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databricks / spark-deep-learning

Deep Learning Pipelines for Apache Spark
https://databricks.github.io/spark-deep-learning
Apache License 2.0
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TypeError: not enough arguments for format string #133

Open happsky opened 6 years ago

happsky commented 6 years ago

featurizer = DeepImageFeaturizer(inputCol="image", outputCol="features", modelName="ResNet50") lr = LogisticRegression(maxIter=20, regParam=0.05, elasticNetParam=0.3, labelCol="label") p = Pipeline(stages=[featurizer, lr]) p_model = p.fit(train_df) Traceback (most recent call last): File "", line 1, in File "/home/ho/image_classification_spark/spark-2.1.1-bin-hadoop2.7/python/pyspark/ml/base.py", line 64, in fit return self._fit(dataset) File "/home/ho/image_classification_spark/spark-2.1.1-bin-hadoop2.7/python/pyspark/ml/pipeline.py", line 106, in _fit dataset = stage.transform(dataset) File "/home/ho/image_classification_spark/spark-2.1.1-bin-hadoop2.7/python/pyspark/ml/base.py", line 105, in transform return self._transform(dataset) File "/tmp/spark-86622d41-f3cf-42ef-ac05-9fb03bf474d1/userFiles-39aeced1-93ed-43f8-be88-30299b05e4a4/databricks_spark-deep-learning-0.1.0-spark2.1-s_2.11.jar/sparkdl/transformers/named_image.py", line 159, in _transform File "/home/ho/image_classification_spark/spark-2.1.1-bin-hadoop2.7/python/pyspark/ml/base.py", line 105, in transform return self._transform(dataset) File "/tmp/spark-86622d41-f3cf-42ef-ac05-9fb03bf474d1/userFiles-39aeced1-93ed-43f8-be88-30299b05e4a4/databricks_spark-deep-learning-0.1.0-spark2.1-s_2.11.jar/sparkdl/transformers/named_image.py", line 212, in _transform File "/tmp/spark-86622d41-f3cf-42ef-ac05-9fb03bf474d1/userFiles-39aeced1-93ed-43f8-be88-30299b05e4a4/databricks_spark-deep-learning-0.1.0-spark2.1-s_2.11.jar/sparkdl/transformers/named_image.py", line 230, in _buildTFGraphForName TypeError: not enough arguments for format string

lukewgreen commented 6 years ago

I'm getting the same error when trying to load ResNet50