class Batcher: def __init__(self, batch_size=1024): self.batch_size = batch_size self.oracle = Oracle() def set_batch_size(self, batch_size: int): self.batch_size = batch_size # make predictions one batch at a time, then aggregate the results and return def batch_predict(self, input_data): output = list() while input_data: batch = self.next_batch(input_data) output.append(self.oracle.query(batch)) output = np.concatenate(output) print('{} results predicted'.format(len(output))) return tf.convert_to_tensor(output, dtype=tf.float32) # pop off a batch from the beginning and return # if no more data, return None def next_batch(self, input_data) -> list: batch = list() for i in range(self.batch_size): if input_data: batch.append(input_data.pop(0)) else: break return batch
def execute(self): # display controller parameters self.output_params() # initialize driver initializer = DriverInitializer(debug=self.debug) driver = initializer.get_driver() # login and refine research login_agent = LoginAgent(driver, job_title=self.job_title, job_location=self.job_location) login_agent.login() refine_agent = RefineAgent(driver, distance=self.distance, experience=self.experience, order_by_date=self.order_by_date) refine_agent.refine() # create PageLooper object looper = PageLooper(driver, limit=self.limit, duration=self.duration, date_limit=self.date_limit) result = looper.loop() # close driver and all windows if not self.debug: driver.quit() # get data from PageLooper object input_data, summaries, links = looper.get_all() if self.mode == 'browse': # use oracle to process input_data oracle = Oracle() output = oracle.query(input_data) # stop timer and record time elapsed in minutes runtime_duration = round((time.time() - self.timer) / 60) # use reporter to process output reporter = Reporter() reporter.report(output, summaries, links, runtime_duration, self.confidence_threshold) else: # save input_data with open(self.feature_path, 'w') as output: for entry in input_data: output.write(entry) output.write('<<END>>\n\n') # return driver return driver
""" A class for aeternity oracle clients and servers. Author: John Newby Copyright (c) 2018 aeternity developers Permission to use, copy, modify, and/or distribute this software for any purpose with or without fee is hereby granted, provided that the above copyright notice and this permission notice appear in all copies. THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. """ from oracle import Oracle import sys oracle = Oracle() oracle_pubkey, query_fee, query_ttl, response_ttl, fee, query = sys.argv[1:7] query_id = oracle.query(oracle_pubkey, query_fee, query_ttl, response_ttl, fee, query) oracle.subscribe_query(query_id)
Copyright (c) 2018 aeternity developers Permission to use, copy, modify, and/or distribute this software for any purpose with or without fee is hereby granted, provided that the above copyright notice and this permission notice appear in all copies. THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. """ import json from oracle import Oracle import sys oracle = Oracle() oracle_pubkey = sys.argv[1] query = json.dumps({"action": "recv"}) query_id = oracle.query(oracle_pubkey, 0, 5, 5, 3, query) oracle.subscribe_query(query_id)