pickle

Numpy load with `allow_pickle=true` old `keras` in `tensorflow.keras`

由 落爺英雄遲暮 提交于 2021-02-05 10:47:41
问题 Numpy load with allow_pickle=true old keras in tensorflow.keras Situation I have taken a course, where a Jupyter-notebook with a few example use-cases was provided. In order to save time and to have a clean working-environment, I've decided to use the Docker-image: jupyter/tensorflow-notebook:latest (see here). These are the pip list results for the relevant modules: [...] Keras-Applications 1.0.8 Keras-Preprocessing 1.1.0 [...] numpy 1.17.5 [...] tensorflow 2.1.0 [...] (a) The following

How to save object using pygame.Surfaces to file using pickle

由 别来无恙 提交于 2021-02-05 06:42:11
问题 If I have created my own class which has some attributes that are pygame.Surfaces and I would like to save this object to a file, how can I do this as an error occurs when I try. The class which I have created is an object which is essentially the following (Item class is included because the player has items which have attributes that are pygame.Surfaces): class Item: def __init__(self,name,icon): self.name = name self.icon = pygame.image.load(icon) class Player(pygame.Sprite): def __init__

saving python object in postgres table with pickle

由 半腔热情 提交于 2021-02-04 07:31:12
问题 I have a python script which creates some objects. I would like to be able to save these objects into my postgres database for use later. My thinking was I could pickle an object, then store that in a field in the db. But I'm going round in circles about how to store and retrieve and use the data. I've tried storing the pickle binary string as text but I can't work out how to encode / escape it. Then how to load the string as a binary string to unpickle. I've tried storing the data as bytea

caffe的python接口

由 坚强是说给别人听的谎言 提交于 2021-02-02 00:57:22
python接口，我的理解主要是两个，一个是原来caffe官方给的，这里是 接口介绍 。另一个是SSD框架加的model_libs.py，主要是添加了一些base_network和一些相关的函数。这两个如果能够用得很好的话，兄弟，恭喜你！你已经精通caffe的python接口了。其实不用说的，这个接口很方便，从此你不再需要手动去写什么网络，单独去执行什么bat又或者是sh的命令训练测试了，接口的可移植性非常好，我们将这些必要的设置写在python文件里，完成上面的一套工作。因此，在我看来，SSD的python接口就是上面两个的完美结合。 第一个就是官方给的，官方是这么介绍的： Python The Python interface – pycaffe – is the caffe module and its scripts in caffe/python. import caffe to load models, do forward and backward , handle IO , visualize networks, and even instrument model solving . All model data, derivatives, and parameters are exposed for reading and writing. caffe.Net

How to load my pickeled ML model from GCS to Dataflow/Apache beam

由 爷，独闯天下 提交于 2021-01-29 10:07:07
问题 I've developed an apache beam pipeline locally where I run predictions on a sample file. Locally on my computer I can load the model like this: with open('gs://newbucket322/my_dumped_classifier.pkl', 'rb') as fid: gnb_loaded = cPickle.load(fid) but when running on google dataflow that doesn't obviously work. I tried changing the path to GS:// but that also obviously does not work. I also tried this code snippet (from here) that was used to load files: class ReadGcsBlobs(beam.DoFn): def

Why is there a large overhead in pickling numpy arrays?

由 左心房为你撑大大i 提交于 2021-01-28 04:19:25
问题 Suppose I have a simple array in Python: >>> x = [1.0, 2.0, 3.0, 4.0] When pickled, it is a reasonably small size: >>> pickle.dumps(x).__len__() 44 How come if I use a numpy array, the size is so much larger? >>> xn = np.array(x) >>> pickle.dumps(xn).__len__() 187 Converting it to a less precise data type only helps a little bit... >>> x16 = xn.astype('float16') >>> pickle.dumps(x16).__len__() 163 Other numpy/scipy data structures like sparse matrices also don't pickle well. Why? 回答1:

Python3 unpickle a string representation of bytes object

由 雨燕双飞 提交于 2021-01-28 01:11:50
问题 Is there a good way to load a bytes object that is represented as a string, so it can be unpickled? Basic Example Here is a dumb example: import pickle mydict = { 'a': 1111, 'b': 2222 } string_of_bytes_obj = str(pickle.dumps(mydict)) # Deliberate string representation for this quick example. unpickled_dict = pickle.loads(string_of_bytes_obj) # ERROR! Loads takes bytes-like object and not string. Attempt at a Solution One solution is of course to eval the string: unpickled_dict = pickle.loads

How can I marshal a pickled object through an API ( preferably using flask-restplus )?

由 女生的网名这么多〃 提交于 2021-01-28 01:11:34
问题 I have an API fully documented and finished, built in python 3.5/flask using flask-restplus. I'd like to add one chunk of functionality - returning a pickled object as part of one of my responses. General solutions not specific to flask-restplus are welcome, but as my API is fully documented and finished (other than this little bit), I'd rather hang this on rather than fundamentally altering the framework I'm using. My model schema looks like this (simplified): get_fields = api.model('get

How do I test that I'm calling pickle.dump() correctly?

由 让人想犯罪 __ 提交于 2021-01-27 16:45:06
问题 I want to test this method: class Data(object): def save(self, filename=''): if filename: self.filename = filename if not self.filename: raise ValueError('Please provide a path to save to') with open(self.filename, 'w') as f: pickle.dump(self, f) I can set up the test to make sure pickle.dump gets called, and that the first argument is the object: @patch('pickle.dump') def test_pickle_called(self, dump): self.data.save('foo.pkl') self.assertTrue(dump.called) self.assertEquals(self.data, dump

Python multiprocess can't pickle opencv videocapture object

由 蓝咒 提交于 2021-01-27 12:52:49
问题 I am trying to create a independent process to handle my image acquire from camera. But multiprocessing seems to have difficulty pickling videocapture module from opencv. Can anyone suggest a work around ? I am using python 3.7.1 from multiprocessing import Process import multiprocessing as mp import time import logging import logging.handlers import sys import logging from enum import Enum import cv2 class Logger(): @property def logger(self): component = "{}.{}".format(type(self).__module__
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