Class: Google::Apis::MlV1::GoogleCloudMlV1PredictRequest

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
generated/google/apis/ml_v1/classes.rb,
generated/google/apis/ml_v1/representations.rb,
generated/google/apis/ml_v1/representations.rb

Overview

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:

instances
A JSON array containing values representing the instances to use for prediction.

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:


`"instances": ["1.0,true,\\"x\\"", "-2.0,false,\\"y\\""]`

Plain text:


`"instances": ["the quick brown fox", "la bruja le dio"]`

Sentences encoded as lists of words (vectors of strings):


`
"instances": [
["the","quick","brown"],
["la","bruja","le"],
...
]
`

Floating point scalar values:


`"instances": [0.0, 1.1, 2.2]`

Vectors of integers:


`
"instances": [
[0, 1, 2],
[3, 4, 5],
...
]
`

Tensors (in this case, two-dimensional tensors):


`
"instances": [
[
[0, 1, 2],
[3, 4, 5]
],
...
]
`

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.


`
"instances": [
[
[
[138, 30, 66],
[130, 20, 56],
...
],
[
[126, 38, 61],
[122, 24, 57],
...
],
...
],
...
]
`

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:

`"b64": "..."`

For example: Two Serialized tf.Examples (fake data, for illustrative purposes only):


`"instances": [`"b64": "X5ad6u"`, `"b64": "IA9j4nx"`]`

Two JPEG image byte strings (fake data, for illustrative purposes only):


`"instances": [`"b64": "ASa8asdf"`, `"b64": "JLK7ljk3"`]`

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:


`
"instances": [
`
"a": 1.0,
"b": true,
"c": "x"
`,
`
"a": -2.0,
"b": false,
"c": "y"
`
]
`

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):


`
"instances": [
`
"tag": "beach",
"image": `"b64": "ASa8asdf"`
`,
`
"tag": "car",
"image": `"b64": "JLK7ljk3"`
`
]
`

For a graph with input tensor aliases "tag" (string) and "image" (3-dimensional array of 8-bit ints):


`
"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],
...
],
...
]
`,
...
]
`

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.

Instance Attribute Summary collapse

Instance Method Summary collapse

Methods included from Core::JsonObjectSupport

#to_json

Methods included from Core::Hashable

process_value, #to_h

Constructor Details

#initialize(**args) ⇒ GoogleCloudMlV1PredictRequest

Returns a new instance of GoogleCloudMlV1PredictRequest



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# File 'generated/google/apis/ml_v1/classes.rb', line 571

def initialize(**args)
   update!(**args)
end

Instance Attribute Details

#http_body ⇒ Google::Apis::MlV1::GoogleApiHttpBody

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. Corresponds to the JSON property httpBody

Returns:



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# File 'generated/google/apis/ml_v1/classes.rb', line 569

def http_body
  @http_body
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



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# File 'generated/google/apis/ml_v1/classes.rb', line 576

def update!(**args)
  @http_body = args[:http_body] if args.key?(:http_body)
end