mxnet
executor.h
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19 
26 #ifndef MXNET_EXECUTOR_H_
27 #define MXNET_EXECUTOR_H_
28 
29 #include <dmlc/base.h>
30 #include <vector>
31 #include <memory>
32 #include <map>
33 #include <string>
34 #include <utility>
35 #include "./base.h"
36 #include "./c_api.h"
37 #include "./ndarray.h"
38 #include "./operator.h"
39 
40 // check c++11
41 #if DMLC_USE_CXX11 == 0
42 #error "CXX11 was required for symbolic module"
43 #endif
44 
45 namespace mxnet {
47 using nnvm::Symbol;
48 
53 class Executor {
54  public:
56  virtual ~Executor() {}
61  virtual void Forward(bool is_train) = 0;
70  virtual void PartialForward(bool is_train, int step, int *step_left) = 0;
80  virtual void Backward(const std::vector<NDArray> &head_grads, bool is_train = true) = 0;
85  virtual void Print(std::ostream &os) const {} // NOLINT(*)
90  virtual const std::vector<NDArray> &outputs() const = 0;
95  virtual const std::unordered_map<std::string, NDArray>& in_arg_map() const = 0;
100  virtual const std::unordered_map<std::string, NDArray>& arg_grad_map() const = 0;
105  virtual const std::unordered_map<std::string, NDArray>& aux_state_map() const = 0;
120  virtual Executor* Reshape(const bool partial_shaping,
121  const bool allow_up_sizing,
122  const Context& default_ctx,
123  const std::map<std::string, Context>& ctx_map,
124  const std::unordered_map<std::string, TShape>&
125  provided_arg_shapes,
126  std::vector<NDArray>* in_args,
127  std::vector<NDArray>* arg_grads,
128  std::vector<NDArray>* aux_states) = 0;
143  static Executor *Bind(nnvm::Symbol symbol,
144  const Context& default_ctx,
145  const std::map<std::string, Context>& group2ctx,
146  const std::vector<NDArray> &in_args,
147  const std::vector<NDArray> &arg_grad_store,
148  const std::vector<OpReqType> &grad_req_type,
149  const std::vector<NDArray> &aux_states,
150  Executor* shared_exec = NULL);
151 
152  static Executor* SimpleBind(nnvm::Symbol symbol,
153  const Context& default_ctx,
154  const std::map<std::string, Context>& group2ctx,
155  const std::vector<Context>& in_arg_ctxes,
156  const std::vector<Context>& arg_grad_ctxes,
157  const std::vector<Context>& aux_state_ctxes,
158  const std::unordered_map<std::string, TShape>& arg_shape_map,
159  const std::unordered_map<std::string, int>& arg_dtype_map,
160  const std::unordered_map<std::string, int>& arg_stype_map,
161  const std::vector<OpReqType>& grad_req_types,
162  const std::unordered_set<std::string>& param_names,
163  std::vector<NDArray>* in_args,
164  std::vector<NDArray>* arg_grads,
165  std::vector<NDArray>* aux_states,
166  std::unordered_map<std::string, NDArray>*
167  shared_data_arrays = nullptr,
168  Executor* shared_exec = nullptr);
169 
173  typedef std::function<void(const char*, void*)> MonitorCallback;
177  virtual void SetMonitorCallback(const MonitorCallback& callback) {}
178 }; // class executor
179 } // namespace mxnet
180 #endif // MXNET_EXECUTOR_H_
Executor of a computation graph. Executor can be created by Binding a symbol.
Definition: executor.h:53
C API of mxnet.
virtual ~Executor()
destructor
Definition: executor.h:56
static Executor * SimpleBind(nnvm::Symbol symbol, const Context &default_ctx, const std::map< std::string, Context > &group2ctx, const std::vector< Context > &in_arg_ctxes, const std::vector< Context > &arg_grad_ctxes, const std::vector< Context > &aux_state_ctxes, const std::unordered_map< std::string, TShape > &arg_shape_map, const std::unordered_map< std::string, int > &arg_dtype_map, const std::unordered_map< std::string, int > &arg_stype_map, const std::vector< OpReqType > &grad_req_types, const std::unordered_set< std::string > &param_names, std::vector< NDArray > *in_args, std::vector< NDArray > *arg_grads, std::vector< NDArray > *aux_states, std::unordered_map< std::string, NDArray > *shared_data_arrays=nullptr, Executor *shared_exec=nullptr)
std::function< void(const char *, void *)> MonitorCallback
the prototype of user-defined monitor callback
Definition: executor.h:173
virtual void Backward(const std::vector< NDArray > &head_grads, bool is_train=true)=0
Perform a Backward operation of the Operator. This must be called after Forward. After this operation...
namespace of mxnet
Definition: base.h:118
static Executor * Bind(nnvm::Symbol symbol, const Context &default_ctx, const std::map< std::string, Context > &group2ctx, const std::vector< NDArray > &in_args, const std::vector< NDArray > &arg_grad_store, const std::vector< OpReqType > &grad_req_type, const std::vector< NDArray > &aux_states, Executor *shared_exec=NULL)
Create an operator by bind symbol with context and arguments. If user do not want to compute the grad...
virtual void Print(std::ostream &os) const
print the execution plan info to output stream.
Definition: executor.h:85
virtual const std::unordered_map< std::string, NDArray > & in_arg_map() const =0
get input argument map, key is arg name, value is arg&#39;s NDArray.
virtual const std::vector< NDArray > & outputs() const =0
get array of outputs in the executor.
virtual void SetMonitorCallback(const MonitorCallback &callback)
Install a callback to notify the completion of operation.
Definition: executor.h:177
virtual void Forward(bool is_train)=0
Perform a Forward operation of Operator After this operation, user can get the result by using functi...
virtual void PartialForward(bool is_train, int step, int *step_left)=0
Perform a Partial Forward operation of Operator. Only issue operation specified by step...
virtual const std::unordered_map< std::string, NDArray > & arg_grad_map() const =0
get input argument graident map, key is arg name, value is gradient&#39;s NDArray.
virtual const std::unordered_map< std::string, NDArray > & aux_state_map() const =0
get aux state map, key is arg name, value is aux state&#39;s NDArray.
Context information about the execution environment.
Definition: base.h:133
virtual Executor * Reshape(const bool partial_shaping, const bool allow_up_sizing, const Context &default_ctx, const std::map< std::string, Context > &ctx_map, const std::unordered_map< std::string, TShape > &provided_arg_shapes, std::vector< NDArray > *in_args, std::vector< NDArray > *arg_grads, std::vector< NDArray > *aux_states)=0
Return a new executor with the same symbol and shared memory, but different input/output shapes...