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autocast(self.mix_precision)
extract_features(self, x)
self.conv(self.features(x)
infer_head(self, x, skip_pool=False)
self._glob_feature_vector(x, self.pooling_type, reduce_dims=False)
self.classifier(glob_features.view(x.shape[0], -1)
_initialize_weights(self)
self.modules()
isinstance(m, nn.Conv2d)
m.weight.data.normal_(0, math.sqrt(2. / n)
m.bias.data.zero_()
isinstance(m, nn.BatchNorm2d)
m.weight.data.fill_(1)
m.bias.data.zero_()
isinstance(m, nn.Linear)
m.weight.size(1)
m.weight.data.normal_(0, 0.01)
m.bias.data.zero_()
forward(self, x, return_featuremaps=False, get_embeddings=False, gt_labels=None)
self.input_IN(x)
self.extract_features(x)
no_nncf_head_context()
self.infer_head(y, skip_pool=False)
EvalModeSetter([self.output], m_type=(nn.BatchNorm1d, nn.BatchNorm2d)
self.infer_head(x, skip_pool=True)
self.is_classification()
KeyError("Unsupported loss: {}".format(self.loss)
tuple(out_data)
init_pretrained_weights(model, key='', **kwargs)
_get_torch_home()
os.getenv(ENV_XDG_CACHE_HOME, DEFAULT_CACHE_DIR)
_get_torch_home()
os.path.join(torch_home, 'checkpoints')
os.makedirs(model_dir)
os.path.join(model_dir, filename)
os.path.exists(cached_file)
gdown.download(pretrained_urls[key], cached_file)
load_pretrained_weights(model, cached_file, **kwargs)
mobilenetv3_large_075(pretrained=False, **kwargs)
MobileNetV3(cfgs, mode='large', width_mult =.75, **kwargs)
init_pretrained_weights(net, key='mobilenetv3_large_075')
mobilenetv3_large(pretrained=False, **kwargs)
MobileNetV3(cfgs, mode='large', width_mult = 1., **kwargs)
init_pretrained_weights(net, key='mobilenetv3_large')
mobilenetv3_large_150(pretrained=False, **kwargs)
MobileNetV3(cfgs, mode='large', width_mult = 1.5, **kwargs)
NotImplementedError("The weights for this configuration are not available")
mobilenetv3_large_125(pretrained=False, **kwargs)
MobileNetV3(cfgs, mode='large', width_mult = 1.25, **kwargs)
NotImplementedError("The weights for this configuration are not available")
mobilenetv3_small(pretrained=False, **kwargs)
MobileNetV3(cfgs, mode='small', width_mult = 1., **kwargs)
init_pretrained_weights(net, key='mobilenetv3_small')
all(config, cfg_dir)
os.path.exists(cfg_dir)
os.makedirs(cfg_dir)
list()
sorted(os.listdir(cfg_dir)
cfg_list.append(config(os.path.join(cfg_dir, file)
open("README.md", "r")
fh.read()
open("VERSION", "r")
fversion.read()
setuptools.find_packages()
os.path.join(root_data_folder, 'raw_dat')
os.path.join(root_data_folder, 'preprocessed_dat')
os.path.join(preprocessed_data_folder, 'uq1000_gex_feature.csv')
os.path.join(preprocessed_data_folder, 'xena_uq_mut_standarized.csv')
os.path.join(preprocessed_data_folder, 'ccle_uq_mut_standarized.csv')
os.path.join(raw_data_folder, 'mart_export.txt')
os.path.join(preprocessed_data_folder, 'CosmicHGNC_list.tsv')
os.path.join(raw_data_folder, 'Xena')
os.path.join(xena_folder, 'gencode.v23.annotation.gene.probemap')
os.path.join(xena_folder, 'tcga_RSEM_gene_tpm.gz')
os.path.join(preprocessed_data_folder, 'xena_gex')
os.path.join(xena_folder, 'mc3.v0.2.8.PUBLIC.nonsilentGene.xena.gz')
os.path.join(preprocessed_data_folder, 'xena_mut')
os.path.join(xena_folder, 'TCGA_phenotype_denseDataOnlyDownload.tsv.gz')
os.path.join(raw_data_folder, 'CCLE')
os.path.join(ccle_folder, 'CCLE_expression.csv')
os.path.join(preprocessed_data_folder, 'ccle_gex')
os.path.join(ccle_folder, 'CCLE_mutations.csv')
os.path.join(preprocessed_data_folder, 'ccle_mut')
os.path.join(ccle_folder, 'sample_info.csv')
os.path.join(raw_data_folder, 'GDSC')
os.path.join(gdsc_folder, 'GDSC1_fitted_dose_response_25Feb20.csv')
os.path.join(gdsc_folder, 'GDSC2_fitted_dose_response_25Feb20.csv')
os.path.join(gdsc_folder, 'sanger-dose-response.csv')
os.path.join(gdsc_folder, 'gdsc_cell_line_annotation.csv')
os.path.join(preprocessed_data_folder, 'gdsc_target')
os.path.join(raw_data_folder, 'network')
os.path.join(network_folder, 'STRING')
os.path.join(string_network_folder, '9606.protein.links.v11.0.txt.gz')
os.path.join(string_network_folder, '9606.protein.info.v11.0.txt.gz')
os.path.join(string_network_folder, 'string_network_hgnc.txt')
os.path.join(string_network_folder, 'string_propagation_kernel.file')
EventDefinitionError(ValueError)
EventMeta(ABCMeta, metaclass=ABCMeta)
__new__(cls, name, bases, attrs, **kwargs)
super()