HowToWriteTestsUsingFileCheck.md

How to write tests using FileCheck

What is FileCheck

FileCheck can be seen as an advanced version of grep. We use it for writing small annotated unit tests for optimization passes. FileCheck used in PyTorch is inspired by LLVM FileCheck Tool, but is not the same. FileCheck is available for writing both C++ and python tests.

How does it work

Let's look at a test written with FileCheck. The following test verifies that CSE pass removes one out of two similar aten::mul nodes. Here is how the test looks like:

def test_cse():
    input_str = """graph(%a : Tensor, %b : Tensor):
      # CHECK: aten::mul
      %x : Tensor = aten::mul(%a, %b)
      # Check that the second aten::mul is removed by CSE.
      # CHECK-NOT: aten::mul
      %y : Tensor = aten::mul(%a, %b)
      # CHECK: return
      return (%x, %y)
      """
    parsed = parse_ir(input_str)
    optimized = run_cse(parsed)
    FileCheck().run(input_str, optimized)

Let's look in detail at how it works. First, the input string is parsed by parse_ir. At that stage all annotations are ignored since they are written in comments, so this is what parser essentially sees:

graph(%a : Tensor, %b : Tensor):
      %x : Tensor = aten::mul(%a, %b)
      %y : Tensor = aten::mul(%a, %b)
      return (%x, %y)

We then run CSE on the parsed IR and expect it to remove the second aten::mul, which is redundant. After CSE our IR looks like this:

graph(%a : Tensor, %b : Tensor):
      %x : Tensor = aten::mul(%a, %b)
      return (%x, %x)

And now we run FileCheck passing to it both original input string and the optimized IR. From the input string FileCheck ignores everything except # CHECK pragmas and essentially it sees the input string like this:

      # CHECK: aten::mul       (1)
      # CHECK-NOT: aten::mul   (2)
      # CHECK: return          (3)

It then checks that the optimized IR satisfies the specified annotations. It first finds string %x : Tensor = aten::mul(%a, %b) matching the annotation (1), then it finds string return (%x, %x) matching the annotation (3), and since there were no lines matching aten::mul after the match (1) and before the match (3), the annotation (2) is also satisfied.

One could also register FileCheck annotations using a builder API. To generate annotations from the example above one would write:

      FileCheck().check("aten::mul")     \
                 .check_not("aten::mul") \
                 .check("return")        \
                 .run(optimized)

Supported pragmas

• CHECK: <pattern> Scans the input until PATTERN is found. Fails if the pattern is not found.
• CHECK-NEXT: <pattern> Scans the input on the line immediately following the previous CHECK until PATTERN is found. Fails if the pattern is not found on that line.
• CHECK-NOT: <pattern> Scans the input and fails if PATTERN is found on any line. The scan stops when a match for a next CHECK is found.
• CHECK-SAME: <pattern> Checks that PATTERN is found in the line of the last match.
• CHECK-COUNT-<num>: <pattern> Scans the input and succeeds when a line containing at least NUM entries of PATTERN is found.
• CHECK-COUNT-EXACTLY-<num>: <pattern> Scans the input and succeeds when a line containing exactly NUM entries of PATTERN is found.
• CHECK-DAG: pattern Works similar to the usual CHECK pragma, but also matches if there exists a way to reorder the CHECK-DAG pragmas to satisfy all patterns. For example the following pattern:

  # CHECK: foo
  # CHECK-DAG: bar
  # CHECK-DAG: ham
  # CHECK: end
  

  would match the following input (note that ham and bar are swapped):

  foo
  ham
  bar
  end