[Lang] MatrixType refactor: Support matrix slice

[strongoier]

Issue: #5819

Brief Summary

A slice actually corresponds to several indices. Let's take a look at the following example:

import taichi as ti

ti.init(real_matrix=True, real_matrix_scalarize=True, print_ir=True)

@ti.kernel
def foo():
    c = ti.Vector([1, 2, 3, 4, 5])
    print(c[:4:2])

foo()

c[:4:2] is a "partially selected vector with length 2" which contains references to c[0] and c[2]. Let's represent it with c[(0), (2), shape=2].

This PR does the following:

• expands slices into groups of indices in Python;
• extends IndexExpression to accept a group of indices;
• creates MatrixOfMatrixPtrStmt to represent a "partially selected matrix" in CHI IR;
• eliminates MatrixOfMatrixPtrStmt in the lower_matrix_ptr() pass.

Frontend IR and CHI IR of the above example:

[I 10/25/22 19:54:51.885 816603] [compile_to_offloads.cpp:operator()@22] [foo_c80_0] Initial IR:
kernel {
  $0 = alloca @tmp0
  @tmp0 = [1, 2, 3, 4, 5] (dt=[Tensor (5) i32])
  $2 = alloca @tmp1
  @tmp1 = @tmp0
  print @tmp1[(0), (2), shape=(2)], "\n"
}
[I 10/25/22 19:54:51.885 816603] [compile_to_offloads.cpp:operator()@22] [foo_c80_0] Lowered:
kernel {
  <[Tensor (5) i32]> $0 = alloca
  <i32> $1 = const 1
  <i32> $2 = const 2
  <i32> $3 = const 3
  <i32> $4 = const 4
  <i32> $5 = const 5
  <[Tensor (5) i32]> $6 = [$1, $2, $3, $4, $5]
  $7 : local store [$0 <- $6]
  <[Tensor (5) i32]> $8 = alloca
  $9 = local load [$0]
  $10 : local store [$8 <- $9]
  <i32> $11 = const 0
  <*i32> $12 = shift ptr [$8 + $11]
  <i32> $13 = const 2
  <*i32> $14 = shift ptr [$8 + $13]
  <[Tensor (2) i32]> $15 = matrix of matrix ptr [$12, $14]
  $16 = local load [$15]
  print $16, "\n"
}

Some tests of matrix slice haven't been enabled yet because they require x.transpose(), which depends on #6425.

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[jim19930609]

LGTM!