file(GLOB GENERAL_OPS RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "*_op.cc") string(REPLACE ".cc" "" GENERAL_OPS "${GENERAL_OPS}") set(pybind_file ${PADDLE_SOURCE_DIR}/paddle/pybind/pybind.h) file(WRITE ${pybind_file} "// Generated by the paddle/operator/CMakeLists.txt. DO NOT EDIT!\n\n") function(op_library TARGET) # op_library is a function to create op library. The interface is same as # cc_library. But it handle split GPU/CPU code and link some common library # for ops. set(OP_LIBRARY ${TARGET} ${OP_LIBRARY} PARENT_SCOPE) set(cc_srcs) set(cu_srcs) set(op_common_deps operator op_registry math_function) set(options "") set(oneValueArgs "") set(multiValueArgs SRCS DEPS) set(pybind_flag 0) cmake_parse_arguments(op_library "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN}) list(LENGTH op_library_SRCS op_library_SRCS_len) if (${op_library_SRCS_len} EQUAL 0) if (EXISTS ${CMAKE_CURRENT_SOURCE_DIR}/${TARGET}.cc) list(APPEND cc_srcs ${TARGET}.cc) endif() if (EXISTS ${CMAKE_CURRENT_SOURCE_DIR}/${TARGET}.cu) list(APPEND cu_srcs ${TARGET}.cu) endif() else() foreach(src ${op_library_SRCS}) if (${src} MATCHES ".*\\.cu$") list(APPEND cu_srcs ${src}) elseif(${src} MATCHES ".*\\.cc$") list(APPEND cc_srcs ${src}) else() message(FATAL_ERROR "${TARGET} Source file ${src} should only be .cc or .cu") endif() endforeach() endif() list(LENGTH cc_srcs cc_srcs_len) if (${cc_srcs_len} EQUAL 0) message(FATAL_ERROR "The op library ${TARGET} should contains at least one .cc file") endif() if (WITH_GPU) nv_library(${TARGET} SRCS ${cc_srcs} ${cu_srcs} DEPS ${op_library_DEPS} ${op_common_deps}) else() cc_library(${TARGET} SRCS ${cc_srcs} DEPS ${op_library_DEPS} ${op_common_deps}) endif() # net_op doesn't need pybind if ("${TARGET}" STREQUAL "net_op") set(pybind_flag 1) endif() # pool_op contains several operators if ("${TARGET}" STREQUAL "pool_op") set(pybind_flag 1) # It's enough to just adding one operator to pybind file(APPEND ${pybind_file} "USE_OP(pool2d);\n") endif() if ("${TARGET}" STREQUAL "compare_op") set(pybind_flag 1) file(APPEND ${pybind_file} "USE_OP(less_than);\nUSE_OP(equal);\n") endif() # pool_with_index_op contains several operators if ("${TARGET}" STREQUAL "pool_with_index_op") set(pybind_flag 1) # It's enough to just adding one operator to pybind file(APPEND ${pybind_file} "USE_OP(max_pool2d_with_index);\n") endif() # conv_op contains several operators if ("${TARGET}" STREQUAL "conv_op") set(pybind_flag 1) # It's enough to just adding one operator to pybind file(APPEND ${pybind_file} "USE_OP(conv2d);\n") endif() # conv_transpose_op contains several operators if ("${TARGET}" STREQUAL "conv_transpose_op") set(pybind_flag 1) # It's enough to just adding one operator to pybind file(APPEND ${pybind_file} "USE_OP(conv2d_transpose);\n") endif() # pool_cudnn_op contains several operators if ("${TARGET}" STREQUAL "pool_cudnn_op") set(pybind_flag 1) # It's enough to just adding one operator to pybind file(APPEND ${pybind_file} "USE_OP(pool2d_cudnn);\n") endif() # save_restore_op contains several operators if ("${TARGET}" STREQUAL "save_restore_op") set(pybind_flag 1) # It's enough to just adding one operator to pybind file(APPEND ${pybind_file} "USE_NO_KERNEL_OP(save);\n") endif() # activation_op contains several operators if ("${TARGET}" STREQUAL "activation_op") set(pybind_flag 1) # It's enough to just adding one operator to pybind file(APPEND ${pybind_file} "USE_OP(sigmoid);\n") endif() # nccl_op contains several operators if ("${TARGET}" STREQUAL "nccl_op") set(pybind_flag 1) # It's enough to just adding one operator to pybind file(APPEND ${pybind_file} "USE_GPU_ONLY_OP(ncclAllReduce);\n") endif() # reduce_op contains several operators if ("${TARGET}" STREQUAL "reduce_op") set(pybind_flag 1) # It's enough to just adding one operator to pybind file(APPEND ${pybind_file} "USE_OP(reduce_sum);\n") endif() if ("${TARGET}" STREQUAL "tensor_array_read_write_op") set(pybind_flag 1) file(APPEND ${pybind_file} "USE_NO_KERNEL_OP(read_from_array);\nUSE_NO_KERNEL_OP(write_to_array);\n") endif() # pybind USE_NO_KERNEL_OP # HACK: if REGISTER_OP_CPU_KERNEL presents the operator must have kernel file(READ ${TARGET}.cc TARGET_CONTENT) string(REGEX MATCH "REGISTER_OP_CPU_KERNEL" regex_result "${TARGET_CONTENT}") string(REPLACE "_op" "" TARGET "${TARGET}") if (${pybind_flag} EQUAL 0 AND regex_result STREQUAL "") file(APPEND ${pybind_file} "USE_NO_KERNEL_OP(${TARGET});\n") set(pybind_flag 1) endif() # pybind USE_CPU_ONLY_OP list(LENGTH cu_srcs cu_srcs_len) if (${pybind_flag} EQUAL 0 AND ${cu_srcs_len} EQUAL 0) file(APPEND ${pybind_file} "USE_CPU_ONLY_OP(${TARGET});\n") set(pybind_flag 1) endif() # pybind USE_OP if (${pybind_flag} EQUAL 0) file(APPEND ${pybind_file} "USE_OP(${TARGET});\n") endif() endfunction() add_subdirectory(math) add_subdirectory(nccl) set(DEPS_OPS cond_op cross_entropy_op recurrent_op dynamic_recurrent_op softmax_with_cross_entropy_op sum_op pool_op maxout_op pool_with_index_op conv_op lstm_op conv_transpose_op nccl_op sequence_conv_op sequence_pool_op lod_rank_table_op lod_tensor_to_array_op array_to_lod_tensor_op lstm_op tensor_array_read_write_op gru_op) op_library(cond_op SRCS cond_op.cc DEPS framework_proto tensor operator net_op) op_library(cross_entropy_op DEPS cross_entropy) op_library(softmax_with_cross_entropy_op DEPS cross_entropy softmax) op_library(conv_op DEPS vol2col) op_library(sum_op DEPS net_op selected_rows_functor) op_library(pool_op DEPS pooling) op_library(maxout_op DEPS maxouting) op_library(pool_with_index_op DEPS pooling) op_library(lod_rank_table_op SRCS lod_rank_table_op.cc DEPS lod_rank_table) op_library(lod_tensor_to_array_op SRCS lod_tensor_to_array_op.cc DEPS lod_rank_table_op) op_library(array_to_lod_tensor_op SRCS array_to_lod_tensor_op.cc DEPS lod_rank_table_op) op_library(tensor_array_read_write_op SRCS tensor_array_read_write_op.cc) if(WITH_GPU) op_library(nccl_op DEPS nccl_common) endif() op_library(sequence_conv_op DEPS context_project) op_library(sequence_pool_op DEPS sequence_pooling) op_library(lstm_op DEPS sequence2batch lstm_compute) op_library(conv_transpose_op DEPS vol2col) op_library(gru_op DEPS sequence2batch gru_compute) if(WITH_TESTING) op_library(dynamic_recurrent_op SRCS dynamic_recurrent_op.cc rnn/recurrent_op_utils.cc DEPS net_op tensor_array gtest) else() op_library(dynamic_recurrent_op SRCS dynamic_recurrent_op.cc rnn/recurrent_op_utils.cc DEPS net_op tensor_array) endif() op_library(recurrent_op SRCS recurrent_op.cc DEPS executor) list(REMOVE_ITEM GENERAL_OPS ${DEPS_OPS}) foreach(src ${GENERAL_OPS}) op_library(${src}) endforeach() set(GLOB_OP_LIB ${OP_LIBRARY} CACHE INTERNAL "Global OP library") cc_test(gather_test SRCS gather_test.cc DEPS tensor) cc_test(net_op_test SRCS net_op_test.cc DEPS net_op) cc_test(scatter_test SRCS scatter_test.cc DEPS tensor) cc_test(beam_search_decode_op_test SRCS beam_search_decode_op_test.cc DEPS lod_tensor) cc_test(strided_memcpy_test SRCS strided_memcpy_test.cc DEPS tensor paddle_memory) cc_test(dynamic_recurrent_op_test SRCS dynamic_recurrent_op_test.cc rnn/recurrent_op_utils.cc DEPS dynamic_recurrent_op) if(WITH_GPU) nv_test(nccl_op_test SRCS nccl_op_test.cu DEPS nccl_op gpu_info device_context) endif() cc_test(save_load_op_test SRCS save_load_op_test.cc DEPS save_op load_op)