The CompiledProgram is used to transform a program for various optimizations. For example, you can use
with_data_parallel to transform the program to data parallel program so that it can be run in multiple devices.
# Note: # - If you want to specify the GPU cards which are used to run # in ParallelExecutor, you should define the CUDA_VISIBLE_DEVICES # in environment. # - If you want to use multi CPU to run the program in ParallelExecutor, # you should define the CPU_NUM in the environment. # First create the Executor. place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() exe = fluid.Executor(place) # Run the startup program once and only once. exe.run(fluid.default_startup_program()) # Run the main program directly without compile. loss = exe.run(fluid.default_main_program(), feed=feed_dict, fetch_list=[loss.name]) # Or, compiled the program, and then run the model with data parallel. exec_strategy = fluid.ExecutionStrategy() exec_strategy.num_threads = dev_count * 4 # the size of thread pool. build_strategy = fluid.BuildStrategy() build_strategy.memory_optimize = True if memory_opt else False compiled_prog = compiler.CompiledProgram( fluid.default_main_program()).with_data_parallel( loss_name=loss.name, build_strategy=build_strategy, exec_strategy=exec_strategy) loss, = exe.run(compiled_prog, feed=feed_dict, fetch_list=[loss.name])
compiler.CompiledPorgram are completely different
fluid.Porgram is composed of a series of operators.
compiler.CompiledPorgram compiles the
fluid.Porgram and converts it into a computational graph.
compiler.CompiledPorgram cannot be saved at present.
- Related API :