rohan2

thingiverse

# Copyright 2023 The T5X Authors. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. # Standard library imports. from io import BytesIO, StringIO import numpy as np import itertools import pathlib import tarfile import os import pickle # Related third party imports. from fairseq.modules.checkpoint_activations importCheckpointActivations # isort:skip import torch.distributed import tensorflow.compat.v2 as tf # noqa:F401 tf.enable_v2_behavior() from tf_transformers.layers.base import BaseModel # noqa:F401 import yaml # Fairseq imports import argparse import random import shutil from collections import defaultdict, OrderedDict, Counter import copy import dataclasses import functools import logging import math import re from typing import * from sklearn.model_selection import train_test_split logger = logging.getLogger(__name__) FILE_HASHES = {} class Arguments(object): """Module arguments.""" def __init__(self): self.save_dir=None # default value # Setup a new T5 model, based on pre-trained model from hugging face. t5 = TFModelT5( num_encoder_layers=1, encoder_dim=16*128+3, attention_dim=256, max_positions=128) with open("input/data/train.pckl","rb") as file: training_data=np.load(file) X_train = np.array(training_data)