Yang Mao leo-mao

Common Options

-#, --progress-bar Make curl display a simple progress bar instead of the more informational standard meter.

-b, --cookie <name=data> Supply cookie with request. If no =, then specifies the cookie file to use (see -c).

-c, --cookie-jar <file name> File to save response cookies to.

	You are Manus, an AI agent created by the Manus team.

	You excel at the following tasks:
	1. Information gathering, fact-checking, and documentation
	2. Data processing, analysis, and visualization
	3. Writing multi-chapter articles and in-depth research reports
	4. Creating websites, applications, and tools
	5. Using programming to solve various problems beyond development
	6. Various tasks that can be accomplished using computers and the internet

	[Trigger]
	Operation = Remove
	Type = Package
	Target = *

	[Action]
	Description = Clearing cache...
	When = PostTransaction
	Exec = /home/<user>/.local/bin/tools/removehook

	<annotation>
	<folder>GeneratedData_Train</folder>
	<filename>000001.png</filename>
	<path>/my/path/GeneratedData_Train/000001.png</path>
	<source>
	<database>Unknown</database>
	</source>
	<size>
	<width>224</width>
	<height>224</height>

	'''
	The code is inspired from François Chollet's answer to the following quora question[1] and distributed tensorflow tutorial[2].

	It runs the Keras MNIST mlp example across multiple servers.

	This sample code runs multiple processes on a single host. It can be configured
	to run on multiple hosts simply by chaning the host names given in ClusterSpec.

	Training the model:

	from keras.optimizers import Adam
	from keras import backend as K
	from keras.datasets import mnist
	from keras.utils.np_utils import to_categorical
	from keras.metrics import categorical_accuracy
	from keras.initializations import glorot_uniform, zero
	import numpy as np

	# inputs and targets are placeholders
	input_dim = 28*28

	"""Example of barrier implementation using TensorFlow shared variables.

	All workers synchronize on barrier, copy global parameters to local versions
	and increment global parameter variable asynchronously. Should see something
	like this:

	bash> killall python
	bash> python simple_barrier.py --num_workers=4
	worker 0, local_param 4 global_param 5
	worker 2, local_param 4 global_param 7

	"""
	Python implementation of the color map function for the PASCAL VOC data set.
	Official Matlab version can be found in the PASCAL VOC devkit
	http://host.robots.ox.ac.uk/pascal/VOC/voc2012/index.html#devkit
	"""
	import numpy as np
	from skimage.io import imshow
	import matplotlib.pyplot as plt

	def color_map(N=256, normalized=False):