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_flatten.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_flatten.cc b/test/singa/test_flatten.cc
index f139a75..2a77272 100644
--- a/test/singa/test_flatten.cc
+++ b/test/singa/test_flatten.cc
@@ -55,7 +55,7 @@ TEST(Flatten, ForwardCPU) {
EXPECT_EQ(n, out.Size());
EXPECT_EQ(6u, out.shape(0));
EXPECT_EQ(2u, out.shape(1));
- const float *yptr = out.data<const float *>();
+ const float *yptr = out.data<float>();
for (size_t i = 0; i < n; i++) EXPECT_FLOAT_EQ(x[i], yptr[i]);
}
@@ -77,7 +77,7 @@ TEST(Flatten, BackwardCPU) {
singa::Tensor temp = flt.Forward(singa::kTrain, in);
const auto out = flt.Backward(singa::kTrain, temp);
- const float *xptr = out.first.data<const float *>();
+ const float *xptr = out.first.data<float>();
EXPECT_EQ(n, out.first.Size());
EXPECT_EQ(2u, out.first.shape(0));
EXPECT_EQ(1u, out.first.shape(1));
@@ -108,7 +108,7 @@ TEST(Flatten, ForwardGPU) {
EXPECT_EQ(n, out.Size());
EXPECT_EQ(6u, out.shape(0));
EXPECT_EQ(2u, out.shape(1));
- const float *yptr = out.data<const float *>();
+ const float *yptr = out.data<float>();
for (size_t i = 0; i < n; i++) EXPECT_FLOAT_EQ(x[i], yptr[i]);
}
@@ -134,7 +134,7 @@ TEST(Flatten, BackwardGPU) {
singa::CppCPU host(0, 1);
singa::Tensor in_diff = ret.first;
in_diff.ToDevice(&host);
- const float *xptr = in_diff.data<const float *>();
+ const float *xptr = in_diff.data<float>();
EXPECT_EQ(n, in_diff.Size());
EXPECT_EQ(2u, in_diff.shape(0));
EXPECT_EQ(1u, in_diff.shape(1));
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_initializer.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_initializer.cc b/test/singa/test_initializer.cc
index a64d59e..e99cd79 100644
--- a/test/singa/test_initializer.cc
+++ b/test/singa/test_initializer.cc
@@ -27,7 +27,7 @@ TEST(Initializer, Constant) {
conf.set_value(3.1f);
x.Setup(conf);
x.Fill(&t);
- const float* xPtr = t.data<const float*>();
+ const float* xPtr = t.data<float>();
for (size_t i = 0; i < n; i++)
EXPECT_FLOAT_EQ(xPtr[i], 3.1f);
}
@@ -42,7 +42,7 @@ TEST(Initializer, Gaussian) {
conf.set_std(0.01f);
x.Setup(conf);
x.Fill(&t);
- const float* xPtr = t.data<const float*>();
+ const float* xPtr = t.data<float>();
float mean = 0.0f, std = 0.0f;
for (size_t i = 0; i < n; i++)
mean += xPtr[i];
@@ -66,7 +66,7 @@ TEST(Initializer, ConstantCUDA) {
x.Setup(conf);
x.Fill(&t);
t.ToHost();
- const float* xPtr = t.data<const float*>();
+ const float* xPtr = t.data<float>();
for (size_t i = 0; i < n; i++)
EXPECT_FLOAT_EQ(xPtr[i], 3.1f);
@@ -75,7 +75,7 @@ TEST(Initializer, ConstantCUDA) {
singa::Tensor s(singa::Shape{n}, &dev);
y.Fill(&s);
s.ToHost();
- const float* sPtr = s.data<const float*>();
+ const float* sPtr = s.data<float>();
for (size_t i = 0; i < n; i++)
EXPECT_FLOAT_EQ(sPtr[i], -0.1f);
}
@@ -92,7 +92,7 @@ TEST(Initializer, GaussianCUDA) {
x.Setup(conf);
x.Fill(&t);
t.ToHost();
- const float* tPtr = t.data<const float*>();
+ const float* tPtr = t.data<float>();
float mean = 0.0f, std = 0.0f;
for (size_t i = 0; i < n; i++)
mean += tPtr[i];
@@ -109,7 +109,7 @@ TEST(Initializer, GaussianCUDA) {
singa::Tensor s(singa::Shape{n}, &dev);
y.Fill(&s);
s.ToHost();
- const float* sPtr = s.data<const float*>();
+ const float* sPtr = s.data<float>();
for (size_t i = 0; i < n; i++)
mean += sPtr[i];
mean /= n;
@@ -128,7 +128,7 @@ TEST(Initializer, XavierCUDA) {
singa::Tensor t(singa::Shape{m, n}, &dev);
x.Fill(&t);
t.ToHost();
- const float* xPtr = t.data<const float*>();
+ const float* xPtr = t.data<float>();
float mean = 0.0f;
float high = -100.0f, low = 100.0f;
for (size_t i = 0; i < n; i++) {
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_mse.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_mse.cc b/test/singa/test_mse.cc
index 9ba062d..928be9d 100644
--- a/test/singa/test_mse.cc
+++ b/test/singa/test_mse.cc
@@ -44,7 +44,7 @@ class TestMSE : public ::testing::Test {
TEST_F(TestMSE, CppForward) {
singa::MSE mse;
const Tensor& loss = mse.Forward(p, t);
- auto ldat = loss.data<const float*>();
+ auto ldat = loss.data<float>();
for (size_t i = 0, k = 0; i < loss.Size(); i++) {
float l = 0.f;
@@ -61,7 +61,7 @@ TEST_F(TestMSE, CppBackward) {
mse.Forward(p, t);
const Tensor& grad = mse.Backward();
- auto gdat = grad.data<const float*>();
+ auto gdat = grad.data<float>();
for (size_t i = 0; i < grad.Size(); i++)
EXPECT_FLOAT_EQ(gdat[i], (1.0f / p.shape().at(0)) * (pdat[i] - tdat[i]));
@@ -76,7 +76,7 @@ TEST_F(TestMSE, CudaForward) {
Tensor loss = mse.Forward(p, t);
loss.ToHost();
- auto ldat = loss.data<const float*>();
+ auto ldat = loss.data<float>();
for (size_t i = 0, k = 0; i < loss.Size(); i++) {
float l = 0.f;
@@ -95,7 +95,7 @@ TEST_F(TestMSE, CudaBackward) {
mse.Forward(p, t);
Tensor grad = mse.Backward();
grad.ToHost();
- auto gdat = grad.data<const float*>();
+ auto gdat = grad.data<float>();
for (size_t i = 0; i < grad.Size(); i++)
EXPECT_FLOAT_EQ(gdat[i], (1.0f / p.shape().at(0)) * (pdat[i] - tdat[i]));
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_nesterov.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_nesterov.cc b/test/singa/test_nesterov.cc
index a9b264c..35b2b4d 100644
--- a/test/singa/test_nesterov.cc
+++ b/test/singa/test_nesterov.cc
@@ -38,7 +38,7 @@ TEST(Nesterov, ApplyCPU) {
nesterov.Apply(0, lr, "xx", grad, &value);
singa::Tensor v1 = value.Clone();
- const float* newv1 = v1.data<const float*>();
+ const float* newv1 = v1.data<float>();
float history[4], tmp[4];
for (int i = 0; i < 4; ++i) {
history[i] = g[i] * lr;
@@ -49,7 +49,7 @@ TEST(Nesterov, ApplyCPU) {
grad.CopyDataFromHostPtr(g, 4);
nesterov.Apply(1, lr, "xx", grad, &value);
singa::Tensor v2 = value.Clone();
- const float* newv2 = v2.data<const float*>();
+ const float* newv2 = v2.data<float>();
for (int i = 0; i < 4; ++i) {
tmp[i] = history[i];
history[i] = history[i] * func(1) + g[i] * lr;
@@ -77,7 +77,7 @@ TEST(Nesterov, ApplyCUDA) {
singa::Tensor v1 = value.Clone();
v1.ToHost();
- const float* newv1 = v1.data<const float*>();
+ const float* newv1 = v1.data<float>();
float history[4], tmp[4];
for (int i = 0; i < 4; ++i) {
history[i] = g[i] * lr;
@@ -89,7 +89,7 @@ TEST(Nesterov, ApplyCUDA) {
nesterov.Apply(1, lr, "xx", grad, &value);
singa::Tensor v2 = value.Clone();
v2.ToHost();
- const float* newv2 = v2.data<const float*>();
+ const float* newv2 = v2.data<float>();
for (int i = 0; i < 4; ++i) {
tmp[i] = history[i];
history[i] = history[i] * func(1) + g[i] * lr;
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_prelu.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_prelu.cc b/test/singa/test_prelu.cc
index faff093..fee7c5b 100644
--- a/test/singa/test_prelu.cc
+++ b/test/singa/test_prelu.cc
@@ -60,7 +60,7 @@ TEST(PReLU, ForwardCPU) {
prelu.Set_a(a);
singa::Tensor out = prelu.Forward(singa::kTrain, in);
- const float *yptr = out.data<const float *>();
+ const float *yptr = out.data<float>();
EXPECT_EQ(n, out.Size());
float *y = new float[n];
@@ -106,8 +106,8 @@ TEST(PReLU, BackwardCPU) {
singa::Tensor out_diff(singa::Shape{batchsize, c, h, w});
out_diff.CopyDataFromHostPtr<float>(grad, n);
const auto ret = prelu.Backward(singa::kTrain, out_diff);
- const float *xptr = ret.first.data<const float *>();
- const float *aptr = ret.second.at(0).data<const float *>();
+ const float *xptr = ret.first.data<float>();
+ const float *aptr = ret.second.at(0).data<float>();
float *dx = new float[n];
size_t div_factor = prelu.Channel_shared() ? c : 1;
size_t params = prelu.Channel_shared() ? 1 : c;
@@ -162,7 +162,7 @@ TEST(PReLU, ForwardGPU) {
singa::Tensor out = prelu.Forward(singa::kTrain, in);
singa::CppCPU host(0, 1);
out.ToDevice(&host);
- const float *yptr = out.data<const float *>();
+ const float *yptr = out.data<float>();
EXPECT_EQ(n, out.Size());
float *y = new float[n];
@@ -212,10 +212,10 @@ TEST(PReLU, BackwardGPU) {
singa::Tensor in_diff = ret.first;
singa::CppCPU host(0, 1);
in_diff.ToDevice(&host);
- const float *xptr = in_diff.data<const float *>();
+ const float *xptr = in_diff.data<float>();
singa::Tensor a_diff = ret.second.at(0);
a_diff.ToDevice(&host);
- const float *aptr = a_diff.data<const float *>();
+ const float *aptr = a_diff.data<float>();
float *dx = new float[n];
size_t div_factor = prelu.Channel_shared() ? c : 1;
size_t params = prelu.Channel_shared() ? 1 : c;
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_rmsprop.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_rmsprop.cc b/test/singa/test_rmsprop.cc
index ddfdefe..004a9b6 100644
--- a/test/singa/test_rmsprop.cc
+++ b/test/singa/test_rmsprop.cc
@@ -43,7 +43,7 @@ TEST(RMSProp, ApplyCPU) {
rmsprop.Apply(0, lr, "xx", grad, &value);
singa::Tensor v1 = value.Clone();
- const float* newv1 = v1.data<const float*>();
+ const float* newv1 = v1.data<float>();
float history[4];
for (int i = 0; i < 4; ++i) history[i] = g[i] * g[i] * (1 - rho);
for (int i = 0; i < 4; ++i)
@@ -53,7 +53,7 @@ TEST(RMSProp, ApplyCPU) {
grad.CopyDataFromHostPtr(g, 4);
rmsprop.Apply(1, lr, "xx", grad, &value);
singa::Tensor v2 = value.Clone();
- const float* newv2 = v2.data<const float*>();
+ const float* newv2 = v2.data<float>();
for (int i = 0; i < 4; ++i)
history[i] = history[i] * rho + g[i] * g[i] * (1 - rho);
@@ -84,7 +84,7 @@ TEST(RMSProp, ApplyCUDA) {
singa::Tensor v1 = value.Clone();
v1.ToHost();
- const float* newv1 = v1.data<const float*>();
+ const float* newv1 = v1.data<float>();
float history[4];
for (int i = 0; i < 4; ++i) history[i] = g[i] * g[i] * (1 - rho);
for (int i = 0; i < 4; ++i)
@@ -95,7 +95,7 @@ TEST(RMSProp, ApplyCUDA) {
rmsprop.Apply(1, lr, "xx", grad, &value);
singa::Tensor v2 = value.Clone();
v2.ToHost();
- const float* newv2 = v2.data<const float*>();
+ const float* newv2 = v2.data<float>();
for (int i = 0; i < 4; ++i)
history[i] = history[i] * rho + g[i] * g[i] * (1 - rho);
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_sgd.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_sgd.cc b/test/singa/test_sgd.cc
index 5417b04..b9c6368 100644
--- a/test/singa/test_sgd.cc
+++ b/test/singa/test_sgd.cc
@@ -36,7 +36,7 @@ TEST(SGD, ApplyWithoutMomentum) {
sgd.Apply(0, lr, "xx", grad, &value);
singa::Tensor v1 = value.Clone();
- const float* newv1 = v1.data<const float*>();
+ const float* newv1 = v1.data<float>();
for (int i = 0; i < 4; i++) {
EXPECT_FLOAT_EQ(newv1[i], v[i] - g[i] * lr);
}
@@ -46,7 +46,7 @@ TEST(SGD, ApplyWithoutMomentum) {
grad.CopyDataFromHostPtr(g, 4);
sgd.Apply(1, lr, "xx", grad, &value);
singa::Tensor v2 = value.Clone();
- const float* newv2 = v2.data<const float*>();
+ const float* newv2 = v2.data<float>();
for (int i = 0; i < 4; i++) {
EXPECT_FLOAT_EQ(newv2[i], newv1[i] - g[i] * lr);
}
@@ -68,7 +68,7 @@ TEST(SGD, ApplyWithMomentum) {
sgd.Apply(0, lr, "xx", grad, &value);
singa::Tensor v1 = value.Clone();
- const float* newv1 = v1.data<const float*>();
+ const float* newv1 = v1.data<float>();
for (int i = 0; i < 4; i++) {
EXPECT_FLOAT_EQ(newv1[i], v[i] - g[i] * lr);
}
@@ -76,7 +76,7 @@ TEST(SGD, ApplyWithMomentum) {
grad.CopyDataFromHostPtr(g, 4);
sgd.Apply(1, lr, "xx", grad, &value);
singa::Tensor v2 = value.Clone();
- const float* newv2 = v2.data<const float*>();
+ const float* newv2 = v2.data<float>();
for (int i = 0; i < 4; i++) {
EXPECT_FLOAT_EQ(newv2[i], newv1[i] - (g[i] * lr + g[i] * lr * func(1)));
}
@@ -98,7 +98,7 @@ TEST(SGD, ApplyWithoutMomentumCuda) {
singa::Tensor v1 = value.Clone();
v1.ToHost();
- const float* newv1 = v1.data<const float*>();
+ const float* newv1 = v1.data<float>();
for (int i = 0; i < 4; i++) {
EXPECT_FLOAT_EQ(newv1[i], v[i] - g[i] * lr);
}
@@ -109,7 +109,7 @@ TEST(SGD, ApplyWithoutMomentumCuda) {
sgd.Apply(1, lr, "xx", grad, &value);
singa::Tensor v2 = value.Clone();
v2.ToHost();
- const float* newv2 = v2.data<const float*>();
+ const float* newv2 = v2.data<float>();
for (int i = 0; i < 4; i++) {
EXPECT_FLOAT_EQ(newv2[i], newv1[i] - g[i] * lr);
}
@@ -133,7 +133,7 @@ TEST(SGD, ApplyWithMomentumCuda) {
singa::Tensor v1 = value.Clone();
v1.ToHost();
- const float* newv1 = v1.data<const float*>();
+ const float* newv1 = v1.data<float>();
for (int i = 0; i < 4; i++) {
EXPECT_FLOAT_EQ(newv1[i], v[i] - g[i] * lr);
}
@@ -142,7 +142,7 @@ TEST(SGD, ApplyWithMomentumCuda) {
sgd.Apply(1, lr, "xx", grad, &value);
singa::Tensor v2 = value.Clone();
v2.ToHost();
- const float* newv2 = v2.data<const float*>();
+ const float* newv2 = v2.data<float>();
for (int i = 0; i < 4; i++) {
EXPECT_FLOAT_EQ(newv2[i], newv1[i] - (g[i] * lr + g[i] * lr * func(1)));
}
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_softmax.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_softmax.cc b/test/singa/test_softmax.cc
index 2bf4505..f4a3bd7 100644
--- a/test/singa/test_softmax.cc
+++ b/test/singa/test_softmax.cc
@@ -47,7 +47,7 @@ TEST(Softmax, Forward) {
sft.Setup(Shape{col}, conf);
singa::Tensor out = sft.Forward(singa::kTrain, in);
- const float* yptr = out.data<const float*>();
+ const float* yptr = out.data<float>();
EXPECT_EQ(n, out.Size());
float* sigma = new float[row];
@@ -74,13 +74,13 @@ TEST(Softmax, Backward) {
singa::LayerConf conf;
sft.Setup(Shape{col}, conf);
singa::Tensor out = sft.Forward(singa::kTrain, in);
- const float* yptr = out.data<const float*>();
+ const float* yptr = out.data<float>();
const float grad[] = {2.0f, -3.0f, 1.0f, 3.0f, -1.0f, -2.0};
singa::Tensor out_diff(singa::Shape{row, col});
out_diff.CopyDataFromHostPtr<float>(grad, n);
const auto in_diff = sft.Backward(singa::kTrain, out_diff);
- const float* xptr = in_diff.first.data<const float*>();
+ const float* xptr = in_diff.first.data<float>();
float* dx = new float[n];
float* sigma = new float[row];
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/833f4619/test/singa/test_tensor_math.cc
----------------------------------------------------------------------
diff --git a/test/singa/test_tensor_math.cc b/test/singa/test_tensor_math.cc
index 1092d69..7deb339 100644
--- a/test/singa/test_tensor_math.cc
+++ b/test/singa/test_tensor_math.cc
@@ -26,13 +26,13 @@ TEST_F(TestTensorMath, MemberAbs) {
Tensor aa = a.Clone();
Tensor bb = b.Clone();
Tensor cc = aa - bb;
- const float *dptr = cc.data<const float *>();
+ const float *dptr = cc.data<float>();
EXPECT_NEAR(-0.1, dptr[0], 1e-5);
EXPECT_NEAR(-0.1, dptr[1], 1e-5);
EXPECT_NEAR(-0.1, dptr[2], 1e-5);
Tensor p = Abs(cc);
- const float *dptr1 = p.data<const float *>();
+ const float *dptr1 = p.data<float>();
EXPECT_NEAR(0.1, dptr1[0], 1e-5);
EXPECT_NEAR(0.1, dptr1[1], 1e-5);
EXPECT_NEAR(0.1, dptr1[2], 1e-5);
@@ -40,7 +40,7 @@ TEST_F(TestTensorMath, MemberAbs) {
TEST_F(TestTensorMath, MemberExp) {
Tensor p = Exp(a);
- const float *dptr1 = p.data<const float *>();
+ const float *dptr1 = p.data<float>();
EXPECT_NEAR(exp(1.0f), dptr1[0], 1e-5);
EXPECT_NEAR(exp(2.0f), dptr1[1], 1e-5);
EXPECT_NEAR(exp(3.0f), dptr1[2], 1e-5);
@@ -48,7 +48,7 @@ TEST_F(TestTensorMath, MemberExp) {
TEST_F(TestTensorMath, MemberLog) {
Tensor p = Log(a);
- const float *dptr1 = p.data<const float *>();
+ const float *dptr1 = p.data<float>();
EXPECT_NEAR(log(1.0f), dptr1[0], 1e-5);
EXPECT_NEAR(log(2.0f), dptr1[1], 1e-5);
EXPECT_NEAR(log(3.0f), dptr1[2], 1e-5);
@@ -57,13 +57,13 @@ TEST_F(TestTensorMath, MemberLog) {
TEST_F(TestTensorMath, MemberReLU) {
Tensor aa = a.Clone();
Tensor cc = aa - 2.0f;
- const float *dptr = cc.data<const float *>();
+ const float *dptr = cc.data<float>();
EXPECT_NEAR(-1.0f, dptr[0], 1e-5);
EXPECT_NEAR(0.0f, dptr[1], 1e-5);
EXPECT_NEAR(1.0f, dptr[2], 1e-5);
Tensor p = ReLU(cc);
- const float *dptr1 = p.data<const float *>();
+ const float *dptr1 = p.data<float>();
EXPECT_NEAR(0.0f, dptr1[0], 1e-5);
EXPECT_NEAR(0.0f, dptr1[1], 1e-5);
EXPECT_NEAR(1.0f, dptr1[2], 1e-5);
@@ -71,7 +71,7 @@ TEST_F(TestTensorMath, MemberReLU) {
TEST_F(TestTensorMath, MemberSigmoid) {
Tensor p = Sigmoid(a);
- const float *dptr1 = p.data<const float *>();
+ const float *dptr1 = p.data<float>();
EXPECT_NEAR(1.0f / (1.0f + exp(-1.0f)), dptr1[0], 1e-5);
EXPECT_NEAR(1.0f / (1.0f + exp(-2.0f)), dptr1[1], 1e-5);
EXPECT_NEAR(1.0f / (1.0f + exp(-3.0f)), dptr1[2], 1e-5);
@@ -80,13 +80,13 @@ TEST_F(TestTensorMath, MemberSigmoid) {
TEST_F(TestTensorMath, MemberSign) {
Tensor aa = a.Clone();
Tensor cc = aa - 2.0f;
- const float *dptr = cc.data<const float *>();
+ const float *dptr = cc.data<float>();
EXPECT_NEAR(-1.0f, dptr[0], 1e-5);
EXPECT_NEAR(0.0f, dptr[1], 1e-5);
EXPECT_NEAR(1.0f, dptr[2], 1e-5);
Tensor p = Sign(cc);
- const float *dptr1 = p.data<const float *>();
+ const float *dptr1 = p.data<float>();
EXPECT_EQ(0.0f, dptr1[0]);
EXPECT_EQ(0.0f, dptr1[1]);
EXPECT_EQ(1.0f, dptr1[2]);
@@ -94,7 +94,7 @@ TEST_F(TestTensorMath, MemberSign) {
TEST_F(TestTensorMath, MemberSqrt) {
Tensor p = Sqrt(a);
- const float *dptr1 = p.data<const float *>();
+ const float *dptr1 = p.data<float>();
EXPECT_NEAR(sqrt(1.0), dptr1[0], 1e-5);
EXPECT_NEAR(sqrt(2.0), dptr1[1], 1e-5);
EXPECT_NEAR(sqrt(3.0), dptr1[2], 1e-5);
@@ -102,7 +102,7 @@ TEST_F(TestTensorMath, MemberSqrt) {
TEST_F(TestTensorMath, MemberSquare) {
Tensor p = Square(a);
- const float *dptr1 = p.data<const float *>();
+ const float *dptr1 = p.data<float>();
EXPECT_NEAR(1.0, dptr1[0], 1e-5);
EXPECT_NEAR(4.0, dptr1[1], 1e-5);
EXPECT_NEAR(9.0, dptr1[2], 1e-5);
@@ -110,7 +110,7 @@ TEST_F(TestTensorMath, MemberSquare) {
TEST_F(TestTensorMath, MemberTanh) {
Tensor p = Tanh(a);
- const float *dptr1 = p.data<const float *>();
+ const float *dptr1 = p.data<float>();
EXPECT_NEAR(tanh(1.0), dptr1[0], 1e-5);
EXPECT_NEAR(tanh(2.0), dptr1[1], 1e-5);
EXPECT_NEAR(tanh(3.0), dptr1[2], 1e-5);
@@ -118,13 +118,13 @@ TEST_F(TestTensorMath, MemberTanh) {
TEST_F(TestTensorMath, Sum) {
Tensor p1 = Sum(e, 0);
- const float *dptr1 = p1.data<const float *>();
+ const float *dptr1 = p1.data<float>();
EXPECT_FLOAT_EQ(9.0f, dptr1[0]);
EXPECT_FLOAT_EQ(12.0f, dptr1[1]);
Tensor p2(Shape{3, 1});
p2 = Sum(e, 1);
- const float *dptr2 = p2.data<const float *>();
+ const float *dptr2 = p2.data<float>();
EXPECT_FLOAT_EQ(3.0f, dptr2[0]);
EXPECT_FLOAT_EQ(7.0f, dptr2[1]);
EXPECT_FLOAT_EQ(11.0f, dptr2[2]);
@@ -132,7 +132,7 @@ TEST_F(TestTensorMath, Sum) {
TEST_F(TestTensorMath, SoftMax) {
Tensor p1 = SoftMax(Reshape(e, Shape{1, 6}));
- const float *dptr1 = p1.data<const float *>();
+ const float *dptr1 = p1.data<float>();
float sum = 0;
for (int i = 0; i < 6; i++) sum += exp(i + 1);
EXPECT_NEAR(exp(1) / sum, dptr1[0], 1e-5);
@@ -143,14 +143,14 @@ TEST_F(TestTensorMath, SoftMax) {
EXPECT_NEAR(exp(6) / sum, dptr1[5], 1e-5);
Tensor p2 = SoftMax(e);
- const float *dptr2 = p2.data<const float *>();
+ const float *dptr2 = p2.data<float>();
EXPECT_NEAR(exp(1) / (exp(1) + exp(2)), dptr2[0], 1e-5);
EXPECT_NEAR(exp(2) / (exp(1) + exp(2)), dptr2[1], 1e-5);
}
TEST_F(TestTensorMath, MemberLT) {
Tensor p1 = a < 2.0f;
- const float *dptr1 = p1.data<const float *>();
+ const float *dptr1 = p1.data<float>();
EXPECT_FLOAT_EQ(1.0f, dptr1[0]);
EXPECT_FLOAT_EQ(0.0f, dptr1[1]);
EXPECT_FLOAT_EQ(0.0f, dptr1[2]);
@@ -158,7 +158,7 @@ TEST_F(TestTensorMath, MemberLT) {
TEST_F(TestTensorMath, MemberLE) {
Tensor p1 = a <= 2.0f;
- const float *dptr1 = p1.data<const float *>();
+ const float *dptr1 = p1.data<float>();
EXPECT_FLOAT_EQ(1.0f, dptr1[0]);
EXPECT_FLOAT_EQ(1.0f, dptr1[1]);
EXPECT_FLOAT_EQ(0.0f, dptr1[2]);
@@ -166,7 +166,7 @@ TEST_F(TestTensorMath, MemberLE) {
TEST_F(TestTensorMath, MemberGT) {
Tensor p1 = a > 2.0f;
- const float *dptr1 = p1.data<const float *>();
+ const float *dptr1 = p1.data<float>();
EXPECT_FLOAT_EQ(0.0f, dptr1[0]);
EXPECT_FLOAT_EQ(0.0f, dptr1[1]);
EXPECT_FLOAT_EQ(1.0f, dptr1[2]);
@@ -174,7 +174,7 @@ TEST_F(TestTensorMath, MemberGT) {
TEST_F(TestTensorMath, MemberGE) {
Tensor p1 = a >= 2.0f;
- const float *dptr1 = p1.data<const float *>();
+ const float *dptr1 = p1.data<float>();
EXPECT_FLOAT_EQ(0.0f, dptr1[0]);
EXPECT_FLOAT_EQ(1.0f, dptr1[1]);
EXPECT_FLOAT_EQ(1.0f, dptr1[2]);
@@ -182,7 +182,7 @@ TEST_F(TestTensorMath, MemberGE) {
TEST_F(TestTensorMath, MemberPow) {
Tensor p1 = Pow(b, 3.0f);
- const float *dptr1 = p1.data<const float *>();
+ const float *dptr1 = p1.data<float>();
EXPECT_FLOAT_EQ(pow(1.1f, 3.0f), dptr1[0]);
EXPECT_FLOAT_EQ(pow(2.1f, 3.0f), dptr1[1]);
EXPECT_FLOAT_EQ(pow(3.1f, 3.0f), dptr1[2]);
@@ -190,7 +190,7 @@ TEST_F(TestTensorMath, MemberPow) {
// TODO(Yuchen): check pow(tensor a, tensor b) and add testcase after the
// function is complete
// Tensor p2 = Pow(a,b);
- // const float *dptr2 = p2.data<const float *>();
+ // const float *dptr2 = p2.data<float>();
// EXPECT_FLOAT_EQ(pow(1.0f,1.1f), dptr2[0]);
// EXPECT_FLOAT_EQ(pow(2.0f,2.1f), dptr2[1]);
// EXPECT_FLOAT_EQ(pow(3.0f,3.1f), dptr2[2]);
@@ -198,7 +198,7 @@ TEST_F(TestTensorMath, MemberPow) {
TEST_F(TestTensorMath, MemberSub) {
Tensor p1 = a - b;
- const float *dptr1 = p1.data<const float *>();
+ const float *dptr1 = p1.data<float>();
EXPECT_NEAR(-0.1, dptr1[0], 1e-5);
EXPECT_NEAR(-0.1, dptr1[1], 1e-5);
EXPECT_NEAR(-0.1, dptr1[2], 1e-5);
@@ -206,7 +206,7 @@ TEST_F(TestTensorMath, MemberSub) {
TEST_F(TestTensorMath, MemberEltwiseMult) {
Tensor p1 = a * b;
- const float *dptr1 = p1.data<const float *>();
+ const float *dptr1 = p1.data<float>();
EXPECT_NEAR(1.0 * 1.1, dptr1[0], 1e-5);
EXPECT_NEAR(2.0 * 2.1, dptr1[1], 1e-5);
EXPECT_NEAR(3.0 * 3.1, dptr1[2], 1e-5);
@@ -214,19 +214,19 @@ TEST_F(TestTensorMath, MemberEltwiseMult) {
TEST_F(TestTensorMath, MemberDiv) {
Tensor p1 = a / b;
- const float *dptr1 = p1.data<const float *>();
+ const float *dptr1 = p1.data<float>();
EXPECT_NEAR(1.0 / 1.1, dptr1[0], 1e-5);
EXPECT_NEAR(2.0 / 2.1, dptr1[1], 1e-5);
EXPECT_NEAR(3.0 / 3.1, dptr1[2], 1e-5);
Tensor p2 = Div(10.0f, b);
- const float *dptr2 = p2.data<const float *>();
+ const float *dptr2 = p2.data<float>();
EXPECT_NEAR(10.0 / 1.1, dptr2[0], 1e-5);
EXPECT_NEAR(10.0 / 2.1, dptr2[1], 1e-5);
EXPECT_NEAR(10.0 / 3.1, dptr2[2], 1e-5);
Tensor p3 = a / 8.0f;
- const float *dptr3 = p3.data<const float *>();
+ const float *dptr3 = p3.data<float>();
EXPECT_NEAR(1.0 / 8.0, dptr3[0], 1e-5);
EXPECT_NEAR(2.0 / 8.0, dptr3[1], 1e-5);
EXPECT_NEAR(3.0 / 8.0, dptr3[2], 1e-5);
@@ -235,7 +235,7 @@ TEST_F(TestTensorMath, MemberDiv) {
TEST_F(TestTensorMath, MemberBernoulli) {
Tensor p1(Shape{10000});
Bernoulli(0.3f, &p1);
- const float *dptr1 = p1.data<const float *>();
+ const float *dptr1 = p1.data<float>();
float sum = 0;
for (int i = 0; i < 10000; i++) sum += dptr1[i];
float mean = sum / 10000;
@@ -250,7 +250,7 @@ TEST_F(TestTensorMath, MemberBernoulli) {
TEST_F(TestTensorMath, MemberUniform) {
Tensor p1(Shape{10000});
Uniform(0.1f, 0.2f, &p1);
- const float *dptr1 = p1.data<const float *>();
+ const float *dptr1 = p1.data<float>();
float sum = 0;
for (int i = 0; i < 10000; i++) sum += dptr1[i];
float mean = sum / 10000;
@@ -265,7 +265,7 @@ TEST_F(TestTensorMath, MemberUniform) {
TEST_F(TestTensorMath, MemberGaussian) {
Tensor p1(Shape{50000});
Gaussian(0.0f, 1.0f, &p1);
- const float *dptr1 = p1.data<const float *>();
+ const float *dptr1 = p1.data<float>();
float sum = 0;
for (int i = 0; i < 50000; i++) sum += dptr1[i];
float mean = sum / 50000;
@@ -280,7 +280,7 @@ TEST_F(TestTensorMath, MemberGaussian) {
TEST_F(TestTensorMath, MemberAddTensor) {
Tensor aa = a.Clone();
aa += a;
- const float *dptr = aa.data<const float *>();
+ const float *dptr = aa.data<float>();
EXPECT_FLOAT_EQ(2.0f, dptr[0]);
EXPECT_FLOAT_EQ(4.0f, dptr[1]);
EXPECT_FLOAT_EQ(6.0f, dptr[2]);
@@ -288,13 +288,13 @@ TEST_F(TestTensorMath, MemberAddTensor) {
// check p is initialized to 0
Tensor p(Shape{6});
p += aa;
- const float *dptr1 = p.data<const float *>();
+ const float *dptr1 = p.data<float>();
EXPECT_FLOAT_EQ(2.0f, dptr1[0]);
EXPECT_FLOAT_EQ(4.0f, dptr1[1]);
EXPECT_FLOAT_EQ(6.0f, dptr1[2]);
a += b;
- const float *dptr2 = a.data<const float *>();
+ const float *dptr2 = a.data<float>();
EXPECT_FLOAT_EQ(2.1f, dptr2[0]);
EXPECT_FLOAT_EQ(4.1f, dptr2[1]);
EXPECT_FLOAT_EQ(6.1f, dptr2[2]);
@@ -304,21 +304,21 @@ TEST_F(TestTensorMath, MemberAddTensor) {
TEST_F(TestTensorMath, AddTensors) {
Tensor ret(a.shape(), a.device(), a.data_type());
Add(a, b, &ret);
- const float *dptr = ret.data<const float *>();
+ const float *dptr = ret.data<float>();
EXPECT_FLOAT_EQ(2.1f, dptr[0]);
EXPECT_FLOAT_EQ(4.1f, dptr[1]);
EXPECT_FLOAT_EQ(6.1f, dptr[2]);
EXPECT_FLOAT_EQ(12.1f, dptr[5]);
const Tensor d = a + b;
- const float *dptr2 = d.data<const float *>();
+ const float *dptr2 = d.data<float>();
EXPECT_FLOAT_EQ(2.1f, dptr2[0]);
EXPECT_FLOAT_EQ(4.1f, dptr2[1]);
EXPECT_FLOAT_EQ(6.1f, dptr2[2]);
EXPECT_FLOAT_EQ(12.1f, dptr2[5]);
Add(a, b, &a);
- const float *dptr1 = a.data<const float *>();
+ const float *dptr1 = a.data<float>();
EXPECT_FLOAT_EQ(2.1f, dptr1[0]);
EXPECT_FLOAT_EQ(4.1f, dptr1[1]);
EXPECT_FLOAT_EQ(6.1f, dptr1[2]);
@@ -328,7 +328,7 @@ TEST_F(TestTensorMath, AddTensors) {
TEST_F(TestTensorMath, SetValue) {
Tensor t(Shape{4});
t.SetValue(0.3f);
- const float *ptr = t.data<const float *>();
+ const float *ptr = t.data<float>();
for (int i = 0; i < 4; i++) EXPECT_FLOAT_EQ(ptr[i], 0.3f);
}
@@ -336,7 +336,7 @@ TEST_F(TestTensorMath, Reshape) {
Tensor t(Shape{4});
t.SetValue(0.3f);
Tensor p = Reshape(t, Shape{4, 1});
- const float *ptr = t.data<const float *>();
+ const float *ptr = t.data<float>();
EXPECT_EQ(p.shape(0), 4u);
EXPECT_EQ(p.shape(1), 1u);
for (int i = 0; i < 4; i++) EXPECT_FLOAT_EQ(ptr[i], 0.3f);
@@ -354,7 +354,7 @@ TEST_F(TestTensorMath, MultCpp) {
t.CopyDataFromHostPtr(x, 4);
d.CopyDataFromHostPtr(dat1, 6);
Tensor C = Mult(d, t);
- const float *xptr = C.data<const float *>();
+ const float *xptr = C.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 2; j++) {
float tmp = 0;
@@ -367,10 +367,10 @@ TEST_F(TestTensorMath, MultCpp) {
const float y[8] = {1.0f, 2.0f, 3.0f, 4.0f, 1.1f, 2.1f, 3.1f, 4.1f};
Tensor s(Shape{4, 2});
s.CopyDataFromHostPtr(y, 8);
- const float *sPtr = s.data<const float *>();
+ const float *sPtr = s.data<float>();
for (int i = 0; i < 8; i++) EXPECT_FLOAT_EQ(sPtr[i], y[i]);
Tensor D = Mult(d, s.T());
- const float *DPtr = D.data<const float *>();
+ const float *DPtr = D.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 4; j++) {
float tmp = 0;
@@ -387,7 +387,7 @@ TEST_F(TestTensorMath, MultCpp) {
Tensor o(Shape{4, 4});
Mult(p, q, &o);
- const float *oPtr = o.data<const float *>();
+ const float *oPtr = o.data<float>();
for (int i = 0; i < 4; i++) {
for (int j = 0; j < 4; j++) {
EXPECT_FLOAT_EQ(oPtr[i * 4 + j], x[i]);
@@ -401,7 +401,7 @@ TEST_F(TestTensorMath, AddColumnCpp) {
t.CopyDataFromHostPtr(x, 3);
d.CopyDataFromHostPtr(dat1, 6);
AddColumn(t, &d);
- const float *xptr = d.data<const float *>();
+ const float *xptr = d.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 2; j++) {
EXPECT_FLOAT_EQ(xptr[i * 2 + j], dat1[i * 2 + j] + x[i]);
@@ -414,7 +414,7 @@ TEST_F(TestTensorMath, SubColumnCpp) {
t.CopyDataFromHostPtr(x, 3);
d.CopyDataFromHostPtr(dat1, 6);
SubColumn(t, &d);
- const float *xptr = d.data<const float *>();
+ const float *xptr = d.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 2; j++) {
EXPECT_FLOAT_EQ(xptr[i * 2 + j], dat1[i * 2 + j] - x[i]);
@@ -428,7 +428,7 @@ TEST_F(TestTensorMath, DivColumnCpp) {
t.CopyDataFromHostPtr(x, 3);
d.CopyDataFromHostPtr(dat1, 6);
DivColumn(t, &d);
- const float *xptr = d.data<const float *>();
+ const float *xptr = d.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 2; j++) {
EXPECT_FLOAT_EQ(xptr[i * 2 + j], dat1[i * 2 + j] / x[i]);
@@ -442,7 +442,7 @@ TEST_F(TestTensorMath, AddRowCpp) {
t.CopyDataFromHostPtr(x, 2);
d.CopyDataFromHostPtr(dat1, 6);
AddRow(t, &d);
- const float *xptr = d.data<const float *>();
+ const float *xptr = d.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 2; j++) {
EXPECT_FLOAT_EQ(xptr[i * 2 + j], dat1[i * 2 + j] + x[j]);
@@ -456,7 +456,7 @@ TEST_F(TestTensorMath, SubRowCpp) {
t.CopyDataFromHostPtr(x, 2);
d.CopyDataFromHostPtr(dat1, 6);
SubRow(t, &d);
- const float *xptr = d.data<const float *>();
+ const float *xptr = d.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 2; j++) {
EXPECT_FLOAT_EQ(xptr[i * 2 + j], dat1[i * 2 + j] - x[j]);
@@ -470,7 +470,7 @@ TEST_F(TestTensorMath, MultRowCpp) {
t.CopyDataFromHostPtr(x, 2);
d.CopyDataFromHostPtr(dat1, 6);
MultRow(t, &d);
- const float *xptr = d.data<const float *>();
+ const float *xptr = d.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 2; j++) {
EXPECT_FLOAT_EQ(xptr[i * 2 + j], dat1[i * 2 + j] * x[j]);
@@ -482,7 +482,7 @@ TEST_F(TestTensorMath, SumRowsCpp) {
Tensor t(Shape{2});
d.CopyDataFromHostPtr(dat1, 6);
SumRows(d, &t);
- const float *tptr = t.data<const float *>();
+ const float *tptr = t.data<float>();
for (int i = 0; i < 2; i++) {
float tmp = 0;
for (int j = 0; j < 3; j++) {
@@ -496,7 +496,7 @@ TEST_F(TestTensorMath, SumColumnsCpp) {
Tensor t(Shape{3});
d.CopyDataFromHostPtr(dat1, 6);
SumColumns(d, &t);
- const float *tptr = t.data<const float *>();
+ const float *tptr = t.data<float>();
for (int i = 0; i < 3; i++) {
float tmp = 0;
for (int j = 0; j < 2; j++) {
@@ -525,7 +525,7 @@ TEST_F(TestTensorMath, MultCuda) {
d.CopyDataFromHostPtr(dat1, 6);
Tensor C = Mult(d, t);
C.ToHost();
- const float *xptr = C.data<const float *>();
+ const float *xptr = C.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 2; j++) {
float tmp = 0;
@@ -541,7 +541,7 @@ TEST_F(TestTensorMath, MultCuda) {
s.CopyDataFromHostPtr(y, 8);
Tensor D = Mult(d, s.T());
D.ToHost();
- const float *DPtr = D.data<const float *>();
+ const float *DPtr = D.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 4; j++) {
float tmp = 0;
@@ -559,7 +559,7 @@ TEST_F(TestTensorMath, MultCuda) {
Mult(p, q, &o);
o.ToHost();
- const float *oPtr = o.data<const float *>();
+ const float *oPtr = o.data<float>();
for (int i = 0; i < 4; i++) {
for (int j = 0; j < 4; j++) {
EXPECT_FLOAT_EQ(oPtr[i * 4 + j], x[i]);
@@ -576,7 +576,7 @@ TEST_F(TestTensorMath, AddColumnCuda) {
d.ToDevice(&dev);
AddColumn(t, &d);
d.ToHost();
- const float *xptr = d.data<const float *>();
+ const float *xptr = d.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 2; j++) {
EXPECT_FLOAT_EQ(xptr[i * 2 + j], dat1[i * 2 + j] + x[i]);
@@ -593,7 +593,7 @@ TEST_F(TestTensorMath, SubColumnCuda) {
d.ToDevice(&dev);
SubColumn(t, &d);
d.ToHost();
- const float *xptr = d.data<const float *>();
+ const float *xptr = d.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 2; j++) {
EXPECT_FLOAT_EQ(xptr[i * 2 + j], dat1[i * 2 + j] - x[i]);
@@ -607,7 +607,7 @@ TEST_F(TestTensorMath, MultColumnCpp) {
t.CopyDataFromHostPtr(x, 3);
d.CopyDataFromHostPtr(dat1, 6);
MultColumn(t, &d);
- const float *xptr = d.data<const float *>();
+ const float *xptr = d.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 2; j++) {
EXPECT_FLOAT_EQ(xptr[i * 2 + j], dat1[i * 2 + j] * x[i]);
@@ -624,7 +624,7 @@ TEST_F(TestTensorMath, MultColumnCuda) {
d.ToDevice(&dev);
MultColumn(t, &d);
d.ToHost();
- const float *xptr = d.data<const float *>();
+ const float *xptr = d.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 2; j++) {
EXPECT_FLOAT_EQ(xptr[i * 2 + j], dat1[i * 2 + j] * x[i]);
@@ -640,7 +640,7 @@ TEST_F(TestTensorMath, DivColumnCuda) {
d.ToDevice(&dev);
DivColumn(t, &d);
d.ToHost();
- const float *xptr = d.data<const float *>();
+ const float *xptr = d.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 2; j++) {
EXPECT_FLOAT_EQ(xptr[i * 2 + j], dat1[i * 2 + j] / x[i]);
@@ -656,7 +656,7 @@ TEST_F(TestTensorMath, AddRowCuda) {
d.ToDevice(&dev);
AddRow(t, &d);
d.ToHost();
- const float *xptr = d.data<const float *>();
+ const float *xptr = d.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 2; j++) {
EXPECT_FLOAT_EQ(xptr[i * 2 + j], dat1[i * 2 + j] + x[j]);
@@ -672,7 +672,7 @@ TEST_F(TestTensorMath, SubRowCuda) {
d.ToDevice(&dev);
SubRow(t, &d);
d.ToHost();
- const float *xptr = d.data<const float *>();
+ const float *xptr = d.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 2; j++) {
EXPECT_FLOAT_EQ(xptr[i * 2 + j], dat1[i * 2 + j] - x[j]);
@@ -688,7 +688,7 @@ TEST_F(TestTensorMath, MultRowCuda) {
d.ToDevice(&dev);
MultRow(t, &d);
d.ToHost();
- const float *xptr = d.data<const float *>();
+ const float *xptr = d.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 2; j++) {
EXPECT_FLOAT_EQ(xptr[i * 2 + j], dat1[i * 2 + j] * x[j]);
@@ -702,7 +702,7 @@ TEST_F(TestTensorMath, DivRowCpp) {
t.CopyDataFromHostPtr(x, 2);
d.CopyDataFromHostPtr(dat1, 6);
DivRow(t, &d);
- const float *xptr = d.data<const float *>();
+ const float *xptr = d.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 2; j++) {
EXPECT_FLOAT_EQ(xptr[i * 2 + j], dat1[i * 2 + j] / x[j]);
@@ -719,7 +719,7 @@ TEST_F(TestTensorMath, DivRowCuda) {
d.ToDevice(&dev);
DivRow(t, &d);
d.ToHost();
- const float *xptr = d.data<const float *>();
+ const float *xptr = d.data<float>();
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 2; j++) {
EXPECT_FLOAT_EQ(xptr[i * 2 + j], dat1[i * 2 + j] / x[j]);
@@ -733,7 +733,7 @@ TEST_F(TestTensorMath, SumRowsCuda) {
d.ToDevice(&dev);
SumRows(d, &t);
t.ToHost();
- const float *tptr = t.data<const float *>();
+ const float *tptr = t.data<float>();
for (int i = 0; i < 2; i++) {
float tmp = 0;
for (int j = 0; j < 3; j++) {
@@ -749,7 +749,7 @@ TEST_F(TestTensorMath, SumColumnCuda) {
d.ToDevice(&dev);
SumColumns(d, &t);
t.ToHost();
- const float *tptr = t.data<const float *>();
+ const float *tptr = t.data<float>();
for (int i = 0; i < 3; i++) {
float tmp = 0;
for (int j = 0; j < 2; j++) {
[2/4] incubator-singa git commit: SINGA-203 Add OpenCV detection for
cmake compilation
Posted by wa...@apache.org.
SINGA-203 Add OpenCV detection for cmake compilation
If USE_OPENCV is ON (default OFF), the compilation will search for OpenCV libraries installed in the system.
Project: http://git-wip-us.apache.org/repos/asf/incubator-singa/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-singa/commit/67ee3c5b
Tree: http://git-wip-us.apache.org/repos/asf/incubator-singa/tree/67ee3c5b
Diff: http://git-wip-us.apache.org/repos/asf/incubator-singa/diff/67ee3c5b
Branch: refs/heads/dev
Commit: 67ee3c5bb97c484f9b4da3db45b5ab55310ae0b9
Parents: bef1db0
Author: xiezl <xi...@comp.nus.edu.sg>
Authored: Tue Jun 21 17:51:59 2016 +0800
Committer: jixin <ji...@comp.nus.edu.sg>
Committed: Thu Jun 23 17:20:38 2016 +0800
----------------------------------------------------------------------
cmake/Dependencies.cmake | 7 +++++++
test/CMakeLists.txt | 3 ++-
2 files changed, 9 insertions(+), 1 deletion(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/67ee3c5b/cmake/Dependencies.cmake
----------------------------------------------------------------------
diff --git a/cmake/Dependencies.cmake b/cmake/Dependencies.cmake
index 11823b7..ab869fb 100644
--- a/cmake/Dependencies.cmake
+++ b/cmake/Dependencies.cmake
@@ -33,6 +33,13 @@ INCLUDE_DIRECTORIES(SYSTEM ${GLOG_INCLUDE_DIRS})
LIST(APPEND SINGA_LINKER_LIBS ${GLOG_LIBRARIES})
#MESSAGE(STATUS "Found glog at ${GLOG_INCLUDE_DIRS}")
+IF(USE_OPENCV)
+ FIND_PACKAGE(OpenCV REQUIRED)
+ MESSAGE(STATUS "Found OpenCV_${OpenCV_VERSION} at ${OpenCV_INCLUDE_DIRS}")
+ INCLUDE_DIRECTORIES(SYSTEM ${OpenCV_INCLUDE_DIRS})
+ LIST(APPEND SINGA_LINKER_LIBS ${OpenCV_LIBRARIES})
+ENDIF()
+
#LIST(APPEND SINGA_LINKER_LIBS "/home/wangwei/local/lib/libopenblas.so")
#MESSAGE(STATUS "link lib : " ${SINGA_LINKER_LIBS})
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/67ee3c5b/test/CMakeLists.txt
----------------------------------------------------------------------
diff --git a/test/CMakeLists.txt b/test/CMakeLists.txt
index 92401ad..95c3cf7 100644
--- a/test/CMakeLists.txt
+++ b/test/CMakeLists.txt
@@ -7,5 +7,6 @@ AUX_SOURCE_DIRECTORY(singa singa_test_source)
ADD_EXECUTABLE(test_singa "gtest/gtest_main.cc" ${singa_test_source})
ADD_DEPENDENCIES(test_singa singa_core singa_utils)
MESSAGE(STATUS "link libs" ${singa_linker_libs})
-TARGET_LINK_LIBRARIES(test_singa gtest singa_core singa_utils singa_model proto protobuf ${SINGA_LINKER_LIBS})
+TARGET_LINK_LIBRARIES(test_singa gtest singa_core singa_utils singa_model
+ singa_io proto protobuf ${SINGA_LINKER_LIBS})
SET_TARGET_PROPERTIES(test_singa PROPERTIES LINK_FLAGS "${LINK_FLAGS} -pthread")
[3/4] incubator-singa git commit: SINGA-200 - Implement Encoder and
Decoder for data pre-processing
Posted by wa...@apache.org.
SINGA-200 - Implement Encoder and Decoder for data pre-processing
Add base class Encoder and Decoder.
Add inheritance class Image2JPG_Encoder and Image2JPG_Decoder, which uses opencv to encode and decode image source files.
Add test which contains partial pre-processing procedures (read_raw_image, encode, decode) for images.
Reader and Writer, which uses user specified offline store mechanisms (i.e., kvfile, lmdb, ...), are not implemented in this ticket.
Use random value initialized image for test.
Add derived encoder/decoder class definition in its base class head file (decoder.h/encoder.h).
Project: http://git-wip-us.apache.org/repos/asf/incubator-singa/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-singa/commit/13d60b03
Tree: http://git-wip-us.apache.org/repos/asf/incubator-singa/tree/13d60b03
Diff: http://git-wip-us.apache.org/repos/asf/incubator-singa/diff/13d60b03
Branch: refs/heads/dev
Commit: 13d60b034fe0b08f2fe128a8ad575d72e68001ea
Parents: 67ee3c5
Author: jixin <ji...@comp.nus.edu.sg>
Authored: Wed Jun 22 19:22:17 2016 +0800
Committer: jixin <ji...@comp.nus.edu.sg>
Committed: Thu Jun 23 17:20:38 2016 +0800
----------------------------------------------------------------------
.gitignore | 1 +
CMakeLists.txt | 2 +-
include/singa/io/decoder.h | 14 +++--
include/singa/io/encoder.h | 11 +++-
include/singa/io/image2jpg_decoder.h | 40 --------------
include/singa/io/image2jpg_encoder.h | 40 --------------
src/CMakeLists.txt | 2 +-
src/io/image2jpg_decoder.cc | 54 -------------------
src/io/image2jpg_encoder.cc | 69 ------------------------
src/io/jpg2proto_encoder.cc | 70 +++++++++++++++++++++++++
src/io/proto2jpg_decoder.cc | 57 ++++++++++++++++++++
src/proto/model.proto | 28 ++++------
test/singa/test_decoder.cc | 87 +++++++++++++++++++++++++++++++
test/singa/test_io.cc | 65 -----------------------
14 files changed, 247 insertions(+), 293 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/13d60b03/.gitignore
----------------------------------------------------------------------
diff --git a/.gitignore b/.gitignore
index eaa2d84..221b3d7 100644
--- a/.gitignore
+++ b/.gitignore
@@ -10,3 +10,4 @@
build/
thirdparty/*
!thirdparty/install.sh
+test/samples/
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/13d60b03/CMakeLists.txt
----------------------------------------------------------------------
diff --git a/CMakeLists.txt b/CMakeLists.txt
index 46b6bfb..c61f8a4 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -22,7 +22,7 @@ INCLUDE_DIRECTORIES(${SINGA_INCLUDE_DIR})
OPTION(USE_CBLAS "Use CBlas libs" ON)
OPTION(USE_CUDA "Use Cuda libs" ON)
OPTION(USE_CUDNN "Use Cudnn libs" ON)
-OPTION(USE_OPENCV "Use opencv" OFF)
+OPTION(USE_OPENCV "Use opencv" ON)
OPTION(USE_LMDB "Use LMDB libs" OFF)
OPTION(USE_PYTHON "Generate py wrappers" OFF)
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/13d60b03/include/singa/io/decoder.h
----------------------------------------------------------------------
diff --git a/include/singa/io/decoder.h b/include/singa/io/decoder.h
index 8330e34..003dd59 100644
--- a/include/singa/io/decoder.h
+++ b/include/singa/io/decoder.h
@@ -22,6 +22,7 @@
#include <vector>
#include <string>
#include "singa/core/tensor.h"
+#include "singa/proto/model.pb.h"
namespace singa {
namespace io {
@@ -31,13 +32,18 @@ class Decoder {
Decoder() { }
virtual ~Decoder() { }
+ virtual void Setup(const DecoderConf& conf) = 0;
+
/**
* Decode value to get data and labels
*/
- virtual std::vector<Tensor> Decode(std::string value) {
- vector<Tensor> output;
- return output;
- }
+ virtual std::vector<Tensor> Decode(std::string value) = 0;
+};
+
+class Proto2JPGDecoder : public Decoder {
+ public:
+ void Setup(const DecoderConf& conf) override;
+ std::vector<Tensor> Decode(std::string value) override;
};
} // namespace io
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/13d60b03/include/singa/io/encoder.h
----------------------------------------------------------------------
diff --git a/include/singa/io/encoder.h b/include/singa/io/encoder.h
index 66a2fe5..5a8dbeb 100644
--- a/include/singa/io/encoder.h
+++ b/include/singa/io/encoder.h
@@ -22,6 +22,7 @@
#include <vector>
#include <string>
#include "singa/core/tensor.h"
+#include "singa/proto/model.pb.h"
namespace singa {
namespace io {
@@ -30,13 +31,21 @@ class Encoder {
public:
Encoder() { }
virtual ~Encoder() { }
+
+ virtual void Setup(const EncoderConf& conf) = 0;
/**
* Format each sample data as a string,
* whose structure depends on the proto definition.
* e.g., {key, shape, label, type, data, ...}
*/
- virtual std::string Encode(vector<Tensor>& data) { return ""; }
+ virtual std::string Encode(vector<Tensor>& data) = 0;
+};
+
+class JPG2ProtoEncoder : public Encoder {
+ public:
+ void Setup(const EncoderConf& conf) override;
+ std::string Encode(vector<Tensor>& data) override;
};
} // namespace io
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/13d60b03/include/singa/io/image2jpg_decoder.h
----------------------------------------------------------------------
diff --git a/include/singa/io/image2jpg_decoder.h b/include/singa/io/image2jpg_decoder.h
deleted file mode 100644
index 6895c29..0000000
--- a/include/singa/io/image2jpg_decoder.h
+++ /dev/null
@@ -1,40 +0,0 @@
-/**
- * Licensed to the Apache Software Foundation (ASF) under one
- * or more contributor license agreements. See the NOTICE file
- * distributed with this work for additional information
- * regarding copyright ownership. The ASF licenses this file
- * to you under the Apache License, Version 2.0 (the
- * "License"); you may not use this file except in compliance
- * with the License. You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef SINGA_IO_IMAGE2JPG_DECODER_H_
-#define SINGA_IO_IMAGE2JPG_DECODER_H_
-
-#include <vector>
-#include <string>
-#include "singa/core/tensor.h"
-#include "singa/io/decoder.h"
-#include "singa/proto/model.pb.h"
-#include <opencv2/highgui/highgui.hpp>
-#include <opencv2/imgproc/imgproc.hpp>
-
-namespace singa {
-namespace io {
-
-class Image2JPGDecoder : public Decoder {
- public:
- std::vector<Tensor> Decode(std::string value) override;
-};
-
-} // namespace io
-} // namespace singa
-#endif // SINGA_IO_IMAGE2JPG_DECODER_H_
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/13d60b03/include/singa/io/image2jpg_encoder.h
----------------------------------------------------------------------
diff --git a/include/singa/io/image2jpg_encoder.h b/include/singa/io/image2jpg_encoder.h
deleted file mode 100644
index 2e94b64..0000000
--- a/include/singa/io/image2jpg_encoder.h
+++ /dev/null
@@ -1,40 +0,0 @@
-/**
- * Licensed to the Apache Software Foundation (ASF) under one
- * or more contributor license agreements. See the NOTICE file
- * distributed with this work for additional information
- * regarding copyright ownership. The ASF licenses this file
- * to you under the Apache License, Version 2.0 (the
- * "License"); you may not use this file except in compliance
- * with the License. You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#ifndef SINGA_IO_IMAGE2JPG_ENCODER_H_
-#define SINGA_IO_IMAGE2JPG_ENCODER_H_
-
-#include <vector>
-#include <string>
-#include "singa/core/tensor.h"
-#include "singa/io/encoder.h"
-#include "singa/proto/model.pb.h"
-#include <opencv2/highgui/highgui.hpp>
-#include <opencv2/imgproc/imgproc.hpp>
-
-namespace singa {
-namespace io {
-
-class Image2JPGEncoder : public Encoder {
- public:
- std::string Encode(vector<Tensor>& data) override;
-};
-
-} // namespace io
-} // namespace singa
-#endif // SINGA_IO_IMAGE2JPG_ENCODER_H_
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/13d60b03/src/CMakeLists.txt
----------------------------------------------------------------------
diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt
index 90343d5..e5970d8 100644
--- a/src/CMakeLists.txt
+++ b/src/CMakeLists.txt
@@ -57,7 +57,7 @@ LIST(APPEND SINGA_LINKER_LIBS singa_model)
AUX_SOURCE_DIRECTORY(io io_source)
ADD_LIBRARY(singa_io SHARED ${io_source})
-TARGET_LINK_LIBRARIES(singa_io ${SINGA_LIBKER_LIBS})
+TARGET_LINK_LIBRARIES(singa_io ${SINGA_LINKER_LIBS})
LIST(APPEND SINGA_LINKER_LIBS singa_io)
#ADD_LIBRARY(singa_layer SHARED ${LAYER_SOURCE})
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/13d60b03/src/io/image2jpg_decoder.cc
----------------------------------------------------------------------
diff --git a/src/io/image2jpg_decoder.cc b/src/io/image2jpg_decoder.cc
deleted file mode 100644
index da0c909..0000000
--- a/src/io/image2jpg_decoder.cc
+++ /dev/null
@@ -1,54 +0,0 @@
-/**
- * Licensed to the Apache Software Foundation (ASF) under one
- * or more contributor license agreements. See the NOTICE file
- * distributed with this work for additional information
- * regarding copyright ownership. The ASF licenses this file
- * to you under the Apache License, Version 2.0 (the
- * "License"); you may not use this file except in compliance
- * with the License. You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include "singa/io/image2jpg_decoder.h"
-#include <vector>
-//#include <opencv2/core/core.hpp>
-//#include <opencv2/highgui/highgui.hpp>
-//#include "opencv2/opencv.hpp"
-
-using namespace cv;
-using namespace std;
-
-namespace singa {
-
-namespace io {
- vector<Tensor> Image2JPGDecoder::Decode(string value) {
- vector<Tensor> output;
- RecordProto image;
- image.ParseFromString(value);
- Shape shape(image.shape().begin(), image.shape().end());
- Tensor features(shape), labels(Shape{1});
-
- //string pixel = image.pixel();
- vector<unsigned char> pixel(image.pixel().begin(), image.pixel().end());
- Mat buff(shape[1], shape[2], CV_8UC3, pixel.data());
- Mat mat = imdecode(buff, CV_LOAD_IMAGE_COLOR);
- vector<int> data;
- data.assign(mat.datastart, mat.dataend);
- //for (size_t i = 0; i < image.pixel().size(); i++)
- // data[i] = static_cast<int>(static_cast<uint8_t>(pixel[i]));
- features.CopyDataFromHostPtr<vector<int>>(&data, data.size());
- int l[1] = {image.label()};
- labels.CopyDataFromHostPtr(l, 1);
- output.push_back(features);
- output.push_back(labels);
- return output;
- }
-}
-}
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/13d60b03/src/io/image2jpg_encoder.cc
----------------------------------------------------------------------
diff --git a/src/io/image2jpg_encoder.cc b/src/io/image2jpg_encoder.cc
deleted file mode 100644
index 4a1f428..0000000
--- a/src/io/image2jpg_encoder.cc
+++ /dev/null
@@ -1,69 +0,0 @@
-/**
- * Licensed to the Apache Software Foundation (ASF) under one
- * or more contributor license agreements. See the NOTICE file
- * distributed with this work for additional information
- * regarding copyright ownership. The ASF licenses this file
- * to you under the Apache License, Version 2.0 (the
- * "License"); you may not use this file except in compliance
- * with the License. You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-#include "singa/io/image2jpg_encoder.h"
-//#include <opencv2/core/core.hpp>
-//#include <opencv2/highgui/highgui.hpp>
-//#include "opencv2/opencv.hpp"
-
-using namespace cv;
-using namespace std;
-
-namespace singa {
-
-namespace io{
- string Image2JPGEncoder::Encode(vector<Tensor>& data) {
- // suppose data[0]: data, data[1]: label
- // suppose data[0] has a shape as {channel, height, width}
- CHECK_EQ(data[0].nDim(), 3u);
- string output;
- size_t height = data[0].shape()[1];
- size_t width = data[0].shape()[2];
- Mat mat = Mat(height, width, CV_8UC3);
- Mat resized;
- resize(mat, resized, Size(256, 256));
- Mat test = imread("test/samples/test.jpeg", CV_LOAD_IMAGE_COLOR);
- if (data[0].data_type() == kInt)
- memcpy(mat.data, data[0].data<const int*>(), data[0].Size()*sizeof(int));
- else LOG(FATAL) << "Data type is invalid for an raw image";
- //cout << mat << endl;
-
- const int* label;
- // suppose each image is attached with only one label
- if (data[1].data_type() == kInt)
- label = data[1].data<const int*>();
- else LOG(FATAL) << "Data type is invalid for image label";
-
- vector<uchar> buff;
- vector<int> param = vector<int>(2);
- param[0] = CV_IMWRITE_JPEG_QUALITY;
- param[1] = 95; // default is 95
- imencode(".jpg", mat, buff, param);
- string buf(buff.begin(), buff.end());
-
- RecordProto image;
- image.set_label(label[0]);
- for (size_t i = 0; i < data[0].nDim(); i++)
- image.add_shape(data[0].shape()[i]);
- image.set_pixel(buf);
- image.SerializeToString(&output);
-
- return output;
- }
-}
-}
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/13d60b03/src/io/jpg2proto_encoder.cc
----------------------------------------------------------------------
diff --git a/src/io/jpg2proto_encoder.cc b/src/io/jpg2proto_encoder.cc
new file mode 100644
index 0000000..5b006e1
--- /dev/null
+++ b/src/io/jpg2proto_encoder.cc
@@ -0,0 +1,70 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "singa/io/encoder.h"
+#include "singa/proto/model.pb.h"
+#include <opencv2/highgui/highgui.hpp>
+#include <opencv2/imgproc/imgproc.hpp>
+
+namespace singa {
+
+namespace io{
+ void JPG2ProtoEncoder::Setup(const EncoderConf& conf) { return; }
+
+ std::string JPG2ProtoEncoder::Encode(vector<Tensor>& data) {
+ // suppose data[0]: data, data[1]: label
+ // data[0] has a shape as {height, width, channel}
+ CHECK_EQ(data[0].nDim(), 3u);
+ int height = data[0].shape()[0];
+ int width = data[0].shape()[1];
+ int channel = data[0].shape()[2];
+ cv::Mat mat = cv::Mat(height, width, CV_8UC3, cv::Scalar(0, 0, 0));
+ CHECK_EQ(height, mat.rows);
+ CHECK_EQ(width, mat.cols);
+ CHECK_EQ(channel, mat.channels());
+
+ if (data[0].data_type() != kInt)
+ LOG(FATAL) << "Data type " << data[0].data_type() <<" is invalid for an raw image";
+ const int* raw = data[0].data<const int*>();
+ for (int i = 0; i < height; i++)
+ for (int j = 0; j < width; j++)
+ for (int k = 0; k < channel; k++)
+ mat.at<cv::Vec3b>(i, j)[k] = static_cast<uchar>(raw[i * width * channel + j * channel + k]);
+ // suppose each image is attached with only one label
+ const int* label = data[1].data<const int*>();
+ CHECK_EQ(label[0], 2);
+
+ // encode image with jpg format
+ std::vector<uchar> buff;
+ std::vector<int> param = std::vector<int>(2);
+ param[0] = CV_IMWRITE_JPEG_QUALITY;
+ param[1] = 100; // default is 95
+ cv::imencode(".jpg", mat, buff, param);
+ std::string buf(buff.begin(), buff.end());
+
+ std::string output;
+ ImageRecordProto image;
+ image.set_label(label[0]);
+ for (size_t i = 0; i < data[0].nDim(); i++)
+ image.add_shape(data[0].shape()[i]);
+ image.set_pixel(buf);
+ image.SerializeToString(&output);
+ return output;
+ }
+}
+}
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/13d60b03/src/io/proto2jpg_decoder.cc
----------------------------------------------------------------------
diff --git a/src/io/proto2jpg_decoder.cc b/src/io/proto2jpg_decoder.cc
new file mode 100644
index 0000000..fd8d9b3
--- /dev/null
+++ b/src/io/proto2jpg_decoder.cc
@@ -0,0 +1,57 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "singa/io/decoder.h"
+#include "singa/proto/model.pb.h"
+#include <opencv2/highgui/highgui.hpp>
+#include <opencv2/imgproc/imgproc.hpp>
+
+namespace singa {
+
+namespace io {
+ void Proto2JPGDecoder::Setup(const DecoderConf& conf) { return; }
+
+ std::vector<Tensor> Proto2JPGDecoder::Decode(std::string value) {
+ std::vector<Tensor> output;
+ ImageRecordProto image;
+ image.ParseFromString(value);
+ Shape shape(image.shape().begin(), image.shape().end());
+ Tensor raw(shape), label(Shape{1});
+ std::vector<uchar> pixel(image.pixel().begin(), image.pixel().end());
+
+ // decode image
+ cv::Mat mat = cv::imdecode(cv::Mat(pixel), CV_LOAD_IMAGE_COLOR);
+ int height = mat.rows, width = mat.cols, channel = mat.channels();
+ CHECK_EQ(shape[0], height);
+ CHECK_EQ(shape[1], width);
+ CHECK_EQ(shape[2], channel);
+
+ float* data = new float[raw.Size()];
+ for (int i = 0; i < height; i++)
+ for (int j = 0; j < width; j++)
+ for (int k = 0; k < channel; k++)
+ data[i * width * channel + j * channel + k] = static_cast<float>(static_cast<int>(mat.at<cv::Vec3b>(i, j)[k]));
+ raw.CopyDataFromHostPtr<float>(data, raw.Size());
+ float l = static_cast<float>(image.label());
+ label.CopyDataFromHostPtr(&l, 1);
+ output.push_back(raw);
+ output.push_back(label);
+ return output;
+ }
+}
+}
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/13d60b03/src/proto/model.proto
----------------------------------------------------------------------
diff --git a/src/proto/model.proto b/src/proto/model.proto
index 77a7f75..8666c30 100644
--- a/src/proto/model.proto
+++ b/src/proto/model.proto
@@ -51,28 +51,20 @@ message BlobProto {
optional int32 width = 4 [default = 0];
}
-/// directly copy from v0.3
-message Record {
- enum Type {
- // each record contains image raw feature and its label.
- kSingleLabelImage = 0;
- }
- optional Type type = 1 [default = kSingleLabelImage];
- optional string user_type =2;
- // configuration for
- optional RecordProto image = 5;
-
- extensions 101 to 200;
-}
-
-// rename SingleLabelImageRecord to RecordProto
-message RecordProto {
+// rename RecordProto to ImageRecordProto
+message ImageRecordProto {
repeated int32 shape = 1;
optional int32 label = 2;
optional bytes pixel = 3;
- repeated float data = 4 [packed = true];
}
-/// end of copy v0.3
+
+message EncoderConf {
+ optional string type = 1 [default = 'jpg'];
+}
+
+message DecoderConf {
+ optional string type = 1 [default = 'jpg'];
+}
message FillerConf {
// The filler type, case insensitive
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/13d60b03/test/singa/test_decoder.cc
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diff --git a/test/singa/test_decoder.cc b/test/singa/test_decoder.cc
new file mode 100644
index 0000000..33c4cd4
--- /dev/null
+++ b/test/singa/test_decoder.cc
@@ -0,0 +1,87 @@
+/************************************************************
+*
+* Licensed to the Apache Software Foundation (ASF) under one
+* or more contributor license agreements. See the NOTICE file
+* distributed with this work for additional information
+* regarding copyright ownership. The ASF licenses this file
+* to you under the Apache License, Version 2.0 (the
+* "License"); you may not use this file except in compliance
+* with the License. You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing,
+* software distributed under the License is distributed on an
+* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+* KIND, either express or implied. See the License for the
+* specific language governing permissions and limitations
+* under the License.
+*
+*************************************************************/
+
+#include "../include/singa/io/encoder.h"
+#include "../include/singa/io/decoder.h"
+#include "gtest/gtest.h"
+#include <time.h>
+#include <opencv2/highgui/highgui.hpp>
+#include <opencv2/imgproc/imgproc.hpp>
+
+using namespace singa;
+
+TEST(Decoder, Decode) {
+ io::JPG2ProtoEncoder encoder;
+ io::Proto2JPGDecoder decoder;
+
+ // initial random seed
+ srand(time(NULL));
+
+ size_t height = 40, width = 30;
+ size_t nheight = 256, nwidth = 256, channel = 3;
+ size_t total = nheight * nwidth * channel;
+ int raw_label = 2;
+ cv::Mat image(height, width, CV_8UC3);
+ for (size_t i = 0; i < height; i++)
+ for (size_t j = 0; j < width; j++)
+ for (size_t k = 0; k < channel; k++)
+ image.at<cv::Vec3b>(i, j)[k] = static_cast<uchar>(rand() % 256);
+
+ cv::Mat transformed;
+ cv::Size size(nwidth, nheight);
+ cv::resize(image, transformed, size);
+ EXPECT_EQ(nwidth, transformed.cols);
+ EXPECT_EQ(nheight, transformed.rows);
+ EXPECT_EQ(channel, transformed.channels());
+
+ unsigned char* buff = transformed.data;
+ int* buf = new int[total];
+ for (size_t i = 0; i < total; i++)
+ buf[i] = static_cast<int>(buff[i]);
+ Shape shape{nheight, nwidth, channel};
+ Tensor pixel(shape, kInt), label(Shape{1}, kInt);
+ pixel.CopyDataFromHostPtr<int>(buf, total);
+ label.CopyDataFromHostPtr<int>(&raw_label, 1);
+
+ std::vector<Tensor> input;
+ input.push_back(pixel);
+ input.push_back(label);
+ const int* in_pixel = input[0].data<const int *>();
+ for(size_t i = 0; i < total; i++)
+ EXPECT_EQ(buf[i], in_pixel[i]);
+ const int* in_label = input[1].data<const int *>();
+ EXPECT_EQ(2, in_label[0]);
+ EXPECT_EQ(2, input.size());
+
+ std::string tmp = encoder.Encode(input);
+ std::vector<Tensor> output = decoder.Decode(tmp);
+ EXPECT_EQ(2, output.size());
+ EXPECT_EQ(kFloat32, output[0].data_type());
+ Shape out_shape = output[0].shape();
+ for (size_t i = 0; i < shape.size(); i++)
+ EXPECT_EQ(shape[i], out_shape[i]);
+ const float* out_label = output[1].data<const float*>();
+ EXPECT_EQ(raw_label, out_label[0]);
+ // opencv imencode will have some information loss
+ //const float* out_pixel = output[0].data<const float*>();
+ //for(size_t i = 0; i < total; i++)
+ // EXPECT_LE(fabs(in_pixel[i]-out_pixel[i]), 10.f);
+}
http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/13d60b03/test/singa/test_io.cc
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diff --git a/test/singa/test_io.cc b/test/singa/test_io.cc
deleted file mode 100644
index 16853c4..0000000
--- a/test/singa/test_io.cc
+++ /dev/null
@@ -1,65 +0,0 @@
-/************************************************************
-*
-* Licensed to the Apache Software Foundation (ASF) under one
-* or more contributor license agreements. See the NOTICE file
-* distributed with this work for additional information
-* regarding copyright ownership. The ASF licenses this file
-* to you under the Apache License, Version 2.0 (the
-* "License"); you may not use this file except in compliance
-* with the License. You may obtain a copy of the License at
-*
-* http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing,
-* software distributed under the License is distributed on an
-* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-* KIND, either express or implied. See the License for the
-* specific language governing permissions and limitations
-* under the License.
-*
-*************************************************************/
-
-#include "../include/singa/io/image2jpg_encoder.h"
-#include "../include/singa/io/image2jpg_decoder.h"
-#include "gtest/gtest.h"
-#include <opencv2/highgui/highgui.hpp>
-#include <opencv2/imgproc/imgproc.hpp>
-
-using namespace singa;
-using namespace singa::io;
-using namespace cv;
-
-TEST(Decoder, Decode) {
- Encoder encoder;
- Decoder decoder;
- string path = "test/samples/test.jpeg";
- size_t resize_height = 256;
- size_t resize_width = 256;
- size_t channel = 3;
- int raw_label[] = {1};
- Mat image = imread(path, CV_LOAD_IMAGE_COLOR);
- Mat transformed;
- Size size(resize_height, resize_width);
- resize(image, transformed, size);
-
- vector<int> buff;
- buff.assign(transformed.datastart, transformed.dataend);
- Shape shape{channel, (size_t)transformed.size().height, (size_t)transformed.size().width};
- Tensor pixel(shape), label(Shape{1});
- pixel.CopyDataFromHostPtr<vector<int>>(&buff, buff.size());
- label.CopyDataFromHostPtr<int>(raw_label, 1);
-
- vector<Tensor> input;
- input.push_back(pixel);
- input.push_back(label);
- string str0 = encoder.Encode(input);
- vector<Tensor> output = decoder.Decode(str0);
- Shape out_shape = output.at(0).shape();
- const int* out_pixel = output.at(0).data<const int *>();
- const int* out_label = output.at(1).data<const int *>();
- EXPECT_EQ(raw_label[0], out_label[0]);
- for (size_t i = 0; i < shape.size(); i++)
- EXPECT_EQ(shape[i], out_shape[i]);
- for(size_t i = 0; i < 10; i++)
- EXPECT_EQ(buff[i], out_pixel[i]);
-}