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@ -12,7 +12,6 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#pragma once
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#include <stddef.h>
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@ -61,8 +60,8 @@ class RangeError {};
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/// Not support Error, such as access GPU memory directly, etc.
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class UnsupportError : public std::runtime_error {
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public:
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UnsupportError() : std::runtime_error(" ") {};
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UnsupportError(const std::string& message) : std::runtime_error(message) {};
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UnsupportError() : std::runtime_error(" "){};
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UnsupportError(const std::string& message) : std::runtime_error(message){};
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};
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/// This type will map to python's list of float.
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@ -112,7 +111,8 @@ public:
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/**
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* Create A Matrix with height,width, which is filled by zero.
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*/
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static Matrix* createZero(size_t height, size_t width,
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static Matrix* createZero(size_t height,
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size_t width,
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bool useGpu = isUsingGpu());
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/**
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@ -124,8 +124,11 @@ public:
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*
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* @note the default sparse type is SPARSE_CSR.
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*/
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static Matrix* createSparse(size_t height, size_t width, size_t nnz,
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bool isNonVal = true, bool trans = false,
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static Matrix* createSparse(size_t height,
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size_t width,
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size_t nnz,
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bool isNonVal = true,
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bool trans = false,
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bool useGpu = isUsingGpu());
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/**
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@ -134,13 +137,17 @@ public:
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* @param data list of float should be passed in python.
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* @note the value will be copy into a new matrix.
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*/
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static Matrix* createDense(const std::vector<float>& data, size_t height,
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size_t width, bool useGpu = isUsingGpu());
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static Matrix* createDenseFromNumpy(float* data, int dim1, int dim2,
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bool copy = true,
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bool useGpu = isUsingGpu())
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throw (UnsupportError);
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static Matrix* createDense(const std::vector<float>& data,
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size_t height,
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size_t width,
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bool useGpu = isUsingGpu());
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static Matrix* createDenseFromNumpy(
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float* data,
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int dim1,
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int dim2,
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bool copy = true,
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bool useGpu = isUsingGpu()) throw(UnsupportError);
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/**
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* Create Cpu Dense Matrix from numpy matrix, dtype=float32
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@ -151,7 +158,9 @@ public:
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* @param copy true if copy into a new matrix, false will create
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* matrix inplace.
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*/
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static Matrix* createCpuDenseFromNumpy(float* data, int dim1, int dim2,
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static Matrix* createCpuDenseFromNumpy(float* data,
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int dim1,
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int dim2,
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bool copy = false);
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/// Create Gpu Dense Matrix from numpy matrix, dtype=float32
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@ -171,11 +180,13 @@ public:
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* numpy_mat = m.toNumpyMat()
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* @endcode
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*/
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void toNumpyMatInplace(float** view_data, int* dim1,
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void toNumpyMatInplace(float** view_data,
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int* dim1,
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int* dim2) throw(UnsupportError);
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/// Copy To numpy mat.
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void copyToNumpyMat(float** view_m_data, int* dim1,
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void copyToNumpyMat(float** view_m_data,
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int* dim1,
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int* dim2) throw(UnsupportError);
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/// Copy From Numpy Mat
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@ -248,15 +259,18 @@ public:
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static Vector* create(const std::vector<float>& data,
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bool useGpu = isUsingGpu());
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static Vector* createVectorFromNumpy(float* data, int dim, bool copy = true,
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bool useGpu = isUsingGpu())
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throw (UnsupportError);
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static Vector* createVectorFromNumpy(
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float* data,
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int dim,
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bool copy = true,
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bool useGpu = isUsingGpu()) throw(UnsupportError);
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/**
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* Create Cpu Vector from numpy array, which dtype=float32
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*
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* If copy is false, it will create vector inplace.
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*/
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static Vector* createCpuVectorFromNumpy(float* data, int dim,
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static Vector* createCpuVectorFromNumpy(float* data,
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int dim,
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bool copy = false);
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/// Create Gpu Vector from numpy array, which dtype=float32
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@ -312,16 +326,19 @@ public:
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static IVector* create(const std::vector<int>& data,
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bool useGpu = isUsingGpu());
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static IVector* createVectorFromNumpy(int* data, int dim, bool copy = true,
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bool useGpu = isUsingGpu())
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throw (UnsupportError);
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static IVector* createVectorFromNumpy(
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int* data,
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int dim,
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bool copy = true,
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bool useGpu = isUsingGpu()) throw(UnsupportError);
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/**
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* Create Cpu IVector from numpy array, which dtype=int32
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*
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* If copy is false, it will create vector inplace
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*/
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static IVector* createCpuVectorFromNumpy(int* data, int dim,
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static IVector* createCpuVectorFromNumpy(int* data,
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int dim,
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bool copy = false);
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/**
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* Create Gpu IVector from numpy array, which dtype=int32
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@ -605,7 +622,8 @@ class ParameterTraverseCallback {
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public:
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~ParameterTraverseCallback();
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void apply(const std::vector<Vector*>& vecs, const ParameterConfig& config,
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void apply(const std::vector<Vector*>& vecs,
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const ParameterConfig& config,
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size_t sparseId);
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private:
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@ -638,7 +656,8 @@ public:
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void finishBatch();
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void update(const std::vector<Vector*>& vecs, const ParameterConfig& conf,
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void update(const std::vector<Vector*>& vecs,
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const ParameterConfig& conf,
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size_t sparseId = NO_SPARSE_ID);
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std::vector<int> getParameterTypes() const;
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@ -678,7 +697,8 @@ public:
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* model config by TrainerConfig
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*/
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static GradientMachine* createByModelConfig(
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ModelConfig* conf, GradientMatchineCreateMode mode = CREATE_MODE_NORMAL,
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ModelConfig* conf,
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GradientMatchineCreateMode mode = CREATE_MODE_NORMAL,
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const std::vector<int>& parameterTypes = defaultParamTypes);
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/**
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@ -701,7 +721,8 @@ public:
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/**
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* Combine forward/backward
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*/
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void forwardBackward(const Arguments& inArgs, Arguments* outArgs,
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void forwardBackward(const Arguments& inArgs,
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Arguments* outArgs,
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PassType passType,
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const UpdateCallback& callback = UpdateCallback());
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@ -722,14 +743,17 @@ public:
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*/
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SequenceGenerator* asSequenceGenerator(
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const std::vector<std::string>& dict = std::vector<std::string>(),
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size_t begin_id = 0UL, size_t end_id = 0UL, size_t max_length = 100UL,
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size_t begin_id = 0UL,
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size_t end_id = 0UL,
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size_t max_length = 100UL,
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size_t beam_size = -1UL);
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private:
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GradientMachinePrivate* m;
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static GradientMachine* createFromPaddleModelPtr(
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const void* confPtr, GradientMatchineCreateMode mode,
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const void* confPtr,
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GradientMatchineCreateMode mode,
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const std::vector<int>& types);
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// Not to use c++ 11 init-list, so we use static var as function default arg.
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@ -751,8 +775,8 @@ public:
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/// Create A Trainer By TrainerConfig. using paddle command line.
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static Trainer* createByCommandLine() throw(IOError);
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static Trainer* create(TrainerConfig* optConfig, GradientMachine* gm)
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throw(IOError);
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static Trainer* create(TrainerConfig* optConfig,
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GradientMachine* gm) throw(IOError);
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/// Start training
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void startTrain();
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dangqingqing
9 years ago