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| <h1><a href="ml_v1.html">Google Cloud Machine Learning Engine</a> . <a href="ml_v1.projects.html">projects</a></h1> | |
| <h2>Instance Methods</h2> | |
| <p class="toc_element"> | |
| <code><a href="ml_v1.projects.jobs.html">jobs()</a></code> | |
| </p> | |
| <p class="firstline">Returns the jobs Resource.</p> | |
| <p class="toc_element"> | |
| <code><a href="ml_v1.projects.models.html">models()</a></code> | |
| </p> | |
| <p class="firstline">Returns the models Resource.</p> | |
| <p class="toc_element"> | |
| <code><a href="ml_v1.projects.operations.html">operations()</a></code> | |
| </p> | |
| <p class="firstline">Returns the operations Resource.</p> | |
| <p class="toc_element"> | |
| <code><a href="#getConfig">getConfig(name, x__xgafv=None)</a></code></p> | |
| <p class="firstline">Get the service account information associated with your project. You need</p> | |
| <p class="toc_element"> | |
| <code><a href="#predict">predict(name, body, x__xgafv=None)</a></code></p> | |
| <p class="firstline">Performs prediction on the data in the request.</p> | |
| <h3>Method Details</h3> | |
| <div class="method"> | |
| <code class="details" id="getConfig">getConfig(name, x__xgafv=None)</code> | |
| <pre>Get the service account information associated with your project. You need | |
| this information in order to grant the service account persmissions for | |
| the Google Cloud Storage location where you put your model training code | |
| for training the model with Google Cloud Machine Learning. | |
| Args: | |
| name: string, Required. The project name. | |
| Authorization: requires `Viewer` role on the specified project. (required) | |
| x__xgafv: string, V1 error format. | |
| Allowed values | |
| 1 - v1 error format | |
| 2 - v2 error format | |
| Returns: | |
| An object of the form: | |
| { # Returns service account information associated with a project. | |
| "serviceAccountProject": "A String", # The project number for `service_account`. | |
| "serviceAccount": "A String", # The service account Cloud ML uses to access resources in the project. | |
| }</pre> | |
| </div> | |
| <div class="method"> | |
| <code class="details" id="predict">predict(name, body, x__xgafv=None)</code> | |
| <pre>Performs prediction on the data in the request. | |
| **** REMOVE FROM GENERATED DOCUMENTATION | |
| Args: | |
| name: string, Required. The resource name of a model or a version. | |
| Authorization: requires `Viewer` role on the parent project. (required) | |
| body: object, The request body. (required) | |
| The object takes the form of: | |
| { # Request for predictions to be issued against a trained model. | |
| # | |
| # The body of the request is a single JSON object with a single top-level | |
| # field: | |
| # | |
| # <dl> | |
| # <dt>instances</dt> | |
| # <dd>A JSON array containing values representing the instances to use for | |
| # prediction.</dd> | |
| # </dl> | |
| # | |
| # The structure of each element of the instances list is determined by your | |
| # model's input definition. Instances can include named inputs or can contain | |
| # only unlabeled values. | |
| # | |
| # Not all data includes named inputs. Some instances will be simple | |
| # JSON values (boolean, number, or string). However, instances are often lists | |
| # of simple values, or complex nested lists. Here are some examples of request | |
| # bodies: | |
| # | |
| # CSV data with each row encoded as a string value: | |
| # <pre> | |
| # {"instances": ["1.0,true,\\"x\\"", "-2.0,false,\\"y\\""]} | |
| # </pre> | |
| # Plain text: | |
| # <pre> | |
| # {"instances": ["the quick brown fox", "la bruja le dio"]} | |
| # </pre> | |
| # Sentences encoded as lists of words (vectors of strings): | |
| # <pre> | |
| # { | |
| # "instances": [ | |
| # ["the","quick","brown"], | |
| # ["la","bruja","le"], | |
| # ... | |
| # ] | |
| # } | |
| # </pre> | |
| # Floating point scalar values: | |
| # <pre> | |
| # {"instances": [0.0, 1.1, 2.2]} | |
| # </pre> | |
| # Vectors of integers: | |
| # <pre> | |
| # { | |
| # "instances": [ | |
| # [0, 1, 2], | |
| # [3, 4, 5], | |
| # ... | |
| # ] | |
| # } | |
| # </pre> | |
| # Tensors (in this case, two-dimensional tensors): | |
| # <pre> | |
| # { | |
| # "instances": [ | |
| # [ | |
| # [0, 1, 2], | |
| # [3, 4, 5] | |
| # ], | |
| # ... | |
| # ] | |
| # } | |
| # </pre> | |
| # Images can be represented different ways. In this encoding scheme the first | |
| # two dimensions represent the rows and columns of the image, and the third | |
| # contains lists (vectors) of the R, G, and B values for each pixel. | |
| # <pre> | |
| # { | |
| # "instances": [ | |
| # [ | |
| # [ | |
| # [138, 30, 66], | |
| # [130, 20, 56], | |
| # ... | |
| # ], | |
| # [ | |
| # [126, 38, 61], | |
| # [122, 24, 57], | |
| # ... | |
| # ], | |
| # ... | |
| # ], | |
| # ... | |
| # ] | |
| # } | |
| # </pre> | |
| # JSON strings must be encoded as UTF-8. To send binary data, you must | |
| # base64-encode the data and mark it as binary. To mark a JSON string | |
| # as binary, replace it with a JSON object with a single attribute named `b64`: | |
| # <pre>{"b64": "..."} </pre> | |
| # For example: | |
| # | |
| # Two Serialized tf.Examples (fake data, for illustrative purposes only): | |
| # <pre> | |
| # {"instances": [{"b64": "X5ad6u"}, {"b64": "IA9j4nx"}]} | |
| # </pre> | |
| # Two JPEG image byte strings (fake data, for illustrative purposes only): | |
| # <pre> | |
| # {"instances": [{"b64": "ASa8asdf"}, {"b64": "JLK7ljk3"}]} | |
| # </pre> | |
| # If your data includes named references, format each instance as a JSON object | |
| # with the named references as the keys: | |
| # | |
| # JSON input data to be preprocessed: | |
| # <pre> | |
| # { | |
| # "instances": [ | |
| # { | |
| # "a": 1.0, | |
| # "b": true, | |
| # "c": "x" | |
| # }, | |
| # { | |
| # "a": -2.0, | |
| # "b": false, | |
| # "c": "y" | |
| # } | |
| # ] | |
| # } | |
| # </pre> | |
| # Some models have an underlying TensorFlow graph that accepts multiple input | |
| # tensors. In this case, you should use the names of JSON name/value pairs to | |
| # identify the input tensors, as shown in the following exmaples: | |
| # | |
| # For a graph with input tensor aliases "tag" (string) and "image" | |
| # (base64-encoded string): | |
| # <pre> | |
| # { | |
| # "instances": [ | |
| # { | |
| # "tag": "beach", | |
| # "image": {"b64": "ASa8asdf"} | |
| # }, | |
| # { | |
| # "tag": "car", | |
| # "image": {"b64": "JLK7ljk3"} | |
| # } | |
| # ] | |
| # } | |
| # </pre> | |
| # For a graph with input tensor aliases "tag" (string) and "image" | |
| # (3-dimensional array of 8-bit ints): | |
| # <pre> | |
| # { | |
| # "instances": [ | |
| # { | |
| # "tag": "beach", | |
| # "image": [ | |
| # [ | |
| # [138, 30, 66], | |
| # [130, 20, 56], | |
| # ... | |
| # ], | |
| # [ | |
| # [126, 38, 61], | |
| # [122, 24, 57], | |
| # ... | |
| # ], | |
| # ... | |
| # ] | |
| # }, | |
| # { | |
| # "tag": "car", | |
| # "image": [ | |
| # [ | |
| # [255, 0, 102], | |
| # [255, 0, 97], | |
| # ... | |
| # ], | |
| # [ | |
| # [254, 1, 101], | |
| # [254, 2, 93], | |
| # ... | |
| # ], | |
| # ... | |
| # ] | |
| # }, | |
| # ... | |
| # ] | |
| # } | |
| # </pre> | |
| # If the call is successful, the response body will contain one prediction | |
| # entry per instance in the request body. If prediction fails for any | |
| # instance, the response body will contain no predictions and will contian | |
| # a single error entry instead. | |
| "httpBody": { # Message that represents an arbitrary HTTP body. It should only be used for # | |
| # Required. The prediction request body. | |
| # payload formats that can't be represented as JSON, such as raw binary or | |
| # an HTML page. | |
| # | |
| # | |
| # This message can be used both in streaming and non-streaming API methods in | |
| # the request as well as the response. | |
| # | |
| # It can be used as a top-level request field, which is convenient if one | |
| # wants to extract parameters from either the URL or HTTP template into the | |
| # request fields and also want access to the raw HTTP body. | |
| # | |
| # Example: | |
| # | |
| # message GetResourceRequest { | |
| # // A unique request id. | |
| # string request_id = 1; | |
| # | |
| # // The raw HTTP body is bound to this field. | |
| # google.api.HttpBody http_body = 2; | |
| # } | |
| # | |
| # service ResourceService { | |
| # rpc GetResource(GetResourceRequest) returns (google.api.HttpBody); | |
| # rpc UpdateResource(google.api.HttpBody) returns (google.protobuf.Empty); | |
| # } | |
| # | |
| # Example with streaming methods: | |
| # | |
| # service CaldavService { | |
| # rpc GetCalendar(stream google.api.HttpBody) | |
| # returns (stream google.api.HttpBody); | |
| # rpc UpdateCalendar(stream google.api.HttpBody) | |
| # returns (stream google.api.HttpBody); | |
| # } | |
| # | |
| # Use of this type only changes how the request and response bodies are | |
| # handled, all other features will continue to work unchanged. | |
| "contentType": "A String", # The HTTP Content-Type string representing the content type of the body. | |
| "data": "A String", # HTTP body binary data. | |
| "extensions": [ # Application specific response metadata. Must be set in the first response | |
| # for streaming APIs. | |
| { | |
| "a_key": "", # Properties of the object. Contains field @type with type URL. | |
| }, | |
| ], | |
| }, | |
| } | |
| x__xgafv: string, V1 error format. | |
| Allowed values | |
| 1 - v1 error format | |
| 2 - v2 error format | |
| Returns: | |
| An object of the form: | |
| { # Message that represents an arbitrary HTTP body. It should only be used for | |
| # payload formats that can't be represented as JSON, such as raw binary or | |
| # an HTML page. | |
| # | |
| # | |
| # This message can be used both in streaming and non-streaming API methods in | |
| # the request as well as the response. | |
| # | |
| # It can be used as a top-level request field, which is convenient if one | |
| # wants to extract parameters from either the URL or HTTP template into the | |
| # request fields and also want access to the raw HTTP body. | |
| # | |
| # Example: | |
| # | |
| # message GetResourceRequest { | |
| # // A unique request id. | |
| # string request_id = 1; | |
| # | |
| # // The raw HTTP body is bound to this field. | |
| # google.api.HttpBody http_body = 2; | |
| # } | |
| # | |
| # service ResourceService { | |
| # rpc GetResource(GetResourceRequest) returns (google.api.HttpBody); | |
| # rpc UpdateResource(google.api.HttpBody) returns (google.protobuf.Empty); | |
| # } | |
| # | |
| # Example with streaming methods: | |
| # | |
| # service CaldavService { | |
| # rpc GetCalendar(stream google.api.HttpBody) | |
| # returns (stream google.api.HttpBody); | |
| # rpc UpdateCalendar(stream google.api.HttpBody) | |
| # returns (stream google.api.HttpBody); | |
| # } | |
| # | |
| # Use of this type only changes how the request and response bodies are | |
| # handled, all other features will continue to work unchanged. | |
| "contentType": "A String", # The HTTP Content-Type string representing the content type of the body. | |
| "data": "A String", # HTTP body binary data. | |
| "extensions": [ # Application specific response metadata. Must be set in the first response | |
| # for streaming APIs. | |
| { | |
| "a_key": "", # Properties of the object. Contains field @type with type URL. | |
| }, | |
| ], | |
| }</pre> | |
| </div> | |
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