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Binary Tensor Data Extension

This document describes Triton's binary tensor data extension. The binary tensor data extension allows Triton to support tensor data represented in a binary format in the body of an HTTP/REST request. Because this extension is supported, Triton reports “binary_tensor_data” in the extensions field of its Server Metadata.

Binary Tensor Request

Tensor data represented as binary data is organized in little-endian byte order, row major, without stride or padding between elements. All tensor data types are representable as binary data in the native size of the data type. For BOOL type element true is a single byte with value 1 and false is a single byte with value 0. For BYTES type an element is represented by a 4-byte unsigned integer giving the length followed by the actual bytes. The binary data for a tensor is delivered in the HTTP body after the JSON object (see Examples).

The binary tensor data extension uses parameters to indicate that an input or output tensor is communicated as binary data. The first parameter is used in $request_input and $response_output to indicate that the input or output tensor is communicated as binary data:

  • "binary_data_size" : int64 parameter indicating the size of the tensor binary data, in bytes.

The second parameter is used in $request_output to indicate that the output should be returned from Triton as binary data.

  • "binary_data" : bool parameter that is true if the output should be returned as binary data and false (or not given) if the tensor should be returned as JSON.

The third parameter is used in $inference_request to indicate that all outputs should be returned from Triton as binary data, unless overridden by "binary_data" on a specific output.

  • "binary_data_output" : bool parameter that is true if all outputs should be returned as binary data and false (or not given) if the outputs should be returned as JSON. If "binary_data" is specified on an output it overrides this setting.

When one or more tensors are communicated as binary data, the HTTP body of the request or response will contain the JSON inference request or response object followed by the binary tensor data in the same order as the order of the input or output tensors are specified in the JSON. If any binary data is present in the request or response the Inference-Header-Content-Length header must be provided to give the length of the JSON object, and Content-Length continues to give the full body length (as HTTP requires).

Examples

For the following request the input tensors are sent as binary data and the output tensor must be returned as binary data as that is what is requested. Also note that the total size of the binary data is 19 bytes and that size must be reflected in the content length headers.

POST /v2/models/mymodel/infer HTTP/1.1
Host: localhost:8000
Content-Type: application/octet-stream
Inference-Header-Content-Length: <xx>
Content-Length: <xx+19>
{
  "model_name" : "mymodel",
  "inputs" : [
    {
      "name" : "input0",
      "shape" : [ 2, 2 ],
      "datatype" : "UINT32",
      "parameters" : {
        "binary_data_size" : 16
      }
    },
    {
      "name" : "input1",
      "shape" : [ 3 ],
      "datatype" : "BOOL",
      "parameters" : {
        "binary_data_size" : 3
      }
    }
  ],
  "outputs" : [
    {
      "name" : "output0",
      "parameters" : {
        "binary_data" : true
      }
    }
  ]
}
<16 bytes of data for input0 tensor>
<3 bytes of data for input1 tensor>

Assuming the model returns a [ 3, 2 ] tensor of data type FP32 the following response would be returned.

HTTP/1.1 200 OK
Content-Type: application/octet-stream
Inference-Header-Content-Length: <yy>
Content-Length: <yy+24>
{
  "outputs" : [
    {
      "name" : "output0",
      "shape" : [ 3, 2 ],
      "datatype"  : "FP32",
      "parameters" : {
        "binary_data_size" : 24
      }
    }
  ]
}
<24 bytes of data for output0 tensor>

Raw Binary Request

For models whose tensor metadata can be deduced from the byte size of the binary data. User may send the binary tensor request without specifying inference header. In other words, the request body only contains the binary data of the tensor. Below is the constraints for the qualified models:

  1. Only has 1 input
  2. If the input data type is non-BYTE, the number of variable size dimensions is at most 1. If the data type is BYTE, the shape must be [1]. The supported data types can be found here

To send a raw binary request, the Inference-Header-Content-Length header must be provided with value 0 to indicate that the request body doesn't include the inference header.

Note: if the model supports batching, the request will be treated as batch-1 request because the inference header is omitted. Additionally, all the model output will be requested to be returned in binary tensor form as described in the previous section.

Examples

The following is the example of sending raw binary request. Note that the total size of the binary data is 16 bytes and that size must be reflected in the content length headers.

POST /v2/models/mymodel/infer HTTP/1.1
Host: localhost:8000
Content-Type: application/octet-stream
Inference-Header-Content-Length: 0
Content-Length: 16
<16 bytes of data for input tensor>

Assuming the model returns two outputs which both has shape [ 3, 1 ] and data type FP32, then the following response would be returned.

HTTP/1.1 200 OK
Content-Type: application/octet-stream
Inference-Header-Content-Length: <yy>
Content-Length: <yy+24>
{
  "outputs" : [
    {
      "name" : "output0",
      "shape" : [ 3, 1 ],
      "datatype"  : "FP32",
      "parameters" : {
        "binary_data_size" : 12
      }
    },
    {
      "name" : "output1",
      "shape" : [ 3, 1 ],
      "datatype"  : "FP32",
      "parameters" : {
        "binary_data_size" : 12
      }
    }
  ]
}
<12 bytes of data for output0 tensor>
<12 bytes of data for output1 tensor>