add TensorType.h

paddle/function/TensorShape.h

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+Licensed 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. */
+
+#pragma once
+
+#include <glog/logging.h>
+
+namespace paddle {
+
+/**
+ * TensorShape used to represent shape of normal tensor.
+ */
+class TensorShape {
+public:
+  TensorShape() : ndims_(0), nelements_(0) { initDims(0); }
+
+  TensorShape(size_t ndims) : ndims_(ndims), nelements_(1) { initDims(ndims); };
+
+  TensorShape(std::initializer_list<size_t> dims) {
+    ndims_ = dims.size();
+    initDims(ndims_);
+    std::copy(dims.begin(), dims.end(), dims_.begin());
+    numElements();
+  };
+
+  TensorShape(const TensorShape& t)
+      : ndims_(t.ndims_), nelements_(t.nelements_) {
+    initDims(ndims_);
+    std::copy(t.dims_.begin(), t.dims_.end(), dims_.begin());
+  };
+
+  // get the size of specified dimension
+  size_t operator[](size_t dim) const {
+    CHECK_GE(dim, 0);
+    CHECK_LT(dim, ndims_);
+    return dims_[dim];
+  }
+
+  // set the size of specified dimension
+  void setDim(size_t dim, size_t size) {
+    CHECK_GE(dim, 0);
+    CHECK_LT(dim, ndims_);
+    dims_[dim] = size;
+    numElements();
+  }
+
+  // number of dimensions of the tensor
+  size_t ndims() const { return ndims_; }
+
+  size_t getElements() const { return nelements_; }
+
+  bool operator==(const TensorShape& t) const {
+    if (ndims() != t.ndims()) return false;
+    for (size_t i = 0; i < ndims(); i++) {
+      if (dims_[i] != t.dims_[i]) return false;
+    }
+
+    return true;
+  }
+
+  bool operator!=(const TensorShape& t) const { return !(*this == t); }
+
+private:
+  // compute number of elements
+  void numElements() {
+    nelements_ = 1;
+    for (size_t n = 0; n < ndims_; n++) {
+      nelements_ *= dims_[n];
+    }
+  }
+
+  // init dims_
+  void initDims(size_t ndims) {
+    size_t count = ndims < 4 ? 4 : ndims;
+    dims_.assign(count, 1);
+  }
+
+  // number of dimensions
+  // ndims_ may be not equeal dims_.size()
+  size_t ndims_;
+  // number of elements
+  size_t nelements_;
+  std::vector<size_t> dims_;
+};
+
+}  // namespace paddle

paddle/function/TensorShapeTest.cpp

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+Licensed 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 "TensorShape.h"
+#include <gtest/gtest.h>
+
+namespace paddle {
+
+TEST(TensorShape, Constructor) {
+  TensorShape t1;
+  EXPECT_EQ(t1.ndims(), 0);
+  EXPECT_EQ(t1.getElements(), 0);
+
+  TensorShape t2(3);
+  EXPECT_EQ(t2.ndims(), 3);
+  EXPECT_EQ(t2.getElements(), 1);
+
+  TensorShape t3({8, 10});
+  EXPECT_EQ(t3.ndims(), 2);
+  EXPECT_EQ(t3.getElements(), 80);
+
+  TensorShape t4(t3);
+  EXPECT_EQ(t4.ndims(), t3.ndims());
+  EXPECT_EQ(t4.getElements(), t3.getElements());
+
+  TensorShape t5({1, 2, 3, 4, 5});
+  EXPECT_EQ(t5.ndims(), 5);
+  EXPECT_EQ(t5.getElements(), 120);
+}
+
+TEST(TensorShape, GetAndSet) {
+  TensorShape t({1, 2, 3});
+  EXPECT_EQ(t.ndims(), 3);
+  EXPECT_EQ(t.getElements(), 6);
+
+  EXPECT_EQ(t[1], 2);
+  t.setDim(1, 100);
+  EXPECT_EQ(t.getElements(), 300);
+  EXPECT_EQ(t[1], 100);
+}
+
+}  // namespace paddle

paddle/function/TensorType.h

@@ -14,7 +14,7 @@ limitations under the License. */
 
 #pragma once
 
-#include <glog/logging.h>
+#include "paddle/math/Matrix.h"
 
 namespace paddle {
 
@@ -57,69 +57,60 @@ struct DataType<double> {
   static const ValueType value = VALUE_TYPE_DOUBLE;
 };
 
-/**
- * TensorShape used to represent shape of normal tensor.
- */
-class TensorShape {
-public:
-  TensorShape() : ndims_(0), nelements_(0) { initDims(0); }
-
-  TensorShape(size_t ndims) : ndims_(ndims), nelements_(1) { initDims(ndims); };
-
-  TensorShape(std::initializer_list<size_t> dims) {
-    ndims_ = dims.size();
-    initDims(ndims_);
-    std::copy(dims.begin(), dims.end(), dims_.begin());
-    numElements();
-  };
-
-  TensorShape(const TensorShape& t)
-      : ndims_(t.ndims_), nelements_(t.nelements_) {
-    initDims(ndims_);
-    std::copy(t.dims_.begin(), t.dims_.end(), dims_.begin());
-  };
-
-  // get the size of specified dimension
-  size_t operator[](size_t dim) const {
-    CHECK_GE(dim, 0);
-    CHECK_LT(dim, ndims_);
-    return dims_[dim];
-  }
+namespace detail {
 
-  // set the size of specified dimension
-  void setDim(size_t dim, size_t size) {
-    CHECK_GE(dim, 0);
-    CHECK_LT(dim, ndims_);
-    dims_[dim] = size;
-    numElements();
-  }
+template <typename VType, DeviceType Device>
+struct MatrixT;
 
-  // number of dimensions of the tensor
-  size_t ndims() const { return ndims_; }
+template <>
+struct MatrixT<real, DEVICE_TYPE_CPU> {
+  using type = CpuMatrix;
+};
 
-  size_t getElements() const { return nelements_; }
+template <>
+struct MatrixT<real, DEVICE_TYPE_GPU> {
+  using type = GpuMatrix;
+};
 
-private:
-  // compute number of elements
-  void numElements() {
-    nelements_ = 1;
-    for (size_t n = 0; n < ndims_; n++) {
-      nelements_ *= dims_[n];
-    }
-  }
+template <>
+struct MatrixT<int, DEVICE_TYPE_CPU> {
+  using type = void;  // Not implemented
+};
 
-  // init dims_
-  void initDims(size_t ndims) {
-    size_t count = ndims < 4 ? 4 : ndims;
-    dims_.assign(count, 1);
-  }
+template <>
+struct MatrixT<int, DEVICE_TYPE_GPU> {
+  using type = void;  // Not implemented
+};
+
+template <typename VType, DeviceType Device>
+struct VectorT;
+
+template <>
+struct VectorT<real, DEVICE_TYPE_CPU> {
+  using type = CpuVector;
+};
+
+template <>
+struct VectorT<real, DEVICE_TYPE_GPU> {
+  using type = GpuVector;
+};
+
+template <>
+struct VectorT<int, DEVICE_TYPE_CPU> {
+  using type = CpuIVector;
+};
+
+template <>
+struct VectorT<int, DEVICE_TYPE_GPU> {
+  using type = GpuIVector;
+};
+
+}  // namespace detail
 
-  // number of dimensions
-  // ndims_ may be not equeal dims_.size()
-  size_t ndims_;
-  // number of elements
-  size_t nelements_;
-  std::vector<size_t> dims_;
+template <typename VType, DeviceType DType>
+struct Tensor {
+  typedef typename detail::MatrixT<VType, DType>::type Matrix;
+  typedef typename detail::VectorT<VType, DType>::type Vector;
 };
 
 }  // namespace paddle

paddle/function/TensorTypeTest.cpp

@@ -17,37 +17,31 @@ limitations under the License. */
 
 namespace paddle {
 
-TEST(TensorShape, Constructor) {
-  TensorShape t1;
-  EXPECT_EQ(t1.ndims(), 0);
-  EXPECT_EQ(t1.getElements(), 0);
-
-  TensorShape t2(3);
-  EXPECT_EQ(t2.ndims(), 3);
-  EXPECT_EQ(t2.getElements(), 1);
-
-  TensorShape t3({8, 10});
-  EXPECT_EQ(t3.ndims(), 2);
-  EXPECT_EQ(t3.getElements(), 80);
-
-  TensorShape t4(t3);
-  EXPECT_EQ(t4.ndims(), t3.ndims());
-  EXPECT_EQ(t4.getElements(), t3.getElements());
-
-  TensorShape t5({1, 2, 3, 4, 5});
-  EXPECT_EQ(t5.ndims(), 5);
-  EXPECT_EQ(t5.getElements(), 120);
+TEST(TensorType, Matrix) {
+  Tensor<real, DEVICE_TYPE_CPU>::Matrix matrix(100, 200);
+  EXPECT_EQ(matrix.getHeight(), 100);
+  EXPECT_EQ(matrix.getWidth(), 200);
+  EXPECT_EQ(matrix.getElementCnt(), 100 * 200);
+  EXPECT_EQ(matrix.useGpu(), false);
+
+  Tensor<real, DEVICE_TYPE_GPU>::Matrix testGpu(100, 200);
+  EXPECT_EQ(testGpu.useGpu(), true);
 }
 
-TEST(TensorShape, GetAndSet) {
-  TensorShape t({1, 2, 3});
-  EXPECT_EQ(t.ndims(), 3);
-  EXPECT_EQ(t.getElements(), 6);
-
-  EXPECT_EQ(t[1], 2);
-  t.setDim(1, 100);
-  EXPECT_EQ(t.getElements(), 300);
-  EXPECT_EQ(t[1], 100);
+TEST(TensorType, Vector) {
+  Tensor<real, DEVICE_TYPE_CPU>::Vector cpuVector(100);
+  Tensor<real, DEVICE_TYPE_GPU>::Vector gpuVector(100);
+  EXPECT_EQ(cpuVector.useGpu(), false);
+  EXPECT_EQ(gpuVector.useGpu(), true);
+  EXPECT_EQ(cpuVector.getSize(), 100);
+  EXPECT_EQ(gpuVector.getSize(), 100);
+
+  Tensor<int, DEVICE_TYPE_CPU>::Vector cpuIVector(100);
+  Tensor<int, DEVICE_TYPE_GPU>::Vector gpuIVector(100);
+  EXPECT_EQ(cpuIVector.useGpu(), false);
+  EXPECT_EQ(gpuIVector.useGpu(), true);
+  EXPECT_EQ(cpuIVector.getSize(), 100);
+  EXPECT_EQ(gpuIVector.getSize(), 100);
 }
 
 }  // namespace paddle