You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: coeffs2vals.m
    path of file: ./repos/chebfun/@chebfun3
    
    the code of the file until where you have to start completion: function V = coeffs2vals(C)
%VAL2COEFFS   Convert tensor of Chebyshev coefficients to values.
%   V = COEFFS2VALS(C) converts a tensor C of bivariate Chebyshev coefficients
%   to a matrix of samples V corresponding to values of 
%                   \sum_i \sum_j C(i,j) T_{i-1}(y) T_{j-1}(x)
%   at a tensor Chebyshev grid of size size(C).
%
% See also chebfun3/vals2coeffs.

% Copyright 2017 by The University of Oxford and The Chebfun Developers.
% See http://www.chebfun.org/ for Chebfun information.

[m, n, p] = size(C);

%% Step 1:
% Mode-1 unfolding of F to get a matrix of size m x n*p:
C1 = chebfun3.unfold(C, 1); 

% Apply 1D "vals2coeffs" in the X direction i.e., the 1st dimension of vals1:
C1 = chebtech2.coeffs2vals(C1); 

% Tensorize vals1 back to its original m x n x p size:
C1 = chebfun3.fold(C1, [m, n, p], 1, [2 3]); 
% This is simply vals1 = reshape(V1, m, n, p);

%% Step 2:
% Mode-2 unfolding of (the tensorized) vals1 to get a matrix of size m x n*p:
C2 = chebfun3.unfold(C1, 2); 

% Apply 1D "vals2coeffs" in the Y direction, i.e. to the 1st direction of
% vals2:

    
function V = coeffs2vals(C)
%VAL2COEFFS   Convert tensor of Chebyshev coefficients to values.
%   V = COEFFS2VALS(C) converts a tensor C of bivariate Chebyshev coefficients
%   to a matrix of samples V corresponding to values of 
%                   \sum_i \sum_j C(i,j) T_{i-1}(y) T_{j-1}(x)
%   at a tensor Chebyshev grid of size size(C).
%
% See also chebfun3/vals2coeffs.

% Copyright 2017 by The University of Oxford and The Chebfun Developers.
% See http://www.chebfun.org/ for Chebfun information.

[m, n, p] = size(C);

%% Step 1:
% Mode-1 unfolding of F to get a matrix of size m x n*p:
C1 = chebfun3.unfold(C, 1); 

% Apply 1D "vals2coeffs" in the X direction i.e., the 1st dimension of vals1:
C1 = chebtech2.coeffs2vals(C1); 

% Tensorize vals1 back to its original m x n x p size:
C1 = chebfun3.fold(C1, [m, n, p], 1, [2 3]); 
% This is simply vals1 = reshape(V1, m, n, p);

%% Step 2:
% Mode-2 unfolding of (the tensorized) vals1 to get a matrix of size m x n*p:
C2 = chebfun3.unfold(C1, 2); 

% Apply 1D "vals2coeffs" in the Y direction, i.e. to the 1st direction of
% vals2:
C2 = chebtech2.coeffs2vals(C2);

% Tensorize vals2 back to its original m x n x p size:
C2 = chebfun3.fold(C2, [m, n, p], 2, [1 3]);

%% Step 3:
% Mode-3 unfolding of (the tensorized) vals2 to get a matrix of size p x m*n:
C3 = chebfun3.unfold(C2, 3);

% Now, vals2coeffs is applied in the Z direction.
C3 = chebtech2.coeffs2vals(C3);

% Reshape vals3 back to the original m x n x p size:
V = chebfun3.fold(C3, [m, n, p], 3, [1 2]);

end