# frozen_string_literal: true

# WARNING ABOUT GENERATED CODE
#
# This file is generated. See the contributing guide for more information:
# https://github.com/aws/aws-sdk-ruby/blob/version-3/CONTRIBUTING.md
#
# WARNING ABOUT GENERATED CODE

require 'seahorse/client/plugins/content_length'
require 'aws-sdk-core/plugins/credentials_configuration'
require 'aws-sdk-core/plugins/logging'
require 'aws-sdk-core/plugins/param_converter'
require 'aws-sdk-core/plugins/param_validator'
require 'aws-sdk-core/plugins/user_agent'
require 'aws-sdk-core/plugins/helpful_socket_errors'
require 'aws-sdk-core/plugins/retry_errors'
require 'aws-sdk-core/plugins/global_configuration'
require 'aws-sdk-core/plugins/regional_endpoint'
require 'aws-sdk-core/plugins/endpoint_discovery'
require 'aws-sdk-core/plugins/endpoint_pattern'
require 'aws-sdk-core/plugins/response_paging'
require 'aws-sdk-core/plugins/stub_responses'
require 'aws-sdk-core/plugins/idempotency_token'
require 'aws-sdk-core/plugins/invocation_id'
require 'aws-sdk-core/plugins/jsonvalue_converter'
require 'aws-sdk-core/plugins/client_metrics_plugin'
require 'aws-sdk-core/plugins/client_metrics_send_plugin'
require 'aws-sdk-core/plugins/transfer_encoding'
require 'aws-sdk-core/plugins/http_checksum'
require 'aws-sdk-core/plugins/checksum_algorithm'
require 'aws-sdk-core/plugins/request_compression'
require 'aws-sdk-core/plugins/defaults_mode'
require 'aws-sdk-core/plugins/recursion_detection'
require 'aws-sdk-core/plugins/telemetry'
require 'aws-sdk-core/plugins/sign'
require 'aws-sdk-core/plugins/protocols/json_rpc'

module Aws::LookoutEquipment
  # An API client for LookoutEquipment.  To construct a client, you need to configure a `:region` and `:credentials`.
  #
  #     client = Aws::LookoutEquipment::Client.new(
  #       region: region_name,
  #       credentials: credentials,
  #       # ...
  #     )
  #
  # For details on configuring region and credentials see
  # the [developer guide](/sdk-for-ruby/v3/developer-guide/setup-config.html).
  #
  # See {#initialize} for a full list of supported configuration options.
  class Client < Seahorse::Client::Base

    include Aws::ClientStubs

    @identifier = :lookoutequipment

    set_api(ClientApi::API)

    add_plugin(Seahorse::Client::Plugins::ContentLength)
    add_plugin(Aws::Plugins::CredentialsConfiguration)
    add_plugin(Aws::Plugins::Logging)
    add_plugin(Aws::Plugins::ParamConverter)
    add_plugin(Aws::Plugins::ParamValidator)
    add_plugin(Aws::Plugins::UserAgent)
    add_plugin(Aws::Plugins::HelpfulSocketErrors)
    add_plugin(Aws::Plugins::RetryErrors)
    add_plugin(Aws::Plugins::GlobalConfiguration)
    add_plugin(Aws::Plugins::RegionalEndpoint)
    add_plugin(Aws::Plugins::EndpointDiscovery)
    add_plugin(Aws::Plugins::EndpointPattern)
    add_plugin(Aws::Plugins::ResponsePaging)
    add_plugin(Aws::Plugins::StubResponses)
    add_plugin(Aws::Plugins::IdempotencyToken)
    add_plugin(Aws::Plugins::InvocationId)
    add_plugin(Aws::Plugins::JsonvalueConverter)
    add_plugin(Aws::Plugins::ClientMetricsPlugin)
    add_plugin(Aws::Plugins::ClientMetricsSendPlugin)
    add_plugin(Aws::Plugins::TransferEncoding)
    add_plugin(Aws::Plugins::HttpChecksum)
    add_plugin(Aws::Plugins::ChecksumAlgorithm)
    add_plugin(Aws::Plugins::RequestCompression)
    add_plugin(Aws::Plugins::DefaultsMode)
    add_plugin(Aws::Plugins::RecursionDetection)
    add_plugin(Aws::Plugins::Telemetry)
    add_plugin(Aws::Plugins::Sign)
    add_plugin(Aws::Plugins::Protocols::JsonRpc)
    add_plugin(Aws::LookoutEquipment::Plugins::Endpoints)

    # @overload initialize(options)
    #   @param [Hash] options
    #
    #   @option options [Array<Seahorse::Client::Plugin>] :plugins ([]])
    #     A list of plugins to apply to the client. Each plugin is either a
    #     class name or an instance of a plugin class.
    #
    #   @option options [required, Aws::CredentialProvider] :credentials
    #     Your AWS credentials used for authentication. This can be any class that includes and implements
    #     `Aws::CredentialProvider`, or instance of any one of the following classes:
    #
    #     * `Aws::Credentials` - Used for configuring static, non-refreshing
    #       credentials.
    #
    #     * `Aws::SharedCredentials` - Used for loading static credentials from a
    #       shared file, such as `~/.aws/config`.
    #
    #     * `Aws::AssumeRoleCredentials` - Used when you need to assume a role.
    #
    #     * `Aws::AssumeRoleWebIdentityCredentials` - Used when you need to
    #       assume a role after providing credentials via the web.
    #
    #     * `Aws::SSOCredentials` - Used for loading credentials from AWS SSO using an
    #       access token generated from `aws login`.
    #
    #     * `Aws::ProcessCredentials` - Used for loading credentials from a
    #       process that outputs to stdout.
    #
    #     * `Aws::InstanceProfileCredentials` - Used for loading credentials
    #       from an EC2 IMDS on an EC2 instance.
    #
    #     * `Aws::ECSCredentials` - Used for loading credentials from
    #       instances running in ECS.
    #
    #     * `Aws::CognitoIdentityCredentials` - Used for loading credentials
    #       from the Cognito Identity service.
    #
    #     When `:credentials` are not configured directly, the following locations will be searched for credentials:
    #
    #     * `Aws.config[:credentials]`
    #
    #     * The `:access_key_id`, `:secret_access_key`, `:session_token`, and
    #       `:account_id` options.
    #
    #     * `ENV['AWS_ACCESS_KEY_ID']`, `ENV['AWS_SECRET_ACCESS_KEY']`,
    #       `ENV['AWS_SESSION_TOKEN']`, and `ENV['AWS_ACCOUNT_ID']`.
    #
    #     * `~/.aws/credentials`
    #
    #     * `~/.aws/config`
    #
    #     * EC2/ECS IMDS instance profile - When used by default, the timeouts are very aggressive.
    #       Construct and pass an instance of `Aws::InstanceProfileCredentials` or `Aws::ECSCredentials` to
    #       enable retries and extended timeouts. Instance profile credential fetching can be disabled by
    #       setting `ENV['AWS_EC2_METADATA_DISABLED']` to `true`.
    #
    #   @option options [required, String] :region
    #     The AWS region to connect to.  The configured `:region` is
    #     used to determine the service `:endpoint`. When not passed,
    #     a default `:region` is searched for in the following locations:
    #
    #     * `Aws.config[:region]`
    #     * `ENV['AWS_REGION']`
    #     * `ENV['AMAZON_REGION']`
    #     * `ENV['AWS_DEFAULT_REGION']`
    #     * `~/.aws/credentials`
    #     * `~/.aws/config`
    #
    #   @option options [String] :access_key_id
    #
    #   @option options [String] :account_id
    #
    #   @option options [Boolean] :active_endpoint_cache (false)
    #     When set to `true`, a thread polling for endpoints will be running in
    #     the background every 60 secs (default). Defaults to `false`.
    #
    #   @option options [Boolean] :adaptive_retry_wait_to_fill (true)
    #     Used only in `adaptive` retry mode.  When true, the request will sleep
    #     until there is sufficent client side capacity to retry the request.
    #     When false, the request will raise a `RetryCapacityNotAvailableError` and will
    #     not retry instead of sleeping.
    #
    #   @option options [Array<String>] :auth_scheme_preference
    #     A list of preferred authentication schemes to use when making a request. Supported values are:
    #     `sigv4`, `sigv4a`, `httpBearerAuth`, and `noAuth`. When set using `ENV['AWS_AUTH_SCHEME_PREFERENCE']` or in
    #     shared config as `auth_scheme_preference`, the value should be a comma-separated list.
    #
    #   @option options [Boolean] :client_side_monitoring (false)
    #     When `true`, client-side metrics will be collected for all API requests from
    #     this client.
    #
    #   @option options [String] :client_side_monitoring_client_id ("")
    #     Allows you to provide an identifier for this client which will be attached to
    #     all generated client side metrics. Defaults to an empty string.
    #
    #   @option options [String] :client_side_monitoring_host ("127.0.0.1")
    #     Allows you to specify the DNS hostname or IPv4 or IPv6 address that the client
    #     side monitoring agent is running on, where client metrics will be published via UDP.
    #
    #   @option options [Integer] :client_side_monitoring_port (31000)
    #     Required for publishing client metrics. The port that the client side monitoring
    #     agent is running on, where client metrics will be published via UDP.
    #
    #   @option options [Aws::ClientSideMonitoring::Publisher] :client_side_monitoring_publisher (Aws::ClientSideMonitoring::Publisher)
    #     Allows you to provide a custom client-side monitoring publisher class. By default,
    #     will use the Client Side Monitoring Agent Publisher.
    #
    #   @option options [Boolean] :convert_params (true)
    #     When `true`, an attempt is made to coerce request parameters into
    #     the required types.
    #
    #   @option options [Boolean] :correct_clock_skew (true)
    #     Used only in `standard` and adaptive retry modes. Specifies whether to apply
    #     a clock skew correction and retry requests with skewed client clocks.
    #
    #   @option options [String] :defaults_mode ("legacy")
    #     See {Aws::DefaultsModeConfiguration} for a list of the
    #     accepted modes and the configuration defaults that are included.
    #
    #   @option options [Boolean] :disable_host_prefix_injection (false)
    #     When `true`, the SDK will not prepend the modeled host prefix to the endpoint.
    #
    #   @option options [Boolean] :disable_request_compression (false)
    #     When set to 'true' the request body will not be compressed
    #     for supported operations.
    #
    #   @option options [String, URI::HTTPS, URI::HTTP] :endpoint
    #     Normally you should not configure the `:endpoint` option
    #     directly. This is normally constructed from the `:region`
    #     option. Configuring `:endpoint` is normally reserved for
    #     connecting to test or custom endpoints. The endpoint should
    #     be a URI formatted like:
    #
    #         'http://example.com'
    #         'https://example.com'
    #         'http://example.com:123'
    #
    #   @option options [Integer] :endpoint_cache_max_entries (1000)
    #     Used for the maximum size limit of the LRU cache storing endpoints data
    #     for endpoint discovery enabled operations. Defaults to 1000.
    #
    #   @option options [Integer] :endpoint_cache_max_threads (10)
    #     Used for the maximum threads in use for polling endpoints to be cached, defaults to 10.
    #
    #   @option options [Integer] :endpoint_cache_poll_interval (60)
    #     When :endpoint_discovery and :active_endpoint_cache is enabled,
    #     Use this option to config the time interval in seconds for making
    #     requests fetching endpoints information. Defaults to 60 sec.
    #
    #   @option options [Boolean] :endpoint_discovery (false)
    #     When set to `true`, endpoint discovery will be enabled for operations when available.
    #
    #   @option options [Boolean] :ignore_configured_endpoint_urls
    #     Setting to true disables use of endpoint URLs provided via environment
    #     variables and the shared configuration file.
    #
    #   @option options [Aws::Log::Formatter] :log_formatter (Aws::Log::Formatter.default)
    #     The log formatter.
    #
    #   @option options [Symbol] :log_level (:info)
    #     The log level to send messages to the `:logger` at.
    #
    #   @option options [Logger] :logger
    #     The Logger instance to send log messages to.  If this option
    #     is not set, logging will be disabled.
    #
    #   @option options [Integer] :max_attempts (3)
    #     An integer representing the maximum number attempts that will be made for
    #     a single request, including the initial attempt.  For example,
    #     setting this value to 5 will result in a request being retried up to
    #     4 times. Used in `standard` and `adaptive` retry modes.
    #
    #   @option options [String] :profile ("default")
    #     Used when loading credentials from the shared credentials file at `HOME/.aws/credentials`.
    #     When not specified, 'default' is used.
    #
    #   @option options [String] :request_checksum_calculation ("when_supported")
    #     Determines when a checksum will be calculated for request payloads. Values are:
    #
    #     * `when_supported` - (default) When set, a checksum will be
    #       calculated for all request payloads of operations modeled with the
    #       `httpChecksum` trait where `requestChecksumRequired` is `true` and/or a
    #       `requestAlgorithmMember` is modeled.
    #     * `when_required` - When set, a checksum will only be calculated for
    #       request payloads of operations modeled with the  `httpChecksum` trait where
    #       `requestChecksumRequired` is `true` or where a `requestAlgorithmMember`
    #       is modeled and supplied.
    #
    #   @option options [Integer] :request_min_compression_size_bytes (10240)
    #     The minimum size in bytes that triggers compression for request
    #     bodies. The value must be non-negative integer value between 0
    #     and 10485780 bytes inclusive.
    #
    #   @option options [String] :response_checksum_validation ("when_supported")
    #     Determines when checksum validation will be performed on response payloads. Values are:
    #
    #     * `when_supported` - (default) When set, checksum validation is performed on all
    #       response payloads of operations modeled with the `httpChecksum` trait where
    #       `responseAlgorithms` is modeled, except when no modeled checksum algorithms
    #       are supported.
    #     * `when_required` - When set, checksum validation is not performed on
    #       response payloads of operations unless the checksum algorithm is supported and
    #       the `requestValidationModeMember` member is set to `ENABLED`.
    #
    #   @option options [Proc] :retry_backoff
    #     A proc or lambda used for backoff. Defaults to 2**retries * retry_base_delay.
    #     This option is only used in the `legacy` retry mode.
    #
    #   @option options [Float] :retry_base_delay (0.3)
    #     The base delay in seconds used by the default backoff function. This option
    #     is only used in the `legacy` retry mode.
    #
    #   @option options [Symbol] :retry_jitter (:none)
    #     A delay randomiser function used by the default backoff function.
    #     Some predefined functions can be referenced by name - :none, :equal, :full,
    #     otherwise a Proc that takes and returns a number. This option is only used
    #     in the `legacy` retry mode.
    #
    #     @see https://www.awsarchitectureblog.com/2015/03/backoff.html
    #
    #   @option options [Integer] :retry_limit (3)
    #     The maximum number of times to retry failed requests.  Only
    #     ~ 500 level server errors and certain ~ 400 level client errors
    #     are retried.  Generally, these are throttling errors, data
    #     checksum errors, networking errors, timeout errors, auth errors,
    #     endpoint discovery, and errors from expired credentials.
    #     This option is only used in the `legacy` retry mode.
    #
    #   @option options [Integer] :retry_max_delay (0)
    #     The maximum number of seconds to delay between retries (0 for no limit)
    #     used by the default backoff function. This option is only used in the
    #     `legacy` retry mode.
    #
    #   @option options [String] :retry_mode ("legacy")
    #     Specifies which retry algorithm to use. Values are:
    #
    #     * `legacy` - The pre-existing retry behavior.  This is default value if
    #       no retry mode is provided.
    #
    #     * `standard` - A standardized set of retry rules across the AWS SDKs.
    #       This includes support for retry quotas, which limit the number of
    #       unsuccessful retries a client can make.
    #
    #     * `adaptive` - An experimental retry mode that includes all the
    #       functionality of `standard` mode along with automatic client side
    #       throttling.  This is a provisional mode that may change behavior
    #       in the future.
    #
    #   @option options [String] :sdk_ua_app_id
    #     A unique and opaque application ID that is appended to the
    #     User-Agent header as app/sdk_ua_app_id. It should have a
    #     maximum length of 50. This variable is sourced from environment
    #     variable AWS_SDK_UA_APP_ID or the shared config profile attribute sdk_ua_app_id.
    #
    #   @option options [String] :secret_access_key
    #
    #   @option options [String] :session_token
    #
    #   @option options [Array] :sigv4a_signing_region_set
    #     A list of regions that should be signed with SigV4a signing. When
    #     not passed, a default `:sigv4a_signing_region_set` is searched for
    #     in the following locations:
    #
    #     * `Aws.config[:sigv4a_signing_region_set]`
    #     * `ENV['AWS_SIGV4A_SIGNING_REGION_SET']`
    #     * `~/.aws/config`
    #
    #   @option options [Boolean] :simple_json (false)
    #     Disables request parameter conversion, validation, and formatting.
    #     Also disables response data type conversions. The request parameters
    #     hash must be formatted exactly as the API expects.This option is useful
    #     when you want to ensure the highest level of performance by avoiding
    #     overhead of walking request parameters and response data structures.
    #
    #   @option options [Boolean] :stub_responses (false)
    #     Causes the client to return stubbed responses. By default
    #     fake responses are generated and returned. You can specify
    #     the response data to return or errors to raise by calling
    #     {ClientStubs#stub_responses}. See {ClientStubs} for more information.
    #
    #     ** Please note ** When response stubbing is enabled, no HTTP
    #     requests are made, and retries are disabled.
    #
    #   @option options [Aws::Telemetry::TelemetryProviderBase] :telemetry_provider (Aws::Telemetry::NoOpTelemetryProvider)
    #     Allows you to provide a telemetry provider, which is used to
    #     emit telemetry data. By default, uses `NoOpTelemetryProvider` which
    #     will not record or emit any telemetry data. The SDK supports the
    #     following telemetry providers:
    #
    #     * OpenTelemetry (OTel) - To use the OTel provider, install and require the
    #     `opentelemetry-sdk` gem and then, pass in an instance of a
    #     `Aws::Telemetry::OTelProvider` for telemetry provider.
    #
    #   @option options [Aws::TokenProvider] :token_provider
    #     Your Bearer token used for authentication. This can be any class that includes and implements
    #     `Aws::TokenProvider`, or instance of any one of the following classes:
    #
    #     * `Aws::StaticTokenProvider` - Used for configuring static, non-refreshing
    #       tokens.
    #
    #     * `Aws::SSOTokenProvider` - Used for loading tokens from AWS SSO using an
    #       access token generated from `aws login`.
    #
    #     When `:token_provider` is not configured directly, the `Aws::TokenProviderChain`
    #     will be used to search for tokens configured for your profile in shared configuration files.
    #
    #   @option options [Boolean] :use_dualstack_endpoint
    #     When set to `true`, dualstack enabled endpoints (with `.aws` TLD)
    #     will be used if available.
    #
    #   @option options [Boolean] :use_fips_endpoint
    #     When set to `true`, fips compatible endpoints will be used if available.
    #     When a `fips` region is used, the region is normalized and this config
    #     is set to `true`.
    #
    #   @option options [Boolean] :validate_params (true)
    #     When `true`, request parameters are validated before
    #     sending the request.
    #
    #   @option options [Aws::LookoutEquipment::EndpointProvider] :endpoint_provider
    #     The endpoint provider used to resolve endpoints. Any object that responds to
    #     `#resolve_endpoint(parameters)` where `parameters` is a Struct similar to
    #     `Aws::LookoutEquipment::EndpointParameters`.
    #
    #   @option options [Float] :http_continue_timeout (1)
    #     The number of seconds to wait for a 100-continue response before sending the
    #     request body.  This option has no effect unless the request has "Expect"
    #     header set to "100-continue".  Defaults to `nil` which  disables this
    #     behaviour.  This value can safely be set per request on the session.
    #
    #   @option options [Float] :http_idle_timeout (5)
    #     The number of seconds a connection is allowed to sit idle before it
    #     is considered stale.  Stale connections are closed and removed from the
    #     pool before making a request.
    #
    #   @option options [Float] :http_open_timeout (15)
    #     The default number of seconds to wait for response data.
    #     This value can safely be set per-request on the session.
    #
    #   @option options [URI::HTTP,String] :http_proxy
    #     A proxy to send requests through.  Formatted like 'http://proxy.com:123'.
    #
    #   @option options [Float] :http_read_timeout (60)
    #     The default number of seconds to wait for response data.
    #     This value can safely be set per-request on the session.
    #
    #   @option options [Boolean] :http_wire_trace (false)
    #     When `true`,  HTTP debug output will be sent to the `:logger`.
    #
    #   @option options [Proc] :on_chunk_received
    #     When a Proc object is provided, it will be used as callback when each chunk
    #     of the response body is received. It provides three arguments: the chunk,
    #     the number of bytes received, and the total number of
    #     bytes in the response (or nil if the server did not send a `content-length`).
    #
    #   @option options [Proc] :on_chunk_sent
    #     When a Proc object is provided, it will be used as callback when each chunk
    #     of the request body is sent. It provides three arguments: the chunk,
    #     the number of bytes read from the body, and the total number of
    #     bytes in the body.
    #
    #   @option options [Boolean] :raise_response_errors (true)
    #     When `true`, response errors are raised.
    #
    #   @option options [String] :ssl_ca_bundle
    #     Full path to the SSL certificate authority bundle file that should be used when
    #     verifying peer certificates.  If you do not pass `:ssl_ca_bundle` or
    #     `:ssl_ca_directory` the the system default will be used if available.
    #
    #   @option options [String] :ssl_ca_directory
    #     Full path of the directory that contains the unbundled SSL certificate
    #     authority files for verifying peer certificates.  If you do
    #     not pass `:ssl_ca_bundle` or `:ssl_ca_directory` the the system
    #     default will be used if available.
    #
    #   @option options [String] :ssl_ca_store
    #     Sets the X509::Store to verify peer certificate.
    #
    #   @option options [OpenSSL::X509::Certificate] :ssl_cert
    #     Sets a client certificate when creating http connections.
    #
    #   @option options [OpenSSL::PKey] :ssl_key
    #     Sets a client key when creating http connections.
    #
    #   @option options [Float] :ssl_timeout
    #     Sets the SSL timeout in seconds
    #
    #   @option options [Boolean] :ssl_verify_peer (true)
    #     When `true`, SSL peer certificates are verified when establishing a connection.
    #
    def initialize(*args)
      super
    end

    # @!group API Operations

    # Creates a container for a collection of data being ingested for
    # analysis. The dataset contains the metadata describing where the data
    # is and what the data actually looks like. For example, it contains the
    # location of the data source, the data schema, and other information. A
    # dataset also contains any tags associated with the ingested data.
    #
    # @option params [required, String] :dataset_name
    #   The name of the dataset being created.
    #
    # @option params [Types::DatasetSchema] :dataset_schema
    #   A JSON description of the data that is in each time series dataset,
    #   including names, column names, and data types.
    #
    # @option params [String] :server_side_kms_key_id
    #   Provides the identifier of the KMS key used to encrypt dataset data by
    #   Amazon Lookout for Equipment.
    #
    # @option params [required, String] :client_token
    #   A unique identifier for the request. If you do not set the client
    #   request token, Amazon Lookout for Equipment generates one.
    #
    #   **A suitable default value is auto-generated.** You should normally
    #   not need to pass this option.**
    #
    # @option params [Array<Types::Tag>] :tags
    #   Any tags associated with the ingested data described in the dataset.
    #
    # @return [Types::CreateDatasetResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::CreateDatasetResponse#dataset_name #dataset_name} => String
    #   * {Types::CreateDatasetResponse#dataset_arn #dataset_arn} => String
    #   * {Types::CreateDatasetResponse#status #status} => String
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.create_dataset({
    #     dataset_name: "DatasetName", # required
    #     dataset_schema: {
    #       inline_data_schema: "InlineDataSchema",
    #     },
    #     server_side_kms_key_id: "NameOrArn",
    #     client_token: "IdempotenceToken", # required
    #     tags: [
    #       {
    #         key: "TagKey", # required
    #         value: "TagValue", # required
    #       },
    #     ],
    #   })
    #
    # @example Response structure
    #
    #   resp.dataset_name #=> String
    #   resp.dataset_arn #=> String
    #   resp.status #=> String, one of "CREATED", "INGESTION_IN_PROGRESS", "ACTIVE", "IMPORT_IN_PROGRESS"
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/CreateDataset AWS API Documentation
    #
    # @overload create_dataset(params = {})
    # @param [Hash] params ({})
    def create_dataset(params = {}, options = {})
      req = build_request(:create_dataset, params)
      req.send_request(options)
    end

    # Creates a scheduled inference. Scheduling an inference is setting up a
    # continuous real-time inference plan to analyze new measurement data.
    # When setting up the schedule, you provide an S3 bucket location for
    # the input data, assign it a delimiter between separate entries in the
    # data, set an offset delay if desired, and set the frequency of
    # inferencing. You must also provide an S3 bucket location for the
    # output data.
    #
    # @option params [required, String] :model_name
    #   The name of the previously trained machine learning model being used
    #   to create the inference scheduler.
    #
    # @option params [required, String] :inference_scheduler_name
    #   The name of the inference scheduler being created.
    #
    # @option params [Integer] :data_delay_offset_in_minutes
    #   The interval (in minutes) of planned delay at the start of each
    #   inference segment. For example, if inference is set to run every ten
    #   minutes, the delay is set to five minutes and the time is 09:08. The
    #   inference scheduler will wake up at the configured interval (which,
    #   without a delay configured, would be 09:10) plus the additional five
    #   minute delay time (so 09:15) to check your Amazon S3 bucket. The delay
    #   provides a buffer for you to upload data at the same frequency, so
    #   that you don't have to stop and restart the scheduler when uploading
    #   new data.
    #
    #   For more information, see [Understanding the inference process][1].
    #
    #
    #
    #   [1]: https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-inference-process.html
    #
    # @option params [required, String] :data_upload_frequency
    #   How often data is uploaded to the source Amazon S3 bucket for the
    #   input data. The value chosen is the length of time between data
    #   uploads. For instance, if you select 5 minutes, Amazon Lookout for
    #   Equipment will upload the real-time data to the source bucket once
    #   every 5 minutes. This frequency also determines how often Amazon
    #   Lookout for Equipment runs inference on your data.
    #
    #   For more information, see [Understanding the inference process][1].
    #
    #
    #
    #   [1]: https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-inference-process.html
    #
    # @option params [required, Types::InferenceInputConfiguration] :data_input_configuration
    #   Specifies configuration information for the input data for the
    #   inference scheduler, including delimiter, format, and dataset
    #   location.
    #
    # @option params [required, Types::InferenceOutputConfiguration] :data_output_configuration
    #   Specifies configuration information for the output results for the
    #   inference scheduler, including the S3 location for the output.
    #
    # @option params [required, String] :role_arn
    #   The Amazon Resource Name (ARN) of a role with permission to access the
    #   data source being used for the inference.
    #
    # @option params [String] :server_side_kms_key_id
    #   Provides the identifier of the KMS key used to encrypt inference
    #   scheduler data by Amazon Lookout for Equipment.
    #
    # @option params [required, String] :client_token
    #   A unique identifier for the request. If you do not set the client
    #   request token, Amazon Lookout for Equipment generates one.
    #
    #   **A suitable default value is auto-generated.** You should normally
    #   not need to pass this option.**
    #
    # @option params [Array<Types::Tag>] :tags
    #   Any tags associated with the inference scheduler.
    #
    # @return [Types::CreateInferenceSchedulerResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::CreateInferenceSchedulerResponse#inference_scheduler_arn #inference_scheduler_arn} => String
    #   * {Types::CreateInferenceSchedulerResponse#inference_scheduler_name #inference_scheduler_name} => String
    #   * {Types::CreateInferenceSchedulerResponse#status #status} => String
    #   * {Types::CreateInferenceSchedulerResponse#model_quality #model_quality} => String
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.create_inference_scheduler({
    #     model_name: "ModelName", # required
    #     inference_scheduler_name: "InferenceSchedulerName", # required
    #     data_delay_offset_in_minutes: 1,
    #     data_upload_frequency: "PT5M", # required, accepts PT5M, PT10M, PT15M, PT30M, PT1H
    #     data_input_configuration: { # required
    #       s3_input_configuration: {
    #         bucket: "S3Bucket", # required
    #         prefix: "S3Prefix",
    #       },
    #       input_time_zone_offset: "TimeZoneOffset",
    #       inference_input_name_configuration: {
    #         timestamp_format: "FileNameTimestampFormat",
    #         component_timestamp_delimiter: "ComponentTimestampDelimiter",
    #       },
    #     },
    #     data_output_configuration: { # required
    #       s3_output_configuration: { # required
    #         bucket: "S3Bucket", # required
    #         prefix: "S3Prefix",
    #       },
    #       kms_key_id: "NameOrArn",
    #     },
    #     role_arn: "IamRoleArn", # required
    #     server_side_kms_key_id: "NameOrArn",
    #     client_token: "IdempotenceToken", # required
    #     tags: [
    #       {
    #         key: "TagKey", # required
    #         value: "TagValue", # required
    #       },
    #     ],
    #   })
    #
    # @example Response structure
    #
    #   resp.inference_scheduler_arn #=> String
    #   resp.inference_scheduler_name #=> String
    #   resp.status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
    #   resp.model_quality #=> String, one of "QUALITY_THRESHOLD_MET", "CANNOT_DETERMINE_QUALITY", "POOR_QUALITY_DETECTED"
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/CreateInferenceScheduler AWS API Documentation
    #
    # @overload create_inference_scheduler(params = {})
    # @param [Hash] params ({})
    def create_inference_scheduler(params = {}, options = {})
      req = build_request(:create_inference_scheduler, params)
      req.send_request(options)
    end

    # Creates a label for an event.
    #
    # @option params [required, String] :label_group_name
    #   The name of a group of labels.
    #
    #   Data in this field will be retained for service usage. Follow best
    #   practices for the security of your data.
    #
    # @option params [required, Time,DateTime,Date,Integer,String] :start_time
    #   The start time of the labeled event.
    #
    # @option params [required, Time,DateTime,Date,Integer,String] :end_time
    #   The end time of the labeled event.
    #
    # @option params [required, String] :rating
    #   Indicates whether a labeled event represents an anomaly.
    #
    # @option params [String] :fault_code
    #   Provides additional information about the label. The fault code must
    #   be defined in the FaultCodes attribute of the label group.
    #
    #   Data in this field will be retained for service usage. Follow best
    #   practices for the security of your data.
    #
    # @option params [String] :notes
    #   Metadata providing additional information about the label.
    #
    #   Data in this field will be retained for service usage. Follow best
    #   practices for the security of your data.
    #
    # @option params [String] :equipment
    #   Indicates that a label pertains to a particular piece of equipment.
    #
    #   Data in this field will be retained for service usage. Follow best
    #   practices for the security of your data.
    #
    # @option params [required, String] :client_token
    #   A unique identifier for the request to create a label. If you do not
    #   set the client request token, Lookout for Equipment generates one.
    #
    #   **A suitable default value is auto-generated.** You should normally
    #   not need to pass this option.**
    #
    # @return [Types::CreateLabelResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::CreateLabelResponse#label_id #label_id} => String
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.create_label({
    #     label_group_name: "LabelGroupName", # required
    #     start_time: Time.now, # required
    #     end_time: Time.now, # required
    #     rating: "ANOMALY", # required, accepts ANOMALY, NO_ANOMALY, NEUTRAL
    #     fault_code: "FaultCode",
    #     notes: "Comments",
    #     equipment: "Equipment",
    #     client_token: "IdempotenceToken", # required
    #   })
    #
    # @example Response structure
    #
    #   resp.label_id #=> String
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/CreateLabel AWS API Documentation
    #
    # @overload create_label(params = {})
    # @param [Hash] params ({})
    def create_label(params = {}, options = {})
      req = build_request(:create_label, params)
      req.send_request(options)
    end

    # Creates a group of labels.
    #
    # @option params [required, String] :label_group_name
    #   Names a group of labels.
    #
    #   Data in this field will be retained for service usage. Follow best
    #   practices for the security of your data.
    #
    # @option params [Array<String>] :fault_codes
    #   The acceptable fault codes (indicating the type of anomaly associated
    #   with the label) that can be used with this label group.
    #
    #   Data in this field will be retained for service usage. Follow best
    #   practices for the security of your data.
    #
    # @option params [required, String] :client_token
    #   A unique identifier for the request to create a label group. If you do
    #   not set the client request token, Lookout for Equipment generates one.
    #
    #   **A suitable default value is auto-generated.** You should normally
    #   not need to pass this option.**
    #
    # @option params [Array<Types::Tag>] :tags
    #   Tags that provide metadata about the label group you are creating.
    #
    #   Data in this field will be retained for service usage. Follow best
    #   practices for the security of your data.
    #
    # @return [Types::CreateLabelGroupResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::CreateLabelGroupResponse#label_group_name #label_group_name} => String
    #   * {Types::CreateLabelGroupResponse#label_group_arn #label_group_arn} => String
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.create_label_group({
    #     label_group_name: "LabelGroupName", # required
    #     fault_codes: ["FaultCode"],
    #     client_token: "IdempotenceToken", # required
    #     tags: [
    #       {
    #         key: "TagKey", # required
    #         value: "TagValue", # required
    #       },
    #     ],
    #   })
    #
    # @example Response structure
    #
    #   resp.label_group_name #=> String
    #   resp.label_group_arn #=> String
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/CreateLabelGroup AWS API Documentation
    #
    # @overload create_label_group(params = {})
    # @param [Hash] params ({})
    def create_label_group(params = {}, options = {})
      req = build_request(:create_label_group, params)
      req.send_request(options)
    end

    # Creates a machine learning model for data inference.
    #
    # A machine-learning (ML) model is a mathematical model that finds
    # patterns in your data. In Amazon Lookout for Equipment, the model
    # learns the patterns of normal behavior and detects abnormal behavior
    # that could be potential equipment failure (or maintenance events). The
    # models are made by analyzing normal data and abnormalities in machine
    # behavior that have already occurred.
    #
    # Your model is trained using a portion of the data from your dataset
    # and uses that data to learn patterns of normal behavior and abnormal
    # patterns that lead to equipment failure. Another portion of the data
    # is used to evaluate the model's accuracy.
    #
    # @option params [required, String] :model_name
    #   The name for the machine learning model to be created.
    #
    # @option params [required, String] :dataset_name
    #   The name of the dataset for the machine learning model being created.
    #
    # @option params [Types::DatasetSchema] :dataset_schema
    #   The data schema for the machine learning model being created.
    #
    # @option params [Types::LabelsInputConfiguration] :labels_input_configuration
    #   The input configuration for the labels being used for the machine
    #   learning model that's being created.
    #
    # @option params [required, String] :client_token
    #   A unique identifier for the request. If you do not set the client
    #   request token, Amazon Lookout for Equipment generates one.
    #
    #   **A suitable default value is auto-generated.** You should normally
    #   not need to pass this option.**
    #
    # @option params [Time,DateTime,Date,Integer,String] :training_data_start_time
    #   Indicates the time reference in the dataset that should be used to
    #   begin the subset of training data for the machine learning model.
    #
    # @option params [Time,DateTime,Date,Integer,String] :training_data_end_time
    #   Indicates the time reference in the dataset that should be used to end
    #   the subset of training data for the machine learning model.
    #
    # @option params [Time,DateTime,Date,Integer,String] :evaluation_data_start_time
    #   Indicates the time reference in the dataset that should be used to
    #   begin the subset of evaluation data for the machine learning model.
    #
    # @option params [Time,DateTime,Date,Integer,String] :evaluation_data_end_time
    #   Indicates the time reference in the dataset that should be used to end
    #   the subset of evaluation data for the machine learning model.
    #
    # @option params [String] :role_arn
    #   The Amazon Resource Name (ARN) of a role with permission to access the
    #   data source being used to create the machine learning model.
    #
    # @option params [Types::DataPreProcessingConfiguration] :data_pre_processing_configuration
    #   The configuration is the `TargetSamplingRate`, which is the sampling
    #   rate of the data after post processing by Amazon Lookout for
    #   Equipment. For example, if you provide data that has been collected at
    #   a 1 second level and you want the system to resample the data at a 1
    #   minute rate before training, the `TargetSamplingRate` is 1 minute.
    #
    #   When providing a value for the `TargetSamplingRate`, you must attach
    #   the prefix "PT" to the rate you want. The value for a 1 second rate
    #   is therefore *PT1S*, the value for a 15 minute rate is *PT15M*, and
    #   the value for a 1 hour rate is *PT1H*
    #
    # @option params [String] :server_side_kms_key_id
    #   Provides the identifier of the KMS key used to encrypt model data by
    #   Amazon Lookout for Equipment.
    #
    # @option params [Array<Types::Tag>] :tags
    #   Any tags associated with the machine learning model being created.
    #
    # @option params [String] :off_condition
    #   Indicates that the asset associated with this sensor has been shut
    #   off. As long as this condition is met, Lookout for Equipment will not
    #   use data from this asset for training, evaluation, or inference.
    #
    # @option params [Types::ModelDiagnosticsOutputConfiguration] :model_diagnostics_output_configuration
    #   The Amazon S3 location where you want Amazon Lookout for Equipment to
    #   save the pointwise model diagnostics. You must also specify the
    #   `RoleArn` request parameter.
    #
    # @return [Types::CreateModelResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::CreateModelResponse#model_arn #model_arn} => String
    #   * {Types::CreateModelResponse#status #status} => String
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.create_model({
    #     model_name: "ModelName", # required
    #     dataset_name: "DatasetIdentifier", # required
    #     dataset_schema: {
    #       inline_data_schema: "InlineDataSchema",
    #     },
    #     labels_input_configuration: {
    #       s3_input_configuration: {
    #         bucket: "S3Bucket", # required
    #         prefix: "S3Prefix",
    #       },
    #       label_group_name: "LabelGroupName",
    #     },
    #     client_token: "IdempotenceToken", # required
    #     training_data_start_time: Time.now,
    #     training_data_end_time: Time.now,
    #     evaluation_data_start_time: Time.now,
    #     evaluation_data_end_time: Time.now,
    #     role_arn: "IamRoleArn",
    #     data_pre_processing_configuration: {
    #       target_sampling_rate: "PT1S", # accepts PT1S, PT5S, PT10S, PT15S, PT30S, PT1M, PT5M, PT10M, PT15M, PT30M, PT1H
    #     },
    #     server_side_kms_key_id: "NameOrArn",
    #     tags: [
    #       {
    #         key: "TagKey", # required
    #         value: "TagValue", # required
    #       },
    #     ],
    #     off_condition: "OffCondition",
    #     model_diagnostics_output_configuration: {
    #       s3_output_configuration: { # required
    #         bucket: "S3Bucket", # required
    #         prefix: "S3Prefix",
    #       },
    #       kms_key_id: "NameOrArn",
    #     },
    #   })
    #
    # @example Response structure
    #
    #   resp.model_arn #=> String
    #   resp.status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS"
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/CreateModel AWS API Documentation
    #
    # @overload create_model(params = {})
    # @param [Hash] params ({})
    def create_model(params = {}, options = {})
      req = build_request(:create_model, params)
      req.send_request(options)
    end

    # Creates a retraining scheduler on the specified model.
    #
    # @option params [required, String] :model_name
    #   The name of the model to add the retraining scheduler to.
    #
    # @option params [Time,DateTime,Date,Integer,String] :retraining_start_date
    #   The start date for the retraining scheduler. Lookout for Equipment
    #   truncates the time you provide to the nearest UTC day.
    #
    # @option params [required, String] :retraining_frequency
    #   This parameter uses the [ISO 8601][1] standard to set the frequency at
    #   which you want retraining to occur in terms of Years, Months, and/or
    #   Days (note: other parameters like Time are not currently supported).
    #   The minimum value is 30 days (P30D) and the maximum value is 1 year
    #   (P1Y). For example, the following values are valid:
    #
    #   * P3M15D – Every 3 months and 15 days
    #
    #   * P2M – Every 2 months
    #
    #   * P150D – Every 150 days
    #
    #
    #
    #   [1]: https://en.wikipedia.org/wiki/ISO_8601#Durations
    #
    # @option params [required, String] :lookback_window
    #   The number of past days of data that will be used for retraining.
    #
    # @option params [String] :promote_mode
    #   Indicates how the service will use new models. In `MANAGED` mode, new
    #   models will automatically be used for inference if they have better
    #   performance than the current model. In `MANUAL` mode, the new models
    #   will not be used [until they are manually activated][1].
    #
    #
    #
    #   [1]: https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/versioning-model.html#model-activation
    #
    # @option params [required, String] :client_token
    #   A unique identifier for the request. If you do not set the client
    #   request token, Amazon Lookout for Equipment generates one.
    #
    #   **A suitable default value is auto-generated.** You should normally
    #   not need to pass this option.**
    #
    # @return [Types::CreateRetrainingSchedulerResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::CreateRetrainingSchedulerResponse#model_name #model_name} => String
    #   * {Types::CreateRetrainingSchedulerResponse#model_arn #model_arn} => String
    #   * {Types::CreateRetrainingSchedulerResponse#status #status} => String
    #
    #
    # @example Example: Creates a retraining scheduler with manual promote mode
    #
    #   resp = client.create_retraining_scheduler({
    #     client_token: "sample-client-token", 
    #     lookback_window: "P360D", 
    #     model_name: "sample-model", 
    #     promote_mode: "MANUAL", 
    #     retraining_frequency: "P1M", 
    #   })
    #
    #   resp.to_h outputs the following:
    #   {
    #     model_arn: "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111", 
    #     model_name: "sample-model", 
    #     status: "PENDING", 
    #   }
    #
    # @example Example: Creates a retraining scheduler with a specific start date
    #
    #   resp = client.create_retraining_scheduler({
    #     client_token: "sample-client-token", 
    #     lookback_window: "P360D", 
    #     model_name: "sample-model", 
    #     retraining_frequency: "P1M", 
    #     retraining_start_date: Time.parse("2024-01-01T00:00:00Z"), 
    #   })
    #
    #   resp.to_h outputs the following:
    #   {
    #     model_arn: "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111", 
    #     model_name: "sample-model", 
    #     status: "PENDING", 
    #   }
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.create_retraining_scheduler({
    #     model_name: "ModelName", # required
    #     retraining_start_date: Time.now,
    #     retraining_frequency: "RetrainingFrequency", # required
    #     lookback_window: "LookbackWindow", # required
    #     promote_mode: "MANAGED", # accepts MANAGED, MANUAL
    #     client_token: "IdempotenceToken", # required
    #   })
    #
    # @example Response structure
    #
    #   resp.model_name #=> String
    #   resp.model_arn #=> String
    #   resp.status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/CreateRetrainingScheduler AWS API Documentation
    #
    # @overload create_retraining_scheduler(params = {})
    # @param [Hash] params ({})
    def create_retraining_scheduler(params = {}, options = {})
      req = build_request(:create_retraining_scheduler, params)
      req.send_request(options)
    end

    # Deletes a dataset and associated artifacts. The operation will check
    # to see if any inference scheduler or data ingestion job is currently
    # using the dataset, and if there isn't, the dataset, its metadata, and
    # any associated data stored in S3 will be deleted. This does not affect
    # any models that used this dataset for training and evaluation, but
    # does prevent it from being used in the future.
    #
    # @option params [required, String] :dataset_name
    #   The name of the dataset to be deleted.
    #
    # @return [Struct] Returns an empty {Seahorse::Client::Response response}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.delete_dataset({
    #     dataset_name: "DatasetIdentifier", # required
    #   })
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/DeleteDataset AWS API Documentation
    #
    # @overload delete_dataset(params = {})
    # @param [Hash] params ({})
    def delete_dataset(params = {}, options = {})
      req = build_request(:delete_dataset, params)
      req.send_request(options)
    end

    # Deletes an inference scheduler that has been set up. Prior inference
    # results will not be deleted.
    #
    # @option params [required, String] :inference_scheduler_name
    #   The name of the inference scheduler to be deleted.
    #
    # @return [Struct] Returns an empty {Seahorse::Client::Response response}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.delete_inference_scheduler({
    #     inference_scheduler_name: "InferenceSchedulerIdentifier", # required
    #   })
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/DeleteInferenceScheduler AWS API Documentation
    #
    # @overload delete_inference_scheduler(params = {})
    # @param [Hash] params ({})
    def delete_inference_scheduler(params = {}, options = {})
      req = build_request(:delete_inference_scheduler, params)
      req.send_request(options)
    end

    # Deletes a label.
    #
    # @option params [required, String] :label_group_name
    #   The name of the label group that contains the label that you want to
    #   delete. Data in this field will be retained for service usage. Follow
    #   best practices for the security of your data.
    #
    # @option params [required, String] :label_id
    #   The ID of the label that you want to delete.
    #
    # @return [Struct] Returns an empty {Seahorse::Client::Response response}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.delete_label({
    #     label_group_name: "LabelGroupName", # required
    #     label_id: "LabelId", # required
    #   })
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/DeleteLabel AWS API Documentation
    #
    # @overload delete_label(params = {})
    # @param [Hash] params ({})
    def delete_label(params = {}, options = {})
      req = build_request(:delete_label, params)
      req.send_request(options)
    end

    # Deletes a group of labels.
    #
    # @option params [required, String] :label_group_name
    #   The name of the label group that you want to delete. Data in this
    #   field will be retained for service usage. Follow best practices for
    #   the security of your data.
    #
    # @return [Struct] Returns an empty {Seahorse::Client::Response response}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.delete_label_group({
    #     label_group_name: "LabelGroupName", # required
    #   })
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/DeleteLabelGroup AWS API Documentation
    #
    # @overload delete_label_group(params = {})
    # @param [Hash] params ({})
    def delete_label_group(params = {}, options = {})
      req = build_request(:delete_label_group, params)
      req.send_request(options)
    end

    # Deletes a machine learning model currently available for Amazon
    # Lookout for Equipment. This will prevent it from being used with an
    # inference scheduler, even one that is already set up.
    #
    # @option params [required, String] :model_name
    #   The name of the machine learning model to be deleted.
    #
    # @return [Struct] Returns an empty {Seahorse::Client::Response response}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.delete_model({
    #     model_name: "ModelName", # required
    #   })
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/DeleteModel AWS API Documentation
    #
    # @overload delete_model(params = {})
    # @param [Hash] params ({})
    def delete_model(params = {}, options = {})
      req = build_request(:delete_model, params)
      req.send_request(options)
    end

    # Deletes the resource policy attached to the resource.
    #
    # @option params [required, String] :resource_arn
    #   The Amazon Resource Name (ARN) of the resource for which the resource
    #   policy should be deleted.
    #
    # @return [Struct] Returns an empty {Seahorse::Client::Response response}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.delete_resource_policy({
    #     resource_arn: "ResourceArn", # required
    #   })
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/DeleteResourcePolicy AWS API Documentation
    #
    # @overload delete_resource_policy(params = {})
    # @param [Hash] params ({})
    def delete_resource_policy(params = {}, options = {})
      req = build_request(:delete_resource_policy, params)
      req.send_request(options)
    end

    # Deletes a retraining scheduler from a model. The retraining scheduler
    # must be in the `STOPPED` status.
    #
    # @option params [required, String] :model_name
    #   The name of the model whose retraining scheduler you want to delete.
    #
    # @return [Struct] Returns an empty {Seahorse::Client::Response response}.
    #
    #
    # @example Example: Deletes a retraining scheduler
    #
    #   resp = client.delete_retraining_scheduler({
    #     model_name: "sample-model", 
    #   })
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.delete_retraining_scheduler({
    #     model_name: "ModelName", # required
    #   })
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/DeleteRetrainingScheduler AWS API Documentation
    #
    # @overload delete_retraining_scheduler(params = {})
    # @param [Hash] params ({})
    def delete_retraining_scheduler(params = {}, options = {})
      req = build_request(:delete_retraining_scheduler, params)
      req.send_request(options)
    end

    # Provides information on a specific data ingestion job such as creation
    # time, dataset ARN, and status.
    #
    # @option params [required, String] :job_id
    #   The job ID of the data ingestion job.
    #
    # @return [Types::DescribeDataIngestionJobResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::DescribeDataIngestionJobResponse#job_id #job_id} => String
    #   * {Types::DescribeDataIngestionJobResponse#dataset_arn #dataset_arn} => String
    #   * {Types::DescribeDataIngestionJobResponse#ingestion_input_configuration #ingestion_input_configuration} => Types::IngestionInputConfiguration
    #   * {Types::DescribeDataIngestionJobResponse#role_arn #role_arn} => String
    #   * {Types::DescribeDataIngestionJobResponse#created_at #created_at} => Time
    #   * {Types::DescribeDataIngestionJobResponse#status #status} => String
    #   * {Types::DescribeDataIngestionJobResponse#failed_reason #failed_reason} => String
    #   * {Types::DescribeDataIngestionJobResponse#data_quality_summary #data_quality_summary} => Types::DataQualitySummary
    #   * {Types::DescribeDataIngestionJobResponse#ingested_files_summary #ingested_files_summary} => Types::IngestedFilesSummary
    #   * {Types::DescribeDataIngestionJobResponse#status_detail #status_detail} => String
    #   * {Types::DescribeDataIngestionJobResponse#ingested_data_size #ingested_data_size} => Integer
    #   * {Types::DescribeDataIngestionJobResponse#data_start_time #data_start_time} => Time
    #   * {Types::DescribeDataIngestionJobResponse#data_end_time #data_end_time} => Time
    #   * {Types::DescribeDataIngestionJobResponse#source_dataset_arn #source_dataset_arn} => String
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.describe_data_ingestion_job({
    #     job_id: "IngestionJobId", # required
    #   })
    #
    # @example Response structure
    #
    #   resp.job_id #=> String
    #   resp.dataset_arn #=> String
    #   resp.ingestion_input_configuration.s3_input_configuration.bucket #=> String
    #   resp.ingestion_input_configuration.s3_input_configuration.prefix #=> String
    #   resp.ingestion_input_configuration.s3_input_configuration.key_pattern #=> String
    #   resp.role_arn #=> String
    #   resp.created_at #=> Time
    #   resp.status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS"
    #   resp.failed_reason #=> String
    #   resp.data_quality_summary.insufficient_sensor_data.missing_complete_sensor_data.affected_sensor_count #=> Integer
    #   resp.data_quality_summary.insufficient_sensor_data.sensors_with_short_date_range.affected_sensor_count #=> Integer
    #   resp.data_quality_summary.missing_sensor_data.affected_sensor_count #=> Integer
    #   resp.data_quality_summary.missing_sensor_data.total_number_of_missing_values #=> Integer
    #   resp.data_quality_summary.invalid_sensor_data.affected_sensor_count #=> Integer
    #   resp.data_quality_summary.invalid_sensor_data.total_number_of_invalid_values #=> Integer
    #   resp.data_quality_summary.unsupported_timestamps.total_number_of_unsupported_timestamps #=> Integer
    #   resp.data_quality_summary.duplicate_timestamps.total_number_of_duplicate_timestamps #=> Integer
    #   resp.ingested_files_summary.total_number_of_files #=> Integer
    #   resp.ingested_files_summary.ingested_number_of_files #=> Integer
    #   resp.ingested_files_summary.discarded_files #=> Array
    #   resp.ingested_files_summary.discarded_files[0].bucket #=> String
    #   resp.ingested_files_summary.discarded_files[0].key #=> String
    #   resp.status_detail #=> String
    #   resp.ingested_data_size #=> Integer
    #   resp.data_start_time #=> Time
    #   resp.data_end_time #=> Time
    #   resp.source_dataset_arn #=> String
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/DescribeDataIngestionJob AWS API Documentation
    #
    # @overload describe_data_ingestion_job(params = {})
    # @param [Hash] params ({})
    def describe_data_ingestion_job(params = {}, options = {})
      req = build_request(:describe_data_ingestion_job, params)
      req.send_request(options)
    end

    # Provides a JSON description of the data in each time series dataset,
    # including names, column names, and data types.
    #
    # @option params [required, String] :dataset_name
    #   The name of the dataset to be described.
    #
    # @return [Types::DescribeDatasetResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::DescribeDatasetResponse#dataset_name #dataset_name} => String
    #   * {Types::DescribeDatasetResponse#dataset_arn #dataset_arn} => String
    #   * {Types::DescribeDatasetResponse#created_at #created_at} => Time
    #   * {Types::DescribeDatasetResponse#last_updated_at #last_updated_at} => Time
    #   * {Types::DescribeDatasetResponse#status #status} => String
    #   * {Types::DescribeDatasetResponse#schema #schema} => String
    #   * {Types::DescribeDatasetResponse#server_side_kms_key_id #server_side_kms_key_id} => String
    #   * {Types::DescribeDatasetResponse#ingestion_input_configuration #ingestion_input_configuration} => Types::IngestionInputConfiguration
    #   * {Types::DescribeDatasetResponse#data_quality_summary #data_quality_summary} => Types::DataQualitySummary
    #   * {Types::DescribeDatasetResponse#ingested_files_summary #ingested_files_summary} => Types::IngestedFilesSummary
    #   * {Types::DescribeDatasetResponse#role_arn #role_arn} => String
    #   * {Types::DescribeDatasetResponse#data_start_time #data_start_time} => Time
    #   * {Types::DescribeDatasetResponse#data_end_time #data_end_time} => Time
    #   * {Types::DescribeDatasetResponse#source_dataset_arn #source_dataset_arn} => String
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.describe_dataset({
    #     dataset_name: "DatasetIdentifier", # required
    #   })
    #
    # @example Response structure
    #
    #   resp.dataset_name #=> String
    #   resp.dataset_arn #=> String
    #   resp.created_at #=> Time
    #   resp.last_updated_at #=> Time
    #   resp.status #=> String, one of "CREATED", "INGESTION_IN_PROGRESS", "ACTIVE", "IMPORT_IN_PROGRESS"
    #   resp.schema #=> String
    #   resp.server_side_kms_key_id #=> String
    #   resp.ingestion_input_configuration.s3_input_configuration.bucket #=> String
    #   resp.ingestion_input_configuration.s3_input_configuration.prefix #=> String
    #   resp.ingestion_input_configuration.s3_input_configuration.key_pattern #=> String
    #   resp.data_quality_summary.insufficient_sensor_data.missing_complete_sensor_data.affected_sensor_count #=> Integer
    #   resp.data_quality_summary.insufficient_sensor_data.sensors_with_short_date_range.affected_sensor_count #=> Integer
    #   resp.data_quality_summary.missing_sensor_data.affected_sensor_count #=> Integer
    #   resp.data_quality_summary.missing_sensor_data.total_number_of_missing_values #=> Integer
    #   resp.data_quality_summary.invalid_sensor_data.affected_sensor_count #=> Integer
    #   resp.data_quality_summary.invalid_sensor_data.total_number_of_invalid_values #=> Integer
    #   resp.data_quality_summary.unsupported_timestamps.total_number_of_unsupported_timestamps #=> Integer
    #   resp.data_quality_summary.duplicate_timestamps.total_number_of_duplicate_timestamps #=> Integer
    #   resp.ingested_files_summary.total_number_of_files #=> Integer
    #   resp.ingested_files_summary.ingested_number_of_files #=> Integer
    #   resp.ingested_files_summary.discarded_files #=> Array
    #   resp.ingested_files_summary.discarded_files[0].bucket #=> String
    #   resp.ingested_files_summary.discarded_files[0].key #=> String
    #   resp.role_arn #=> String
    #   resp.data_start_time #=> Time
    #   resp.data_end_time #=> Time
    #   resp.source_dataset_arn #=> String
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/DescribeDataset AWS API Documentation
    #
    # @overload describe_dataset(params = {})
    # @param [Hash] params ({})
    def describe_dataset(params = {}, options = {})
      req = build_request(:describe_dataset, params)
      req.send_request(options)
    end

    # Specifies information about the inference scheduler being used,
    # including name, model, status, and associated metadata
    #
    # @option params [required, String] :inference_scheduler_name
    #   The name of the inference scheduler being described.
    #
    # @return [Types::DescribeInferenceSchedulerResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::DescribeInferenceSchedulerResponse#model_arn #model_arn} => String
    #   * {Types::DescribeInferenceSchedulerResponse#model_name #model_name} => String
    #   * {Types::DescribeInferenceSchedulerResponse#inference_scheduler_name #inference_scheduler_name} => String
    #   * {Types::DescribeInferenceSchedulerResponse#inference_scheduler_arn #inference_scheduler_arn} => String
    #   * {Types::DescribeInferenceSchedulerResponse#status #status} => String
    #   * {Types::DescribeInferenceSchedulerResponse#data_delay_offset_in_minutes #data_delay_offset_in_minutes} => Integer
    #   * {Types::DescribeInferenceSchedulerResponse#data_upload_frequency #data_upload_frequency} => String
    #   * {Types::DescribeInferenceSchedulerResponse#created_at #created_at} => Time
    #   * {Types::DescribeInferenceSchedulerResponse#updated_at #updated_at} => Time
    #   * {Types::DescribeInferenceSchedulerResponse#data_input_configuration #data_input_configuration} => Types::InferenceInputConfiguration
    #   * {Types::DescribeInferenceSchedulerResponse#data_output_configuration #data_output_configuration} => Types::InferenceOutputConfiguration
    #   * {Types::DescribeInferenceSchedulerResponse#role_arn #role_arn} => String
    #   * {Types::DescribeInferenceSchedulerResponse#server_side_kms_key_id #server_side_kms_key_id} => String
    #   * {Types::DescribeInferenceSchedulerResponse#latest_inference_result #latest_inference_result} => String
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.describe_inference_scheduler({
    #     inference_scheduler_name: "InferenceSchedulerIdentifier", # required
    #   })
    #
    # @example Response structure
    #
    #   resp.model_arn #=> String
    #   resp.model_name #=> String
    #   resp.inference_scheduler_name #=> String
    #   resp.inference_scheduler_arn #=> String
    #   resp.status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
    #   resp.data_delay_offset_in_minutes #=> Integer
    #   resp.data_upload_frequency #=> String, one of "PT5M", "PT10M", "PT15M", "PT30M", "PT1H"
    #   resp.created_at #=> Time
    #   resp.updated_at #=> Time
    #   resp.data_input_configuration.s3_input_configuration.bucket #=> String
    #   resp.data_input_configuration.s3_input_configuration.prefix #=> String
    #   resp.data_input_configuration.input_time_zone_offset #=> String
    #   resp.data_input_configuration.inference_input_name_configuration.timestamp_format #=> String
    #   resp.data_input_configuration.inference_input_name_configuration.component_timestamp_delimiter #=> String
    #   resp.data_output_configuration.s3_output_configuration.bucket #=> String
    #   resp.data_output_configuration.s3_output_configuration.prefix #=> String
    #   resp.data_output_configuration.kms_key_id #=> String
    #   resp.role_arn #=> String
    #   resp.server_side_kms_key_id #=> String
    #   resp.latest_inference_result #=> String, one of "ANOMALOUS", "NORMAL"
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/DescribeInferenceScheduler AWS API Documentation
    #
    # @overload describe_inference_scheduler(params = {})
    # @param [Hash] params ({})
    def describe_inference_scheduler(params = {}, options = {})
      req = build_request(:describe_inference_scheduler, params)
      req.send_request(options)
    end

    # Returns the name of the label.
    #
    # @option params [required, String] :label_group_name
    #   Returns the name of the group containing the label.
    #
    # @option params [required, String] :label_id
    #   Returns the ID of the label.
    #
    # @return [Types::DescribeLabelResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::DescribeLabelResponse#label_group_name #label_group_name} => String
    #   * {Types::DescribeLabelResponse#label_group_arn #label_group_arn} => String
    #   * {Types::DescribeLabelResponse#label_id #label_id} => String
    #   * {Types::DescribeLabelResponse#start_time #start_time} => Time
    #   * {Types::DescribeLabelResponse#end_time #end_time} => Time
    #   * {Types::DescribeLabelResponse#rating #rating} => String
    #   * {Types::DescribeLabelResponse#fault_code #fault_code} => String
    #   * {Types::DescribeLabelResponse#notes #notes} => String
    #   * {Types::DescribeLabelResponse#equipment #equipment} => String
    #   * {Types::DescribeLabelResponse#created_at #created_at} => Time
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.describe_label({
    #     label_group_name: "LabelGroupName", # required
    #     label_id: "LabelId", # required
    #   })
    #
    # @example Response structure
    #
    #   resp.label_group_name #=> String
    #   resp.label_group_arn #=> String
    #   resp.label_id #=> String
    #   resp.start_time #=> Time
    #   resp.end_time #=> Time
    #   resp.rating #=> String, one of "ANOMALY", "NO_ANOMALY", "NEUTRAL"
    #   resp.fault_code #=> String
    #   resp.notes #=> String
    #   resp.equipment #=> String
    #   resp.created_at #=> Time
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/DescribeLabel AWS API Documentation
    #
    # @overload describe_label(params = {})
    # @param [Hash] params ({})
    def describe_label(params = {}, options = {})
      req = build_request(:describe_label, params)
      req.send_request(options)
    end

    # Returns information about the label group.
    #
    # @option params [required, String] :label_group_name
    #   Returns the name of the label group.
    #
    # @return [Types::DescribeLabelGroupResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::DescribeLabelGroupResponse#label_group_name #label_group_name} => String
    #   * {Types::DescribeLabelGroupResponse#label_group_arn #label_group_arn} => String
    #   * {Types::DescribeLabelGroupResponse#fault_codes #fault_codes} => Array&lt;String&gt;
    #   * {Types::DescribeLabelGroupResponse#created_at #created_at} => Time
    #   * {Types::DescribeLabelGroupResponse#updated_at #updated_at} => Time
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.describe_label_group({
    #     label_group_name: "LabelGroupName", # required
    #   })
    #
    # @example Response structure
    #
    #   resp.label_group_name #=> String
    #   resp.label_group_arn #=> String
    #   resp.fault_codes #=> Array
    #   resp.fault_codes[0] #=> String
    #   resp.created_at #=> Time
    #   resp.updated_at #=> Time
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/DescribeLabelGroup AWS API Documentation
    #
    # @overload describe_label_group(params = {})
    # @param [Hash] params ({})
    def describe_label_group(params = {}, options = {})
      req = build_request(:describe_label_group, params)
      req.send_request(options)
    end

    # Provides a JSON containing the overall information about a specific
    # machine learning model, including model name and ARN, dataset,
    # training and evaluation information, status, and so on.
    #
    # @option params [required, String] :model_name
    #   The name of the machine learning model to be described.
    #
    # @return [Types::DescribeModelResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::DescribeModelResponse#model_name #model_name} => String
    #   * {Types::DescribeModelResponse#model_arn #model_arn} => String
    #   * {Types::DescribeModelResponse#dataset_name #dataset_name} => String
    #   * {Types::DescribeModelResponse#dataset_arn #dataset_arn} => String
    #   * {Types::DescribeModelResponse#schema #schema} => String
    #   * {Types::DescribeModelResponse#labels_input_configuration #labels_input_configuration} => Types::LabelsInputConfiguration
    #   * {Types::DescribeModelResponse#training_data_start_time #training_data_start_time} => Time
    #   * {Types::DescribeModelResponse#training_data_end_time #training_data_end_time} => Time
    #   * {Types::DescribeModelResponse#evaluation_data_start_time #evaluation_data_start_time} => Time
    #   * {Types::DescribeModelResponse#evaluation_data_end_time #evaluation_data_end_time} => Time
    #   * {Types::DescribeModelResponse#role_arn #role_arn} => String
    #   * {Types::DescribeModelResponse#data_pre_processing_configuration #data_pre_processing_configuration} => Types::DataPreProcessingConfiguration
    #   * {Types::DescribeModelResponse#status #status} => String
    #   * {Types::DescribeModelResponse#training_execution_start_time #training_execution_start_time} => Time
    #   * {Types::DescribeModelResponse#training_execution_end_time #training_execution_end_time} => Time
    #   * {Types::DescribeModelResponse#failed_reason #failed_reason} => String
    #   * {Types::DescribeModelResponse#model_metrics #model_metrics} => String
    #   * {Types::DescribeModelResponse#last_updated_time #last_updated_time} => Time
    #   * {Types::DescribeModelResponse#created_at #created_at} => Time
    #   * {Types::DescribeModelResponse#server_side_kms_key_id #server_side_kms_key_id} => String
    #   * {Types::DescribeModelResponse#off_condition #off_condition} => String
    #   * {Types::DescribeModelResponse#source_model_version_arn #source_model_version_arn} => String
    #   * {Types::DescribeModelResponse#import_job_start_time #import_job_start_time} => Time
    #   * {Types::DescribeModelResponse#import_job_end_time #import_job_end_time} => Time
    #   * {Types::DescribeModelResponse#active_model_version #active_model_version} => Integer
    #   * {Types::DescribeModelResponse#active_model_version_arn #active_model_version_arn} => String
    #   * {Types::DescribeModelResponse#model_version_activated_at #model_version_activated_at} => Time
    #   * {Types::DescribeModelResponse#previous_active_model_version #previous_active_model_version} => Integer
    #   * {Types::DescribeModelResponse#previous_active_model_version_arn #previous_active_model_version_arn} => String
    #   * {Types::DescribeModelResponse#previous_model_version_activated_at #previous_model_version_activated_at} => Time
    #   * {Types::DescribeModelResponse#prior_model_metrics #prior_model_metrics} => String
    #   * {Types::DescribeModelResponse#latest_scheduled_retraining_failed_reason #latest_scheduled_retraining_failed_reason} => String
    #   * {Types::DescribeModelResponse#latest_scheduled_retraining_status #latest_scheduled_retraining_status} => String
    #   * {Types::DescribeModelResponse#latest_scheduled_retraining_model_version #latest_scheduled_retraining_model_version} => Integer
    #   * {Types::DescribeModelResponse#latest_scheduled_retraining_start_time #latest_scheduled_retraining_start_time} => Time
    #   * {Types::DescribeModelResponse#latest_scheduled_retraining_available_data_in_days #latest_scheduled_retraining_available_data_in_days} => Integer
    #   * {Types::DescribeModelResponse#next_scheduled_retraining_start_date #next_scheduled_retraining_start_date} => Time
    #   * {Types::DescribeModelResponse#accumulated_inference_data_start_time #accumulated_inference_data_start_time} => Time
    #   * {Types::DescribeModelResponse#accumulated_inference_data_end_time #accumulated_inference_data_end_time} => Time
    #   * {Types::DescribeModelResponse#retraining_scheduler_status #retraining_scheduler_status} => String
    #   * {Types::DescribeModelResponse#model_diagnostics_output_configuration #model_diagnostics_output_configuration} => Types::ModelDiagnosticsOutputConfiguration
    #   * {Types::DescribeModelResponse#model_quality #model_quality} => String
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.describe_model({
    #     model_name: "ModelName", # required
    #   })
    #
    # @example Response structure
    #
    #   resp.model_name #=> String
    #   resp.model_arn #=> String
    #   resp.dataset_name #=> String
    #   resp.dataset_arn #=> String
    #   resp.schema #=> String
    #   resp.labels_input_configuration.s3_input_configuration.bucket #=> String
    #   resp.labels_input_configuration.s3_input_configuration.prefix #=> String
    #   resp.labels_input_configuration.label_group_name #=> String
    #   resp.training_data_start_time #=> Time
    #   resp.training_data_end_time #=> Time
    #   resp.evaluation_data_start_time #=> Time
    #   resp.evaluation_data_end_time #=> Time
    #   resp.role_arn #=> String
    #   resp.data_pre_processing_configuration.target_sampling_rate #=> String, one of "PT1S", "PT5S", "PT10S", "PT15S", "PT30S", "PT1M", "PT5M", "PT10M", "PT15M", "PT30M", "PT1H"
    #   resp.status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS"
    #   resp.training_execution_start_time #=> Time
    #   resp.training_execution_end_time #=> Time
    #   resp.failed_reason #=> String
    #   resp.model_metrics #=> String
    #   resp.last_updated_time #=> Time
    #   resp.created_at #=> Time
    #   resp.server_side_kms_key_id #=> String
    #   resp.off_condition #=> String
    #   resp.source_model_version_arn #=> String
    #   resp.import_job_start_time #=> Time
    #   resp.import_job_end_time #=> Time
    #   resp.active_model_version #=> Integer
    #   resp.active_model_version_arn #=> String
    #   resp.model_version_activated_at #=> Time
    #   resp.previous_active_model_version #=> Integer
    #   resp.previous_active_model_version_arn #=> String
    #   resp.previous_model_version_activated_at #=> Time
    #   resp.prior_model_metrics #=> String
    #   resp.latest_scheduled_retraining_failed_reason #=> String
    #   resp.latest_scheduled_retraining_status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS", "CANCELED"
    #   resp.latest_scheduled_retraining_model_version #=> Integer
    #   resp.latest_scheduled_retraining_start_time #=> Time
    #   resp.latest_scheduled_retraining_available_data_in_days #=> Integer
    #   resp.next_scheduled_retraining_start_date #=> Time
    #   resp.accumulated_inference_data_start_time #=> Time
    #   resp.accumulated_inference_data_end_time #=> Time
    #   resp.retraining_scheduler_status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
    #   resp.model_diagnostics_output_configuration.s3_output_configuration.bucket #=> String
    #   resp.model_diagnostics_output_configuration.s3_output_configuration.prefix #=> String
    #   resp.model_diagnostics_output_configuration.kms_key_id #=> String
    #   resp.model_quality #=> String, one of "QUALITY_THRESHOLD_MET", "CANNOT_DETERMINE_QUALITY", "POOR_QUALITY_DETECTED"
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/DescribeModel AWS API Documentation
    #
    # @overload describe_model(params = {})
    # @param [Hash] params ({})
    def describe_model(params = {}, options = {})
      req = build_request(:describe_model, params)
      req.send_request(options)
    end

    # Retrieves information about a specific machine learning model version.
    #
    # @option params [required, String] :model_name
    #   The name of the machine learning model that this version belongs to.
    #
    # @option params [required, Integer] :model_version
    #   The version of the machine learning model.
    #
    # @return [Types::DescribeModelVersionResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::DescribeModelVersionResponse#model_name #model_name} => String
    #   * {Types::DescribeModelVersionResponse#model_arn #model_arn} => String
    #   * {Types::DescribeModelVersionResponse#model_version #model_version} => Integer
    #   * {Types::DescribeModelVersionResponse#model_version_arn #model_version_arn} => String
    #   * {Types::DescribeModelVersionResponse#status #status} => String
    #   * {Types::DescribeModelVersionResponse#source_type #source_type} => String
    #   * {Types::DescribeModelVersionResponse#dataset_name #dataset_name} => String
    #   * {Types::DescribeModelVersionResponse#dataset_arn #dataset_arn} => String
    #   * {Types::DescribeModelVersionResponse#schema #schema} => String
    #   * {Types::DescribeModelVersionResponse#labels_input_configuration #labels_input_configuration} => Types::LabelsInputConfiguration
    #   * {Types::DescribeModelVersionResponse#training_data_start_time #training_data_start_time} => Time
    #   * {Types::DescribeModelVersionResponse#training_data_end_time #training_data_end_time} => Time
    #   * {Types::DescribeModelVersionResponse#evaluation_data_start_time #evaluation_data_start_time} => Time
    #   * {Types::DescribeModelVersionResponse#evaluation_data_end_time #evaluation_data_end_time} => Time
    #   * {Types::DescribeModelVersionResponse#role_arn #role_arn} => String
    #   * {Types::DescribeModelVersionResponse#data_pre_processing_configuration #data_pre_processing_configuration} => Types::DataPreProcessingConfiguration
    #   * {Types::DescribeModelVersionResponse#training_execution_start_time #training_execution_start_time} => Time
    #   * {Types::DescribeModelVersionResponse#training_execution_end_time #training_execution_end_time} => Time
    #   * {Types::DescribeModelVersionResponse#failed_reason #failed_reason} => String
    #   * {Types::DescribeModelVersionResponse#model_metrics #model_metrics} => String
    #   * {Types::DescribeModelVersionResponse#last_updated_time #last_updated_time} => Time
    #   * {Types::DescribeModelVersionResponse#created_at #created_at} => Time
    #   * {Types::DescribeModelVersionResponse#server_side_kms_key_id #server_side_kms_key_id} => String
    #   * {Types::DescribeModelVersionResponse#off_condition #off_condition} => String
    #   * {Types::DescribeModelVersionResponse#source_model_version_arn #source_model_version_arn} => String
    #   * {Types::DescribeModelVersionResponse#import_job_start_time #import_job_start_time} => Time
    #   * {Types::DescribeModelVersionResponse#import_job_end_time #import_job_end_time} => Time
    #   * {Types::DescribeModelVersionResponse#imported_data_size_in_bytes #imported_data_size_in_bytes} => Integer
    #   * {Types::DescribeModelVersionResponse#prior_model_metrics #prior_model_metrics} => String
    #   * {Types::DescribeModelVersionResponse#retraining_available_data_in_days #retraining_available_data_in_days} => Integer
    #   * {Types::DescribeModelVersionResponse#auto_promotion_result #auto_promotion_result} => String
    #   * {Types::DescribeModelVersionResponse#auto_promotion_result_reason #auto_promotion_result_reason} => String
    #   * {Types::DescribeModelVersionResponse#model_diagnostics_output_configuration #model_diagnostics_output_configuration} => Types::ModelDiagnosticsOutputConfiguration
    #   * {Types::DescribeModelVersionResponse#model_diagnostics_results_object #model_diagnostics_results_object} => Types::S3Object
    #   * {Types::DescribeModelVersionResponse#model_quality #model_quality} => String
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.describe_model_version({
    #     model_name: "ModelName", # required
    #     model_version: 1, # required
    #   })
    #
    # @example Response structure
    #
    #   resp.model_name #=> String
    #   resp.model_arn #=> String
    #   resp.model_version #=> Integer
    #   resp.model_version_arn #=> String
    #   resp.status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS", "CANCELED"
    #   resp.source_type #=> String, one of "TRAINING", "RETRAINING", "IMPORT"
    #   resp.dataset_name #=> String
    #   resp.dataset_arn #=> String
    #   resp.schema #=> String
    #   resp.labels_input_configuration.s3_input_configuration.bucket #=> String
    #   resp.labels_input_configuration.s3_input_configuration.prefix #=> String
    #   resp.labels_input_configuration.label_group_name #=> String
    #   resp.training_data_start_time #=> Time
    #   resp.training_data_end_time #=> Time
    #   resp.evaluation_data_start_time #=> Time
    #   resp.evaluation_data_end_time #=> Time
    #   resp.role_arn #=> String
    #   resp.data_pre_processing_configuration.target_sampling_rate #=> String, one of "PT1S", "PT5S", "PT10S", "PT15S", "PT30S", "PT1M", "PT5M", "PT10M", "PT15M", "PT30M", "PT1H"
    #   resp.training_execution_start_time #=> Time
    #   resp.training_execution_end_time #=> Time
    #   resp.failed_reason #=> String
    #   resp.model_metrics #=> String
    #   resp.last_updated_time #=> Time
    #   resp.created_at #=> Time
    #   resp.server_side_kms_key_id #=> String
    #   resp.off_condition #=> String
    #   resp.source_model_version_arn #=> String
    #   resp.import_job_start_time #=> Time
    #   resp.import_job_end_time #=> Time
    #   resp.imported_data_size_in_bytes #=> Integer
    #   resp.prior_model_metrics #=> String
    #   resp.retraining_available_data_in_days #=> Integer
    #   resp.auto_promotion_result #=> String, one of "MODEL_PROMOTED", "MODEL_NOT_PROMOTED", "RETRAINING_INTERNAL_ERROR", "RETRAINING_CUSTOMER_ERROR", "RETRAINING_CANCELLED"
    #   resp.auto_promotion_result_reason #=> String
    #   resp.model_diagnostics_output_configuration.s3_output_configuration.bucket #=> String
    #   resp.model_diagnostics_output_configuration.s3_output_configuration.prefix #=> String
    #   resp.model_diagnostics_output_configuration.kms_key_id #=> String
    #   resp.model_diagnostics_results_object.bucket #=> String
    #   resp.model_diagnostics_results_object.key #=> String
    #   resp.model_quality #=> String, one of "QUALITY_THRESHOLD_MET", "CANNOT_DETERMINE_QUALITY", "POOR_QUALITY_DETECTED"
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/DescribeModelVersion AWS API Documentation
    #
    # @overload describe_model_version(params = {})
    # @param [Hash] params ({})
    def describe_model_version(params = {}, options = {})
      req = build_request(:describe_model_version, params)
      req.send_request(options)
    end

    # Provides the details of a resource policy attached to a resource.
    #
    # @option params [required, String] :resource_arn
    #   The Amazon Resource Name (ARN) of the resource that is associated with
    #   the resource policy.
    #
    # @return [Types::DescribeResourcePolicyResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::DescribeResourcePolicyResponse#policy_revision_id #policy_revision_id} => String
    #   * {Types::DescribeResourcePolicyResponse#resource_policy #resource_policy} => String
    #   * {Types::DescribeResourcePolicyResponse#creation_time #creation_time} => Time
    #   * {Types::DescribeResourcePolicyResponse#last_modified_time #last_modified_time} => Time
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.describe_resource_policy({
    #     resource_arn: "ResourceArn", # required
    #   })
    #
    # @example Response structure
    #
    #   resp.policy_revision_id #=> String
    #   resp.resource_policy #=> String
    #   resp.creation_time #=> Time
    #   resp.last_modified_time #=> Time
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/DescribeResourcePolicy AWS API Documentation
    #
    # @overload describe_resource_policy(params = {})
    # @param [Hash] params ({})
    def describe_resource_policy(params = {}, options = {})
      req = build_request(:describe_resource_policy, params)
      req.send_request(options)
    end

    # Provides a description of the retraining scheduler, including
    # information such as the model name and retraining parameters.
    #
    # @option params [required, String] :model_name
    #   The name of the model that the retraining scheduler is attached to.
    #
    # @return [Types::DescribeRetrainingSchedulerResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::DescribeRetrainingSchedulerResponse#model_name #model_name} => String
    #   * {Types::DescribeRetrainingSchedulerResponse#model_arn #model_arn} => String
    #   * {Types::DescribeRetrainingSchedulerResponse#retraining_start_date #retraining_start_date} => Time
    #   * {Types::DescribeRetrainingSchedulerResponse#retraining_frequency #retraining_frequency} => String
    #   * {Types::DescribeRetrainingSchedulerResponse#lookback_window #lookback_window} => String
    #   * {Types::DescribeRetrainingSchedulerResponse#status #status} => String
    #   * {Types::DescribeRetrainingSchedulerResponse#promote_mode #promote_mode} => String
    #   * {Types::DescribeRetrainingSchedulerResponse#created_at #created_at} => Time
    #   * {Types::DescribeRetrainingSchedulerResponse#updated_at #updated_at} => Time
    #
    #
    # @example Example: Describes a retraining scheduler
    #
    #   resp = client.describe_retraining_scheduler({
    #     model_name: "sample-model", 
    #   })
    #
    #   resp.to_h outputs the following:
    #   {
    #     created_at: Time.parse("2023-10-01T15:00:00Z"), 
    #     lookback_window: "P360D", 
    #     model_arn: "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111", 
    #     model_name: "sample-model", 
    #     promote_mode: "MANAGED", 
    #     retraining_frequency: "P1M", 
    #     retraining_start_date: Time.parse("2023-11-01T00:00:00Z"), 
    #     status: "RUNNING", 
    #     updated_at: Time.parse("2023-10-01T15:00:00Z"), 
    #   }
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.describe_retraining_scheduler({
    #     model_name: "ModelName", # required
    #   })
    #
    # @example Response structure
    #
    #   resp.model_name #=> String
    #   resp.model_arn #=> String
    #   resp.retraining_start_date #=> Time
    #   resp.retraining_frequency #=> String
    #   resp.lookback_window #=> String
    #   resp.status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
    #   resp.promote_mode #=> String, one of "MANAGED", "MANUAL"
    #   resp.created_at #=> Time
    #   resp.updated_at #=> Time
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/DescribeRetrainingScheduler AWS API Documentation
    #
    # @overload describe_retraining_scheduler(params = {})
    # @param [Hash] params ({})
    def describe_retraining_scheduler(params = {}, options = {})
      req = build_request(:describe_retraining_scheduler, params)
      req.send_request(options)
    end

    # Imports a dataset.
    #
    # @option params [required, String] :source_dataset_arn
    #   The Amazon Resource Name (ARN) of the dataset to import.
    #
    # @option params [String] :dataset_name
    #   The name of the machine learning dataset to be created. If the dataset
    #   already exists, Amazon Lookout for Equipment overwrites the existing
    #   dataset. If you don't specify this field, it is filled with the name
    #   of the source dataset.
    #
    # @option params [required, String] :client_token
    #   A unique identifier for the request. If you do not set the client
    #   request token, Amazon Lookout for Equipment generates one.
    #
    #   **A suitable default value is auto-generated.** You should normally
    #   not need to pass this option.**
    #
    # @option params [String] :server_side_kms_key_id
    #   Provides the identifier of the KMS key key used to encrypt model data
    #   by Amazon Lookout for Equipment.
    #
    # @option params [Array<Types::Tag>] :tags
    #   Any tags associated with the dataset to be created.
    #
    # @return [Types::ImportDatasetResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::ImportDatasetResponse#dataset_name #dataset_name} => String
    #   * {Types::ImportDatasetResponse#dataset_arn #dataset_arn} => String
    #   * {Types::ImportDatasetResponse#status #status} => String
    #   * {Types::ImportDatasetResponse#job_id #job_id} => String
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.import_dataset({
    #     source_dataset_arn: "DatasetArn", # required
    #     dataset_name: "DatasetName",
    #     client_token: "IdempotenceToken", # required
    #     server_side_kms_key_id: "NameOrArn",
    #     tags: [
    #       {
    #         key: "TagKey", # required
    #         value: "TagValue", # required
    #       },
    #     ],
    #   })
    #
    # @example Response structure
    #
    #   resp.dataset_name #=> String
    #   resp.dataset_arn #=> String
    #   resp.status #=> String, one of "CREATED", "INGESTION_IN_PROGRESS", "ACTIVE", "IMPORT_IN_PROGRESS"
    #   resp.job_id #=> String
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/ImportDataset AWS API Documentation
    #
    # @overload import_dataset(params = {})
    # @param [Hash] params ({})
    def import_dataset(params = {}, options = {})
      req = build_request(:import_dataset, params)
      req.send_request(options)
    end

    # Imports a model that has been trained successfully.
    #
    # @option params [required, String] :source_model_version_arn
    #   The Amazon Resource Name (ARN) of the model version to import.
    #
    # @option params [String] :model_name
    #   The name for the machine learning model to be created. If the model
    #   already exists, Amazon Lookout for Equipment creates a new version. If
    #   you do not specify this field, it is filled with the name of the
    #   source model.
    #
    # @option params [required, String] :dataset_name
    #   The name of the dataset for the machine learning model being imported.
    #
    # @option params [Types::LabelsInputConfiguration] :labels_input_configuration
    #   Contains the configuration information for the S3 location being used
    #   to hold label data.
    #
    # @option params [required, String] :client_token
    #   A unique identifier for the request. If you do not set the client
    #   request token, Amazon Lookout for Equipment generates one.
    #
    #   **A suitable default value is auto-generated.** You should normally
    #   not need to pass this option.**
    #
    # @option params [String] :role_arn
    #   The Amazon Resource Name (ARN) of a role with permission to access the
    #   data source being used to create the machine learning model.
    #
    # @option params [String] :server_side_kms_key_id
    #   Provides the identifier of the KMS key key used to encrypt model data
    #   by Amazon Lookout for Equipment.
    #
    # @option params [Array<Types::Tag>] :tags
    #   The tags associated with the machine learning model to be created.
    #
    # @option params [String] :inference_data_import_strategy
    #   Indicates how to import the accumulated inference data when a model
    #   version is imported. The possible values are as follows:
    #
    #   * NO\_IMPORT – Don't import the data.
    #
    #   * ADD\_WHEN\_EMPTY – Only import the data from the source model if
    #     there is no existing data in the target model.
    #
    #   * OVERWRITE – Import the data from the source model and overwrite the
    #     existing data in the target model.
    #
    # @return [Types::ImportModelVersionResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::ImportModelVersionResponse#model_name #model_name} => String
    #   * {Types::ImportModelVersionResponse#model_arn #model_arn} => String
    #   * {Types::ImportModelVersionResponse#model_version_arn #model_version_arn} => String
    #   * {Types::ImportModelVersionResponse#model_version #model_version} => Integer
    #   * {Types::ImportModelVersionResponse#status #status} => String
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.import_model_version({
    #     source_model_version_arn: "ModelVersionArn", # required
    #     model_name: "ModelName",
    #     dataset_name: "DatasetIdentifier", # required
    #     labels_input_configuration: {
    #       s3_input_configuration: {
    #         bucket: "S3Bucket", # required
    #         prefix: "S3Prefix",
    #       },
    #       label_group_name: "LabelGroupName",
    #     },
    #     client_token: "IdempotenceToken", # required
    #     role_arn: "IamRoleArn",
    #     server_side_kms_key_id: "NameOrArn",
    #     tags: [
    #       {
    #         key: "TagKey", # required
    #         value: "TagValue", # required
    #       },
    #     ],
    #     inference_data_import_strategy: "NO_IMPORT", # accepts NO_IMPORT, ADD_WHEN_EMPTY, OVERWRITE
    #   })
    #
    # @example Response structure
    #
    #   resp.model_name #=> String
    #   resp.model_arn #=> String
    #   resp.model_version_arn #=> String
    #   resp.model_version #=> Integer
    #   resp.status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS", "CANCELED"
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/ImportModelVersion AWS API Documentation
    #
    # @overload import_model_version(params = {})
    # @param [Hash] params ({})
    def import_model_version(params = {}, options = {})
      req = build_request(:import_model_version, params)
      req.send_request(options)
    end

    # Provides a list of all data ingestion jobs, including dataset name and
    # ARN, S3 location of the input data, status, and so on.
    #
    # @option params [String] :dataset_name
    #   The name of the dataset being used for the data ingestion job.
    #
    # @option params [String] :next_token
    #   An opaque pagination token indicating where to continue the listing of
    #   data ingestion jobs.
    #
    # @option params [Integer] :max_results
    #   Specifies the maximum number of data ingestion jobs to list.
    #
    # @option params [String] :status
    #   Indicates the status of the data ingestion job.
    #
    # @return [Types::ListDataIngestionJobsResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::ListDataIngestionJobsResponse#next_token #next_token} => String
    #   * {Types::ListDataIngestionJobsResponse#data_ingestion_job_summaries #data_ingestion_job_summaries} => Array&lt;Types::DataIngestionJobSummary&gt;
    #
    # The returned {Seahorse::Client::Response response} is a pageable response and is Enumerable. For details on usage see {Aws::PageableResponse PageableResponse}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.list_data_ingestion_jobs({
    #     dataset_name: "DatasetName",
    #     next_token: "NextToken",
    #     max_results: 1,
    #     status: "IN_PROGRESS", # accepts IN_PROGRESS, SUCCESS, FAILED, IMPORT_IN_PROGRESS
    #   })
    #
    # @example Response structure
    #
    #   resp.next_token #=> String
    #   resp.data_ingestion_job_summaries #=> Array
    #   resp.data_ingestion_job_summaries[0].job_id #=> String
    #   resp.data_ingestion_job_summaries[0].dataset_name #=> String
    #   resp.data_ingestion_job_summaries[0].dataset_arn #=> String
    #   resp.data_ingestion_job_summaries[0].ingestion_input_configuration.s3_input_configuration.bucket #=> String
    #   resp.data_ingestion_job_summaries[0].ingestion_input_configuration.s3_input_configuration.prefix #=> String
    #   resp.data_ingestion_job_summaries[0].ingestion_input_configuration.s3_input_configuration.key_pattern #=> String
    #   resp.data_ingestion_job_summaries[0].status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS"
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/ListDataIngestionJobs AWS API Documentation
    #
    # @overload list_data_ingestion_jobs(params = {})
    # @param [Hash] params ({})
    def list_data_ingestion_jobs(params = {}, options = {})
      req = build_request(:list_data_ingestion_jobs, params)
      req.send_request(options)
    end

    # Lists all datasets currently available in your account, filtering on
    # the dataset name.
    #
    # @option params [String] :next_token
    #   An opaque pagination token indicating where to continue the listing of
    #   datasets.
    #
    # @option params [Integer] :max_results
    #   Specifies the maximum number of datasets to list.
    #
    # @option params [String] :dataset_name_begins_with
    #   The beginning of the name of the datasets to be listed.
    #
    # @return [Types::ListDatasetsResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::ListDatasetsResponse#next_token #next_token} => String
    #   * {Types::ListDatasetsResponse#dataset_summaries #dataset_summaries} => Array&lt;Types::DatasetSummary&gt;
    #
    # The returned {Seahorse::Client::Response response} is a pageable response and is Enumerable. For details on usage see {Aws::PageableResponse PageableResponse}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.list_datasets({
    #     next_token: "NextToken",
    #     max_results: 1,
    #     dataset_name_begins_with: "DatasetName",
    #   })
    #
    # @example Response structure
    #
    #   resp.next_token #=> String
    #   resp.dataset_summaries #=> Array
    #   resp.dataset_summaries[0].dataset_name #=> String
    #   resp.dataset_summaries[0].dataset_arn #=> String
    #   resp.dataset_summaries[0].status #=> String, one of "CREATED", "INGESTION_IN_PROGRESS", "ACTIVE", "IMPORT_IN_PROGRESS"
    #   resp.dataset_summaries[0].created_at #=> Time
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/ListDatasets AWS API Documentation
    #
    # @overload list_datasets(params = {})
    # @param [Hash] params ({})
    def list_datasets(params = {}, options = {})
      req = build_request(:list_datasets, params)
      req.send_request(options)
    end

    # Lists all inference events that have been found for the specified
    # inference scheduler.
    #
    # @option params [String] :next_token
    #   An opaque pagination token indicating where to continue the listing of
    #   inference events.
    #
    # @option params [Integer] :max_results
    #   Specifies the maximum number of inference events to list.
    #
    # @option params [required, String] :inference_scheduler_name
    #   The name of the inference scheduler for the inference events listed.
    #
    # @option params [required, Time,DateTime,Date,Integer,String] :interval_start_time
    #   Lookout for Equipment will return all the inference events with an end
    #   time equal to or greater than the start time given.
    #
    # @option params [required, Time,DateTime,Date,Integer,String] :interval_end_time
    #   Returns all the inference events with an end start time equal to or
    #   greater than less than the end time given.
    #
    # @return [Types::ListInferenceEventsResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::ListInferenceEventsResponse#next_token #next_token} => String
    #   * {Types::ListInferenceEventsResponse#inference_event_summaries #inference_event_summaries} => Array&lt;Types::InferenceEventSummary&gt;
    #
    # The returned {Seahorse::Client::Response response} is a pageable response and is Enumerable. For details on usage see {Aws::PageableResponse PageableResponse}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.list_inference_events({
    #     next_token: "NextToken",
    #     max_results: 1,
    #     inference_scheduler_name: "InferenceSchedulerIdentifier", # required
    #     interval_start_time: Time.now, # required
    #     interval_end_time: Time.now, # required
    #   })
    #
    # @example Response structure
    #
    #   resp.next_token #=> String
    #   resp.inference_event_summaries #=> Array
    #   resp.inference_event_summaries[0].inference_scheduler_arn #=> String
    #   resp.inference_event_summaries[0].inference_scheduler_name #=> String
    #   resp.inference_event_summaries[0].event_start_time #=> Time
    #   resp.inference_event_summaries[0].event_end_time #=> Time
    #   resp.inference_event_summaries[0].diagnostics #=> String
    #   resp.inference_event_summaries[0].event_duration_in_seconds #=> Integer
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/ListInferenceEvents AWS API Documentation
    #
    # @overload list_inference_events(params = {})
    # @param [Hash] params ({})
    def list_inference_events(params = {}, options = {})
      req = build_request(:list_inference_events, params)
      req.send_request(options)
    end

    # Lists all inference executions that have been performed by the
    # specified inference scheduler.
    #
    # @option params [String] :next_token
    #   An opaque pagination token indicating where to continue the listing of
    #   inference executions.
    #
    # @option params [Integer] :max_results
    #   Specifies the maximum number of inference executions to list.
    #
    # @option params [required, String] :inference_scheduler_name
    #   The name of the inference scheduler for the inference execution
    #   listed.
    #
    # @option params [Time,DateTime,Date,Integer,String] :data_start_time_after
    #   The time reference in the inferenced dataset after which Amazon
    #   Lookout for Equipment started the inference execution.
    #
    # @option params [Time,DateTime,Date,Integer,String] :data_end_time_before
    #   The time reference in the inferenced dataset before which Amazon
    #   Lookout for Equipment stopped the inference execution.
    #
    # @option params [String] :status
    #   The status of the inference execution.
    #
    # @return [Types::ListInferenceExecutionsResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::ListInferenceExecutionsResponse#next_token #next_token} => String
    #   * {Types::ListInferenceExecutionsResponse#inference_execution_summaries #inference_execution_summaries} => Array&lt;Types::InferenceExecutionSummary&gt;
    #
    # The returned {Seahorse::Client::Response response} is a pageable response and is Enumerable. For details on usage see {Aws::PageableResponse PageableResponse}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.list_inference_executions({
    #     next_token: "NextToken",
    #     max_results: 1,
    #     inference_scheduler_name: "InferenceSchedulerIdentifier", # required
    #     data_start_time_after: Time.now,
    #     data_end_time_before: Time.now,
    #     status: "IN_PROGRESS", # accepts IN_PROGRESS, SUCCESS, FAILED
    #   })
    #
    # @example Response structure
    #
    #   resp.next_token #=> String
    #   resp.inference_execution_summaries #=> Array
    #   resp.inference_execution_summaries[0].model_name #=> String
    #   resp.inference_execution_summaries[0].model_arn #=> String
    #   resp.inference_execution_summaries[0].inference_scheduler_name #=> String
    #   resp.inference_execution_summaries[0].inference_scheduler_arn #=> String
    #   resp.inference_execution_summaries[0].scheduled_start_time #=> Time
    #   resp.inference_execution_summaries[0].data_start_time #=> Time
    #   resp.inference_execution_summaries[0].data_end_time #=> Time
    #   resp.inference_execution_summaries[0].data_input_configuration.s3_input_configuration.bucket #=> String
    #   resp.inference_execution_summaries[0].data_input_configuration.s3_input_configuration.prefix #=> String
    #   resp.inference_execution_summaries[0].data_input_configuration.input_time_zone_offset #=> String
    #   resp.inference_execution_summaries[0].data_input_configuration.inference_input_name_configuration.timestamp_format #=> String
    #   resp.inference_execution_summaries[0].data_input_configuration.inference_input_name_configuration.component_timestamp_delimiter #=> String
    #   resp.inference_execution_summaries[0].data_output_configuration.s3_output_configuration.bucket #=> String
    #   resp.inference_execution_summaries[0].data_output_configuration.s3_output_configuration.prefix #=> String
    #   resp.inference_execution_summaries[0].data_output_configuration.kms_key_id #=> String
    #   resp.inference_execution_summaries[0].customer_result_object.bucket #=> String
    #   resp.inference_execution_summaries[0].customer_result_object.key #=> String
    #   resp.inference_execution_summaries[0].status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED"
    #   resp.inference_execution_summaries[0].failed_reason #=> String
    #   resp.inference_execution_summaries[0].model_version #=> Integer
    #   resp.inference_execution_summaries[0].model_version_arn #=> String
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/ListInferenceExecutions AWS API Documentation
    #
    # @overload list_inference_executions(params = {})
    # @param [Hash] params ({})
    def list_inference_executions(params = {}, options = {})
      req = build_request(:list_inference_executions, params)
      req.send_request(options)
    end

    # Retrieves a list of all inference schedulers currently available for
    # your account.
    #
    # @option params [String] :next_token
    #   An opaque pagination token indicating where to continue the listing of
    #   inference schedulers.
    #
    # @option params [Integer] :max_results
    #   Specifies the maximum number of inference schedulers to list.
    #
    # @option params [String] :inference_scheduler_name_begins_with
    #   The beginning of the name of the inference schedulers to be listed.
    #
    # @option params [String] :model_name
    #   The name of the machine learning model used by the inference scheduler
    #   to be listed.
    #
    # @option params [String] :status
    #   Specifies the current status of the inference schedulers.
    #
    # @return [Types::ListInferenceSchedulersResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::ListInferenceSchedulersResponse#next_token #next_token} => String
    #   * {Types::ListInferenceSchedulersResponse#inference_scheduler_summaries #inference_scheduler_summaries} => Array&lt;Types::InferenceSchedulerSummary&gt;
    #
    # The returned {Seahorse::Client::Response response} is a pageable response and is Enumerable. For details on usage see {Aws::PageableResponse PageableResponse}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.list_inference_schedulers({
    #     next_token: "NextToken",
    #     max_results: 1,
    #     inference_scheduler_name_begins_with: "InferenceSchedulerIdentifier",
    #     model_name: "ModelName",
    #     status: "PENDING", # accepts PENDING, RUNNING, STOPPING, STOPPED
    #   })
    #
    # @example Response structure
    #
    #   resp.next_token #=> String
    #   resp.inference_scheduler_summaries #=> Array
    #   resp.inference_scheduler_summaries[0].model_name #=> String
    #   resp.inference_scheduler_summaries[0].model_arn #=> String
    #   resp.inference_scheduler_summaries[0].inference_scheduler_name #=> String
    #   resp.inference_scheduler_summaries[0].inference_scheduler_arn #=> String
    #   resp.inference_scheduler_summaries[0].status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
    #   resp.inference_scheduler_summaries[0].data_delay_offset_in_minutes #=> Integer
    #   resp.inference_scheduler_summaries[0].data_upload_frequency #=> String, one of "PT5M", "PT10M", "PT15M", "PT30M", "PT1H"
    #   resp.inference_scheduler_summaries[0].latest_inference_result #=> String, one of "ANOMALOUS", "NORMAL"
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/ListInferenceSchedulers AWS API Documentation
    #
    # @overload list_inference_schedulers(params = {})
    # @param [Hash] params ({})
    def list_inference_schedulers(params = {}, options = {})
      req = build_request(:list_inference_schedulers, params)
      req.send_request(options)
    end

    # Returns a list of the label groups.
    #
    # @option params [String] :label_group_name_begins_with
    #   The beginning of the name of the label groups to be listed.
    #
    # @option params [String] :next_token
    #   An opaque pagination token indicating where to continue the listing of
    #   label groups.
    #
    # @option params [Integer] :max_results
    #   Specifies the maximum number of label groups to list.
    #
    # @return [Types::ListLabelGroupsResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::ListLabelGroupsResponse#next_token #next_token} => String
    #   * {Types::ListLabelGroupsResponse#label_group_summaries #label_group_summaries} => Array&lt;Types::LabelGroupSummary&gt;
    #
    # The returned {Seahorse::Client::Response response} is a pageable response and is Enumerable. For details on usage see {Aws::PageableResponse PageableResponse}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.list_label_groups({
    #     label_group_name_begins_with: "LabelGroupName",
    #     next_token: "NextToken",
    #     max_results: 1,
    #   })
    #
    # @example Response structure
    #
    #   resp.next_token #=> String
    #   resp.label_group_summaries #=> Array
    #   resp.label_group_summaries[0].label_group_name #=> String
    #   resp.label_group_summaries[0].label_group_arn #=> String
    #   resp.label_group_summaries[0].created_at #=> Time
    #   resp.label_group_summaries[0].updated_at #=> Time
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/ListLabelGroups AWS API Documentation
    #
    # @overload list_label_groups(params = {})
    # @param [Hash] params ({})
    def list_label_groups(params = {}, options = {})
      req = build_request(:list_label_groups, params)
      req.send_request(options)
    end

    # Provides a list of labels.
    #
    # @option params [required, String] :label_group_name
    #   Returns the name of the label group.
    #
    # @option params [Time,DateTime,Date,Integer,String] :interval_start_time
    #   Returns all the labels with a end time equal to or later than the
    #   start time given.
    #
    # @option params [Time,DateTime,Date,Integer,String] :interval_end_time
    #   Returns all labels with a start time earlier than the end time given.
    #
    # @option params [String] :fault_code
    #   Returns labels with a particular fault code.
    #
    # @option params [String] :equipment
    #   Lists the labels that pertain to a particular piece of equipment.
    #
    # @option params [String] :next_token
    #   An opaque pagination token indicating where to continue the listing of
    #   label groups.
    #
    # @option params [Integer] :max_results
    #   Specifies the maximum number of labels to list.
    #
    # @return [Types::ListLabelsResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::ListLabelsResponse#next_token #next_token} => String
    #   * {Types::ListLabelsResponse#label_summaries #label_summaries} => Array&lt;Types::LabelSummary&gt;
    #
    # The returned {Seahorse::Client::Response response} is a pageable response and is Enumerable. For details on usage see {Aws::PageableResponse PageableResponse}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.list_labels({
    #     label_group_name: "LabelGroupName", # required
    #     interval_start_time: Time.now,
    #     interval_end_time: Time.now,
    #     fault_code: "FaultCode",
    #     equipment: "Equipment",
    #     next_token: "NextToken",
    #     max_results: 1,
    #   })
    #
    # @example Response structure
    #
    #   resp.next_token #=> String
    #   resp.label_summaries #=> Array
    #   resp.label_summaries[0].label_group_name #=> String
    #   resp.label_summaries[0].label_id #=> String
    #   resp.label_summaries[0].label_group_arn #=> String
    #   resp.label_summaries[0].start_time #=> Time
    #   resp.label_summaries[0].end_time #=> Time
    #   resp.label_summaries[0].rating #=> String, one of "ANOMALY", "NO_ANOMALY", "NEUTRAL"
    #   resp.label_summaries[0].fault_code #=> String
    #   resp.label_summaries[0].equipment #=> String
    #   resp.label_summaries[0].created_at #=> Time
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/ListLabels AWS API Documentation
    #
    # @overload list_labels(params = {})
    # @param [Hash] params ({})
    def list_labels(params = {}, options = {})
      req = build_request(:list_labels, params)
      req.send_request(options)
    end

    # Generates a list of all model versions for a given model, including
    # the model version, model version ARN, and status. To list a subset of
    # versions, use the `MaxModelVersion` and `MinModelVersion` fields.
    #
    # @option params [required, String] :model_name
    #   Then name of the machine learning model for which the model versions
    #   are to be listed.
    #
    # @option params [String] :next_token
    #   If the total number of results exceeds the limit that the response can
    #   display, the response returns an opaque pagination token indicating
    #   where to continue the listing of machine learning model versions. Use
    #   this token in the `NextToken` field in the request to list the next
    #   page of results.
    #
    # @option params [Integer] :max_results
    #   Specifies the maximum number of machine learning model versions to
    #   list.
    #
    # @option params [String] :status
    #   Filter the results based on the current status of the model version.
    #
    # @option params [String] :source_type
    #   Filter the results based on the way the model version was generated.
    #
    # @option params [Time,DateTime,Date,Integer,String] :created_at_end_time
    #   Filter results to return all the model versions created before this
    #   time.
    #
    # @option params [Time,DateTime,Date,Integer,String] :created_at_start_time
    #   Filter results to return all the model versions created after this
    #   time.
    #
    # @option params [Integer] :max_model_version
    #   Specifies the highest version of the model to return in the list.
    #
    # @option params [Integer] :min_model_version
    #   Specifies the lowest version of the model to return in the list.
    #
    # @return [Types::ListModelVersionsResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::ListModelVersionsResponse#next_token #next_token} => String
    #   * {Types::ListModelVersionsResponse#model_version_summaries #model_version_summaries} => Array&lt;Types::ModelVersionSummary&gt;
    #
    # The returned {Seahorse::Client::Response response} is a pageable response and is Enumerable. For details on usage see {Aws::PageableResponse PageableResponse}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.list_model_versions({
    #     model_name: "ModelName", # required
    #     next_token: "NextToken",
    #     max_results: 1,
    #     status: "IN_PROGRESS", # accepts IN_PROGRESS, SUCCESS, FAILED, IMPORT_IN_PROGRESS, CANCELED
    #     source_type: "TRAINING", # accepts TRAINING, RETRAINING, IMPORT
    #     created_at_end_time: Time.now,
    #     created_at_start_time: Time.now,
    #     max_model_version: 1,
    #     min_model_version: 1,
    #   })
    #
    # @example Response structure
    #
    #   resp.next_token #=> String
    #   resp.model_version_summaries #=> Array
    #   resp.model_version_summaries[0].model_name #=> String
    #   resp.model_version_summaries[0].model_arn #=> String
    #   resp.model_version_summaries[0].model_version #=> Integer
    #   resp.model_version_summaries[0].model_version_arn #=> String
    #   resp.model_version_summaries[0].created_at #=> Time
    #   resp.model_version_summaries[0].status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS", "CANCELED"
    #   resp.model_version_summaries[0].source_type #=> String, one of "TRAINING", "RETRAINING", "IMPORT"
    #   resp.model_version_summaries[0].model_quality #=> String, one of "QUALITY_THRESHOLD_MET", "CANNOT_DETERMINE_QUALITY", "POOR_QUALITY_DETECTED"
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/ListModelVersions AWS API Documentation
    #
    # @overload list_model_versions(params = {})
    # @param [Hash] params ({})
    def list_model_versions(params = {}, options = {})
      req = build_request(:list_model_versions, params)
      req.send_request(options)
    end

    # Generates a list of all models in the account, including model name
    # and ARN, dataset, and status.
    #
    # @option params [String] :next_token
    #   An opaque pagination token indicating where to continue the listing of
    #   machine learning models.
    #
    # @option params [Integer] :max_results
    #   Specifies the maximum number of machine learning models to list.
    #
    # @option params [String] :status
    #   The status of the machine learning model.
    #
    # @option params [String] :model_name_begins_with
    #   The beginning of the name of the machine learning models being listed.
    #
    # @option params [String] :dataset_name_begins_with
    #   The beginning of the name of the dataset of the machine learning
    #   models to be listed.
    #
    # @return [Types::ListModelsResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::ListModelsResponse#next_token #next_token} => String
    #   * {Types::ListModelsResponse#model_summaries #model_summaries} => Array&lt;Types::ModelSummary&gt;
    #
    # The returned {Seahorse::Client::Response response} is a pageable response and is Enumerable. For details on usage see {Aws::PageableResponse PageableResponse}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.list_models({
    #     next_token: "NextToken",
    #     max_results: 1,
    #     status: "IN_PROGRESS", # accepts IN_PROGRESS, SUCCESS, FAILED, IMPORT_IN_PROGRESS
    #     model_name_begins_with: "ModelName",
    #     dataset_name_begins_with: "DatasetName",
    #   })
    #
    # @example Response structure
    #
    #   resp.next_token #=> String
    #   resp.model_summaries #=> Array
    #   resp.model_summaries[0].model_name #=> String
    #   resp.model_summaries[0].model_arn #=> String
    #   resp.model_summaries[0].dataset_name #=> String
    #   resp.model_summaries[0].dataset_arn #=> String
    #   resp.model_summaries[0].status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS"
    #   resp.model_summaries[0].created_at #=> Time
    #   resp.model_summaries[0].active_model_version #=> Integer
    #   resp.model_summaries[0].active_model_version_arn #=> String
    #   resp.model_summaries[0].latest_scheduled_retraining_status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS", "CANCELED"
    #   resp.model_summaries[0].latest_scheduled_retraining_model_version #=> Integer
    #   resp.model_summaries[0].latest_scheduled_retraining_start_time #=> Time
    #   resp.model_summaries[0].next_scheduled_retraining_start_date #=> Time
    #   resp.model_summaries[0].retraining_scheduler_status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
    #   resp.model_summaries[0].model_diagnostics_output_configuration.s3_output_configuration.bucket #=> String
    #   resp.model_summaries[0].model_diagnostics_output_configuration.s3_output_configuration.prefix #=> String
    #   resp.model_summaries[0].model_diagnostics_output_configuration.kms_key_id #=> String
    #   resp.model_summaries[0].model_quality #=> String, one of "QUALITY_THRESHOLD_MET", "CANNOT_DETERMINE_QUALITY", "POOR_QUALITY_DETECTED"
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/ListModels AWS API Documentation
    #
    # @overload list_models(params = {})
    # @param [Hash] params ({})
    def list_models(params = {}, options = {})
      req = build_request(:list_models, params)
      req.send_request(options)
    end

    # Lists all retraining schedulers in your account, filtering by model
    # name prefix and status.
    #
    # @option params [String] :model_name_begins_with
    #   Specify this field to only list retraining schedulers whose machine
    #   learning models begin with the value you specify.
    #
    # @option params [String] :status
    #   Specify this field to only list retraining schedulers whose status
    #   matches the value you specify.
    #
    # @option params [String] :next_token
    #   If the number of results exceeds the maximum, a pagination token is
    #   returned. Use the token in the request to show the next page of
    #   retraining schedulers.
    #
    # @option params [Integer] :max_results
    #   Specifies the maximum number of retraining schedulers to list.
    #
    # @return [Types::ListRetrainingSchedulersResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::ListRetrainingSchedulersResponse#retraining_scheduler_summaries #retraining_scheduler_summaries} => Array&lt;Types::RetrainingSchedulerSummary&gt;
    #   * {Types::ListRetrainingSchedulersResponse#next_token #next_token} => String
    #
    # The returned {Seahorse::Client::Response response} is a pageable response and is Enumerable. For details on usage see {Aws::PageableResponse PageableResponse}.
    #
    #
    # @example Example: Listing retraining schedulers
    #
    #   resp = client.list_retraining_schedulers({
    #     max_results: 50, 
    #   })
    #
    #   resp.to_h outputs the following:
    #   {
    #     retraining_scheduler_summaries: [
    #       {
    #         lookback_window: "P180D", 
    #         model_arn: "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model-1/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111", 
    #         model_name: "sample-model-1", 
    #         retraining_frequency: "P1M", 
    #         retraining_start_date: Time.parse("2023-06-01T00:00:00Z"), 
    #         status: "RUNNING", 
    #       }, 
    #       {
    #         lookback_window: "P180D", 
    #         model_arn: "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model-2/a1b2c3d4-5678-90ab-cdef-EXAMPLE22222", 
    #         model_name: "sample-model-2", 
    #         retraining_frequency: "P30D", 
    #         retraining_start_date: Time.parse("2023-08-15T00:00:00Z"), 
    #         status: "RUNNING", 
    #       }, 
    #       {
    #         lookback_window: "P360D", 
    #         model_arn: "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model-3/a1b2c3d4-5678-90ab-cdef-EXAMPLE33333", 
    #         model_name: "sample-model-3", 
    #         retraining_frequency: "P1M", 
    #         retraining_start_date: Time.parse("2023-09-01T00:00:00Z"), 
    #         status: "STOPPED", 
    #       }, 
    #     ], 
    #   }
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.list_retraining_schedulers({
    #     model_name_begins_with: "ModelName",
    #     status: "PENDING", # accepts PENDING, RUNNING, STOPPING, STOPPED
    #     next_token: "NextToken",
    #     max_results: 1,
    #   })
    #
    # @example Response structure
    #
    #   resp.retraining_scheduler_summaries #=> Array
    #   resp.retraining_scheduler_summaries[0].model_name #=> String
    #   resp.retraining_scheduler_summaries[0].model_arn #=> String
    #   resp.retraining_scheduler_summaries[0].status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
    #   resp.retraining_scheduler_summaries[0].retraining_start_date #=> Time
    #   resp.retraining_scheduler_summaries[0].retraining_frequency #=> String
    #   resp.retraining_scheduler_summaries[0].lookback_window #=> String
    #   resp.next_token #=> String
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/ListRetrainingSchedulers AWS API Documentation
    #
    # @overload list_retraining_schedulers(params = {})
    # @param [Hash] params ({})
    def list_retraining_schedulers(params = {}, options = {})
      req = build_request(:list_retraining_schedulers, params)
      req.send_request(options)
    end

    # Lists statistics about the data collected for each of the sensors that
    # have been successfully ingested in the particular dataset. Can also be
    # used to retreive Sensor Statistics for a previous ingestion job.
    #
    # @option params [required, String] :dataset_name
    #   The name of the dataset associated with the list of Sensor Statistics.
    #
    # @option params [String] :ingestion_job_id
    #   The ingestion job id associated with the list of Sensor Statistics. To
    #   get sensor statistics for a particular ingestion job id, both dataset
    #   name and ingestion job id must be submitted as inputs.
    #
    # @option params [Integer] :max_results
    #   Specifies the maximum number of sensors for which to retrieve
    #   statistics.
    #
    # @option params [String] :next_token
    #   An opaque pagination token indicating where to continue the listing of
    #   sensor statistics.
    #
    # @return [Types::ListSensorStatisticsResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::ListSensorStatisticsResponse#sensor_statistics_summaries #sensor_statistics_summaries} => Array&lt;Types::SensorStatisticsSummary&gt;
    #   * {Types::ListSensorStatisticsResponse#next_token #next_token} => String
    #
    # The returned {Seahorse::Client::Response response} is a pageable response and is Enumerable. For details on usage see {Aws::PageableResponse PageableResponse}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.list_sensor_statistics({
    #     dataset_name: "DatasetName", # required
    #     ingestion_job_id: "IngestionJobId",
    #     max_results: 1,
    #     next_token: "NextToken",
    #   })
    #
    # @example Response structure
    #
    #   resp.sensor_statistics_summaries #=> Array
    #   resp.sensor_statistics_summaries[0].component_name #=> String
    #   resp.sensor_statistics_summaries[0].sensor_name #=> String
    #   resp.sensor_statistics_summaries[0].data_exists #=> Boolean
    #   resp.sensor_statistics_summaries[0].missing_values.count #=> Integer
    #   resp.sensor_statistics_summaries[0].missing_values.percentage #=> Float
    #   resp.sensor_statistics_summaries[0].invalid_values.count #=> Integer
    #   resp.sensor_statistics_summaries[0].invalid_values.percentage #=> Float
    #   resp.sensor_statistics_summaries[0].invalid_date_entries.count #=> Integer
    #   resp.sensor_statistics_summaries[0].invalid_date_entries.percentage #=> Float
    #   resp.sensor_statistics_summaries[0].duplicate_timestamps.count #=> Integer
    #   resp.sensor_statistics_summaries[0].duplicate_timestamps.percentage #=> Float
    #   resp.sensor_statistics_summaries[0].categorical_values.status #=> String, one of "POTENTIAL_ISSUE_DETECTED", "NO_ISSUE_DETECTED"
    #   resp.sensor_statistics_summaries[0].categorical_values.number_of_category #=> Integer
    #   resp.sensor_statistics_summaries[0].multiple_operating_modes.status #=> String, one of "POTENTIAL_ISSUE_DETECTED", "NO_ISSUE_DETECTED"
    #   resp.sensor_statistics_summaries[0].large_timestamp_gaps.status #=> String, one of "POTENTIAL_ISSUE_DETECTED", "NO_ISSUE_DETECTED"
    #   resp.sensor_statistics_summaries[0].large_timestamp_gaps.number_of_large_timestamp_gaps #=> Integer
    #   resp.sensor_statistics_summaries[0].large_timestamp_gaps.max_timestamp_gap_in_days #=> Integer
    #   resp.sensor_statistics_summaries[0].monotonic_values.status #=> String, one of "POTENTIAL_ISSUE_DETECTED", "NO_ISSUE_DETECTED"
    #   resp.sensor_statistics_summaries[0].monotonic_values.monotonicity #=> String, one of "DECREASING", "INCREASING", "STATIC"
    #   resp.sensor_statistics_summaries[0].data_start_time #=> Time
    #   resp.sensor_statistics_summaries[0].data_end_time #=> Time
    #   resp.next_token #=> String
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/ListSensorStatistics AWS API Documentation
    #
    # @overload list_sensor_statistics(params = {})
    # @param [Hash] params ({})
    def list_sensor_statistics(params = {}, options = {})
      req = build_request(:list_sensor_statistics, params)
      req.send_request(options)
    end

    # Lists all the tags for a specified resource, including key and value.
    #
    # @option params [required, String] :resource_arn
    #   The Amazon Resource Name (ARN) of the resource (such as the dataset or
    #   model) that is the focus of the `ListTagsForResource` operation.
    #
    # @return [Types::ListTagsForResourceResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::ListTagsForResourceResponse#tags #tags} => Array&lt;Types::Tag&gt;
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.list_tags_for_resource({
    #     resource_arn: "AmazonResourceArn", # required
    #   })
    #
    # @example Response structure
    #
    #   resp.tags #=> Array
    #   resp.tags[0].key #=> String
    #   resp.tags[0].value #=> String
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/ListTagsForResource AWS API Documentation
    #
    # @overload list_tags_for_resource(params = {})
    # @param [Hash] params ({})
    def list_tags_for_resource(params = {}, options = {})
      req = build_request(:list_tags_for_resource, params)
      req.send_request(options)
    end

    # Creates a resource control policy for a given resource.
    #
    # @option params [required, String] :resource_arn
    #   The Amazon Resource Name (ARN) of the resource for which the policy is
    #   being created.
    #
    # @option params [required, String] :resource_policy
    #   The JSON-formatted resource policy to create.
    #
    # @option params [String] :policy_revision_id
    #   A unique identifier for a revision of the resource policy.
    #
    # @option params [required, String] :client_token
    #   A unique identifier for the request. If you do not set the client
    #   request token, Amazon Lookout for Equipment generates one.
    #
    #   **A suitable default value is auto-generated.** You should normally
    #   not need to pass this option.**
    #
    # @return [Types::PutResourcePolicyResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::PutResourcePolicyResponse#resource_arn #resource_arn} => String
    #   * {Types::PutResourcePolicyResponse#policy_revision_id #policy_revision_id} => String
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.put_resource_policy({
    #     resource_arn: "ResourceArn", # required
    #     resource_policy: "Policy", # required
    #     policy_revision_id: "PolicyRevisionId",
    #     client_token: "IdempotenceToken", # required
    #   })
    #
    # @example Response structure
    #
    #   resp.resource_arn #=> String
    #   resp.policy_revision_id #=> String
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/PutResourcePolicy AWS API Documentation
    #
    # @overload put_resource_policy(params = {})
    # @param [Hash] params ({})
    def put_resource_policy(params = {}, options = {})
      req = build_request(:put_resource_policy, params)
      req.send_request(options)
    end

    # Starts a data ingestion job. Amazon Lookout for Equipment returns the
    # job status.
    #
    # @option params [required, String] :dataset_name
    #   The name of the dataset being used by the data ingestion job.
    #
    # @option params [required, Types::IngestionInputConfiguration] :ingestion_input_configuration
    #   Specifies information for the input data for the data ingestion job,
    #   including dataset S3 location.
    #
    # @option params [required, String] :role_arn
    #   The Amazon Resource Name (ARN) of a role with permission to access the
    #   data source for the data ingestion job.
    #
    # @option params [required, String] :client_token
    #   A unique identifier for the request. If you do not set the client
    #   request token, Amazon Lookout for Equipment generates one.
    #
    #   **A suitable default value is auto-generated.** You should normally
    #   not need to pass this option.**
    #
    # @return [Types::StartDataIngestionJobResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::StartDataIngestionJobResponse#job_id #job_id} => String
    #   * {Types::StartDataIngestionJobResponse#status #status} => String
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.start_data_ingestion_job({
    #     dataset_name: "DatasetIdentifier", # required
    #     ingestion_input_configuration: { # required
    #       s3_input_configuration: { # required
    #         bucket: "S3Bucket", # required
    #         prefix: "S3Prefix",
    #         key_pattern: "KeyPattern",
    #       },
    #     },
    #     role_arn: "IamRoleArn", # required
    #     client_token: "IdempotenceToken", # required
    #   })
    #
    # @example Response structure
    #
    #   resp.job_id #=> String
    #   resp.status #=> String, one of "IN_PROGRESS", "SUCCESS", "FAILED", "IMPORT_IN_PROGRESS"
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/StartDataIngestionJob AWS API Documentation
    #
    # @overload start_data_ingestion_job(params = {})
    # @param [Hash] params ({})
    def start_data_ingestion_job(params = {}, options = {})
      req = build_request(:start_data_ingestion_job, params)
      req.send_request(options)
    end

    # Starts an inference scheduler.
    #
    # @option params [required, String] :inference_scheduler_name
    #   The name of the inference scheduler to be started.
    #
    # @return [Types::StartInferenceSchedulerResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::StartInferenceSchedulerResponse#model_arn #model_arn} => String
    #   * {Types::StartInferenceSchedulerResponse#model_name #model_name} => String
    #   * {Types::StartInferenceSchedulerResponse#inference_scheduler_name #inference_scheduler_name} => String
    #   * {Types::StartInferenceSchedulerResponse#inference_scheduler_arn #inference_scheduler_arn} => String
    #   * {Types::StartInferenceSchedulerResponse#status #status} => String
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.start_inference_scheduler({
    #     inference_scheduler_name: "InferenceSchedulerIdentifier", # required
    #   })
    #
    # @example Response structure
    #
    #   resp.model_arn #=> String
    #   resp.model_name #=> String
    #   resp.inference_scheduler_name #=> String
    #   resp.inference_scheduler_arn #=> String
    #   resp.status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/StartInferenceScheduler AWS API Documentation
    #
    # @overload start_inference_scheduler(params = {})
    # @param [Hash] params ({})
    def start_inference_scheduler(params = {}, options = {})
      req = build_request(:start_inference_scheduler, params)
      req.send_request(options)
    end

    # Starts a retraining scheduler.
    #
    # @option params [required, String] :model_name
    #   The name of the model whose retraining scheduler you want to start.
    #
    # @return [Types::StartRetrainingSchedulerResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::StartRetrainingSchedulerResponse#model_name #model_name} => String
    #   * {Types::StartRetrainingSchedulerResponse#model_arn #model_arn} => String
    #   * {Types::StartRetrainingSchedulerResponse#status #status} => String
    #
    #
    # @example Example: Starts a retraining scheduler
    #
    #   resp = client.start_retraining_scheduler({
    #     model_name: "sample-model", 
    #   })
    #
    #   resp.to_h outputs the following:
    #   {
    #     model_arn: "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111", 
    #     model_name: "sample-model", 
    #     status: "PENDING", 
    #   }
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.start_retraining_scheduler({
    #     model_name: "ModelName", # required
    #   })
    #
    # @example Response structure
    #
    #   resp.model_name #=> String
    #   resp.model_arn #=> String
    #   resp.status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/StartRetrainingScheduler AWS API Documentation
    #
    # @overload start_retraining_scheduler(params = {})
    # @param [Hash] params ({})
    def start_retraining_scheduler(params = {}, options = {})
      req = build_request(:start_retraining_scheduler, params)
      req.send_request(options)
    end

    # Stops an inference scheduler.
    #
    # @option params [required, String] :inference_scheduler_name
    #   The name of the inference scheduler to be stopped.
    #
    # @return [Types::StopInferenceSchedulerResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::StopInferenceSchedulerResponse#model_arn #model_arn} => String
    #   * {Types::StopInferenceSchedulerResponse#model_name #model_name} => String
    #   * {Types::StopInferenceSchedulerResponse#inference_scheduler_name #inference_scheduler_name} => String
    #   * {Types::StopInferenceSchedulerResponse#inference_scheduler_arn #inference_scheduler_arn} => String
    #   * {Types::StopInferenceSchedulerResponse#status #status} => String
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.stop_inference_scheduler({
    #     inference_scheduler_name: "InferenceSchedulerIdentifier", # required
    #   })
    #
    # @example Response structure
    #
    #   resp.model_arn #=> String
    #   resp.model_name #=> String
    #   resp.inference_scheduler_name #=> String
    #   resp.inference_scheduler_arn #=> String
    #   resp.status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/StopInferenceScheduler AWS API Documentation
    #
    # @overload stop_inference_scheduler(params = {})
    # @param [Hash] params ({})
    def stop_inference_scheduler(params = {}, options = {})
      req = build_request(:stop_inference_scheduler, params)
      req.send_request(options)
    end

    # Stops a retraining scheduler.
    #
    # @option params [required, String] :model_name
    #   The name of the model whose retraining scheduler you want to stop.
    #
    # @return [Types::StopRetrainingSchedulerResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::StopRetrainingSchedulerResponse#model_name #model_name} => String
    #   * {Types::StopRetrainingSchedulerResponse#model_arn #model_arn} => String
    #   * {Types::StopRetrainingSchedulerResponse#status #status} => String
    #
    #
    # @example Example: Stops a retraining scheduler
    #
    #   resp = client.stop_retraining_scheduler({
    #     model_name: "sample-model", 
    #   })
    #
    #   resp.to_h outputs the following:
    #   {
    #     model_arn: "arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111", 
    #     model_name: "sample-model", 
    #     status: "STOPPING", 
    #   }
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.stop_retraining_scheduler({
    #     model_name: "ModelName", # required
    #   })
    #
    # @example Response structure
    #
    #   resp.model_name #=> String
    #   resp.model_arn #=> String
    #   resp.status #=> String, one of "PENDING", "RUNNING", "STOPPING", "STOPPED"
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/StopRetrainingScheduler AWS API Documentation
    #
    # @overload stop_retraining_scheduler(params = {})
    # @param [Hash] params ({})
    def stop_retraining_scheduler(params = {}, options = {})
      req = build_request(:stop_retraining_scheduler, params)
      req.send_request(options)
    end

    # Associates a given tag to a resource in your account. A tag is a
    # key-value pair which can be added to an Amazon Lookout for Equipment
    # resource as metadata. Tags can be used for organizing your resources
    # as well as helping you to search and filter by tag. Multiple tags can
    # be added to a resource, either when you create it, or later. Up to 50
    # tags can be associated with each resource.
    #
    # @option params [required, String] :resource_arn
    #   The Amazon Resource Name (ARN) of the specific resource to which the
    #   tag should be associated.
    #
    # @option params [required, Array<Types::Tag>] :tags
    #   The tag or tags to be associated with a specific resource. Both the
    #   tag key and value are specified.
    #
    # @return [Struct] Returns an empty {Seahorse::Client::Response response}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.tag_resource({
    #     resource_arn: "AmazonResourceArn", # required
    #     tags: [ # required
    #       {
    #         key: "TagKey", # required
    #         value: "TagValue", # required
    #       },
    #     ],
    #   })
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/TagResource AWS API Documentation
    #
    # @overload tag_resource(params = {})
    # @param [Hash] params ({})
    def tag_resource(params = {}, options = {})
      req = build_request(:tag_resource, params)
      req.send_request(options)
    end

    # Removes a specific tag from a given resource. The tag is specified by
    # its key.
    #
    # @option params [required, String] :resource_arn
    #   The Amazon Resource Name (ARN) of the resource to which the tag is
    #   currently associated.
    #
    # @option params [required, Array<String>] :tag_keys
    #   Specifies the key of the tag to be removed from a specified resource.
    #
    # @return [Struct] Returns an empty {Seahorse::Client::Response response}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.untag_resource({
    #     resource_arn: "AmazonResourceArn", # required
    #     tag_keys: ["TagKey"], # required
    #   })
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/UntagResource AWS API Documentation
    #
    # @overload untag_resource(params = {})
    # @param [Hash] params ({})
    def untag_resource(params = {}, options = {})
      req = build_request(:untag_resource, params)
      req.send_request(options)
    end

    # Sets the active model version for a given machine learning model.
    #
    # @option params [required, String] :model_name
    #   The name of the machine learning model for which the active model
    #   version is being set.
    #
    # @option params [required, Integer] :model_version
    #   The version of the machine learning model for which the active model
    #   version is being set.
    #
    # @return [Types::UpdateActiveModelVersionResponse] Returns a {Seahorse::Client::Response response} object which responds to the following methods:
    #
    #   * {Types::UpdateActiveModelVersionResponse#model_name #model_name} => String
    #   * {Types::UpdateActiveModelVersionResponse#model_arn #model_arn} => String
    #   * {Types::UpdateActiveModelVersionResponse#current_active_version #current_active_version} => Integer
    #   * {Types::UpdateActiveModelVersionResponse#previous_active_version #previous_active_version} => Integer
    #   * {Types::UpdateActiveModelVersionResponse#current_active_version_arn #current_active_version_arn} => String
    #   * {Types::UpdateActiveModelVersionResponse#previous_active_version_arn #previous_active_version_arn} => String
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.update_active_model_version({
    #     model_name: "ModelName", # required
    #     model_version: 1, # required
    #   })
    #
    # @example Response structure
    #
    #   resp.model_name #=> String
    #   resp.model_arn #=> String
    #   resp.current_active_version #=> Integer
    #   resp.previous_active_version #=> Integer
    #   resp.current_active_version_arn #=> String
    #   resp.previous_active_version_arn #=> String
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/UpdateActiveModelVersion AWS API Documentation
    #
    # @overload update_active_model_version(params = {})
    # @param [Hash] params ({})
    def update_active_model_version(params = {}, options = {})
      req = build_request(:update_active_model_version, params)
      req.send_request(options)
    end

    # Updates an inference scheduler.
    #
    # @option params [required, String] :inference_scheduler_name
    #   The name of the inference scheduler to be updated.
    #
    # @option params [Integer] :data_delay_offset_in_minutes
    #   A period of time (in minutes) by which inference on the data is
    #   delayed after the data starts. For instance, if you select an offset
    #   delay time of five minutes, inference will not begin on the data until
    #   the first data measurement after the five minute mark. For example, if
    #   five minutes is selected, the inference scheduler will wake up at the
    #   configured frequency with the additional five minute delay time to
    #   check the customer S3 bucket. The customer can upload data at the same
    #   frequency and they don't need to stop and restart the scheduler when
    #   uploading new data.
    #
    # @option params [String] :data_upload_frequency
    #   How often data is uploaded to the source S3 bucket for the input data.
    #   The value chosen is the length of time between data uploads. For
    #   instance, if you select 5 minutes, Amazon Lookout for Equipment will
    #   upload the real-time data to the source bucket once every 5 minutes.
    #   This frequency also determines how often Amazon Lookout for Equipment
    #   starts a scheduled inference on your data. In this example, it starts
    #   once every 5 minutes.
    #
    # @option params [Types::InferenceInputConfiguration] :data_input_configuration
    #   Specifies information for the input data for the inference scheduler,
    #   including delimiter, format, and dataset location.
    #
    # @option params [Types::InferenceOutputConfiguration] :data_output_configuration
    #   Specifies information for the output results from the inference
    #   scheduler, including the output S3 location.
    #
    # @option params [String] :role_arn
    #   The Amazon Resource Name (ARN) of a role with permission to access the
    #   data source for the inference scheduler.
    #
    # @return [Struct] Returns an empty {Seahorse::Client::Response response}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.update_inference_scheduler({
    #     inference_scheduler_name: "InferenceSchedulerIdentifier", # required
    #     data_delay_offset_in_minutes: 1,
    #     data_upload_frequency: "PT5M", # accepts PT5M, PT10M, PT15M, PT30M, PT1H
    #     data_input_configuration: {
    #       s3_input_configuration: {
    #         bucket: "S3Bucket", # required
    #         prefix: "S3Prefix",
    #       },
    #       input_time_zone_offset: "TimeZoneOffset",
    #       inference_input_name_configuration: {
    #         timestamp_format: "FileNameTimestampFormat",
    #         component_timestamp_delimiter: "ComponentTimestampDelimiter",
    #       },
    #     },
    #     data_output_configuration: {
    #       s3_output_configuration: { # required
    #         bucket: "S3Bucket", # required
    #         prefix: "S3Prefix",
    #       },
    #       kms_key_id: "NameOrArn",
    #     },
    #     role_arn: "IamRoleArn",
    #   })
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/UpdateInferenceScheduler AWS API Documentation
    #
    # @overload update_inference_scheduler(params = {})
    # @param [Hash] params ({})
    def update_inference_scheduler(params = {}, options = {})
      req = build_request(:update_inference_scheduler, params)
      req.send_request(options)
    end

    # Updates the label group.
    #
    # @option params [required, String] :label_group_name
    #   The name of the label group to be updated.
    #
    # @option params [Array<String>] :fault_codes
    #   Updates the code indicating the type of anomaly associated with the
    #   label.
    #
    #   Data in this field will be retained for service usage. Follow best
    #   practices for the security of your data.
    #
    # @return [Struct] Returns an empty {Seahorse::Client::Response response}.
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.update_label_group({
    #     label_group_name: "LabelGroupName", # required
    #     fault_codes: ["FaultCode"],
    #   })
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/UpdateLabelGroup AWS API Documentation
    #
    # @overload update_label_group(params = {})
    # @param [Hash] params ({})
    def update_label_group(params = {}, options = {})
      req = build_request(:update_label_group, params)
      req.send_request(options)
    end

    # Updates a model in the account.
    #
    # @option params [required, String] :model_name
    #   The name of the model to update.
    #
    # @option params [Types::LabelsInputConfiguration] :labels_input_configuration
    #   Contains the configuration information for the S3 location being used
    #   to hold label data.
    #
    # @option params [String] :role_arn
    #   The ARN of the model to update.
    #
    # @option params [Types::ModelDiagnosticsOutputConfiguration] :model_diagnostics_output_configuration
    #   The Amazon S3 location where you want Amazon Lookout for Equipment to
    #   save the pointwise model diagnostics for the model. You must also
    #   specify the `RoleArn` request parameter.
    #
    # @return [Struct] Returns an empty {Seahorse::Client::Response response}.
    #
    #
    # @example Example: Updates a model
    #
    #   resp = client.update_model({
    #     labels_input_configuration: {
    #       label_group_name: "sample-label-group", 
    #     }, 
    #     model_name: "sample-model", 
    #   })
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.update_model({
    #     model_name: "ModelName", # required
    #     labels_input_configuration: {
    #       s3_input_configuration: {
    #         bucket: "S3Bucket", # required
    #         prefix: "S3Prefix",
    #       },
    #       label_group_name: "LabelGroupName",
    #     },
    #     role_arn: "IamRoleArn",
    #     model_diagnostics_output_configuration: {
    #       s3_output_configuration: { # required
    #         bucket: "S3Bucket", # required
    #         prefix: "S3Prefix",
    #       },
    #       kms_key_id: "NameOrArn",
    #     },
    #   })
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/UpdateModel AWS API Documentation
    #
    # @overload update_model(params = {})
    # @param [Hash] params ({})
    def update_model(params = {}, options = {})
      req = build_request(:update_model, params)
      req.send_request(options)
    end

    # Updates a retraining scheduler.
    #
    # @option params [required, String] :model_name
    #   The name of the model whose retraining scheduler you want to update.
    #
    # @option params [Time,DateTime,Date,Integer,String] :retraining_start_date
    #   The start date for the retraining scheduler. Lookout for Equipment
    #   truncates the time you provide to the nearest UTC day.
    #
    # @option params [String] :retraining_frequency
    #   This parameter uses the [ISO 8601][1] standard to set the frequency at
    #   which you want retraining to occur in terms of Years, Months, and/or
    #   Days (note: other parameters like Time are not currently supported).
    #   The minimum value is 30 days (P30D) and the maximum value is 1 year
    #   (P1Y). For example, the following values are valid:
    #
    #   * P3M15D – Every 3 months and 15 days
    #
    #   * P2M – Every 2 months
    #
    #   * P150D – Every 150 days
    #
    #
    #
    #   [1]: https://en.wikipedia.org/wiki/ISO_8601#Durations
    #
    # @option params [String] :lookback_window
    #   The number of past days of data that will be used for retraining.
    #
    # @option params [String] :promote_mode
    #   Indicates how the service will use new models. In `MANAGED` mode, new
    #   models will automatically be used for inference if they have better
    #   performance than the current model. In `MANUAL` mode, the new models
    #   will not be used [until they are manually activated][1].
    #
    #
    #
    #   [1]: https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/versioning-model.html#model-activation
    #
    # @return [Struct] Returns an empty {Seahorse::Client::Response response}.
    #
    #
    # @example Example: Updates a retraining scheduler
    #
    #   resp = client.update_retraining_scheduler({
    #     model_name: "sample-model", 
    #     retraining_frequency: "P1Y", 
    #     retraining_start_date: Time.parse("2024-01-01T00:00:00Z"), 
    #   })
    #
    # @example Request syntax with placeholder values
    #
    #   resp = client.update_retraining_scheduler({
    #     model_name: "ModelName", # required
    #     retraining_start_date: Time.now,
    #     retraining_frequency: "RetrainingFrequency",
    #     lookback_window: "LookbackWindow",
    #     promote_mode: "MANAGED", # accepts MANAGED, MANUAL
    #   })
    #
    # @see http://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15/UpdateRetrainingScheduler AWS API Documentation
    #
    # @overload update_retraining_scheduler(params = {})
    # @param [Hash] params ({})
    def update_retraining_scheduler(params = {}, options = {})
      req = build_request(:update_retraining_scheduler, params)
      req.send_request(options)
    end

    # @!endgroup

    # @param params ({})
    # @api private
    def build_request(operation_name, params = {})
      handlers = @handlers.for(operation_name)
      tracer = config.telemetry_provider.tracer_provider.tracer(
        Aws::Telemetry.module_to_tracer_name('Aws::LookoutEquipment')
      )
      context = Seahorse::Client::RequestContext.new(
        operation_name: operation_name,
        operation: config.api.operation(operation_name),
        client: self,
        params: params,
        config: config,
        tracer: tracer
      )
      context[:gem_name] = 'aws-sdk-lookoutequipment'
      context[:gem_version] = '1.55.0'
      Seahorse::Client::Request.new(handlers, context)
    end

    # @api private
    # @deprecated
    def waiter_names
      []
    end

    class << self

      # @api private
      attr_reader :identifier

      # @api private
      def errors_module
        Errors
      end

    end
  end
end
