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Bidirectional lstm example #2093 #2096

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May 12, 2016
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config mk
xlvector committed May 11, 2016
commit 2280c0acdc36342df6c7a6017a02fded4da52b9c
15 changes: 8 additions & 7 deletions make/config.mk
Original file line number Diff line number Diff line change
@@ -28,10 +28,10 @@ export NVCC = nvcc
DEBUG = 0

# the additional link flags you want to add
ADD_LDFLAGS =
ADD_LDFLAGS =

# the additional compile flags you want to add
ADD_CFLAGS =
ADD_CFLAGS =

#---------------------------------------------
# matrix computation libraries for CPU/GPU
@@ -43,18 +43,18 @@ USE_CUDA = 0
# add the path to CUDA library to link and compile flag
# if you have already add them to environment variable, leave it as NONE
# USE_CUDA_PATH = /usr/local/cuda
USE_CUDA_PATH = /usr/local/cuda-7.5
USE_CUDA_PATH = NONE

# whether use CuDNN R3 library
USE_CUDNN = 1
USE_CUDNN = 0

# whether use cuda runtime compiling for writing kernels in native language (i.e. Python)
USE_NVRTC = 1
USE_NVRTC = 0

# whether use opencv during compilation
# you can disable it, however, you will not able to use
# imbin iterator
USE_OPENCV = 0
USE_OPENCV = 1

# use openmp for parallelization
USE_OPENMP = 1
@@ -66,7 +66,7 @@ UNAME_S := $(shell uname -s)
ifeq ($(UNAME_S), Darwin)
USE_BLAS = apple
else
USE_BLAS = openblas
USE_BLAS = atlas
endif

# add path to intel library, you may need it for MKL, if you did not add the path
@@ -112,6 +112,7 @@ EXTRA_OPERATORS =
#----------------------------

# whether to use torch integration. This requires installing torch.
# You also need to add TORCH_PATH/install/lib to your LD_LIBRARY_PATH
# TORCH_PATH = $(HOME)/torch
# MXNET_PLUGINS += plugin/torch/torch.mk