sgraaf

#!/usr/bin/env python
# -*- coding: utf-8 -*-
from argparse import ArgumentParser

import torch
import torch.distributed as dist
from torch.nn.parallel import DistributedDataParallel as DDP
from torch.utils.data import DataLoader, Dataset
from torch.utils.data.distributed import DistributedSampler
from transformers import BertForMaskedLM

danielwatson6

"""Automatically build a vanilla or Cudnn RNN."""

import numpy as np
import tensorflow as tf


def gru(inputs,
        num_layers,
        num_units,
        direction='unidirectional',

asimshankar

Training TensorFlow models in C++

Python is the primary language in which TensorFlow models are typically developed and trained. TensorFlow does have bindings for other programming languages. These bindings have the low-level primitives that are required to build a more complete API, however, lack much of the higher-level API richness of the Python bindings, particularly for defining the model structure.

This file demonstrates taking a model (a TensorFlow graph) created by a Python program and running the training loop in C++.