代码空间


摘要(Abstract)

Python是一种计算机程序设计语言。是一种面向对象的动态类型语言,最初被设计用于编写自动化脚本(shell),随着版本的不断更新和语言新功能的添加,越来越多被用于独立的、大型项目的开发。Python(英国发音:/ˈpaɪθən/ 美国发音:/ˈpaɪθɑːn/),是一种广泛使用的解释型,高级编程,通用型编程语言,由吉多·范罗苏姆创造,第一版发布于1991年。可以视之为一种改良(加入一些其他编程语言的优点,如面向对象)的LISP。Python的设计哲学强调代码的可读性和简洁的语法(尤其是使用空格缩进划分代码块,而非使用大括号或者关键词)。相比于C++或Java,Python让开发者能够用更少的代码表达想法。不管是小型还是大型程序,该语言都试图让程序的结构清晰明了。 与Scheme、Ruby、Perl、Tcl等动态类型编程语言一样,Python拥有动态类型系统和垃圾回收功能,能够自动管理内存使用,并且支持多种编程范式,包括面向对象、命令式、函数式和过程式编程。其本身拥有一个巨大而广泛的标准库。 Python 解释器本身几乎可以在所有的操作系统中运行。Python的其中一个解释器CPython是用C语言编写的、是一个由社群驱动的自由软件,当前由Python软件基金会管理。


主题(Topic)

项目(Project)
brews/baysplinepy britzl/oneroom sollywollyson/Edhesive-AP-Comp-Sci-Term-1 Tym17/RemoteRanch LudumHub/LD37-Artisan Jovvik/M3137year2019 Desulfo/PSD-to-HTML-3 nidup/ludumdare37 maxpostnikov/ludum-dare-37 markusfisch/RobotClash test_main() File "cnn_test_auto.py", line 119, in test_main loss,acuracy = test(data_path,generate_test, model_path) File "cnn_test_auto.py", line 76, in test loss, accuracy = my_spatial_model.evaluate_generator(generate_test, steps=test_step) #98需要才能重新确定值的大小 File "D:\python 3.6.4\lib\site-packages\keras\legacy\interfaces.py", line 91, in wrapper return func(*args, **kwargs) File "D:\python 3.6.4\lib\site-packages\keras\engine\training.py", line 1472, in evaluate_generator verbose=verbose) File "D:\python 3.6.4\lib\site-packages\keras\engine\training_generator.py", line 346, in evaluate_generator outs = model.test_on_batch(x, y, sample_weight=sample_weight) File "D:\python 3.6.4\lib\site-packages\keras\engine\training.py", line 1256, in test_on_batch outputs = self.test_function(ins) File "D:\python 3.6.4\lib\site-packages\keras\backend\tensorflow_backend.py", line 2715, in __call__ return self._call(inputs) File "D:\python 3.6.4\lib\site-packages\keras\backend\tensorflow_backend.py", line 2675, in _call fetched = self._callable_fn(*array_vals) File "D:\python 3.6.4\lib\site-packages\tensorflow\python\client\session.py", line 1439, in __call__ run_metadata_ptr) File "D:\python 3.6.4\lib\site-packages\tensorflow\python\framework\errors_impl.py", line 528, in __exit__ c_api.TF_GetCode(self.status.status)) tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[128,64,1,1] and type float on /job :localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc [[{{node block2_sepconv1_1/separable_conv2d}}]] Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. [[{{node metrics_33/acc/Mean_1}}]] Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info." class="topic-tag topic-tag-link"> out-of-GPU-memoery free-creations/rachmaninow-vigil NikolaiVChr/flightgear-saab-ja-37-viggen Dorthu/ld37-one-room asyzruffz/Ludum-Dare-37 JaniceZhao/Douban-Dushu-Dataset DK22Pac/vice-37 cliwrap/alpine-37 Zeyad-37/UseCases Zeyad-37/RxRedux knek-little-projects/salt-formula-python-alt-37 37Questions/web laugengebaeck/BwInf-37-R2 T-N-L-37/live_streams aasu14/Garden-Nerd-Flower-Recognition-Data-Science-Competition griseouslight/NEET-Simulator-LD37 jo-37/ban-net yifan-you-37/logistic_reg jo-37/Jo-Util krsh-37/PCA-Analysis 全部项目