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Remove repo path (#2050)
* Remove repo path * Remove repo path * Reformat too long lines * Reformat too long lines * Remove an empty line
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docs/blogs/elasticdl-antfin-introduction.md

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@@ -207,8 +207,8 @@ model = custom_model()
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outputs = model.call(tf.constant([[0.4, 0.7, 1.5, 0.3], [1.4, 0.2, 0.5, 1.3]]))
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```
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训练一个模型不只需要上述模型定义,还需要指定数据 (dataset)、优化目标(cost)、
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优化算法(optimizer)。ElasticDL 和 TensorFlow 其他的 high-level API,
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训练一个模型不只需要上述模型定义,还需要指定数据 (dataset)、优化目标(cost)、
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和优化算法(optimizer)。ElasticDL 和 TensorFlow 其他的 high-level API,
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例如 Keras 和 TensorFlow Estimator 一样,提供了相关配置的定义方式,比如
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```python
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elasticdl train \
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--image_base=elasticdl:latest \
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--model_zoo=model_zoo \
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--docker_image_repository=reg.docker.alibaba-inc.com/qinlong-wql/ \
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--docker_image_repository={REPO} \
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--model_def=dac_ctr.elasticdl_train.custom_model \
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--minibatch_size=512 \
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--num_epochs=20 \
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--training_data=/testdata/elasticdl/dac_records/train \
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--validation_data=/testdata/elasticdl/dac_records/val \
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--evaluation_steps=10000 \
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--job_name=test-edl-changfan \
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--job_name=test-edl \
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```
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### Keras 特征预处理 layer

docs/designs/high_level_api.md

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@@ -186,7 +186,9 @@ building process should add a *model zoo* into the Docker image. The function
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1. A URL pointing to a Git repo
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```python
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elasticdl.train(model_zoo="https://git.company.com/sql-machine-learning/models", ...)
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elasticdl.train(
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model_zoo="https://git.company.com/sql-machine-learning/models", ...
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)
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```
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A model zoo is a plain Python source directory that's added to `/model_zoo` in

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