PyTorch CPU

Name	pytorch-cpu
Version	v1.0.1
DockerHub	weevenetwork/pytorch-cpu
Authors	Jakub Grzelak

• PyTorch CPU
  • Description
  • Environment Variables
    • Module Specific
    • Set by the weeve Agent on the edge-node
  • Dependencies
  • Input
  • Output

Description

Use your pre-trained PyTorch model with weeve modules. This module supports only CPU models and we plan to make a separate module to run PyTorch with CUDA. The model should be available to the module via a downloadable URL or it should be stored in the edge device local filesystem. The module will take input data and then compose a tensor with data in the order assigned to the Ordered Labels environment variable. Later, the module will input that tensor into the model.

Environment Variables

Module Specific

The following module configurations can be provided in a data service designer section on weeve platform:

Name	Environment Variables	type	Description
Model Download URL	MODEL_DOWNLOAD_URL	string	If model is stored online, then provide a download URL to parse the model. Leave empty field to search for the model in the local filesystem (see Model Filepath configuration field).
Model Filepath	MODEL_FILEPATH	string	If model is stored in the local filesystem of the edge device or node (above field for the URL was left empty), then provide a path to the model file.
Model Input dtype	INPUT_DTYPE	string	dtype of the input tensor to the model: float32/float, float64/double, float16/half, bfloat16, complex32/chalf, complex64/cfloat, complex128/cdouble, uint8, int8, int16/short, int32/int, int64/long, bool, quint8, qint8, qint32, quint4x2
Ordered Labels	ORDERED_LABELS	string	Input data labels in the order of feeding into the model. Later a tensor will be created to feed that data into the model in the given order.
Output Label	OUTPUT_LABEL	string	The output label at which data is dispatched.

Set by the weeve Agent on the edge-node

Other features required for establishing the inter-container communication between modules in a data service are set by weeve agent.

Environment Variables	type	Description
MODULE_NAME	string	Name of the module
MODULE_TYPE	string	Type of the module (Input, Processing, Output)
EGRESS_URLS	string	HTTP ReST endpoints for the next module
INGRESS_HOST	string	Host to which data will be received
INGRESS_PORT	string	Port to which data will be received

Dependencies

bottle
requests

Input

Input to this module is:

• JSON body single object, example:

{
    "temperature": 12,
    "volume": 1.3,
    "pressure": 0.32
}

• array of JSON body objects, example:

[
    {
        "temperature": 12,
        "volume": 1.3,
        "pressure": 0.32
    },
    {
        "temperature": 13,
        "volume": 2.1,
        "pressure": 0.34
    }
]

Output

Output of this module is

• JSON body single object, example:

{
    "prediction": 14.323
}

• array of JSON body objects, example:

[
    {
        "prediction": 14.323
    },
    {
        "prediction": 13.45
    }
]