import?os?pdb?platform?time?warnings
import?ctypes?as?ct
import?numpy?as?np
import?scipy.sparse?as?sp

MAX_ONES?=?1024*1024*32

if?platform.system（）?==?‘Windows‘:
????_cudamat?=?ct.cdll.LoadLibrary（‘libcudamat.dll‘）
else:
????_cudamat?=?ct.cdll.LoadLibrary（‘libcudamat.so‘）

_cudamat.get_last_cuda_error.restype?=?ct.c_char_p
_cudamat.cublas_init.restype?=?ct.c_int
_cudamat.cublas_shutdown.restype?=?ct.c_int
_cudamat.cuda_set_device.restype?=?ct.c_int
_cudamat.init_random.restype?=?ct.c_int

_cudamat.init_empty.restype?=?ct.c_int
_cudamat.reshape.restype?=?ct.c_int
_cudamat.copy_to_host.restype?=?ct.c_int
_cudamat.allocate_device_memory?=?ct.c_int
_cudamat.copy_to_device.restype?=?ct.c_int
_cudamat.copy_on_device.restype?=?ct.c_int
_cudamat.free_device_memory.restype?=?ct.c_int

_cudamat.get_slice.restype?=?ct.c_int
_cudamat.get_row_slice.restype?=?ct.c_int
_cudamat.set_row_slice.restype?=?ct.c_int
_cudamat.copy_transpose.restype?=?ct.c_int
_cudamat.get_vector_slice.restype?=?ct.c_int
_cudamat.fill_with_rand.restype?=?ct.c_int
_cudamat.fill_with_randn.restype?=?ct.c_int

_cudamat.add_col_vec.restype?=?ct.c_int
_cudamat.add_col_mult.restype?=?ct.c_int
_cudamat.add_row_mult.restype?=?ct.c_int
_cudamat.add_row_vec.restype?=?ct.c_int
_cudamat.mult_by_col_vec.restype?=?ct.c_int
_cudamat.mult_by_row_vec.restype?=?ct.c_int

_cudamat.less_than.restype?=?ct.c_int
_cudamat.less_than_scalar.restype?=?ct.c_int
_cudamat.greater_than.restype?=?ct.c_int
_cudamat.greater_than_scalar.restype?=?ct.c_int
_cudamat.max_by_axis.restype?=?ct.c_int
_cudamat.argmax_by_axis.restype?=?ct.c_int
_cudamat.sqsum_by_axis.restype?=?ct.c_int
_cudamat.normlimit_by_axis.restype?=?ct.c_int
_cudamat.sign.restype?=?ct.c_int
_cudamat.apply_sigmoid.restype?=?ct.c_int
_cudamat.apply_tanh.restype?=?ct.c_int
_cudamat.apply_abs.restype?=?ct.c_int
_cudamat.apply_log_1_plus_exp.restype?=?ct.c_int
_cudamat.apply_log.restype?=?ct.c_int
_cudamat.apply_floor.restype?=?ct.c_int
_cudamat.apply_ceil.restype?=?ct.c_int
_cudamat.apply_exp.restype?=?ct.c_int
_cudamat.apply_sqrt.restype?=?ct.c_int
_cudamat.apply_pow.restype?=?ct.c_int
_cudamat.apply_pow_matrix.restype?=?ct.c_int
_cudamat.reciprocal.restype?=?ct.c_int

_cudamat.add_elementwise.restype?=?ct.c_int
_cudamat.subtract_elementwise.restype?=?ct.c_int
_cudamat.divide_elementwise.restype?=?ct.c_int
_cudamat.mult_elementwise.restype?=?ct.c_int
_cudamat.apply_logistic_deriv.restype?=?ct.c_int
_cudamat.assign_scalar.restype?=?ct.c_int
_cudamat.mult_by_scalar.restype?=?ct.c_int
_cudamat.divide_by_scalar.restype?=?ct.c_int
_cudamat.add_scalar.restype?=?ct.c_int

_cudamat.read_from.restype?=?ct.c_float
_cudamat.euclid_norm.restype?=?ct.c_float
_cudamat.selectRows.restype?=?ct.c_int
_cudamat.setSelectedRows.restype?=?ct.c_int
_cudamat.vdot.restype?=?ct.c_float
_cudamat.dot.restype?=?ct.c_int

def?deprecated（func）:
????“““This?is?a?decorator?which?can?be?used?to?mark?functions
????as?deprecated.?It?will?result?in?a?warning?being?emmitted
????when?the?f

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????文件?????????233??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\.gitignore
?????文件????????1896??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\INSTALL
?????文件????????1324??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\LICENSE.txt
?????文件????????2996??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\Makefile
?????文件?????????737??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\README.md
?????文件??????????71??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\bin\.gitignore
?????文件???????12024??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cpu\convnet_cpu.cc
?????文件????????3179??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cpu\convnet_cpu.h
?????文件???????10966??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cpu\cpuconv.cc
?????文件????????2713??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cpu\cpuconv.h
?????文件????????3741??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cpu\extract_representation_cpu.cc
?????文件????????1401??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cpu\Makefile
?????文件??????????66??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\.gitignore
?????文件???????96783??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\cudamat.cu
?????文件???????12481??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\cudamat.cuh
?????文件???????62872??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\cudamat.py
?????文件????????3833??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\cudamat_conv.cuh
?????文件????????8610??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\cudamat_conv.py
?????文件??????158265??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\cudamat_conv_filteracts.cu
?????文件??????187698??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\cudamat_conv_imgacts.cu
?????文件??????193970??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\cudamat_conv_others.cu
?????文件????????1875??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\cudamat_conv_util.cu
?????文件????????2897??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\cudamat_conv_util.cuh
?????文件??????227172??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\cudamat_conv_weightacts.cu
?????文件???????70249??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\cudamat_kernels.cu
?????文件???????14612??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\cudamat_kernels.cuh
?????文件????????7978??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\gpu_lock2.py
?????文件?????????846??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\Makefile
?????文件??????192369??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\rnd_multipliers_32bit.h
?????文件?????????677??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\run_on_me_or_pid_quit
?????文件??????????22??2020-10-22?12:23??TorontoDeepLearning-convnet-981771b\cudamat\__init__.py
............此處省略213個文件信息