chore: import upstream snapshot with attribution

2026-07-13 13:36:25 +08:00
commit 26446540fa
3151 changed files with 974126 additions and 0 deletions
@@ -0,0 +1,131 @@
+# 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 tvm
+import tvm.testing
+from tvm import relax, tirx
+from tvm.ir import Op
+from tvm.script import relax as R
+
+
+def test_op_correctness():
+    x = relax.Var("x", R.Tensor((2, 3), "float32"))
+    dx = relax.Var("dx", R.Tensor((2, 3), "uint8"))
+    s = relax.Var("s", R.Tensor([3], "float32"))
+    zp = relax.Var("zp", R.Tensor([3], "int8"))
+    assert relax.op.quantize(x, s, zp, 1, "int8").op == Op.get("relax.quantize")
+    assert relax.op.dequantize(dx, s, zp, 1, "float32").op == Op.get("relax.dequantize")
+
+
+def _check_inference(bb: relax.BlockBuilder, call: relax.Call, expected_ty: relax.Type):
+    ret = bb.normalize(call)
+    tvm.ir.assert_structural_equal(ret.ty, expected_ty)
+
+
+def test_qdq_op_infer_ty():
+    bb = relax.BlockBuilder()
+    x = relax.Var("x", R.Tensor((2, 3), "float32"))
+    dx = relax.Var("dx", R.Tensor((2, 3), "uint8"))
+    s = relax.Var("s", R.Tensor([3], "float32"))
+    zp = relax.Var("zp", R.Tensor([3], "int8"))
+    _check_inference(bb, relax.op.quantize(x, s, zp, 1, "int8"), relax.TensorType((2, 3), "int8"))
+    _check_inference(
+        bb,
+        relax.op.dequantize(dx, s, zp, 1, "float32"),
+        relax.TensorType((2, 3), "float32"),
+    )
+
+
+def test_qdq_op_infer_ty_unknown_dtype():
+    bb = relax.BlockBuilder()
+    x = relax.Var("x", R.Tensor((2, 3), dtype=None))
+    dx = relax.Var("dx", R.Tensor((2, 3), dtype=None))
+    s = relax.Var("s", R.Tensor([3], "float32"))
+    s_unknown = relax.Var("s_unknown", R.Tensor([3], dtype=None))
+    zp = relax.Var("zp", R.Tensor([3], "int8"))
+    zp_unknown = relax.Var("zp_unknown", R.Tensor([3], dtype=None))
+    _check_inference(
+        bb, relax.op.quantize(x, s, zp, 1, "int8"), relax.TensorType((2, 3), dtype=None)
+    )
+    _check_inference(
+        bb,
+        relax.op.quantize(dx, s_unknown, zp, 1, "int8"),
+        relax.TensorType((2, 3), dtype=None),
+    )
+    _check_inference(
+        bb,
+        relax.op.quantize(dx, s, zp_unknown, 1, "int8"),
+        relax.TensorType((2, 3), dtype=None),
+    )
+    _check_inference(
+        bb,
+        relax.op.dequantize(dx, s, zp, 1, "float32"),
+        relax.TensorType((2, 3), dtype=None),
+    )
+
+
+def test_qdq_op_infer_ty_symbolic():
+    bb = relax.BlockBuilder()
+    n = tirx.Var("n", "int64")
+    x = relax.Var("x", R.Tensor((n, 3), "float32"))
+    dx = relax.Var("dx", R.Tensor((n, 3), "int8"))
+    s = relax.Var("s", R.Tensor([3], "float32"))
+    zp = relax.Var("zp", R.Tensor([3], "int8"))
+    _check_inference(bb, relax.op.quantize(x, s, zp, 1, "int8"), relax.TensorType((n, 3), "int8"))
+    _check_inference(
+        bb,
+        relax.op.dequantize(dx, s, zp, 1, "float32"),
+        relax.TensorType((n, 3), "float32"),
+    )
+
+
+def test_qdq_float8_e4m3fn_op_infer_ty_symbolic():
+    bb = relax.BlockBuilder()
+    n = tirx.Var("n", "int64")
+    x = relax.Var("x", R.Tensor((n, 3), "float32"))
+    dx = relax.Var("dx", R.Tensor((n, 3), "float8_e4m3fn"))
+    s = relax.Var("s", R.Tensor([3], "float32"))
+    zp = relax.Var("zp", R.Tensor([3], "float16"))
+    _check_inference(
+        bb,
+        relax.op.quantize(x, s, zp, 1, "float8_e4m3fn"),
+        relax.TensorType((n, 3), "float8_e4m3fn"),
+    )
+    _check_inference(
+        bb,
+        relax.op.dequantize(dx, s, zp, 1, "float32"),
+        relax.TensorType((n, 3), "float32"),
+    )
+
+
+def test_qdq_float8_e5m2_op_infer_ty_symbolic():
+    dtype = "float8_e5m2"
+    bb = relax.BlockBuilder()
+    n = tirx.Var("n", "int64")
+    x = relax.Var("x", R.Tensor((n, 3), "float32"))
+    dx = relax.Var("dx", R.Tensor((n, 3), dtype))
+    s = relax.Var("s", R.Tensor([3], "float32"))
+    zp = relax.Var("zp", R.Tensor([3], "float16"))
+    _check_inference(bb, relax.op.quantize(x, s, zp, 1, dtype), relax.TensorType((n, 3), dtype))
+    _check_inference(
+        bb,
+        relax.op.dequantize(dx, s, zp, 1, "float32"),
+        relax.TensorType((n, 3), "float32"),
+    )
+
+
+if __name__ == "__main__":
+    tvm.testing.main()