# Copyright (c) 2016, NVIDIA CORPORATION.  All rights reserved.
from __future__ import absolute_import

from . import tasks
import digits.frameworks
from digits.job import Job
from digits.utils import subclass, override


@subclass
class InferenceJob(Job):
    """
    A Job that exercises the forward pass of a neural network
    """

    def __init__(self, model, images, epoch, layers, resize=True, **kwargs):
        """
        Arguments:
        model   -- job object associated with model to perform inference on
        images  -- list of image paths to perform inference on
        epoch   -- epoch of model snapshot to use
        layers  -- layers to import ('all' or 'none')
        """
        super(InferenceJob, self).__init__(persistent=False, **kwargs)

        # get handle to framework object
        fw_id = model.train_task().framework_id
        fw = digits.frameworks.get_framework_by_id(fw_id)

        # create inference task
        self.tasks.append(fw.create_inference_task(
            job_dir=self.dir(),
            model=model,
            images=images,
            epoch=epoch,
            layers=layers,
            resize=resize,
        ))

    @override
    def __getstate__(self):
        fields_to_save = ['_id', '_name']
        full_state = super(InferenceJob, self).__getstate__()
        state_to_save = {}
        for field in fields_to_save:
            state_to_save[field] = full_state[field]
        return state_to_save

    def inference_task(self):
        """Return the first and only InferenceTask for this job"""
        return [t for t in self.tasks if isinstance(t, tasks.InferenceTask)][0]

    @override
    def __setstate__(self, state):
        super(InferenceJob, self).__setstate__(state)

    def get_data(self):
        """Return inference data"""
        task = self.inference_task()
        return task.inference_inputs, task.inference_outputs, task.inference_layers

# Copyright (c) 2016, NVIDIA CORPORATION.  All rights reserved.
from __future__ import absolute_import

from . import tasks
import digits.frameworks
from digits.job import Job
from digits.utils import subclass, override


@subclass
class InferenceJob(Job):
    """
    A Job that exercises the forward pass of a neural network
    """

    def __init__(self, model, images, epoch, layers, resize=True, **kwargs):
        """
        Arguments:
        model   -- job object associated with model to perform inference on
        images  -- list of image paths to perform inference on
        epoch   -- epoch of model snapshot to use
        layers  -- layers to import ('all' or 'none')
        """
        super(InferenceJob, self).__init__(persistent=False, **kwargs)

        # get handle to framework object
        fw_id = model.train_task().framework_id
        fw = digits.frameworks.get_framework_by_id(fw_id)

        if fw is None:
            raise RuntimeError(
                'The "%s" framework cannot be found. Check your server configuration.'
                % fw_id)

        # create inference task
        self.tasks.append(fw.create_inference_task(
            job_dir=self.dir(),
            model=model,
            images=images,
            epoch=epoch,
            layers=layers,
            resize=resize,
        ))

    @override
    def __getstate__(self):
        fields_to_save = ['_id', '_name']
        full_state = super(InferenceJob, self).__getstate__()
        state_to_save = {}
        for field in fields_to_save:
            state_to_save[field] = full_state[field]
        return state_to_save

    def inference_task(self):
        """Return the first and only InferenceTask for this job"""
        return [t for t in self.tasks if isinstance(t, tasks.InferenceTask)][0]

    @override
    def __setstate__(self, state):
        super(InferenceJob, self).__setstate__(state)

    def get_data(self):
        """Return inference data"""
        task = self.inference_task()
        return task.inference_inputs, task.inference_outputs, task.inference_layers

Add explicit error message for missing frameworks