# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. import pytest import tvm import tvm.ir import tvm.testing from tvm import tirx from tvm.script import tirx as T def test_simplify_reshape_flattened_index(): ana = tvm.arith.Analyzer() i0 = tirx.Var("i0", "int64") i1 = tirx.Var("i1", "int64") ana.bind(i0, tvm.ir.Range(0, 8)) ana.bind(i1, tvm.ir.Range(0, 3)) i_flattened = i0 * 3 + i1 tvm.ir.assert_structural_equal( ana.simplify((i_flattened) // 12 * 12 + (i_flattened) % 12 // 4 * 4 + (i_flattened) % 4), i_flattened, ) dtype = tvm.testing.parameter( "uint8", "uint16", "uint32", "uint64", "int8", "int16", "int32", "int64", "float16", "float32", "float64", ) def test_can_prove_self_identity(dtype): ana = tvm.arith.Analyzer() n = tirx.Var("n", dtype) assert ana.can_prove(n == n) def test_can_prove_self_equal_to_self(dtype): ana = tvm.arith.Analyzer() n = tirx.Var("n", dtype) assert ana.can_prove_equal(n, n) def test_simplify_symbolic_comparison(): ana = tvm.arith.Analyzer() i0 = tirx.Var("i0", "int64") i1 = tirx.Var("i1", "int64") n, m = tvm.tirx.Var("n", "int64"), tvm.tirx.Var("m", "int64") outer = (n + 31) // 32 PS = tvm.arith.ProofStrength non_negative = tvm.arith.ConstIntBound(0, tvm.arith.ConstIntBound.POS_INF) ana.update(n, non_negative) ana.update(m, non_negative) ana.bind(i0, tvm.ir.Range(0, outer)) ana.bind(i1, tvm.ir.Range(0, 32)) assert not ana.can_prove(i0 * 32 + i1 < (n + 31) // 32 * 32, PS.DEFAULT) assert ana.can_prove(i0 * 32 + i1 < (n + 31) // 32 * 32, PS.SYMBOLIC_BOUND) assert ana.can_prove(i0 * 32 + i1 < (n + 31) // 32 * 32 + m, PS.SYMBOLIC_BOUND) assert ana.can_prove(i0 * 32 + i1 + 1 <= (n + 31) // 32 * 32, PS.SYMBOLIC_BOUND) assert ana.can_prove((n + 31) // 32 * 32 >= i0 * 32 + i1 + 1, PS.SYMBOLIC_BOUND) assert ana.can_prove((n + 31) // 32 * 32 >= i0 * 32 + i1, PS.SYMBOLIC_BOUND) # These tests exercised arith::CanProve's substitution-based proof loop for # vscale-bearing expressions (iterating over known vscale values for a VLA target). # That loop has been removed -- arith no longer attempts target-dependent proofs # about scalable-vector lengths. The LOG(WARNING) for non-VLA targets is also gone. @pytest.mark.xfail(reason="arith no longer proves vscale-bearing inequalities via substitution") @pytest.mark.parametrize( "expression", [ T.vscale() * 32 < T.vscale() * 64, T.vscale() * 2 * (T.vscale() * 2) >= T.vscale() * 4, (T.vscale() * 4 + 114) // (T.vscale() * 4) * (T.vscale() * 4) >= 115, 64 % T.vscale() <= T.vscale(), ], ) def test_simplify_vscale_comparison_with_sve_target(expression): ana = tvm.arith.Analyzer() with tvm.target.Target({"kind": "llvm", "mtriple": "aarch64-linux-gnu", "mattr": ["+sve"]}): assert ana.can_prove(expression) @pytest.mark.xfail( reason="arith no longer emits a LOG(WARNING) for vscale proofs on non-VLA targets" ) def test_simplify_vscale_comparison_without_sve_target(capfd): ana = tvm.arith.Analyzer() vs = tvm.tirx.vscale() with pytest.raises(AssertionError): with tvm.target.Target({"kind": "llvm", "mtriple": "aarch64-linux-gnu"}): assert ana.can_prove(vs * 32 < vs * 64) warning_prefix = ( "Warning: The expression contains scalable values. An attempt to prove by substituting " "with known values of vscale was not performed. This proof currently only supports " "VLA targets, but the target was " ) capture = capfd.readouterr().err assert warning_prefix in capture assert '"kind":"llvm"' in capture assert '"mtriple":"aarch64-linux-gnu"' in capture def test_regression_simplify_inf_recursion(): ana = tvm.arith.Analyzer() cond = tirx.Var("cond", "int32") res = (tvm.tirx.NE(cond, 0).astype("int8") - tvm.tirx.NE(cond, 0).astype("int8")).astype( "int32" ) == 0 # regression in a previous case # try compare and int set recursive call can cause infinite loop ana.rewrite_simplify(res) def test_bind_allow_override(): ana = tvm.arith.Analyzer() x = tirx.Var("x", "int64") ana.bind(x, tvm.ir.Range(0, 10)) ana.bind(x, tvm.ir.Range(0, 5), allow_override=True) assert ana.can_prove(x < 5) with pytest.raises(RuntimeError, match="Trying to update var 'x' with a different const bound"): ana.bind(x, tvm.ir.Range(0, 3)) def test_simplify_floor_mod_with_linear_offset(): """ Test that the floor_mod is simplified correctly when the offset is linear. """ ana = tvm.arith.Analyzer() past_decoder_sequence_length = tirx.Var("past_decoder_sequence_length", "int64") expr1 = (past_decoder_sequence_length + 1) * 64 divisor1 = (past_decoder_sequence_length + 1) * 32 assert ana.can_prove_equal(tvm.tirx.floormod(expr1, divisor1), 0) divisor2 = 32 * (past_decoder_sequence_length + 1) assert ana.can_prove_equal(tvm.tirx.floormod(expr1, divisor2), 0) def test_simplify_uint_floormod_const_scale_divisible(): """uint32 floormod(x * c1, c2) -> 0 when c1 % c2 == 0 (overflow-free).""" ana = tvm.arith.Analyzer() q = tirx.Var("q_stage_idx", "uint32") expr = q * tirx.Cast("uint32", 128) mod = expr % tirx.const(4, "uint32") assert ana.can_prove_equal(mod, tirx.const(0, "uint32")) tvm.ir.assert_structural_equal(ana.rewrite_simplify(mod), tirx.const(0, "uint32")) def test_simplify_float_division(): # Test for the discussion: # https://discuss.tvm.apache.org/t/discuss-is-constant-division-to-multiplication-rewrite-in-tvm-necessary/18615 ana = tvm.arith.Analyzer() x = tirx.Var("x", "float32") ry = x / 27 # in old version, the division will be rewritten into x * T.float32(1 / 27) sy = ana.rewrite_simplify(ry) tvm.ir.assert_structural_equal(ry, sy) if __name__ == "__main__": tvm.testing.main()