Python init_seq_dataset示例

示例#1

文件： model_pretraining.py 项目： dpaysan/domain_translation

 def initialize_seq_data_set(self):
     seq_data_and_labels_fname = self.data_config["data_fname"]
     self.data_key = self.data_config["data_key"]
     self.label_key = self.data_config["label_key"]
     self.data_set = init_seq_dataset(
         seq_data_and_labels_fname=seq_data_and_labels_fname
     )

示例#2

文件： test_genesetae.py 项目： dpaysan/domain_translation

import copy
import time

import numpy as np
import pandas as pd
import torch

from src.helper.data import DataHandler
from src.models.ae import GeneSetAE, VanillaAE
from src.models.custom_networks import GeneSetAE_v2
from src.utils.torch.data import init_seq_dataset
from src.utils.torch.general import get_device

gene_set_dataset = init_seq_dataset(
    "../../data/cd4/cd4_rna_seq_pbmc_10k/gene_kegg_pathway_data_and_labels.csv"
)
gene_set_adjacencies = pd.read_csv(
    "../../data/cd4/cd4_rna_seq_pbmc_10k/gene_kegg_pathway_adj_filtered_nCD4.csv",
    index_col=0,
)
geneset_adj_matrix = torch.from_numpy(np.array(gene_set_adjacencies))

geneset_ae = GeneSetAE(
    input_dim=5785,
    hidden_dims=[512, 512, 512, 512, 512, 512],
    latent_dim=256,
    geneset_adjacencies=geneset_adj_matrix,
)

# geneset_ae = VanillaAE(input_dim=5785, latent_dim=256, hidden_dims=[2048, 1024, 512, 256, 256])

示例#3

文件： seq_seq_domain_translation.py 项目： GVS-Lab/domain_translation

 def initialize_seq_data_set_2(self):
     seq_data_and_labels_fname = self.seq_data_config_2["data_fname"]
     self.seq_data_key_2 = self.seq_data_config_2["data_key"]
     self.seq_label_key_2 = self.seq_data_config_2["label_key"]
     self.seq_data_set_2 = init_seq_dataset(
         seq_data_and_labels_fname=seq_data_and_labels_fname)