pengzhangzhi

import torch
import matplotlib.pyplot as plt
from torch import nn, Tensor
from sklearn.datasets import make_moons

# Set device
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

class DiscreteFlow(nn.Module):
    def __init__(self, dim: int = 2, h: int = 128, v: int = 128):

pengzhangzhi

# Copyright (c) 2023 Meta Platforms, Inc. and affiliates
# Copyright (c) 2024 Bytedance Ltd. and/or its affiliates
# SPDX-License-Identifier: Apache-2.0
#
# This file has been modified by Xinyou Wang on Jul 21, 2024
#
# Original file was released under MIT, with the full license text
# available at https://github.com/facebookresearch/esm/blob/main/LICENSE
#
# This modified file is released under the same license.

pengzhangzhi

def renum_pdb_str(pdb_str, Ls=None, renum=True, offset=1):
    from string import ascii_uppercase, ascii_lowercase
    assert len(Ls) == 2
    Ls = [int(i) for i in Ls]
    alphabet_list = list(ascii_uppercase+ascii_lowercase)
    if Ls is not None:
        L_init = 0
        new_chain = {}
        for L,c in zip(Ls, alphabet_list):
            new_chain.update({i:c for i in range(L_init,L_init+L)})