Jacob Kimmel jacobkimmel

## forest_lab_kidney_preservation_comparison.ipynb

      
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                jacobkimmel
                / forest_lab_kidney_preservation_comparison.ipynb
            
            
              Created
              June 2, 2023 21:30
            
              
                forest_lab_kidney_preservation_comparison.ipynb
              
          
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## load_dense_as_sparse.py
import gzip
import scipy.sparse as sp
import numpy as np


def load_dense_csv_as_sparse_matrix(
    file_name: str,
    dtype=np.int32,
    skip_lines: int=0,
    batch_size: int=2048,

## make_one_hot.py
def make_one_hot(labels, C=2):
    '''
    Converts an integer label torch.autograd.Variable to a one-hot Variable.

    Parameters
    ----------
    labels : torch.autograd.Variable of torch.cuda.LongTensor
        N x 1 x H x W, where N is batch size.
        Each value is an integer representing correct classification.
    C : integer.
	import gzip
	import scipy.sparse as sp
	import numpy as np


	def load_dense_csv_as_sparse_matrix(
	file_name: str,
	dtype=np.int32,
	skip_lines: int=0,
	batch_size: int=2048,
	def make_one_hot(labels, C=2):
	'''
	Converts an integer label torch.autograd.Variable to a one-hot Variable.

	Parameters
	----------
	labels : torch.autograd.Variable of torch.cuda.LongTensor
	N x 1 x H x W, where N is batch size.
	Each value is an integer representing correct classification.
	C : integer.