miguelgfierro 2019-07-26 14:41:48 +01:00
Π ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒ f2709d00a6
ΠšΠΎΠΌΠΌΠΈΡ‚ fe785b5be4
1 ΠΈΠ·ΠΌΠ΅Π½Ρ‘Π½Π½Ρ‹Ρ… Ρ„Π°ΠΉΠ»ΠΎΠ²: 3 Π΄ΠΎΠ±Π°Π²Π»Π΅Π½ΠΈΠΉ ΠΈ 2 ΡƒΠ΄Π°Π»Π΅Π½ΠΈΠΉ

ΠŸΡ€ΠΎΡΠΌΠΎΡ‚Ρ€Π΅Ρ‚ΡŒ Ρ„Π°ΠΉΠ»

@ -5,7 +5,7 @@ import sys
import pytest
import papermill as pm
import scrapbook as sb
from tests.notebooks_common import OUTPUT_NOTEBOOK
from tests.notebooks_common import OUTPUT_NOTEBOOK, KERNEL_NAME
sys.path.append("../../")
ABS_TOL = 0.2
@ -37,7 +37,7 @@ def baseline_results():
@pytest.mark.integration
def test_similarity_embeddings_baseline_runs(notebooks, baseline_results):
notebook_path = notebooks["similarity_embeddings_baseline"]
pm.execute_notebook(notebook_path, OUTPUT_NOTEBOOK)
pm.execute_notebook(notebook_path, OUTPUT_NOTEBOOK, kernel_name=KERNEL_NAME)
results = sb.read_notebook(OUTPUT_NOTEBOOK).scraps.data_dict["results"]
for key, value in baseline_results.items():
assert results[key] == pytest.approx(value, abs=ABS_TOL)
@ -50,6 +50,7 @@ def test_gensen_local(notebooks):
pm.execute_notebook(
notebook_path,
OUTPUT_NOTEBOOK,
kernel_name=KERNEL_NAME,
parameters=dict(
max_epoch=1,
config_filepath="../../scenarios/sentence_similarity/gensen_config.json",