Update 4 files

- /content/docs/software/machine-learning/netket.mdx
- /content/docs/software/sdk/openacc-mpi.mdx
- /content/docs/software/tools/virtualization.mdx
- /content/docs/storage/acl/nfs4-file-acl.mdx

content/docs/software/machine-learning/netket.mdx

@@ -21,7 +21,7 @@ Load the `Python/3.8.6-GCC-10.2.0-NetKet` and `intel/2020b` modules.
     Set the visible device in the environment variable before loading jax and NetKet, as NetKet loads jax.
 </Callout>
 
-```code
+```console
 # J1-J2 model
 # Version with complex Hamiltonian
 #

content/docs/software/sdk/openacc-mpi.mdx

@@ -43,7 +43,7 @@ this section of code is guarded by the preprocessor macro `_OPENACC`,
 which is defined when the OpenACC directives are enabled in the HPC Fortran compiler
 through the use of the `-⁠acc` command-line compiler option.
 
-```code
+```console
 #ifdef _OPENACC
 #
 function setDevice(nprocs,myrank)
@@ -125,7 +125,7 @@ make verify
 Next, you add six compute regions around the eight parallel loops.
 For example, here's the final reduction loop.
 
-```code
+```console
 !$acc kernels
   do k = kmin,kmax
     do j = NPOINTS_PML+1, NY-NPOINTS_PML
@@ -282,7 +282,7 @@ The final three arrays do need to be copied back to the host to pass their halos
 
 For those cases, we use the update directive.
 
-```code
+```console
 !---
 !---  beginning of time loop
 !---
@@ -334,7 +334,7 @@ This instructs the compiler to copy each array in its entirety as a contiguous b
 and eliminates the inefficiency we noted earlier
 when interior sub-arrays were being copied in multiple blocks.
 
-```code
+```console
 !$acc data copy(vx,vy,vz)
 
 ... data region spans over 5 compute regions and host code
@@ -434,7 +434,7 @@ In the example code below, note that the source code added to support the halo
 gathers and transfers is guarded by the preprocessor `_OPENACC` macro
 and will only be executed if the code is compiled by an OpenACC-enabled compiler.
 
-```code
+```console
 #ifdef _OPENACC
 #
 ! Gather the sigma 3D arrays to a 2D slice to allow for faster
@@ -509,7 +509,7 @@ The kernel schedule you choose will affect whether and how shared memory is used
 global array accesses, and various types of optimizations.
 Typically, it's better to perform gang scheduling of loops with large iteration counts.
 
-```code
+```console
 !$acc loop gang
   do k = k2begin,NZ_LOCAL
     kglobal = k + offset_k

content/docs/software/tools/virtualization.mdx

@@ -196,7 +196,7 @@ The job script links application data (win), input data (data), and run script (
 
 Example run script (run.bat) for the Windows virtual machine:
 
-```doscon
+```console
     z:
     cd winappl
     call application.bat z:data z:output

content/docs/storage/acl/nfs4-file-acl.mdx

@@ -5,7 +5,7 @@ An NFSv4 ACL consists of one or more NFSv4 ACEs (Access Control Entry), each del
 
 An NFSv4 ACE is written as a colon-delimited, 4-field string in the following format:
 
-```code
+```console
 <type>:<flags>:<principal>:<permissions>
 ```
 
@@ -55,7 +55,7 @@ An NFSv4 ACE is written as a colon-delimited, 4-field string in the following fo
 
 ## Example
 
-``` code
+```console
 [root@login2.karolina proj1]# nfs4_getfacl open-20-11
 
 # file: open-20-11