def create_adset(data, group, platform, basic_data):
json_data = {
"name": common.get_name(group, platform),
"status": "ACTIVE",
"daily_budget": 1000,
"bid_amount": int(os.environ['bid_amount']),
"campaign_id": data['campaign_id'],
"bid_strategy": "LOWEST_COST_WITH_BID_CAP",
"billing_event": "IMPRESSIONS",
"attribution_spec": [{
"event_type": "CLICK_THROUGH",
"window_days": 7
}],
"optimization_goal": "OFFSITE_CONVERSIONS",
"promoted_object": {
"application_id": "634204786734953",
"object_store_url":
basic_data['object_store_url'][platform.lower()],
"custom_event_type": "PURCHASE"
},
"targeting": data['targeting'],
"access_token": os.environ['access_token']
}
res = requests.post(common.get_adset_url(), json=json_data)
out = json.loads(res.text)
res.close()
if 'id' in out:
return out['id']
else:
return None
def create_ad(adset_id, group, platform, videos):
global tindex
video = videos[tindex % len(videos)]
link = "http://play.google.com/store/apps/details?id=com.tap4fun.brutalage_test"
if platform.lower() == 'ios' or 'ios' in platform.lower():
link = "https://itunes.apple.com/app/id1156787368"
json_data = {
"name": common.get_name(group, platform),
"adset_id": adset_id,
"status": "ACTIVE",
"creative": {
"object_story_spec": {
"page_id": "1643949305846284",
"video_data": {
"video_id": video['videoid'],
"message": video['message'],
"call_to_action": {
"type": "INSTALL_MOBILE_APP",
"value": {
"application": "634204786734953",
"link": link
}
},
"image_url": video['image_url']
}
}
},
"access_token": os.environ['access_token']
}
res = requests.post(common.get_ad_url(), json=json_data)
res.close()
out = json.loads(res.text)
tindex += 1
if 'id' in out:
return out['id']
else:
return None
is_iid = False
model = "CNN"
E = 1
project_name = f"{model}{NC}c{E}e{max_rounds}r{n_clients_per_round}f-{server_opt}-{client_opt_strategy[0]}-{client_opt}-scf"
client_lr_lg = -0.5
server_lr_lg = 0
for client_lr_lg in np.arange(-1.5, 1.0, 0.5):
client_lr = 10**client_lr_lg
for server_lr_lg in np.arange(-1, 1.5, 0.5):
server_lr = 10**server_lr_lg
config = TorchFederatedLearnerEMNISTConfig(
CLIENT_LEARNING_RATE=client_lr,
CLIENT_OPT=common.get_name(client_opt),
CLIENT_OPT_ARGS=common.get_args(client_opt),
# CLIENT_OPT_L2=1e-4,
CLIENT_OPT_STRATEGY=client_opt_strategy,
SERVER_OPT=common.get_name(server_opt),
SERVER_OPT_ARGS=common.get_args(server_opt),
SERVER_LEARNING_RATE=server_lr,
IS_IID_DATA=is_iid,
BATCH_SIZE=B,
CLIENT_FRACTION=C,
N_CLIENTS=NC,
N_EPOCH_PER_CLIENT=E,
MAX_ROUNDS=max_rounds,
MODEL=model,
SCAFFOLD=True)
config_technical = TorchFederatedLearnerTechnicalConfig(