if __name__ == "__main__":
odps_project = os.getenv("SQLFLOW_TEST_DB_MAXCOMPUTE_PROJECT")
odps_conf = OdpsConf(
accessid=os.getenv("SQLFLOW_TEST_DB_MAXCOMPUTE_AK"),
accesskey=os.getenv("SQLFLOW_TEST_DB_MAXCOMPUTE_SK"),
# endpoint should looks like: "https://service.cn.maxcompute.aliyun.com/api"
endpoint=os.getenv("SQLFLOW_TEST_DB_MAXCOMPUTE_ENDPOINT"),
project=odps_project)
features = [
SparseColumn(name="deep_id", shape=[15033], dtype="int"),
SparseColumn(name="user_space_stat", shape=[310], dtype="int"),
SparseColumn(name="user_behavior_stat", shape=[511], dtype="int"),
SparseColumn(name="space_stat", shape=[418], dtype="int")
]
labels = DenseColumn(name="l", shape=[1], dtype="int", separator=",")
try:
os.mkdir("scratch")
except FileExistsError:
pass
train(SQLFlowEstimatorBuilder(),
odps_conf=odps_conf,
project=odps_project,
train_table="gomaxcompute_driver_w7u.sparse_column_test",
eval_table="gomaxcompute_driver_w7u.sparse_column_test",
features=features,
labels=labels,
feature_map_table="",
feature_map_partition="",
epochs=1,
batch_size=2,
odps_project = os.getenv("SQLFLOW_TEST_DB_MAXCOMPUTE_PROJECT")
odps_conf = OdpsConf(
accessid=os.getenv("SQLFLOW_TEST_DB_MAXCOMPUTE_AK"),
accesskey=os.getenv("SQLFLOW_TEST_DB_MAXCOMPUTE_SK"),
# endpoint should looks like:
# "https://service.cn.maxcompute.aliyun.com/api"
endpoint=os.getenv("SQLFLOW_TEST_DB_MAXCOMPUTE_ENDPOINT"),
project=odps_project)
features = []
for col_name in [
"sepal_length", "sepal_width", "petal_length", "petal_width"
]:
# NOTE: add sparse columns like:
# SparseColumn(name="deep_id", shape=[15033], dtype="int")
features.append(DenseColumn(name=col_name, shape=[1], dtype="float32"))
labels = DenseColumn(name="class", shape=[1], dtype="int", separator=",")
try:
os.mkdir("scratch")
except FileExistsError:
pass
train(SQLFlowEstimatorBuilder(),
odps_conf=odps_conf,
project=odps_project,
train_table="%s.sqlflow_test_iris_train" % odps_project,
eval_table="%s.sqlflow_test_iris_test" % odps_project,
features=features,
labels=labels,
feature_map_table="",