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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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