def test_runs_sweeps(request_mocker):
"""Request a bunch of runs from different sweeps at the same time.
Ensure each run's sweep attribute is set to the appropriate value.
"""
api = Api()
run_responses = [random_run_response() for _ in range(7)]
sweep_a_response = random_sweep_response()
sweep_b_response = random_sweep_response()
run_responses[0]['sweepName'] = sweep_b_response['name']
run_responses[1]['sweepName'] = sweep_a_response['name']
run_responses[3]['sweepName'] = sweep_b_response['name']
run_responses[4]['sweepName'] = sweep_a_response['name']
run_responses[5]['sweepName'] = sweep_b_response['name']
run_responses[6]['sweepName'] = sweep_b_response['name']
runs_response = {
'project': {
'runCount': len(run_responses),
'runs': {
'pageInfo': {
'hasNextPage': False
},
'edges': [{
'node': r,
'cursor': 'cursor'
} for r in run_responses],
}
}
}
mock_graphql_request(request_mocker,
runs_response,
body_match='query Runs')
mock_graphql_request(request_mocker,
{'project': {
'sweep': sweep_a_response
}},
body_match=sweep_a_response['name'])
mock_graphql_request(request_mocker,
{'project': {
'sweep': sweep_b_response
}},
body_match=sweep_b_response['name'])
runs = list(api.runs('test/test'))
sweep_a = runs[1].sweep
sweep_b = runs[0].sweep
assert len(runs) == len(run_responses)
assert sweep_a.runs == [runs[1], runs[4]]
assert sweep_b.runs == [runs[0], runs[3], runs[5], runs[6]]
assert runs[0].sweep is sweep_b
assert runs[1].sweep is sweep_a
assert runs[2].sweep is None
assert runs[3].sweep is sweep_b
assert runs[4].sweep is sweep_a
assert runs[5].sweep is sweep_b
assert runs[6].sweep is sweep_b
from wandb import Api
import pandas as pd
from tqdm import tqdm
import matplotlib.pyplot as plt
plt.rcParams.update({'font.size': 18, 'legend.fontsize': 14})
api = Api()
runs = api.runs(
"jeppe742/language-of-molecules-graph", {
'$and': [{
'config.model': 'Transformer'
}, {
'config.num_layers': 4
}, {
'config.edge_encoding': 1
}, {
'config.dataset': 'qm9'
}, {
'tags': {
"$ne": "old"
}
}]
})
df = None
for run in tqdm(runs):
df_temp = run.history()
#df_temp['Attention'] = run.config['edge_encoding'] if isinstance(run.config['edge_encoding'], int) else run.config['edge_encoding']['value']
df_temp['dataset'] = run.config['dataset']
df_temp['epsilon_greedy'] = run.config['epsilon_greedy'] if isinstance(
run.config['epsilon_greedy'],
from wandb import Api
import pandas as pd
from tqdm import tqdm
import matplotlib.pyplot as plt
plt.rcParams.update({'font.size': 18, 'legend.fontsize': 14})
api = Api()
runs = api.runs(
"jeppe742/language-of-molecules-graph", {
'$and': [{
'config.model': 'Transformer'
}, {
'config.num_layers': 4
}, {
'tags': {
"$ne": "old"
}
}]
})
attention_types = {
0: 'Graph attention',
2: 'Graph edge attention',
1: 'Full graph attention'
}
df = None
for run in tqdm(runs):
df_temp = run.history()
df_temp['Attention'] = run.config['edge_encoding'] if isinstance(