[FQ2I] fix unary op output affine type in fq2i (apache#12224)

* fix unary op output affine type in fq2i

* better names

* add option to force to positive values for ops that are undefined on negative values

python/tvm/relay/transform/fake_quantization_to_integer.py

@@ -534,7 +534,7 @@ def unary(expr, type_map):
             out_t.scale,
             out_t.zero_point,
         )
-        return [out, x_t]
+        return [out, out_t]
 
     return register_fake_quantization_to_integer(op_name, unary)
 

tests/python/relay/test_pass_fake_quantization_to_integer.py

@@ -318,23 +318,36 @@ def test_fake_quantize_global_avg_pool():
 
 
 class TestUnaryQNNOp:
-    def helper_test_fake_quantize_unary_op(self, fp32_op, scale=0.125):
-        x = relay.var("x", shape=[1, 3, 3, 3], dtype="int8")
-        mid_point = relay.const(-128)
+    def helper_test_fake_quantize_unary_op(self, fp32_op, pos_values=False):
+        for dtype in ["int8", "uint8"]:
+            x = relay.var("x", shape=[1, 3, 3, 3], dtype=dtype)
 
-        x = relay.qnn.op.dequantize(x, relay.const(scale), mid_point)
-        op = fp32_op(x)
-        op = relay.qnn.op.quantize(op, relay.const(scale), mid_point)
+            zero = -128 if dtype == "int8" else 0
+            if pos_values:
+                # Use a positive range for quanitzed ops that only work on positive values
+                input_mid_point = relay.const(zero)
+                output_mid_point = relay.const(zero)
+            else:
+                input_mid_point = relay.const(np.random.randint(0, 255) + zero)
+                output_mid_point = relay.const(np.random.randint(0, 255) + zero)
 
-        x_np = np.random.randint(-128, 127, size=[1, 3, 3, 3], dtype="int8")
+            input_scale = relay.const(np.random.rand())
+            output_scale = relay.const(np.random.rand())
 
-        compare_fq_to_int(op, [x_np], True)
+            x = relay.qnn.op.dequantize(x, input_scale, input_mid_point)
+            op = fp32_op(x)
+
+            op = relay.qnn.op.quantize(op, output_scale, output_mid_point, out_dtype=dtype)
+
+            x_np = np.random.randint(0 + zero, 255 + zero, size=[1, 3, 3, 3], dtype=dtype)
+
+            compare_fq_to_int(op, [x_np], True)
 
     def test_sqrt(self):
-        self.helper_test_fake_quantize_unary_op(fp32_op=relay.sqrt)
+        self.helper_test_fake_quantize_unary_op(fp32_op=relay.sqrt, pos_values=True)
 
     def test_rsqrt(self):
-        self.helper_test_fake_quantize_unary_op(fp32_op=relay.rsqrt)
+        self.helper_test_fake_quantize_unary_op(fp32_op=relay.rsqrt, pos_values=True)
 
     def test_exp(self):
         self.helper_test_fake_quantize_unary_op(fp32_op=relay.exp)
@@ -349,7 +362,7 @@ def test_tanh(self):
         self.helper_test_fake_quantize_unary_op(fp32_op=relay.tanh)
 
     def test_log(self):
-        self.helper_test_fake_quantize_unary_op(fp32_op=relay.log)
+        self.helper_test_fake_quantize_unary_op(fp32_op=relay.log, pos_values=True)
 
 
 def test_fake_quantize_reshape():