/* * Copyright 2018-2023 Amazon.com, Inc. or its affiliates. All Rights Reserved. * * Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with * the License. A copy of the License is located at * * http://aws.amazon.com/apache2.0 * * or in the "license" file accompanying this file. This file 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. */ package com.amazonaws.services.sagemaker.model; import java.io.Serializable; import javax.annotation.Generated; import com.amazonaws.protocol.StructuredPojo; import com.amazonaws.protocol.ProtocolMarshaller; /** *

* A channel is a named input source that training algorithms can consume. This channel is used for AutoML jobs V2 (jobs * created by calling CreateAutoMLJobV2). *

* * @see AWS API * Documentation */ @Generated("com.amazonaws:aws-java-sdk-code-generator") public class AutoMLJobChannel implements Serializable, Cloneable, StructuredPojo { /** *

* The type of channel. Defines whether the data are used for training or validation. The default value is * training. Channels for training and validation must share the same * ContentType *

* *

* The type of channel defaults to training for the time-series forecasting problem type. *

* */ private String channelType; /** *

* The content type of the data from the input source. The following are the allowed content types for different * problems: *

* */ private String contentType; /** *

* The allowed compression types depend on the input format and problem type. We allow the compression type * Gzip for S3Prefix inputs on tabular data only. For all other inputs, the compression * type should be None. If no compression type is provided, we default to None. *

*/ private String compressionType; /** *

* The data source for an AutoML channel (Required). *

*/ private AutoMLDataSource dataSource; /** *

* The type of channel. Defines whether the data are used for training or validation. The default value is * training. Channels for training and validation must share the same * ContentType *

* *

* The type of channel defaults to training for the time-series forecasting problem type. *

* * * @param channelType * The type of channel. Defines whether the data are used for training or validation. The default value is * training. Channels for training and validation must share the same * ContentType

*

* The type of channel defaults to training for the time-series forecasting problem type. *

* @see AutoMLChannelType */ public void setChannelType(String channelType) { this.channelType = channelType; } /** *

* The type of channel. Defines whether the data are used for training or validation. The default value is * training. Channels for training and validation must share the same * ContentType *

* *

* The type of channel defaults to training for the time-series forecasting problem type. *

* * * @return The type of channel. Defines whether the data are used for training or validation. The default value is * training. Channels for training and validation must share the same * ContentType

*

* The type of channel defaults to training for the time-series forecasting problem type. *

* @see AutoMLChannelType */ public String getChannelType() { return this.channelType; } /** *

* The type of channel. Defines whether the data are used for training or validation. The default value is * training. Channels for training and validation must share the same * ContentType *

* *

* The type of channel defaults to training for the time-series forecasting problem type. *

* * * @param channelType * The type of channel. Defines whether the data are used for training or validation. The default value is * training. Channels for training and validation must share the same * ContentType

*

* The type of channel defaults to training for the time-series forecasting problem type. *

* @return Returns a reference to this object so that method calls can be chained together. * @see AutoMLChannelType */ public AutoMLJobChannel withChannelType(String channelType) { setChannelType(channelType); return this; } /** *

* The type of channel. Defines whether the data are used for training or validation. The default value is * training. Channels for training and validation must share the same * ContentType *

* *

* The type of channel defaults to training for the time-series forecasting problem type. *

* * * @param channelType * The type of channel. Defines whether the data are used for training or validation. The default value is * training. Channels for training and validation must share the same * ContentType

*

* The type of channel defaults to training for the time-series forecasting problem type. *

* @return Returns a reference to this object so that method calls can be chained together. * @see AutoMLChannelType */ public AutoMLJobChannel withChannelType(AutoMLChannelType channelType) { this.channelType = channelType.toString(); return this; } /** *

* The content type of the data from the input source. The following are the allowed content types for different * problems: *

*
    *
  • *

    * For tabular problem types: text/csv;header=present or x-application/vnd.amazon+parquet. * The default value is text/csv;header=present. *

    *
    • *
  • *

    * For image classification: image/png, image/jpeg, or image/*. The default * value is image/*. *

    *
    • *
  • *

    * For text classification: text/csv;header=present or x-application/vnd.amazon+parquet. * The default value is text/csv;header=present. *

    *
    • *
  • *

    * For time-series forecasting: text/csv;header=present or * x-application/vnd.amazon+parquet. The default value is text/csv;header=present. *

    *
    • *
* * @param contentType * The content type of the data from the input source. The following are the allowed content types for * different problems:

*
    *
  • *

    * For tabular problem types: text/csv;header=present or * x-application/vnd.amazon+parquet. The default value is text/csv;header=present. *

    *
    • *
  • *

    * For image classification: image/png, image/jpeg, or image/*. The * default value is image/*. *

    *
    • *
  • *

    * For text classification: text/csv;header=present or * x-application/vnd.amazon+parquet. The default value is text/csv;header=present. *

    *
    • *
  • *

    * For time-series forecasting: text/csv;header=present or * x-application/vnd.amazon+parquet. The default value is text/csv;header=present. *

    *
    • */ public void setContentType(String contentType) { this.contentType = contentType; } /** *

    * The content type of the data from the input source. The following are the allowed content types for different * problems: *

    *
      *
    • *

      * For tabular problem types: text/csv;header=present or x-application/vnd.amazon+parquet. * The default value is text/csv;header=present. *

      *
      • *
    • *

      * For image classification: image/png, image/jpeg, or image/*. The default * value is image/*. *

      *
      • *
    • *

      * For text classification: text/csv;header=present or x-application/vnd.amazon+parquet. * The default value is text/csv;header=present. *

      *
      • *
    • *

      * For time-series forecasting: text/csv;header=present or * x-application/vnd.amazon+parquet. The default value is text/csv;header=present. *

      *
      • *
    * * @return The content type of the data from the input source. The following are the allowed content types for * different problems:

    *
      *
    • *

      * For tabular problem types: text/csv;header=present or * x-application/vnd.amazon+parquet. The default value is text/csv;header=present. *

      *
      • *
    • *

      * For image classification: image/png, image/jpeg, or image/*. The * default value is image/*. *

      *
      • *
    • *

      * For text classification: text/csv;header=present or * x-application/vnd.amazon+parquet. The default value is text/csv;header=present. *

      *
      • *
    • *

      * For time-series forecasting: text/csv;header=present or * x-application/vnd.amazon+parquet. The default value is text/csv;header=present. *

      *
      • */ public String getContentType() { return this.contentType; } /** *

      * The content type of the data from the input source. The following are the allowed content types for different * problems: *

      *
        *
      • *

        * For tabular problem types: text/csv;header=present or x-application/vnd.amazon+parquet. * The default value is text/csv;header=present. *

        *
        • *
      • *

        * For image classification: image/png, image/jpeg, or image/*. The default * value is image/*. *

        *
        • *
      • *

        * For text classification: text/csv;header=present or x-application/vnd.amazon+parquet. * The default value is text/csv;header=present. *

        *
        • *
      • *

        * For time-series forecasting: text/csv;header=present or * x-application/vnd.amazon+parquet. The default value is text/csv;header=present. *

        *
        • *
      * * @param contentType * The content type of the data from the input source. The following are the allowed content types for * different problems:

      *
        *
      • *

        * For tabular problem types: text/csv;header=present or * x-application/vnd.amazon+parquet. The default value is text/csv;header=present. *

        *
        • *
      • *

        * For image classification: image/png, image/jpeg, or image/*. The * default value is image/*. *

        *
        • *
      • *

        * For text classification: text/csv;header=present or * x-application/vnd.amazon+parquet. The default value is text/csv;header=present. *

        *
        • *
      • *

        * For time-series forecasting: text/csv;header=present or * x-application/vnd.amazon+parquet. The default value is text/csv;header=present. *

        *
        • * @return Returns a reference to this object so that method calls can be chained together. */ public AutoMLJobChannel withContentType(String contentType) { setContentType(contentType); return this; } /** *

        * The allowed compression types depend on the input format and problem type. We allow the compression type * Gzip for S3Prefix inputs on tabular data only. For all other inputs, the compression * type should be None. If no compression type is provided, we default to None. *

        * * @param compressionType * The allowed compression types depend on the input format and problem type. We allow the compression type * Gzip for S3Prefix inputs on tabular data only. For all other inputs, the * compression type should be None. If no compression type is provided, we default to * None. * @see CompressionType */ public void setCompressionType(String compressionType) { this.compressionType = compressionType; } /** *

        * The allowed compression types depend on the input format and problem type. We allow the compression type * Gzip for S3Prefix inputs on tabular data only. For all other inputs, the compression * type should be None. If no compression type is provided, we default to None. *

        * * @return The allowed compression types depend on the input format and problem type. We allow the compression type * Gzip for S3Prefix inputs on tabular data only. For all other inputs, the * compression type should be None. If no compression type is provided, we default to * None. * @see CompressionType */ public String getCompressionType() { return this.compressionType; } /** *

        * The allowed compression types depend on the input format and problem type. We allow the compression type * Gzip for S3Prefix inputs on tabular data only. For all other inputs, the compression * type should be None. If no compression type is provided, we default to None. *

        * * @param compressionType * The allowed compression types depend on the input format and problem type. We allow the compression type * Gzip for S3Prefix inputs on tabular data only. For all other inputs, the * compression type should be None. If no compression type is provided, we default to * None. * @return Returns a reference to this object so that method calls can be chained together. * @see CompressionType */ public AutoMLJobChannel withCompressionType(String compressionType) { setCompressionType(compressionType); return this; } /** *

        * The allowed compression types depend on the input format and problem type. We allow the compression type * Gzip for S3Prefix inputs on tabular data only. For all other inputs, the compression * type should be None. If no compression type is provided, we default to None. *

        * * @param compressionType * The allowed compression types depend on the input format and problem type. We allow the compression type * Gzip for S3Prefix inputs on tabular data only. For all other inputs, the * compression type should be None. If no compression type is provided, we default to * None. * @return Returns a reference to this object so that method calls can be chained together. * @see CompressionType */ public AutoMLJobChannel withCompressionType(CompressionType compressionType) { this.compressionType = compressionType.toString(); return this; } /** *

        * The data source for an AutoML channel (Required). *

        * * @param dataSource * The data source for an AutoML channel (Required). */ public void setDataSource(AutoMLDataSource dataSource) { this.dataSource = dataSource; } /** *

        * The data source for an AutoML channel (Required). *

        * * @return The data source for an AutoML channel (Required). */ public AutoMLDataSource getDataSource() { return this.dataSource; } /** *

        * The data source for an AutoML channel (Required). *

        * * @param dataSource * The data source for an AutoML channel (Required). * @return Returns a reference to this object so that method calls can be chained together. */ public AutoMLJobChannel withDataSource(AutoMLDataSource dataSource) { setDataSource(dataSource); return this; } /** * Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be * redacted from this string using a placeholder value. * * @return A string representation of this object. * * @see java.lang.Object#toString() */ @Override public String toString() { StringBuilder sb = new StringBuilder(); sb.append("{"); if (getChannelType() != null) sb.append("ChannelType: ").append(getChannelType()).append(","); if (getContentType() != null) sb.append("ContentType: ").append(getContentType()).append(","); if (getCompressionType() != null) sb.append("CompressionType: ").append(getCompressionType()).append(","); if (getDataSource() != null) sb.append("DataSource: ").append(getDataSource()); sb.append("}"); return sb.toString(); } @Override public boolean equals(Object obj) { if (this == obj) return true; if (obj == null) return false; if (obj instanceof AutoMLJobChannel == false) return false; AutoMLJobChannel other = (AutoMLJobChannel) obj; if (other.getChannelType() == null ^ this.getChannelType() == null) return false; if (other.getChannelType() != null && other.getChannelType().equals(this.getChannelType()) == false) return false; if (other.getContentType() == null ^ this.getContentType() == null) return false; if (other.getContentType() != null && other.getContentType().equals(this.getContentType()) == false) return false; if (other.getCompressionType() == null ^ this.getCompressionType() == null) return false; if (other.getCompressionType() != null && other.getCompressionType().equals(this.getCompressionType()) == false) return false; if (other.getDataSource() == null ^ this.getDataSource() == null) return false; if (other.getDataSource() != null && other.getDataSource().equals(this.getDataSource()) == false) return false; return true; } @Override public int hashCode() { final int prime = 31; int hashCode = 1; hashCode = prime * hashCode + ((getChannelType() == null) ? 0 : getChannelType().hashCode()); hashCode = prime * hashCode + ((getContentType() == null) ? 0 : getContentType().hashCode()); hashCode = prime * hashCode + ((getCompressionType() == null) ? 0 : getCompressionType().hashCode()); hashCode = prime * hashCode + ((getDataSource() == null) ? 0 : getDataSource().hashCode()); return hashCode; } @Override public AutoMLJobChannel clone() { try { return (AutoMLJobChannel) super.clone(); } catch (CloneNotSupportedException e) { throw new IllegalStateException("Got a CloneNotSupportedException from Object.clone() " + "even though we're Cloneable!", e); } } @com.amazonaws.annotation.SdkInternalApi @Override public void marshall(ProtocolMarshaller protocolMarshaller) { com.amazonaws.services.sagemaker.model.transform.AutoMLJobChannelMarshaller.getInstance().marshall(this, protocolMarshaller); } }