github-actions[bot] opened a new issue, #630: URL: https://github.com/apache/incubator-wayang/issues/630
fix this test by giving it proper test resources & fixing some type issues with lists. https://github.com/apache/incubator-wayang/blob/1e0f9e8166225176fe3022de5fbcce3dbcba96b9/python/src/pywy/tests/test_dl.py#L31 ```python # # Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with # the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import pytest from typing import List from pywy.dataquanta import WayangContext from pywy.platforms.java import JavaPlugin from pywy.platforms.spark import SparkPlugin from pywy.platforms.tensorflow import TensorflowPlugin from pywy.basic.model.ops import Mean, Cast, Eq, ArgMax, Input, Op, CrossEntropyLoss, Linear, Sigmoid from pywy.basic.model.optimizer import GradientDescent from pywy.basic.model.option import Option from pywy.basic.model.models import DLModel # TODO: fix this test by giving it proper test resources & fixing some type issues with lists. @pytest.mark.skip(reason="no way of currently testing this, since we are missing implementations for proper test resources & types in types.py") def test_dl_tensorflow(): l1 = Linear(4, 64, True) s1 = Sigmoid() l2 = Linear(64, 3, True) s1.with_ops(l1.with_ops(Input(Input.Type.FEATURES))) l2.with_ops(s1) model = DLModel(l2) criterion = CrossEntropyLoss(3) criterion.with_ops( Input(Input.Type.PREDICTED), Input(Input.Type.LABEL, Op.DType.INT32) ) acc = Mean(0) acc.with_ops( Cast(Op.DType.FLOAT32).with_ops( Eq().with_ops( ArgMax(1).with_ops( Input(Input.Type.PREDICTED) ), Input(Input.Type.LABEL, Op.DType.INT32) ) ) ) optimizer = GradientDescent(0.02) option = Option(criterion, optimizer, 6, 100) floats: List[List[int]] = [[5.1, 3.5, 1.4, 0.2]] ints: List[List[int]] = [[0, 0, 1, 1, 2, 2]] ctx = WayangContext() \ .register({JavaPlugin, SparkPlugin, TensorflowPlugin}) trainXSource = ctx.textfile("file:///var/www/html/README.md").map(lambda x: floats, str, List[List[float]]) trainYSource = ctx.textfile("file:///var/www/html/README.md").map(lambda x: floats, str, List[List[float]]) testXSource = ctx.textfile("file:///var/www/html/README.md").map(lambda x: floats, str, List[List[float]]) data_quanta = trainXSource.dlTraining(model, option, trainYSource, List[List[float]], List[List[float]]) \ .predict(testXSource, List[List[float]], List[List[float]]) \ .map(lambda x: "Test", List[List[float]], str) \ .store_textfile("file:///var/www/html/data/wordcount-out-python.txt", List[float]) assert data_quanta is not None ``` ee3e2202c7d8fe4e5bb93b41d4dbe58cb3315879 -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
